Zen Stores
zenml.zen_stores
special
ZenStores define ways to store ZenML relevant data locally or remotely.
base_zen_store
Base Zen Store implementation.
BaseZenStore (BaseModel, ZenStoreInterface, ABC)
pydantic-model
Base class for accessing and persisting ZenML core objects.
Attributes:
| Name | Type | Description |
|---|---|---|
config |
StoreConfiguration |
The configuration of the store. |
Source code in zenml/zen_stores/base_zen_store.py
class BaseZenStore(
BaseModel,
ZenStoreInterface,
ABC,
):
"""Base class for accessing and persisting ZenML core objects.
Attributes:
config: The configuration of the store.
"""
config: StoreConfiguration
TYPE: ClassVar[StoreType]
CONFIG_TYPE: ClassVar[Type[StoreConfiguration]]
# ---------------------------------
# Initialization and configuration
# ---------------------------------
def __init__(
self,
skip_default_registrations: bool = False,
**kwargs: Any,
) -> None:
"""Create and initialize a store.
Args:
skip_default_registrations: If `True`, the creation of the default
stack and user in the store will be skipped.
**kwargs: Additional keyword arguments to pass to the Pydantic
constructor.
Raises:
RuntimeError: If the store cannot be initialized.
AuthorizationException: If the store cannot be initialized due to
authentication errors.
"""
super().__init__(**kwargs)
try:
self._initialize()
# Handle cases where the ZenML server is not available
except ConnectionError as e:
error_message = (
"Cannot connect to the ZenML database because the ZenML server "
f"at {self.url} is not running."
)
if urlparse(self.url).hostname in ["localhost", "127.0.0.1"]:
recommendation = (
"Please run `zenml down` and `zenml up` to restart the "
"server."
)
else:
recommendation = (
"Please run `zenml disconnect` and `zenml connect --url "
f"{self.url}` to reconnect to the server."
)
raise RuntimeError(f"{error_message}\n{recommendation}") from e
except AuthorizationException as e:
raise AuthorizationException(
f"Authorization failed for store at '{self.url}'. Please check "
f"your credentials: {str(e)}"
)
except Exception as e:
raise RuntimeError(
f"Error initializing {self.type.value} store with URL "
f"'{self.url}': {str(e)}"
) from e
if not skip_default_registrations:
logger.debug("Initializing database")
self._initialize_database()
else:
logger.debug("Skipping database initialization")
@staticmethod
def get_store_class(store_type: StoreType) -> Type["BaseZenStore"]:
"""Returns the class of the given store type.
Args:
store_type: The type of the store to get the class for.
Returns:
The class of the given store type or None if the type is unknown.
Raises:
TypeError: If the store type is unsupported.
"""
if store_type == StoreType.SQL:
from zenml.zen_stores.sql_zen_store import SqlZenStore
return SqlZenStore
elif store_type == StoreType.REST:
from zenml.zen_stores.rest_zen_store import RestZenStore
return RestZenStore
else:
raise TypeError(
f"No store implementation found for store type "
f"`{store_type.value}`."
)
@staticmethod
def get_store_config_class(
store_type: StoreType,
) -> Type["StoreConfiguration"]:
"""Returns the store config class of the given store type.
Args:
store_type: The type of the store to get the class for.
Returns:
The config class of the given store type.
"""
store_class = BaseZenStore.get_store_class(store_type)
return store_class.CONFIG_TYPE
@staticmethod
def get_store_type(url: str) -> StoreType:
"""Returns the store type associated with a URL schema.
Args:
url: The store URL.
Returns:
The store type associated with the supplied URL schema.
Raises:
TypeError: If no store type was found to support the supplied URL.
"""
from zenml.zen_stores.rest_zen_store import RestZenStoreConfiguration
from zenml.zen_stores.sql_zen_store import SqlZenStoreConfiguration
if SqlZenStoreConfiguration.supports_url_scheme(url):
return StoreType.SQL
elif RestZenStoreConfiguration.supports_url_scheme(url):
return StoreType.REST
else:
raise TypeError(f"No store implementation found for URL: {url}.")
@staticmethod
def create_store(
config: StoreConfiguration,
skip_default_registrations: bool = False,
**kwargs: Any,
) -> "BaseZenStore":
"""Create and initialize a store from a store configuration.
Args:
config: The store configuration to use.
skip_default_registrations: If `True`, the creation of the default
stack and user in the store will be skipped.
**kwargs: Additional keyword arguments to pass to the store class
Returns:
The initialized store.
"""
logger.debug(f"Creating store with config '{config}'...")
store_class = BaseZenStore.get_store_class(config.type)
store = store_class(
config=config,
skip_default_registrations=skip_default_registrations,
**kwargs,
)
return store
@staticmethod
def get_default_store_config(path: str) -> StoreConfiguration:
"""Get the default store configuration.
The default store is a SQLite store that saves the DB contents on the
local filesystem.
Args:
path: The local path where the store DB will be stored.
Returns:
The default store configuration.
"""
from zenml.zen_stores.sql_zen_store import SqlZenStoreConfiguration
config = SqlZenStoreConfiguration(
type=StoreType.SQL,
url=SqlZenStoreConfiguration.get_local_url(path),
secrets_store=SqlSecretsStoreConfiguration(
type=SecretsStoreType.SQL,
),
)
return config
def _initialize_database(self) -> None:
"""Initialize the database on first use."""
@property
def url(self) -> str:
"""The URL of the store.
Returns:
The URL of the store.
"""
return self.config.url
@property
def type(self) -> StoreType:
"""The type of the store.
Returns:
The type of the store.
"""
return self.TYPE
def validate_active_config(
self,
active_workspace_name_or_id: Optional[Union[str, UUID]] = None,
active_stack_id: Optional[UUID] = None,
config_name: str = "",
) -> Tuple[WorkspaceResponse, StackResponse]:
"""Validate the active configuration.
Call this method to validate the supplied active workspace and active
stack values.
This method is guaranteed to return valid workspace ID and stack ID
values. If the supplied workspace and stack are not set or are not valid
(e.g. they do not exist or are not accessible), the default workspace and
default workspace stack will be returned in their stead.
Args:
active_workspace_name_or_id: The name or ID of the active workspace.
active_stack_id: The ID of the active stack.
config_name: The name of the configuration to validate (used in the
displayed logs/messages).
Returns:
A tuple containing the active workspace and active stack.
"""
active_workspace: WorkspaceResponse
if active_workspace_name_or_id:
try:
active_workspace = self.get_workspace(
active_workspace_name_or_id
)
except KeyError:
active_workspace = self._get_default_workspace()
logger.warning(
f"The current {config_name} active workspace is no longer "
f"available. Resetting the active workspace to "
f"'{active_workspace.name}'."
)
else:
active_workspace = self._get_default_workspace()
logger.info(
f"Setting the {config_name} active workspace "
f"to '{active_workspace.name}'."
)
active_stack: StackResponse
# Sanitize the active stack
if active_stack_id:
# Ensure that the active stack is still valid
try:
active_stack = self.get_stack(stack_id=active_stack_id)
except KeyError:
logger.warning(
"The current %s active stack is no longer available. "
"Resetting the active stack to default.",
config_name,
)
active_stack = self._get_default_stack(
workspace_id=active_workspace.id
)
else:
if active_stack.workspace.id != active_workspace.id:
logger.warning(
"The current %s active stack is not part of the active "
"workspace. Resetting the active stack to default.",
config_name,
)
active_stack = self._get_default_stack(
workspace_id=active_workspace.id
)
else:
logger.warning(
"Setting the %s active stack to default.",
config_name,
)
active_stack = self._get_default_stack(
workspace_id=active_workspace.id
)
return active_workspace, active_stack
def get_store_info(self) -> ServerModel:
"""Get information about the store.
Returns:
Information about the store.
"""
from zenml.zen_stores.sql_zen_store import SqlZenStore
server_config = ServerConfiguration.get_server_config()
deployment_type = server_config.deployment_type
auth_scheme = server_config.auth_scheme
base_url = server_config.base_url
metadata = server_config.metadata
secrets_store_type = SecretsStoreType.NONE
if isinstance(self, SqlZenStore):
secrets_store_type = self.secrets_store.type
return ServerModel(
id=GlobalConfiguration().user_id,
version=zenml.__version__,
deployment_type=deployment_type,
database_type=ServerDatabaseType.OTHER,
debug=IS_DEBUG_ENV,
secrets_store_type=secrets_store_type,
auth_scheme=auth_scheme,
base_url=base_url,
metadata=metadata,
)
def is_local_store(self) -> bool:
"""Check if the store is local or connected to a local ZenML server.
Returns:
True if the store is local, False otherwise.
"""
return self.get_store_info().is_local()
# -----------------------------
# Default workspaces and stacks
# -----------------------------
@property
def _default_workspace_name(self) -> str:
"""Get the default workspace name.
Returns:
The default workspace name.
"""
return os.getenv(
ENV_ZENML_DEFAULT_WORKSPACE_NAME, DEFAULT_WORKSPACE_NAME
)
def _get_default_workspace(self) -> WorkspaceResponse:
"""Get the default workspace.
Raises:
KeyError: If the default workspace doesn't exist.
Returns:
The default workspace.
"""
try:
return self.get_workspace(self._default_workspace_name)
except KeyError:
raise KeyError("Unable to find default workspace.")
def _get_default_stack(
self,
workspace_id: UUID,
) -> StackResponse:
"""Get the default stack for a user in a workspace.
Args:
workspace_id: ID of the workspace.
Returns:
The default stack in the workspace.
Raises:
KeyError: if the workspace or default stack doesn't exist.
"""
default_stacks = self.list_stacks(
StackFilter(
workspace_id=workspace_id,
name=DEFAULT_STACK_AND_COMPONENT_NAME,
)
)
if default_stacks.total == 0:
raise KeyError(
f"No default stack found in workspace {workspace_id}."
)
return default_stacks.items[0]
def get_external_user(self, user_id: UUID) -> UserResponse:
"""Get a user by external ID.
Args:
user_id: The external ID of the user.
Returns:
The user with the supplied external ID.
Raises:
KeyError: If the user doesn't exist.
"""
users = self.list_users(UserFilter(external_user_id=user_id))
if users.total == 0:
raise KeyError(f"User with external ID '{user_id}' not found.")
return users.items[0]
class Config:
"""Pydantic configuration class."""
# Validate attributes when assigning them. We need to set this in order
# to have a mix of mutable and immutable attributes
validate_assignment = True
# Ignore extra attributes from configs of previous ZenML versions
extra = "ignore"
# all attributes with leading underscore are private and therefore
# are mutable and not included in serialization
underscore_attrs_are_private = True
type: StoreType
property
readonly
The type of the store.
Returns:
| Type | Description |
|---|---|
StoreType |
The type of the store. |
url: str
property
readonly
The URL of the store.
Returns:
| Type | Description |
|---|---|
str |
The URL of the store. |
Config
Pydantic configuration class.
Source code in zenml/zen_stores/base_zen_store.py
class Config:
"""Pydantic configuration class."""
# Validate attributes when assigning them. We need to set this in order
# to have a mix of mutable and immutable attributes
validate_assignment = True
# Ignore extra attributes from configs of previous ZenML versions
extra = "ignore"
# all attributes with leading underscore are private and therefore
# are mutable and not included in serialization
underscore_attrs_are_private = True
__init__(self, skip_default_registrations=False, **kwargs)
special
Create and initialize a store.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
skip_default_registrations |
bool |
If |
False |
**kwargs |
Any |
Additional keyword arguments to pass to the Pydantic constructor. |
{} |
Exceptions:
| Type | Description |
|---|---|
RuntimeError |
If the store cannot be initialized. |
AuthorizationException |
If the store cannot be initialized due to authentication errors. |
Source code in zenml/zen_stores/base_zen_store.py
def __init__(
self,
skip_default_registrations: bool = False,
**kwargs: Any,
) -> None:
"""Create and initialize a store.
Args:
skip_default_registrations: If `True`, the creation of the default
stack and user in the store will be skipped.
**kwargs: Additional keyword arguments to pass to the Pydantic
constructor.
Raises:
RuntimeError: If the store cannot be initialized.
AuthorizationException: If the store cannot be initialized due to
authentication errors.
"""
super().__init__(**kwargs)
try:
self._initialize()
# Handle cases where the ZenML server is not available
except ConnectionError as e:
error_message = (
"Cannot connect to the ZenML database because the ZenML server "
f"at {self.url} is not running."
)
if urlparse(self.url).hostname in ["localhost", "127.0.0.1"]:
recommendation = (
"Please run `zenml down` and `zenml up` to restart the "
"server."
)
else:
recommendation = (
"Please run `zenml disconnect` and `zenml connect --url "
f"{self.url}` to reconnect to the server."
)
raise RuntimeError(f"{error_message}\n{recommendation}") from e
except AuthorizationException as e:
raise AuthorizationException(
f"Authorization failed for store at '{self.url}'. Please check "
f"your credentials: {str(e)}"
)
except Exception as e:
raise RuntimeError(
f"Error initializing {self.type.value} store with URL "
f"'{self.url}': {str(e)}"
) from e
if not skip_default_registrations:
logger.debug("Initializing database")
self._initialize_database()
else:
logger.debug("Skipping database initialization")
create_store(config, skip_default_registrations=False, **kwargs)
staticmethod
Create and initialize a store from a store configuration.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
config |
StoreConfiguration |
The store configuration to use. |
required |
skip_default_registrations |
bool |
If |
False |
**kwargs |
Any |
Additional keyword arguments to pass to the store class |
{} |
Returns:
| Type | Description |
|---|---|
BaseZenStore |
The initialized store. |
Source code in zenml/zen_stores/base_zen_store.py
@staticmethod
def create_store(
config: StoreConfiguration,
skip_default_registrations: bool = False,
**kwargs: Any,
) -> "BaseZenStore":
"""Create and initialize a store from a store configuration.
Args:
config: The store configuration to use.
skip_default_registrations: If `True`, the creation of the default
stack and user in the store will be skipped.
**kwargs: Additional keyword arguments to pass to the store class
Returns:
The initialized store.
"""
logger.debug(f"Creating store with config '{config}'...")
store_class = BaseZenStore.get_store_class(config.type)
store = store_class(
config=config,
skip_default_registrations=skip_default_registrations,
**kwargs,
)
return store
get_default_store_config(path)
staticmethod
Get the default store configuration.
The default store is a SQLite store that saves the DB contents on the local filesystem.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
path |
str |
The local path where the store DB will be stored. |
required |
Returns:
| Type | Description |
|---|---|
StoreConfiguration |
The default store configuration. |
Source code in zenml/zen_stores/base_zen_store.py
@staticmethod
def get_default_store_config(path: str) -> StoreConfiguration:
"""Get the default store configuration.
The default store is a SQLite store that saves the DB contents on the
local filesystem.
Args:
path: The local path where the store DB will be stored.
Returns:
The default store configuration.
"""
from zenml.zen_stores.sql_zen_store import SqlZenStoreConfiguration
config = SqlZenStoreConfiguration(
type=StoreType.SQL,
url=SqlZenStoreConfiguration.get_local_url(path),
secrets_store=SqlSecretsStoreConfiguration(
type=SecretsStoreType.SQL,
),
)
return config
get_external_user(self, user_id)
Get a user by external ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
user_id |
UUID |
The external ID of the user. |
required |
Returns:
| Type | Description |
|---|---|
UserResponse |
The user with the supplied external ID. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If the user doesn't exist. |
Source code in zenml/zen_stores/base_zen_store.py
def get_external_user(self, user_id: UUID) -> UserResponse:
"""Get a user by external ID.
Args:
user_id: The external ID of the user.
Returns:
The user with the supplied external ID.
Raises:
KeyError: If the user doesn't exist.
"""
users = self.list_users(UserFilter(external_user_id=user_id))
if users.total == 0:
raise KeyError(f"User with external ID '{user_id}' not found.")
return users.items[0]
get_store_class(store_type)
staticmethod
Returns the class of the given store type.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
store_type |
StoreType |
The type of the store to get the class for. |
required |
Returns:
| Type | Description |
|---|---|
Type[BaseZenStore] |
The class of the given store type or None if the type is unknown. |
Exceptions:
| Type | Description |
|---|---|
TypeError |
If the store type is unsupported. |
Source code in zenml/zen_stores/base_zen_store.py
@staticmethod
def get_store_class(store_type: StoreType) -> Type["BaseZenStore"]:
"""Returns the class of the given store type.
Args:
store_type: The type of the store to get the class for.
Returns:
The class of the given store type or None if the type is unknown.
Raises:
TypeError: If the store type is unsupported.
"""
if store_type == StoreType.SQL:
from zenml.zen_stores.sql_zen_store import SqlZenStore
return SqlZenStore
elif store_type == StoreType.REST:
from zenml.zen_stores.rest_zen_store import RestZenStore
return RestZenStore
else:
raise TypeError(
f"No store implementation found for store type "
f"`{store_type.value}`."
)
get_store_config_class(store_type)
staticmethod
Returns the store config class of the given store type.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
store_type |
StoreType |
The type of the store to get the class for. |
required |
Returns:
| Type | Description |
|---|---|
Type[StoreConfiguration] |
The config class of the given store type. |
Source code in zenml/zen_stores/base_zen_store.py
@staticmethod
def get_store_config_class(
store_type: StoreType,
) -> Type["StoreConfiguration"]:
"""Returns the store config class of the given store type.
Args:
store_type: The type of the store to get the class for.
Returns:
The config class of the given store type.
"""
store_class = BaseZenStore.get_store_class(store_type)
return store_class.CONFIG_TYPE
get_store_info(self)
Get information about the store.
Returns:
| Type | Description |
|---|---|
ServerModel |
Information about the store. |
Source code in zenml/zen_stores/base_zen_store.py
def get_store_info(self) -> ServerModel:
"""Get information about the store.
Returns:
Information about the store.
"""
from zenml.zen_stores.sql_zen_store import SqlZenStore
server_config = ServerConfiguration.get_server_config()
deployment_type = server_config.deployment_type
auth_scheme = server_config.auth_scheme
base_url = server_config.base_url
metadata = server_config.metadata
secrets_store_type = SecretsStoreType.NONE
if isinstance(self, SqlZenStore):
secrets_store_type = self.secrets_store.type
return ServerModel(
id=GlobalConfiguration().user_id,
version=zenml.__version__,
deployment_type=deployment_type,
database_type=ServerDatabaseType.OTHER,
debug=IS_DEBUG_ENV,
secrets_store_type=secrets_store_type,
auth_scheme=auth_scheme,
base_url=base_url,
metadata=metadata,
)
get_store_type(url)
staticmethod
Returns the store type associated with a URL schema.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
url |
str |
The store URL. |
required |
Returns:
| Type | Description |
|---|---|
StoreType |
The store type associated with the supplied URL schema. |
Exceptions:
| Type | Description |
|---|---|
TypeError |
If no store type was found to support the supplied URL. |
Source code in zenml/zen_stores/base_zen_store.py
@staticmethod
def get_store_type(url: str) -> StoreType:
"""Returns the store type associated with a URL schema.
Args:
url: The store URL.
Returns:
The store type associated with the supplied URL schema.
Raises:
TypeError: If no store type was found to support the supplied URL.
"""
from zenml.zen_stores.rest_zen_store import RestZenStoreConfiguration
from zenml.zen_stores.sql_zen_store import SqlZenStoreConfiguration
if SqlZenStoreConfiguration.supports_url_scheme(url):
return StoreType.SQL
elif RestZenStoreConfiguration.supports_url_scheme(url):
return StoreType.REST
else:
raise TypeError(f"No store implementation found for URL: {url}.")
is_local_store(self)
Check if the store is local or connected to a local ZenML server.
Returns:
| Type | Description |
|---|---|
bool |
True if the store is local, False otherwise. |
Source code in zenml/zen_stores/base_zen_store.py
def is_local_store(self) -> bool:
"""Check if the store is local or connected to a local ZenML server.
Returns:
True if the store is local, False otherwise.
"""
return self.get_store_info().is_local()
validate_active_config(self, active_workspace_name_or_id=None, active_stack_id=None, config_name='')
Validate the active configuration.
Call this method to validate the supplied active workspace and active stack values.
This method is guaranteed to return valid workspace ID and stack ID values. If the supplied workspace and stack are not set or are not valid (e.g. they do not exist or are not accessible), the default workspace and default workspace stack will be returned in their stead.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
active_workspace_name_or_id |
Union[str, uuid.UUID] |
The name or ID of the active workspace. |
None |
active_stack_id |
Optional[uuid.UUID] |
The ID of the active stack. |
None |
config_name |
str |
The name of the configuration to validate (used in the displayed logs/messages). |
'' |
Returns:
| Type | Description |
|---|---|
Tuple[zenml.models.v2.core.workspace.WorkspaceResponse, zenml.models.v2.core.stack.StackResponse] |
A tuple containing the active workspace and active stack. |
Source code in zenml/zen_stores/base_zen_store.py
def validate_active_config(
self,
active_workspace_name_or_id: Optional[Union[str, UUID]] = None,
active_stack_id: Optional[UUID] = None,
config_name: str = "",
) -> Tuple[WorkspaceResponse, StackResponse]:
"""Validate the active configuration.
Call this method to validate the supplied active workspace and active
stack values.
This method is guaranteed to return valid workspace ID and stack ID
values. If the supplied workspace and stack are not set or are not valid
(e.g. they do not exist or are not accessible), the default workspace and
default workspace stack will be returned in their stead.
Args:
active_workspace_name_or_id: The name or ID of the active workspace.
active_stack_id: The ID of the active stack.
config_name: The name of the configuration to validate (used in the
displayed logs/messages).
Returns:
A tuple containing the active workspace and active stack.
"""
active_workspace: WorkspaceResponse
if active_workspace_name_or_id:
try:
active_workspace = self.get_workspace(
active_workspace_name_or_id
)
except KeyError:
active_workspace = self._get_default_workspace()
logger.warning(
f"The current {config_name} active workspace is no longer "
f"available. Resetting the active workspace to "
f"'{active_workspace.name}'."
)
else:
active_workspace = self._get_default_workspace()
logger.info(
f"Setting the {config_name} active workspace "
f"to '{active_workspace.name}'."
)
active_stack: StackResponse
# Sanitize the active stack
if active_stack_id:
# Ensure that the active stack is still valid
try:
active_stack = self.get_stack(stack_id=active_stack_id)
except KeyError:
logger.warning(
"The current %s active stack is no longer available. "
"Resetting the active stack to default.",
config_name,
)
active_stack = self._get_default_stack(
workspace_id=active_workspace.id
)
else:
if active_stack.workspace.id != active_workspace.id:
logger.warning(
"The current %s active stack is not part of the active "
"workspace. Resetting the active stack to default.",
config_name,
)
active_stack = self._get_default_stack(
workspace_id=active_workspace.id
)
else:
logger.warning(
"Setting the %s active stack to default.",
config_name,
)
active_stack = self._get_default_stack(
workspace_id=active_workspace.id
)
return active_workspace, active_stack
migrations
special
Alembic database migration utilities.
alembic
Alembic utilities wrapper.
The Alembic class defined here acts as a wrapper around the Alembic library that automatically configures Alembic to use the ZenML SQL store database connection.
Alembic
Alembic environment and migration API.
This class provides a wrapper around the Alembic library that automatically configures Alembic to use the ZenML SQL store database connection.
Source code in zenml/zen_stores/migrations/alembic.py
class Alembic:
"""Alembic environment and migration API.
This class provides a wrapper around the Alembic library that automatically
configures Alembic to use the ZenML SQL store database connection.
"""
def __init__(
self,
engine: Engine,
metadata: MetaData = SQLModel.metadata,
context: Optional[EnvironmentContext] = None,
**kwargs: Any,
) -> None:
"""Initialize the Alembic wrapper.
Args:
engine: The SQLAlchemy engine to use.
metadata: The SQLAlchemy metadata to use.
context: The Alembic environment context to use. If not set, a new
context is created pointing to the ZenML migrations directory.
**kwargs: Additional keyword arguments to pass to the Alembic
environment context.
"""
self.engine = engine
self.metadata = metadata
self.context_kwargs = kwargs
self.config = Config()
self.config.set_main_option(
"script_location", str(Path(__file__).parent)
)
self.script_directory = ScriptDirectory.from_config(self.config)
if context is None:
self.environment_context = EnvironmentContext(
self.config, self.script_directory
)
else:
self.environment_context = context
def db_is_empty(self) -> bool:
"""Check if the database is empty.
Returns:
True if the database is empty, False otherwise.
"""
# Check the existence of any of the SQLModel tables
return not self.engine.dialect.has_table(
self.engine.connect(), schemas.StackSchema.__tablename__
)
def run_migrations(
self,
fn: Optional[Callable[[_RevIdType, MigrationContext], List[Any]]],
) -> None:
"""Run an online migration function in the current migration context.
Args:
fn: Migration function to run. If not set, the function configured
externally by the Alembic CLI command is used.
"""
fn_context_args: Dict[Any, Any] = {}
if fn is not None:
fn_context_args["fn"] = fn
with self.engine.connect() as connection:
self.environment_context.configure(
connection=connection,
target_metadata=self.metadata,
include_object=include_object,
compare_type=True,
render_as_batch=True,
**fn_context_args,
**self.context_kwargs,
)
with self.environment_context.begin_transaction():
self.environment_context.run_migrations()
def head_revisions(self) -> List[str]:
"""Get the head database revisions.
Returns:
List of head revisions.
"""
head_revisions: List[str] = []
def do_get_head_rev(rev: _RevIdType, context: Any) -> List[Any]:
nonlocal head_revisions
for r in self.script_directory.get_heads():
if r is None:
continue
head_revisions.append(r)
return []
self.run_migrations(do_get_head_rev)
return head_revisions
def current_revisions(self) -> List[str]:
"""Get the current database revisions.
Returns:
List of head revisions.
"""
current_revisions: List[str] = []
def do_get_current_rev(rev: _RevIdType, context: Any) -> List[Any]:
nonlocal current_revisions
for r in self.script_directory.get_all_current(
rev # type:ignore [arg-type]
):
if r is None:
continue
current_revisions.append(r.revision)
return []
self.run_migrations(do_get_current_rev)
return current_revisions
def stamp(self, revision: str) -> None:
"""Stamp the revision table with the given revision without running any migrations.
Args:
revision: String revision target.
"""
def do_stamp(rev: _RevIdType, context: Any) -> List[Any]:
return self.script_directory._stamp_revs(revision, rev)
self.run_migrations(do_stamp)
def upgrade(self, revision: str = "heads") -> None:
"""Upgrade the database to a later version.
Args:
revision: String revision target.
"""
def do_upgrade(rev: _RevIdType, context: Any) -> List[Any]:
return self.script_directory._upgrade_revs(
revision,
rev, # type:ignore [arg-type]
)
self.run_migrations(do_upgrade)
def downgrade(self, revision: str) -> None:
"""Revert the database to a previous version.
Args:
revision: String revision target.
"""
def do_downgrade(rev: _RevIdType, context: Any) -> List[Any]:
return self.script_directory._downgrade_revs(
revision,
rev, # type:ignore [arg-type]
)
self.run_migrations(do_downgrade)
__init__(self, engine, metadata=MetaData(), context=None, **kwargs)
special
Initialize the Alembic wrapper.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
engine |
Engine |
The SQLAlchemy engine to use. |
required |
metadata |
MetaData |
The SQLAlchemy metadata to use. |
MetaData() |
context |
Optional[alembic.runtime.environment.EnvironmentContext] |
The Alembic environment context to use. If not set, a new context is created pointing to the ZenML migrations directory. |
None |
**kwargs |
Any |
Additional keyword arguments to pass to the Alembic environment context. |
{} |
Source code in zenml/zen_stores/migrations/alembic.py
def __init__(
self,
engine: Engine,
metadata: MetaData = SQLModel.metadata,
context: Optional[EnvironmentContext] = None,
**kwargs: Any,
) -> None:
"""Initialize the Alembic wrapper.
Args:
engine: The SQLAlchemy engine to use.
metadata: The SQLAlchemy metadata to use.
context: The Alembic environment context to use. If not set, a new
context is created pointing to the ZenML migrations directory.
**kwargs: Additional keyword arguments to pass to the Alembic
environment context.
"""
self.engine = engine
self.metadata = metadata
self.context_kwargs = kwargs
self.config = Config()
self.config.set_main_option(
"script_location", str(Path(__file__).parent)
)
self.script_directory = ScriptDirectory.from_config(self.config)
if context is None:
self.environment_context = EnvironmentContext(
self.config, self.script_directory
)
else:
self.environment_context = context
current_revisions(self)
Get the current database revisions.
Returns:
| Type | Description |
|---|---|
List[str] |
List of head revisions. |
Source code in zenml/zen_stores/migrations/alembic.py
def current_revisions(self) -> List[str]:
"""Get the current database revisions.
Returns:
List of head revisions.
"""
current_revisions: List[str] = []
def do_get_current_rev(rev: _RevIdType, context: Any) -> List[Any]:
nonlocal current_revisions
for r in self.script_directory.get_all_current(
rev # type:ignore [arg-type]
):
if r is None:
continue
current_revisions.append(r.revision)
return []
self.run_migrations(do_get_current_rev)
return current_revisions
db_is_empty(self)
Check if the database is empty.
Returns:
| Type | Description |
|---|---|
bool |
True if the database is empty, False otherwise. |
Source code in zenml/zen_stores/migrations/alembic.py
def db_is_empty(self) -> bool:
"""Check if the database is empty.
Returns:
True if the database is empty, False otherwise.
"""
# Check the existence of any of the SQLModel tables
return not self.engine.dialect.has_table(
self.engine.connect(), schemas.StackSchema.__tablename__
)
downgrade(self, revision)
Revert the database to a previous version.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
revision |
str |
String revision target. |
required |
Source code in zenml/zen_stores/migrations/alembic.py
def downgrade(self, revision: str) -> None:
"""Revert the database to a previous version.
Args:
revision: String revision target.
"""
def do_downgrade(rev: _RevIdType, context: Any) -> List[Any]:
return self.script_directory._downgrade_revs(
revision,
rev, # type:ignore [arg-type]
)
self.run_migrations(do_downgrade)
head_revisions(self)
Get the head database revisions.
Returns:
| Type | Description |
|---|---|
List[str] |
List of head revisions. |
Source code in zenml/zen_stores/migrations/alembic.py
def head_revisions(self) -> List[str]:
"""Get the head database revisions.
Returns:
List of head revisions.
"""
head_revisions: List[str] = []
def do_get_head_rev(rev: _RevIdType, context: Any) -> List[Any]:
nonlocal head_revisions
for r in self.script_directory.get_heads():
if r is None:
continue
head_revisions.append(r)
return []
self.run_migrations(do_get_head_rev)
return head_revisions
run_migrations(self, fn)
Run an online migration function in the current migration context.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
fn |
Optional[Callable[[Union[str, Sequence[str]], alembic.runtime.migration.MigrationContext], List[Any]]] |
Migration function to run. If not set, the function configured externally by the Alembic CLI command is used. |
required |
Source code in zenml/zen_stores/migrations/alembic.py
def run_migrations(
self,
fn: Optional[Callable[[_RevIdType, MigrationContext], List[Any]]],
) -> None:
"""Run an online migration function in the current migration context.
Args:
fn: Migration function to run. If not set, the function configured
externally by the Alembic CLI command is used.
"""
fn_context_args: Dict[Any, Any] = {}
if fn is not None:
fn_context_args["fn"] = fn
with self.engine.connect() as connection:
self.environment_context.configure(
connection=connection,
target_metadata=self.metadata,
include_object=include_object,
compare_type=True,
render_as_batch=True,
**fn_context_args,
**self.context_kwargs,
)
with self.environment_context.begin_transaction():
self.environment_context.run_migrations()
stamp(self, revision)
Stamp the revision table with the given revision without running any migrations.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
revision |
str |
String revision target. |
required |
Source code in zenml/zen_stores/migrations/alembic.py
def stamp(self, revision: str) -> None:
"""Stamp the revision table with the given revision without running any migrations.
Args:
revision: String revision target.
"""
def do_stamp(rev: _RevIdType, context: Any) -> List[Any]:
return self.script_directory._stamp_revs(revision, rev)
self.run_migrations(do_stamp)
upgrade(self, revision='heads')
Upgrade the database to a later version.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
revision |
str |
String revision target. |
'heads' |
Source code in zenml/zen_stores/migrations/alembic.py
def upgrade(self, revision: str = "heads") -> None:
"""Upgrade the database to a later version.
Args:
revision: String revision target.
"""
def do_upgrade(rev: _RevIdType, context: Any) -> List[Any]:
return self.script_directory._upgrade_revs(
revision,
rev, # type:ignore [arg-type]
)
self.run_migrations(do_upgrade)
AlembicVersion (Base)
Alembic version table.
Source code in zenml/zen_stores/migrations/alembic.py
class AlembicVersion(Base): # type: ignore[valid-type,misc]
"""Alembic version table."""
__tablename__ = "alembic_version"
version_num = Column(String, nullable=False, primary_key=True)
include_object(object, name, type_, *args, **kwargs)
Function used to exclude tables from the migration scripts.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
object |
Any |
The schema item object to check. |
required |
name |
str |
The name of the object to check. |
required |
type_ |
str |
The type of the object to check. |
required |
*args |
Any |
Additional arguments. |
() |
**kwargs |
Any |
Additional keyword arguments. |
{} |
Returns:
| Type | Description |
|---|---|
bool |
True if the object should be included, False otherwise. |
Source code in zenml/zen_stores/migrations/alembic.py
def include_object(
object: Any, name: str, type_: str, *args: Any, **kwargs: Any
) -> bool:
"""Function used to exclude tables from the migration scripts.
Args:
object: The schema item object to check.
name: The name of the object to check.
type_: The type of the object to check.
*args: Additional arguments.
**kwargs: Additional keyword arguments.
Returns:
True if the object should be included, False otherwise.
"""
return not (type_ == "table" and name in exclude_tables)
utils
ZenML database migration, backup and recovery utilities.
MigrationUtils (BaseModel)
pydantic-model
Utilities for database migration, backup and recovery.
Source code in zenml/zen_stores/migrations/utils.py
class MigrationUtils(BaseModel):
"""Utilities for database migration, backup and recovery."""
url: URL
connect_args: Dict[str, Any]
engine_args: Dict[str, Any]
_engine: Optional[Engine] = None
_master_engine: Optional[Engine] = None
def create_engine(self, database: Optional[str] = None) -> Engine:
"""Get the SQLAlchemy engine for a database.
Args:
database: The name of the database. If not set, a master engine
will be returned.
Returns:
The SQLAlchemy engine.
"""
url = self.url._replace(database=database)
return create_engine(
url=url,
connect_args=self.connect_args,
**self.engine_args,
)
@property
def engine(self) -> Engine:
"""The SQLAlchemy engine.
Returns:
The SQLAlchemy engine.
"""
if self._engine is None:
self._engine = self.create_engine(database=self.url.database)
return self._engine
@property
def master_engine(self) -> Engine:
"""The SQLAlchemy engine for the master database.
Returns:
The SQLAlchemy engine for the master database.
"""
if self._master_engine is None:
self._master_engine = self.create_engine()
return self._master_engine
@classmethod
def is_mysql_missing_database_error(cls, error: OperationalError) -> bool:
"""Checks if the given error is due to a missing database.
Args:
error: The error to check.
Returns:
If the error because the MySQL database doesn't exist.
"""
from pymysql.constants.ER import BAD_DB_ERROR
if not isinstance(error.orig, pymysql.err.OperationalError):
return False
error_code = cast(int, error.orig.args[0])
return error_code == BAD_DB_ERROR
def database_exists(
self,
database: Optional[str] = None,
) -> bool:
"""Check if a database exists.
Args:
database: The name of the database to check. If not set, the
database name from the configuration will be used.
Returns:
Whether the database exists.
Raises:
OperationalError: If connecting to the database failed.
"""
database = database or self.url.database
engine = self.create_engine(database=database)
try:
engine.connect()
except OperationalError as e:
if self.is_mysql_missing_database_error(e):
return False
else:
logger.exception(
f"Failed to connect to mysql database `{database}`.",
)
raise
else:
return True
def drop_database(
self,
database: Optional[str] = None,
) -> None:
"""Drops a mysql database.
Args:
database: The name of the database to drop. If not set, the
database name from the configuration will be used.
"""
database = database or self.url.database
with self.master_engine.connect() as conn:
# drop the database if it exists
logger.info(f"Dropping database '{database}'")
conn.execute(text(f"DROP DATABASE IF EXISTS `{database}`"))
def create_database(
self,
database: Optional[str] = None,
drop: bool = False,
) -> None:
"""Creates a mysql database.
Args:
database: The name of the database to create. If not set, the
database name from the configuration will be used.
drop: Whether to drop the database if it already exists.
"""
database = database or self.url.database
if drop:
self.drop_database(database=database)
with self.master_engine.connect() as conn:
logger.info(f"Creating database '{database}'")
conn.execute(text(f"CREATE DATABASE IF NOT EXISTS `{database}`"))
def backup_database_to_storage(
self, store_db_info: Callable[[Dict[str, Any]], None]
) -> None:
"""Backup the database to a storage location.
Backup the database to an abstract storage location. The storage
location is specified by a function that is called repeatedly to
store the database information. The function is called with a single
argument, which is a dictionary containing either the table schema or
table data. The dictionary contains the following keys:
* `table`: The name of the table.
* `create_stmt`: The table creation statement.
* `data`: A list of rows in the table.
Args:
store_db_info: The function to call to store the database
information.
"""
metadata = MetaData()
metadata.reflect(bind=self.engine)
with self.engine.connect() as conn:
for table in metadata.sorted_tables:
# 1. extract the table creation statements
create_table_construct = CreateTable(table)
create_table_stmt = str(create_table_construct).strip()
for column in create_table_construct.columns:
# enclosing all column names in backticks. This is because
# some column names are reserved keywords in MySQL. For
# example, keys and values. So, instead of tracking all
# keywords, we just enclose all column names in backticks.
# enclose the first word in the column definition in
# backticks
words = str(column).split()
words[0] = f"`{words[0]}`"
create_table_stmt = create_table_stmt.replace(
f"\n\t{str(column)}", " ".join(words)
)
# if any double quotes are used for column names, replace them
# with backticks
create_table_stmt = create_table_stmt.replace('"', "") + ";"
# Store the table schema
store_db_info(
dict(table=table.name, create_stmt=create_table_stmt)
)
# 2. extract the table data in batches
# If the table has a `created` column, we use it to sort
# the rows in the table starting with the oldest rows.
# This is to ensure that the rows are inserted in the
# correct order, since some tables have inner foreign key
# constraints.
if "created" in table.columns:
order_by = table.columns["created"]
else:
order_by = None
# Fetch the number of rows in the table
row_count = conn.scalar(
select([func.count("*")]).select_from(table)
)
# Fetch the data from the table in batches
batch_size = 50
for i in range(0, row_count, batch_size):
rows = conn.execute(
table.select()
.order_by(order_by)
.limit(batch_size)
.offset(i)
).fetchall()
store_db_info(
dict(
table=table.name,
data=[row._asdict() for row in rows],
),
)
def restore_database_from_storage(
self, load_db_info: Callable[[], Generator[Dict[str, Any], None, None]]
) -> None:
"""Restore the database from a backup storage location.
Restores the database from an abstract storage location. The storage
location is specified by a function that is called repeatedly to
load the database information from the external storage chunk by chunk.
The function must yield a dictionary containing either the table schema
or table data. The dictionary contains the following keys:
* `table`: The name of the table.
* `create_stmt`: The table creation statement.
* `data`: A list of rows in the table.
The function must return `None` when there is no more data to load.
Args:
load_db_info: The function to call to load the database
information.
"""
# Drop and re-create the primary database
self.create_database(
drop=True,
)
metadata = MetaData(bind=self.engine)
with self.engine.begin() as connection:
# read the DB information one JSON object at a time
for table_dump in load_db_info():
table_name = table_dump["table"]
if "create_stmt" in table_dump:
# execute the table creation statement
connection.execute(text(table_dump["create_stmt"]))
# Reload the database metadata after creating the table
metadata.reflect()
if "data" in table_dump:
# insert the data into the database
table = metadata.tables[table_name]
for row in table_dump["data"]:
# Convert column values to the correct type
for column in table.columns:
# Blob columns are stored as binary strings
if column.type.python_type == bytes and isinstance(
row[column.name], str
):
# Convert the string to bytes
row[column.name] = bytes(
row[column.name], "utf-8"
)
# Insert the rows into the table
connection.execute(
table.insert().values(table_dump["data"])
)
def backup_database_to_file(self, dump_file: str) -> None:
"""Backup the database to a file.
This method dumps the entire database into a JSON file. Instead of
using a SQL dump, we use a proprietary JSON dump because:
* it is (mostly) not dependent on the SQL dialect or database version
* it is safer with respect to SQL injection attacks
* it is easier to read and debug
The JSON file contains a list of JSON objects instead of a single JSON
object, because it allows for buffered reading and writing of the file
and thus reduces the memory footprint. Each JSON object can contain
either schema or data information about a single table. For tables with
a large amount of data, the data is split into multiple JSON objects
with the first object always containing the schema.
The format of the dump is as depicted in the following example:
```json
{
"table": "table1",
"create_stmt": "CREATE TABLE table1 (id INTEGER NOT NULL, "
"name VARCHAR(255), PRIMARY KEY (id))"
}
{
"table": "table1",
"data": [
{
"id": 1,
"name": "foo"
},
{
"id": 1,
"name": "bar"
},
...
]
}
{
"table": "table1",
"data": [
{
"id": 101,
"name": "fee"
},
{
"id": 102,
"name": "bee"
},
...
]
}
```
Args:
dump_file: The path to the dump file.
"""
# create the directory if it does not exist
dump_path = os.path.dirname(os.path.abspath(dump_file))
if not os.path.exists(dump_path):
os.makedirs(dump_path)
if self.url.drivername == "sqlite":
# For a sqlite database, we can just make a copy of the database
# file
assert self.url.database is not None
shutil.copyfile(
self.url.database,
dump_file,
)
return
with open(dump_file, "w") as f:
def json_dump(obj: Dict[str, Any]) -> None:
"""Dump a JSON object to the dump file.
Args:
obj: The JSON object to dump.
"""
# Write the data to the JSON file. Use an encoder that
# can handle datetime, Decimal and other types.
json.dump(
obj,
f,
indent=4,
default=pydantic_encoder,
)
f.write("\n")
# Call the generic backup method with a function that dumps the
# JSON objects to the dump file
self.backup_database_to_storage(json_dump)
logger.debug(f"Database backed up to {dump_file}")
def restore_database_from_file(self, dump_file: str) -> None:
"""Restore the database from a backup dump file.
See the documentation of the `backup_database_to_file` method for
details on the format of the dump file.
Args:
dump_file: The path to the dump file.
Raises:
RuntimeError: If the database cannot be restored successfully.
"""
if not os.path.exists(dump_file):
raise RuntimeError(
f"Database backup file '{dump_file}' does not "
f"exist or is not accessible."
)
if self.url.drivername == "sqlite":
# For a sqlite database, we just overwrite the database file
# with the backup file
assert self.url.database is not None
shutil.copyfile(
dump_file,
self.url.database,
)
return
# read the DB dump file one JSON object at a time
with open(dump_file, "r") as f:
def json_load() -> Generator[Dict[str, Any], None, None]:
"""Generator that loads the JSON objects in the dump file.
Yields:
The loaded JSON objects.
"""
buffer = ""
while True:
chunk = f.readline()
if not chunk:
break
buffer += chunk
if chunk.rstrip() == "}":
yield json.loads(buffer)
buffer = ""
# Call the generic restore method with a function that loads the
# JSON objects from the dump file
self.restore_database_from_storage(json_load)
logger.info(f"Database successfully restored from '{dump_file}'")
def backup_database_to_memory(self) -> List[Dict[str, Any]]:
"""Backup the database in memory.
Returns:
The in-memory representation of the database backup.
Raises:
RuntimeError: If the database cannot be backed up successfully.
"""
if self.url.drivername == "sqlite":
# For a sqlite database, this is not supported.
raise RuntimeError(
"In-memory backup is not supported for sqlite databases."
)
db_dump: List[Dict[str, Any]] = []
def store_in_mem(obj: Dict[str, Any]) -> None:
"""Store a JSON object in the in-memory database backup.
Args:
obj: The JSON object to store.
"""
db_dump.append(obj)
# Call the generic backup method with a function that stores the
# JSON objects in the in-memory database backup
self.backup_database_to_storage(store_in_mem)
logger.debug("Database backed up in memory")
return db_dump
def restore_database_from_memory(
self, db_dump: List[Dict[str, Any]]
) -> None:
"""Restore the database from an in-memory backup.
Args:
db_dump: The in-memory database backup to restore from generated
by the `backup_database_to_memory` method.
Raises:
RuntimeError: If the database cannot be restored successfully.
"""
if self.url.drivername == "sqlite":
# For a sqlite database, this is not supported.
raise RuntimeError(
"In-memory backup is not supported for sqlite databases."
)
def load_from_mem() -> Generator[Dict[str, Any], None, None]:
"""Generator that loads the JSON objects from the in-memory backup.
Yields:
The loaded JSON objects.
"""
for obj in db_dump:
yield obj
# Call the generic restore method with a function that loads the
# JSON objects from the in-memory database backup
self.restore_database_from_storage(load_from_mem)
logger.info("Database successfully restored from memory")
@classmethod
def _copy_database(cls, src_engine: Engine, dst_engine: Engine) -> None:
"""Copy the database from one engine to another.
This method assumes that the destination database exists and is empty.
Args:
src_engine: The source SQLAlchemy engine.
dst_engine: The destination SQLAlchemy engine.
"""
src_metadata = MetaData(bind=src_engine)
src_metadata.reflect()
dst_metadata = MetaData(bind=dst_engine)
dst_metadata.reflect()
# @event.listens_for(src_metadata, "column_reflect")
# def generalize_datatypes(inspector, tablename, column_dict):
# column_dict["type"] = column_dict["type"].as_generic(allow_nulltype=True)
# Create all tables in the target database
for table in src_metadata.sorted_tables:
table.create(bind=dst_engine)
# Refresh target metadata after creating the tables
dst_metadata.clear()
dst_metadata.reflect()
# Copy all data from the source database to the destination database
with src_engine.begin() as src_conn:
with dst_engine.begin() as dst_conn:
for src_table in src_metadata.sorted_tables:
dst_table = dst_metadata.tables[src_table.name]
insert = dst_table.insert()
# If the table has a `created` column, we use it to sort
# the rows in the table starting with the oldest rows.
# This is to ensure that the rows are inserted in the
# correct order, since some tables have inner foreign key
# constraints.
if "created" in src_table.columns:
order_by = src_table.columns["created"]
else:
order_by = None
row_count = src_conn.scalar(
select([func.count("*")]).select_from(src_table)
)
# Copy rows in batches
batch_size = 50
for i in range(0, row_count, batch_size):
rows = src_conn.execute(
src_table.select()
.order_by(order_by)
.limit(batch_size)
.offset(i)
).fetchall()
dst_conn.execute(
insert, [row._asdict() for row in rows]
)
def backup_database_to_db(self, backup_db_name: str) -> None:
"""Backup the database to a backup database.
Args:
backup_db_name: Backup database name to backup to.
"""
# Re-create the backup database
self.create_database(
database=backup_db_name,
drop=True,
)
backup_engine = self.create_engine(database=backup_db_name)
self._copy_database(self.engine, backup_engine)
logger.debug(
f"Database backed up to the `{backup_db_name}` backup database."
)
def restore_database_from_db(self, backup_db_name: str) -> None:
"""Restore the database from the backup database.
Args:
backup_db_name: Backup database name to restore from.
Raises:
RuntimeError: If the backup database does not exist.
"""
if not self.database_exists(database=backup_db_name):
raise RuntimeError(
f"Backup database `{backup_db_name}` does not exist."
)
backup_engine = self.create_engine(database=backup_db_name)
# Drop and re-create the primary database
self.create_database(
drop=True,
)
self._copy_database(backup_engine, self.engine)
logger.debug(
f"Database restored from the `{backup_db_name}` "
"backup database."
)
class Config:
"""Pydantic configuration class."""
# all attributes with leading underscore are private
underscore_attrs_are_private = True
engine: Engine
property
readonly
The SQLAlchemy engine.
Returns:
| Type | Description |
|---|---|
Engine |
The SQLAlchemy engine. |
master_engine: Engine
property
readonly
The SQLAlchemy engine for the master database.
Returns:
| Type | Description |
|---|---|
Engine |
The SQLAlchemy engine for the master database. |
Config
Pydantic configuration class.
Source code in zenml/zen_stores/migrations/utils.py
class Config:
"""Pydantic configuration class."""
# all attributes with leading underscore are private
underscore_attrs_are_private = True
backup_database_to_db(self, backup_db_name)
Backup the database to a backup database.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
backup_db_name |
str |
Backup database name to backup to. |
required |
Source code in zenml/zen_stores/migrations/utils.py
def backup_database_to_db(self, backup_db_name: str) -> None:
"""Backup the database to a backup database.
Args:
backup_db_name: Backup database name to backup to.
"""
# Re-create the backup database
self.create_database(
database=backup_db_name,
drop=True,
)
backup_engine = self.create_engine(database=backup_db_name)
self._copy_database(self.engine, backup_engine)
logger.debug(
f"Database backed up to the `{backup_db_name}` backup database."
)
backup_database_to_file(self, dump_file)
Backup the database to a file.
This method dumps the entire database into a JSON file. Instead of using a SQL dump, we use a proprietary JSON dump because:
* it is (mostly) not dependent on the SQL dialect or database version
* it is safer with respect to SQL injection attacks
* it is easier to read and debug
The JSON file contains a list of JSON objects instead of a single JSON object, because it allows for buffered reading and writing of the file and thus reduces the memory footprint. Each JSON object can contain either schema or data information about a single table. For tables with a large amount of data, the data is split into multiple JSON objects with the first object always containing the schema.
The format of the dump is as depicted in the following example:
{
"table": "table1",
"create_stmt": "CREATE TABLE table1 (id INTEGER NOT NULL, "
"name VARCHAR(255), PRIMARY KEY (id))"
}
{
"table": "table1",
"data": [
{
"id": 1,
"name": "foo"
},
{
"id": 1,
"name": "bar"
},
...
]
}
{
"table": "table1",
"data": [
{
"id": 101,
"name": "fee"
},
{
"id": 102,
"name": "bee"
},
...
]
}
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
dump_file |
str |
The path to the dump file. |
required |
Source code in zenml/zen_stores/migrations/utils.py
def backup_database_to_file(self, dump_file: str) -> None:
"""Backup the database to a file.
This method dumps the entire database into a JSON file. Instead of
using a SQL dump, we use a proprietary JSON dump because:
* it is (mostly) not dependent on the SQL dialect or database version
* it is safer with respect to SQL injection attacks
* it is easier to read and debug
The JSON file contains a list of JSON objects instead of a single JSON
object, because it allows for buffered reading and writing of the file
and thus reduces the memory footprint. Each JSON object can contain
either schema or data information about a single table. For tables with
a large amount of data, the data is split into multiple JSON objects
with the first object always containing the schema.
The format of the dump is as depicted in the following example:
```json
{
"table": "table1",
"create_stmt": "CREATE TABLE table1 (id INTEGER NOT NULL, "
"name VARCHAR(255), PRIMARY KEY (id))"
}
{
"table": "table1",
"data": [
{
"id": 1,
"name": "foo"
},
{
"id": 1,
"name": "bar"
},
...
]
}
{
"table": "table1",
"data": [
{
"id": 101,
"name": "fee"
},
{
"id": 102,
"name": "bee"
},
...
]
}
```
Args:
dump_file: The path to the dump file.
"""
# create the directory if it does not exist
dump_path = os.path.dirname(os.path.abspath(dump_file))
if not os.path.exists(dump_path):
os.makedirs(dump_path)
if self.url.drivername == "sqlite":
# For a sqlite database, we can just make a copy of the database
# file
assert self.url.database is not None
shutil.copyfile(
self.url.database,
dump_file,
)
return
with open(dump_file, "w") as f:
def json_dump(obj: Dict[str, Any]) -> None:
"""Dump a JSON object to the dump file.
Args:
obj: The JSON object to dump.
"""
# Write the data to the JSON file. Use an encoder that
# can handle datetime, Decimal and other types.
json.dump(
obj,
f,
indent=4,
default=pydantic_encoder,
)
f.write("\n")
# Call the generic backup method with a function that dumps the
# JSON objects to the dump file
self.backup_database_to_storage(json_dump)
logger.debug(f"Database backed up to {dump_file}")
backup_database_to_memory(self)
Backup the database in memory.
Returns:
| Type | Description |
|---|---|
List[Dict[str, Any]] |
The in-memory representation of the database backup. |
Exceptions:
| Type | Description |
|---|---|
RuntimeError |
If the database cannot be backed up successfully. |
Source code in zenml/zen_stores/migrations/utils.py
def backup_database_to_memory(self) -> List[Dict[str, Any]]:
"""Backup the database in memory.
Returns:
The in-memory representation of the database backup.
Raises:
RuntimeError: If the database cannot be backed up successfully.
"""
if self.url.drivername == "sqlite":
# For a sqlite database, this is not supported.
raise RuntimeError(
"In-memory backup is not supported for sqlite databases."
)
db_dump: List[Dict[str, Any]] = []
def store_in_mem(obj: Dict[str, Any]) -> None:
"""Store a JSON object in the in-memory database backup.
Args:
obj: The JSON object to store.
"""
db_dump.append(obj)
# Call the generic backup method with a function that stores the
# JSON objects in the in-memory database backup
self.backup_database_to_storage(store_in_mem)
logger.debug("Database backed up in memory")
return db_dump
backup_database_to_storage(self, store_db_info)
Backup the database to a storage location.
Backup the database to an abstract storage location. The storage location is specified by a function that is called repeatedly to store the database information. The function is called with a single argument, which is a dictionary containing either the table schema or table data. The dictionary contains the following keys:
* `table`: The name of the table.
* `create_stmt`: The table creation statement.
* `data`: A list of rows in the table.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
store_db_info |
Callable[[Dict[str, Any]], NoneType] |
The function to call to store the database information. |
required |
Source code in zenml/zen_stores/migrations/utils.py
def backup_database_to_storage(
self, store_db_info: Callable[[Dict[str, Any]], None]
) -> None:
"""Backup the database to a storage location.
Backup the database to an abstract storage location. The storage
location is specified by a function that is called repeatedly to
store the database information. The function is called with a single
argument, which is a dictionary containing either the table schema or
table data. The dictionary contains the following keys:
* `table`: The name of the table.
* `create_stmt`: The table creation statement.
* `data`: A list of rows in the table.
Args:
store_db_info: The function to call to store the database
information.
"""
metadata = MetaData()
metadata.reflect(bind=self.engine)
with self.engine.connect() as conn:
for table in metadata.sorted_tables:
# 1. extract the table creation statements
create_table_construct = CreateTable(table)
create_table_stmt = str(create_table_construct).strip()
for column in create_table_construct.columns:
# enclosing all column names in backticks. This is because
# some column names are reserved keywords in MySQL. For
# example, keys and values. So, instead of tracking all
# keywords, we just enclose all column names in backticks.
# enclose the first word in the column definition in
# backticks
words = str(column).split()
words[0] = f"`{words[0]}`"
create_table_stmt = create_table_stmt.replace(
f"\n\t{str(column)}", " ".join(words)
)
# if any double quotes are used for column names, replace them
# with backticks
create_table_stmt = create_table_stmt.replace('"', "") + ";"
# Store the table schema
store_db_info(
dict(table=table.name, create_stmt=create_table_stmt)
)
# 2. extract the table data in batches
# If the table has a `created` column, we use it to sort
# the rows in the table starting with the oldest rows.
# This is to ensure that the rows are inserted in the
# correct order, since some tables have inner foreign key
# constraints.
if "created" in table.columns:
order_by = table.columns["created"]
else:
order_by = None
# Fetch the number of rows in the table
row_count = conn.scalar(
select([func.count("*")]).select_from(table)
)
# Fetch the data from the table in batches
batch_size = 50
for i in range(0, row_count, batch_size):
rows = conn.execute(
table.select()
.order_by(order_by)
.limit(batch_size)
.offset(i)
).fetchall()
store_db_info(
dict(
table=table.name,
data=[row._asdict() for row in rows],
),
)
create_database(self, database=None, drop=False)
Creates a mysql database.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
database |
Optional[str] |
The name of the database to create. If not set, the database name from the configuration will be used. |
None |
drop |
bool |
Whether to drop the database if it already exists. |
False |
Source code in zenml/zen_stores/migrations/utils.py
def create_database(
self,
database: Optional[str] = None,
drop: bool = False,
) -> None:
"""Creates a mysql database.
Args:
database: The name of the database to create. If not set, the
database name from the configuration will be used.
drop: Whether to drop the database if it already exists.
"""
database = database or self.url.database
if drop:
self.drop_database(database=database)
with self.master_engine.connect() as conn:
logger.info(f"Creating database '{database}'")
conn.execute(text(f"CREATE DATABASE IF NOT EXISTS `{database}`"))
create_engine(self, database=None)
Get the SQLAlchemy engine for a database.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
database |
Optional[str] |
The name of the database. If not set, a master engine will be returned. |
None |
Returns:
| Type | Description |
|---|---|
Engine |
The SQLAlchemy engine. |
Source code in zenml/zen_stores/migrations/utils.py
def create_engine(self, database: Optional[str] = None) -> Engine:
"""Get the SQLAlchemy engine for a database.
Args:
database: The name of the database. If not set, a master engine
will be returned.
Returns:
The SQLAlchemy engine.
"""
url = self.url._replace(database=database)
return create_engine(
url=url,
connect_args=self.connect_args,
**self.engine_args,
)
database_exists(self, database=None)
Check if a database exists.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
database |
Optional[str] |
The name of the database to check. If not set, the database name from the configuration will be used. |
None |
Returns:
| Type | Description |
|---|---|
bool |
Whether the database exists. |
Exceptions:
| Type | Description |
|---|---|
OperationalError |
If connecting to the database failed. |
Source code in zenml/zen_stores/migrations/utils.py
def database_exists(
self,
database: Optional[str] = None,
) -> bool:
"""Check if a database exists.
Args:
database: The name of the database to check. If not set, the
database name from the configuration will be used.
Returns:
Whether the database exists.
Raises:
OperationalError: If connecting to the database failed.
"""
database = database or self.url.database
engine = self.create_engine(database=database)
try:
engine.connect()
except OperationalError as e:
if self.is_mysql_missing_database_error(e):
return False
else:
logger.exception(
f"Failed to connect to mysql database `{database}`.",
)
raise
else:
return True
drop_database(self, database=None)
Drops a mysql database.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
database |
Optional[str] |
The name of the database to drop. If not set, the database name from the configuration will be used. |
None |
Source code in zenml/zen_stores/migrations/utils.py
def drop_database(
self,
database: Optional[str] = None,
) -> None:
"""Drops a mysql database.
Args:
database: The name of the database to drop. If not set, the
database name from the configuration will be used.
"""
database = database or self.url.database
with self.master_engine.connect() as conn:
# drop the database if it exists
logger.info(f"Dropping database '{database}'")
conn.execute(text(f"DROP DATABASE IF EXISTS `{database}`"))
is_mysql_missing_database_error(error)
classmethod
Checks if the given error is due to a missing database.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
error |
OperationalError |
The error to check. |
required |
Returns:
| Type | Description |
|---|---|
bool |
If the error because the MySQL database doesn't exist. |
Source code in zenml/zen_stores/migrations/utils.py
@classmethod
def is_mysql_missing_database_error(cls, error: OperationalError) -> bool:
"""Checks if the given error is due to a missing database.
Args:
error: The error to check.
Returns:
If the error because the MySQL database doesn't exist.
"""
from pymysql.constants.ER import BAD_DB_ERROR
if not isinstance(error.orig, pymysql.err.OperationalError):
return False
error_code = cast(int, error.orig.args[0])
return error_code == BAD_DB_ERROR
restore_database_from_db(self, backup_db_name)
Restore the database from the backup database.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
backup_db_name |
str |
Backup database name to restore from. |
required |
Exceptions:
| Type | Description |
|---|---|
RuntimeError |
If the backup database does not exist. |
Source code in zenml/zen_stores/migrations/utils.py
def restore_database_from_db(self, backup_db_name: str) -> None:
"""Restore the database from the backup database.
Args:
backup_db_name: Backup database name to restore from.
Raises:
RuntimeError: If the backup database does not exist.
"""
if not self.database_exists(database=backup_db_name):
raise RuntimeError(
f"Backup database `{backup_db_name}` does not exist."
)
backup_engine = self.create_engine(database=backup_db_name)
# Drop and re-create the primary database
self.create_database(
drop=True,
)
self._copy_database(backup_engine, self.engine)
logger.debug(
f"Database restored from the `{backup_db_name}` "
"backup database."
)
restore_database_from_file(self, dump_file)
Restore the database from a backup dump file.
See the documentation of the backup_database_to_file method for
details on the format of the dump file.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
dump_file |
str |
The path to the dump file. |
required |
Exceptions:
| Type | Description |
|---|---|
RuntimeError |
If the database cannot be restored successfully. |
Source code in zenml/zen_stores/migrations/utils.py
def restore_database_from_file(self, dump_file: str) -> None:
"""Restore the database from a backup dump file.
See the documentation of the `backup_database_to_file` method for
details on the format of the dump file.
Args:
dump_file: The path to the dump file.
Raises:
RuntimeError: If the database cannot be restored successfully.
"""
if not os.path.exists(dump_file):
raise RuntimeError(
f"Database backup file '{dump_file}' does not "
f"exist or is not accessible."
)
if self.url.drivername == "sqlite":
# For a sqlite database, we just overwrite the database file
# with the backup file
assert self.url.database is not None
shutil.copyfile(
dump_file,
self.url.database,
)
return
# read the DB dump file one JSON object at a time
with open(dump_file, "r") as f:
def json_load() -> Generator[Dict[str, Any], None, None]:
"""Generator that loads the JSON objects in the dump file.
Yields:
The loaded JSON objects.
"""
buffer = ""
while True:
chunk = f.readline()
if not chunk:
break
buffer += chunk
if chunk.rstrip() == "}":
yield json.loads(buffer)
buffer = ""
# Call the generic restore method with a function that loads the
# JSON objects from the dump file
self.restore_database_from_storage(json_load)
logger.info(f"Database successfully restored from '{dump_file}'")
restore_database_from_memory(self, db_dump)
Restore the database from an in-memory backup.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
db_dump |
List[Dict[str, Any]] |
The in-memory database backup to restore from generated
by the |
required |
Exceptions:
| Type | Description |
|---|---|
RuntimeError |
If the database cannot be restored successfully. |
Source code in zenml/zen_stores/migrations/utils.py
def restore_database_from_memory(
self, db_dump: List[Dict[str, Any]]
) -> None:
"""Restore the database from an in-memory backup.
Args:
db_dump: The in-memory database backup to restore from generated
by the `backup_database_to_memory` method.
Raises:
RuntimeError: If the database cannot be restored successfully.
"""
if self.url.drivername == "sqlite":
# For a sqlite database, this is not supported.
raise RuntimeError(
"In-memory backup is not supported for sqlite databases."
)
def load_from_mem() -> Generator[Dict[str, Any], None, None]:
"""Generator that loads the JSON objects from the in-memory backup.
Yields:
The loaded JSON objects.
"""
for obj in db_dump:
yield obj
# Call the generic restore method with a function that loads the
# JSON objects from the in-memory database backup
self.restore_database_from_storage(load_from_mem)
logger.info("Database successfully restored from memory")
restore_database_from_storage(self, load_db_info)
Restore the database from a backup storage location.
Restores the database from an abstract storage location. The storage location is specified by a function that is called repeatedly to load the database information from the external storage chunk by chunk. The function must yield a dictionary containing either the table schema or table data. The dictionary contains the following keys:
* `table`: The name of the table.
* `create_stmt`: The table creation statement.
* `data`: A list of rows in the table.
The function must return None when there is no more data to load.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
load_db_info |
Callable[[], Generator[Dict[str, Any], NoneType, NoneType]] |
The function to call to load the database information. |
required |
Source code in zenml/zen_stores/migrations/utils.py
def restore_database_from_storage(
self, load_db_info: Callable[[], Generator[Dict[str, Any], None, None]]
) -> None:
"""Restore the database from a backup storage location.
Restores the database from an abstract storage location. The storage
location is specified by a function that is called repeatedly to
load the database information from the external storage chunk by chunk.
The function must yield a dictionary containing either the table schema
or table data. The dictionary contains the following keys:
* `table`: The name of the table.
* `create_stmt`: The table creation statement.
* `data`: A list of rows in the table.
The function must return `None` when there is no more data to load.
Args:
load_db_info: The function to call to load the database
information.
"""
# Drop and re-create the primary database
self.create_database(
drop=True,
)
metadata = MetaData(bind=self.engine)
with self.engine.begin() as connection:
# read the DB information one JSON object at a time
for table_dump in load_db_info():
table_name = table_dump["table"]
if "create_stmt" in table_dump:
# execute the table creation statement
connection.execute(text(table_dump["create_stmt"]))
# Reload the database metadata after creating the table
metadata.reflect()
if "data" in table_dump:
# insert the data into the database
table = metadata.tables[table_name]
for row in table_dump["data"]:
# Convert column values to the correct type
for column in table.columns:
# Blob columns are stored as binary strings
if column.type.python_type == bytes and isinstance(
row[column.name], str
):
# Convert the string to bytes
row[column.name] = bytes(
row[column.name], "utf-8"
)
# Insert the rows into the table
connection.execute(
table.insert().values(table_dump["data"])
)
rest_zen_store
REST Zen Store implementation.
RestZenStore (BaseZenStore)
pydantic-model
Store implementation for accessing data from a REST API.
Source code in zenml/zen_stores/rest_zen_store.py
class RestZenStore(BaseZenStore):
"""Store implementation for accessing data from a REST API."""
config: RestZenStoreConfiguration
TYPE: ClassVar[StoreType] = StoreType.REST
CONFIG_TYPE: ClassVar[Type[StoreConfiguration]] = RestZenStoreConfiguration
_api_token: Optional[str] = None
_session: Optional[requests.Session] = None
# ====================================
# ZenML Store interface implementation
# ====================================
# --------------------------------
# Initialization and configuration
# --------------------------------
def _initialize(self) -> None:
"""Initialize the REST store."""
client_version = zenml.__version__
server_version = self.get_store_info().version
if not DISABLE_CLIENT_SERVER_MISMATCH_WARNING and (
server_version != client_version
):
logger.warning(
"Your ZenML client version (%s) does not match the server "
"version (%s). This version mismatch might lead to errors or "
"unexpected behavior. \nTo disable this warning message, set "
"the environment variable `%s=True`",
client_version,
server_version,
ENV_ZENML_DISABLE_CLIENT_SERVER_MISMATCH_WARNING,
)
def get_store_info(self) -> ServerModel:
"""Get information about the server.
Returns:
Information about the server.
"""
body = self.get(INFO)
return ServerModel.parse_obj(body)
def get_deployment_id(self) -> UUID:
"""Get the ID of the deployment.
Returns:
The ID of the deployment.
"""
return self.get_store_info().id
# ----------------------------- API Keys -----------------------------
def create_api_key(
self, service_account_id: UUID, api_key: APIKeyRequest
) -> APIKeyResponse:
"""Create a new API key for a service account.
Args:
service_account_id: The ID of the service account for which to
create the API key.
api_key: The API key to create.
Returns:
The created API key.
"""
return self._create_resource(
resource=api_key,
route=f"{SERVICE_ACCOUNTS}/{str(service_account_id)}{API_KEYS}",
response_model=APIKeyResponse,
)
def get_api_key(
self,
service_account_id: UUID,
api_key_name_or_id: Union[str, UUID],
hydrate: bool = True,
) -> APIKeyResponse:
"""Get an API key for a service account.
Args:
service_account_id: The ID of the service account for which to fetch
the API key.
api_key_name_or_id: The name or ID of the API key to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The API key with the given ID.
"""
return self._get_resource(
resource_id=api_key_name_or_id,
route=f"{SERVICE_ACCOUNTS}/{str(service_account_id)}{API_KEYS}",
response_model=APIKeyResponse,
params={"hydrate": hydrate},
)
def set_api_key(self, api_key: str) -> None:
"""Set the API key to use for authentication.
Args:
api_key: The API key to use for authentication.
"""
self.config.api_key = api_key
self.clear_session()
# TODO: find a way to persist the API key in the configuration file
# without calling _write_config() here.
# This is the only place where we need to explicitly call
# _write_config() to persist the global configuration.
GlobalConfiguration()._write_config()
def list_api_keys(
self,
service_account_id: UUID,
filter_model: APIKeyFilter,
hydrate: bool = False,
) -> Page[APIKeyResponse]:
"""List all API keys for a service account matching the given filter criteria.
Args:
service_account_id: The ID of the service account for which to list
the API keys.
filter_model: All filter parameters including pagination
params
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all API keys matching the filter criteria.
"""
return self._list_paginated_resources(
route=f"{SERVICE_ACCOUNTS}/{str(service_account_id)}{API_KEYS}",
response_model=APIKeyResponse,
filter_model=filter_model,
params={"hydrate": hydrate},
)
def update_api_key(
self,
service_account_id: UUID,
api_key_name_or_id: Union[str, UUID],
api_key_update: APIKeyUpdate,
) -> APIKeyResponse:
"""Update an API key for a service account.
Args:
service_account_id: The ID of the service account for which to
update the API key.
api_key_name_or_id: The name or ID of the API key to update.
api_key_update: The update request on the API key.
Returns:
The updated API key.
"""
return self._update_resource(
resource_id=api_key_name_or_id,
resource_update=api_key_update,
route=f"{SERVICE_ACCOUNTS}/{str(service_account_id)}{API_KEYS}",
response_model=APIKeyResponse,
)
def rotate_api_key(
self,
service_account_id: UUID,
api_key_name_or_id: Union[str, UUID],
rotate_request: APIKeyRotateRequest,
) -> APIKeyResponse:
"""Rotate an API key for a service account.
Args:
service_account_id: The ID of the service account for which to
rotate the API key.
api_key_name_or_id: The name or ID of the API key to rotate.
rotate_request: The rotate request on the API key.
Returns:
The updated API key.
"""
response_body = self.put(
f"{SERVICE_ACCOUNTS}/{str(service_account_id)}{API_KEYS}/{str(api_key_name_or_id)}{API_KEY_ROTATE}",
body=rotate_request,
)
return APIKeyResponse.parse_obj(response_body)
def delete_api_key(
self,
service_account_id: UUID,
api_key_name_or_id: Union[str, UUID],
) -> None:
"""Delete an API key for a service account.
Args:
service_account_id: The ID of the service account for which to
delete the API key.
api_key_name_or_id: The name or ID of the API key to delete.
"""
self._delete_resource(
resource_id=api_key_name_or_id,
route=f"{SERVICE_ACCOUNTS}/{str(service_account_id)}{API_KEYS}",
)
# ----------------------------- Artifacts -----------------------------
def create_artifact(self, artifact: ArtifactRequest) -> ArtifactResponse:
"""Creates a new artifact.
Args:
artifact: The artifact to create.
Returns:
The newly created artifact.
"""
return self._create_resource(
resource=artifact,
response_model=ArtifactResponse,
route=ARTIFACTS,
)
def get_artifact(
self, artifact_id: UUID, hydrate: bool = True
) -> ArtifactResponse:
"""Gets an artifact.
Args:
artifact_id: The ID of the artifact to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The artifact.
"""
return self._get_resource(
resource_id=artifact_id,
route=ARTIFACTS,
response_model=ArtifactResponse,
params={"hydrate": hydrate},
)
def list_artifacts(
self, filter_model: ArtifactFilter, hydrate: bool = False
) -> Page[ArtifactResponse]:
"""List all artifacts matching the given filter criteria.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all artifacts matching the filter criteria.
"""
return self._list_paginated_resources(
route=ARTIFACTS,
response_model=ArtifactResponse,
filter_model=filter_model,
params={"hydrate": hydrate},
)
def update_artifact(
self, artifact_id: UUID, artifact_update: ArtifactUpdate
) -> ArtifactResponse:
"""Updates an artifact.
Args:
artifact_id: The ID of the artifact to update.
artifact_update: The update to be applied to the artifact.
Returns:
The updated artifact.
"""
return self._update_resource(
resource_id=artifact_id,
resource_update=artifact_update,
response_model=ArtifactResponse,
route=ARTIFACTS,
)
def delete_artifact(self, artifact_id: UUID) -> None:
"""Deletes an artifact.
Args:
artifact_id: The ID of the artifact to delete.
"""
self._delete_resource(resource_id=artifact_id, route=ARTIFACTS)
# -------------------- Artifact Versions --------------------
def create_artifact_version(
self, artifact_version: ArtifactVersionRequest
) -> ArtifactVersionResponse:
"""Creates an artifact version.
Args:
artifact_version: The artifact version to create.
Returns:
The created artifact version.
"""
return self._create_resource(
resource=artifact_version,
response_model=ArtifactVersionResponse,
route=ARTIFACT_VERSIONS,
)
def get_artifact_version(
self, artifact_version_id: UUID, hydrate: bool = True
) -> ArtifactVersionResponse:
"""Gets an artifact.
Args:
artifact_version_id: The ID of the artifact version to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The artifact version.
"""
return self._get_resource(
resource_id=artifact_version_id,
route=ARTIFACT_VERSIONS,
response_model=ArtifactVersionResponse,
params={"hydrate": hydrate},
)
def list_artifact_versions(
self,
artifact_version_filter_model: ArtifactVersionFilter,
hydrate: bool = False,
) -> Page[ArtifactVersionResponse]:
"""List all artifact versions matching the given filter criteria.
Args:
artifact_version_filter_model: All filter parameters including
pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all artifact versions matching the filter criteria.
"""
return self._list_paginated_resources(
route=ARTIFACT_VERSIONS,
response_model=ArtifactVersionResponse,
filter_model=artifact_version_filter_model,
params={"hydrate": hydrate},
)
def update_artifact_version(
self,
artifact_version_id: UUID,
artifact_version_update: ArtifactVersionUpdate,
) -> ArtifactVersionResponse:
"""Updates an artifact version.
Args:
artifact_version_id: The ID of the artifact version to update.
artifact_version_update: The update to be applied to the artifact
version.
Returns:
The updated artifact version.
"""
return self._update_resource(
resource_id=artifact_version_id,
resource_update=artifact_version_update,
response_model=ArtifactVersionResponse,
route=ARTIFACT_VERSIONS,
)
def delete_artifact_version(self, artifact_version_id: UUID) -> None:
"""Deletes an artifact version.
Args:
artifact_version_id: The ID of the artifact version to delete.
"""
self._delete_resource(
resource_id=artifact_version_id, route=ARTIFACT_VERSIONS
)
def prune_artifact_versions(
self,
only_versions: bool = True,
) -> None:
"""Prunes unused artifact versions and their artifacts.
Args:
only_versions: Only delete artifact versions, keeping artifacts
"""
self.delete(
path=ARTIFACT_VERSIONS, params={"only_versions": only_versions}
)
# ------------------------ Artifact Visualizations ------------------------
def get_artifact_visualization(
self, artifact_visualization_id: UUID, hydrate: bool = True
) -> ArtifactVisualizationResponse:
"""Gets an artifact visualization.
Args:
artifact_visualization_id: The ID of the artifact visualization to
get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The artifact visualization.
"""
return self._get_resource(
resource_id=artifact_visualization_id,
route=ARTIFACT_VISUALIZATIONS,
response_model=ArtifactVisualizationResponse,
params={"hydrate": hydrate},
)
# ------------------------ Code References ------------------------
def get_code_reference(
self, code_reference_id: UUID, hydrate: bool = True
) -> CodeReferenceResponse:
"""Gets a code reference.
Args:
code_reference_id: The ID of the code reference to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The code reference.
"""
return self._get_resource(
resource_id=code_reference_id,
route=CODE_REFERENCES,
response_model=CodeReferenceResponse,
params={"hydrate": hydrate},
)
# --------------------------- Code Repositories ---------------------------
def create_code_repository(
self, code_repository: CodeRepositoryRequest
) -> CodeRepositoryResponse:
"""Creates a new code repository.
Args:
code_repository: Code repository to be created.
Returns:
The newly created code repository.
"""
return self._create_workspace_scoped_resource(
resource=code_repository,
response_model=CodeRepositoryResponse,
route=CODE_REPOSITORIES,
)
def get_code_repository(
self, code_repository_id: UUID, hydrate: bool = True
) -> CodeRepositoryResponse:
"""Gets a specific code repository.
Args:
code_repository_id: The ID of the code repository to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested code repository, if it was found.
"""
return self._get_resource(
resource_id=code_repository_id,
route=CODE_REPOSITORIES,
response_model=CodeRepositoryResponse,
params={"hydrate": hydrate},
)
def list_code_repositories(
self,
filter_model: CodeRepositoryFilter,
hydrate: bool = False,
) -> Page[CodeRepositoryResponse]:
"""List all code repositories.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all code repositories.
"""
return self._list_paginated_resources(
route=CODE_REPOSITORIES,
response_model=CodeRepositoryResponse,
filter_model=filter_model,
params={"hydrate": hydrate},
)
def update_code_repository(
self, code_repository_id: UUID, update: CodeRepositoryUpdate
) -> CodeRepositoryResponse:
"""Updates an existing code repository.
Args:
code_repository_id: The ID of the code repository to update.
update: The update to be applied to the code repository.
Returns:
The updated code repository.
"""
return self._update_resource(
resource_id=code_repository_id,
resource_update=update,
response_model=CodeRepositoryResponse,
route=CODE_REPOSITORIES,
)
def delete_code_repository(self, code_repository_id: UUID) -> None:
"""Deletes a code repository.
Args:
code_repository_id: The ID of the code repository to delete.
"""
self._delete_resource(
resource_id=code_repository_id, route=CODE_REPOSITORIES
)
# ----------------------------- Components -----------------------------
def create_stack_component(
self,
component: ComponentRequest,
) -> ComponentResponse:
"""Create a stack component.
Args:
component: The stack component to create.
Returns:
The created stack component.
"""
return self._create_workspace_scoped_resource(
resource=component,
route=STACK_COMPONENTS,
response_model=ComponentResponse,
)
def get_stack_component(
self, component_id: UUID, hydrate: bool = True
) -> ComponentResponse:
"""Get a stack component by ID.
Args:
component_id: The ID of the stack component to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The stack component.
"""
return self._get_resource(
resource_id=component_id,
route=STACK_COMPONENTS,
response_model=ComponentResponse,
params={"hydrate": hydrate},
)
def list_stack_components(
self,
component_filter_model: ComponentFilter,
hydrate: bool = False,
) -> Page[ComponentResponse]:
"""List all stack components matching the given filter criteria.
Args:
component_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all stack components matching the filter criteria.
"""
return self._list_paginated_resources(
route=STACK_COMPONENTS,
response_model=ComponentResponse,
filter_model=component_filter_model,
params={"hydrate": hydrate},
)
def update_stack_component(
self,
component_id: UUID,
component_update: ComponentUpdate,
) -> ComponentResponse:
"""Update an existing stack component.
Args:
component_id: The ID of the stack component to update.
component_update: The update to be applied to the stack component.
Returns:
The updated stack component.
"""
return self._update_resource(
resource_id=component_id,
resource_update=component_update,
route=STACK_COMPONENTS,
response_model=ComponentResponse,
)
def delete_stack_component(self, component_id: UUID) -> None:
"""Delete a stack component.
Args:
component_id: The ID of the stack component to delete.
"""
self._delete_resource(
resource_id=component_id,
route=STACK_COMPONENTS,
)
# ----------------------------- Flavors -----------------------------
def create_flavor(self, flavor: FlavorRequest) -> FlavorResponse:
"""Creates a new stack component flavor.
Args:
flavor: The stack component flavor to create.
Returns:
The newly created flavor.
"""
return self._create_resource(
resource=flavor,
route=FLAVORS,
response_model=FlavorResponse,
)
def get_flavor(
self, flavor_id: UUID, hydrate: bool = True
) -> FlavorResponse:
"""Get a stack component flavor by ID.
Args:
flavor_id: The ID of the stack component flavor to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The stack component flavor.
"""
return self._get_resource(
resource_id=flavor_id,
route=FLAVORS,
response_model=FlavorResponse,
params={"hydrate": hydrate},
)
def list_flavors(
self,
flavor_filter_model: FlavorFilter,
hydrate: bool = False,
) -> Page[FlavorResponse]:
"""List all stack component flavors matching the given filter criteria.
Args:
flavor_filter_model: All filter parameters including pagination
params
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
List of all the stack component flavors matching the given criteria.
"""
return self._list_paginated_resources(
route=FLAVORS,
response_model=FlavorResponse,
filter_model=flavor_filter_model,
params={"hydrate": hydrate},
)
def update_flavor(
self, flavor_id: UUID, flavor_update: FlavorUpdate
) -> FlavorResponse:
"""Updates an existing user.
Args:
flavor_id: The id of the flavor to update.
flavor_update: The update to be applied to the flavor.
Returns:
The updated flavor.
"""
return self._update_resource(
resource_id=flavor_id,
resource_update=flavor_update,
route=FLAVORS,
response_model=FlavorResponse,
)
def delete_flavor(self, flavor_id: UUID) -> None:
"""Delete a stack component flavor.
Args:
flavor_id: The ID of the stack component flavor to delete.
"""
self._delete_resource(
resource_id=flavor_id,
route=FLAVORS,
)
# ------------------------ Logs ------------------------
def get_logs(self, logs_id: UUID, hydrate: bool = True) -> LogsResponse:
"""Gets logs with the given ID.
Args:
logs_id: The ID of the logs to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The logs.
"""
return self._get_resource(
resource_id=logs_id,
route=LOGS,
response_model=LogsResponse,
params={"hydrate": hydrate},
)
# ----------------------------- Pipelines -----------------------------
def create_pipeline(self, pipeline: PipelineRequest) -> PipelineResponse:
"""Creates a new pipeline in a workspace.
Args:
pipeline: The pipeline to create.
Returns:
The newly created pipeline.
"""
return self._create_workspace_scoped_resource(
resource=pipeline,
route=PIPELINES,
response_model=PipelineResponse,
)
def get_pipeline(
self, pipeline_id: UUID, hydrate: bool = True
) -> PipelineResponse:
"""Get a pipeline with a given ID.
Args:
pipeline_id: ID of the pipeline.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The pipeline.
"""
return self._get_resource(
resource_id=pipeline_id,
route=PIPELINES,
response_model=PipelineResponse,
params={"hydrate": hydrate},
)
def list_pipelines(
self,
pipeline_filter_model: PipelineFilter,
hydrate: bool = False,
) -> Page[PipelineResponse]:
"""List all pipelines matching the given filter criteria.
Args:
pipeline_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all pipelines matching the filter criteria.
"""
return self._list_paginated_resources(
route=PIPELINES,
response_model=PipelineResponse,
filter_model=pipeline_filter_model,
params={"hydrate": hydrate},
)
def update_pipeline(
self, pipeline_id: UUID, pipeline_update: PipelineUpdate
) -> PipelineResponse:
"""Updates a pipeline.
Args:
pipeline_id: The ID of the pipeline to be updated.
pipeline_update: The update to be applied.
Returns:
The updated pipeline.
"""
return self._update_resource(
resource_id=pipeline_id,
resource_update=pipeline_update,
route=PIPELINES,
response_model=PipelineResponse,
)
def delete_pipeline(self, pipeline_id: UUID) -> None:
"""Deletes a pipeline.
Args:
pipeline_id: The ID of the pipeline to delete.
"""
self._delete_resource(
resource_id=pipeline_id,
route=PIPELINES,
)
# --------------------------- Pipeline Builds ---------------------------
def create_build(
self,
build: PipelineBuildRequest,
) -> PipelineBuildResponse:
"""Creates a new build in a workspace.
Args:
build: The build to create.
Returns:
The newly created build.
"""
return self._create_workspace_scoped_resource(
resource=build,
route=PIPELINE_BUILDS,
response_model=PipelineBuildResponse,
)
def get_build(
self, build_id: UUID, hydrate: bool = True
) -> PipelineBuildResponse:
"""Get a build with a given ID.
Args:
build_id: ID of the build.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The build.
"""
return self._get_resource(
resource_id=build_id,
route=PIPELINE_BUILDS,
response_model=PipelineBuildResponse,
params={"hydrate": hydrate},
)
def list_builds(
self,
build_filter_model: PipelineBuildFilter,
hydrate: bool = False,
) -> Page[PipelineBuildResponse]:
"""List all builds matching the given filter criteria.
Args:
build_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all builds matching the filter criteria.
"""
return self._list_paginated_resources(
route=PIPELINE_BUILDS,
response_model=PipelineBuildResponse,
filter_model=build_filter_model,
params={"hydrate": hydrate},
)
def delete_build(self, build_id: UUID) -> None:
"""Deletes a build.
Args:
build_id: The ID of the build to delete.
"""
self._delete_resource(
resource_id=build_id,
route=PIPELINE_BUILDS,
)
# ----------------------
# Pipeline Deployments
# ----------------------
# -------------------------- Pipeline Deployments --------------------------
def create_deployment(
self,
deployment: PipelineDeploymentRequest,
) -> PipelineDeploymentResponse:
"""Creates a new deployment in a workspace.
Args:
deployment: The deployment to create.
Returns:
The newly created deployment.
"""
return self._create_workspace_scoped_resource(
resource=deployment,
route=PIPELINE_DEPLOYMENTS,
response_model=PipelineDeploymentResponse,
)
def get_deployment(
self, deployment_id: UUID, hydrate: bool = True
) -> PipelineDeploymentResponse:
"""Get a deployment with a given ID.
Args:
deployment_id: ID of the deployment.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The deployment.
"""
return self._get_resource(
resource_id=deployment_id,
route=PIPELINE_DEPLOYMENTS,
response_model=PipelineDeploymentResponse,
params={"hydrate": hydrate},
)
def list_deployments(
self,
deployment_filter_model: PipelineDeploymentFilter,
hydrate: bool = False,
) -> Page[PipelineDeploymentResponse]:
"""List all deployments matching the given filter criteria.
Args:
deployment_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all deployments matching the filter criteria.
"""
return self._list_paginated_resources(
route=PIPELINE_DEPLOYMENTS,
response_model=PipelineDeploymentResponse,
filter_model=deployment_filter_model,
params={"hydrate": hydrate},
)
def delete_deployment(self, deployment_id: UUID) -> None:
"""Deletes a deployment.
Args:
deployment_id: The ID of the deployment to delete.
"""
self._delete_resource(
resource_id=deployment_id,
route=PIPELINE_DEPLOYMENTS,
)
# -------------------- Event Sources --------------------
def create_event_source(
self, event_source: EventSourceRequest
) -> EventSourceResponse:
"""Create an event_source.
Args:
event_source: The event_source to create.
Returns:
The created event_source.
"""
return self._create_resource(
resource=event_source,
route=EVENT_SOURCES,
response_model=EventSourceResponse,
)
def get_event_source(
self,
event_source_id: UUID,
hydrate: bool = True,
) -> EventSourceResponse:
"""Get an event_source by ID.
Args:
event_source_id: The ID of the event_source to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The event_source.
"""
return self._get_resource(
resource_id=event_source_id,
route=EVENT_SOURCES,
response_model=EventSourceResponse,
params={"hydrate": hydrate},
)
def list_event_sources(
self,
event_source_filter_model: EventSourceFilter,
hydrate: bool = False,
) -> Page[EventSourceResponse]:
"""List all event_sources matching the given filter criteria.
Args:
event_source_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all event_sources matching the filter criteria.
"""
return self._list_paginated_resources(
route=EVENT_SOURCES,
response_model=EventSourceResponse,
filter_model=event_source_filter_model,
params={"hydrate": hydrate},
)
def update_event_source(
self,
event_source_id: UUID,
event_source_update: EventSourceUpdate,
) -> EventSourceResponse:
"""Update an existing event_source.
Args:
event_source_id: The ID of the event_source to update.
event_source_update: The update to be applied to the event_source.
Returns:
The updated event_source.
"""
return self._update_resource(
resource_id=event_source_id,
resource_update=event_source_update,
route=EVENT_SOURCES,
response_model=EventSourceResponse,
)
def delete_event_source(self, event_source_id: UUID) -> None:
"""Delete an event_source.
Args:
event_source_id: The ID of the event_source to delete.
"""
self._delete_resource(
resource_id=event_source_id,
route=EVENT_SOURCES,
)
# ----------------------------- Pipeline runs -----------------------------
def create_run(
self, pipeline_run: PipelineRunRequest
) -> PipelineRunResponse:
"""Creates a pipeline run.
Args:
pipeline_run: The pipeline run to create.
Returns:
The created pipeline run.
"""
return self._create_workspace_scoped_resource(
resource=pipeline_run,
response_model=PipelineRunResponse,
route=RUNS,
)
def get_run(
self, run_name_or_id: Union[UUID, str], hydrate: bool = True
) -> PipelineRunResponse:
"""Gets a pipeline run.
Args:
run_name_or_id: The name or ID of the pipeline run to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The pipeline run.
"""
return self._get_resource(
resource_id=run_name_or_id,
route=RUNS,
response_model=PipelineRunResponse,
params={"hydrate": hydrate},
)
def list_runs(
self,
runs_filter_model: PipelineRunFilter,
hydrate: bool = False,
) -> Page[PipelineRunResponse]:
"""List all pipeline runs matching the given filter criteria.
Args:
runs_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all pipeline runs matching the filter criteria.
"""
return self._list_paginated_resources(
route=RUNS,
response_model=PipelineRunResponse,
filter_model=runs_filter_model,
params={"hydrate": hydrate},
)
def update_run(
self, run_id: UUID, run_update: PipelineRunUpdate
) -> PipelineRunResponse:
"""Updates a pipeline run.
Args:
run_id: The ID of the pipeline run to update.
run_update: The update to be applied to the pipeline run.
Returns:
The updated pipeline run.
"""
return self._update_resource(
resource_id=run_id,
resource_update=run_update,
response_model=PipelineRunResponse,
route=RUNS,
)
def delete_run(self, run_id: UUID) -> None:
"""Deletes a pipeline run.
Args:
run_id: The ID of the pipeline run to delete.
"""
self._delete_resource(
resource_id=run_id,
route=RUNS,
)
def get_or_create_run(
self, pipeline_run: PipelineRunRequest
) -> Tuple[PipelineRunResponse, bool]:
"""Gets or creates a pipeline run.
If a run with the same ID or name already exists, it is returned.
Otherwise, a new run is created.
Args:
pipeline_run: The pipeline run to get or create.
Returns:
The pipeline run, and a boolean indicating whether the run was
created or not.
"""
return self._get_or_create_workspace_scoped_resource(
resource=pipeline_run,
route=RUNS,
response_model=PipelineRunResponse,
)
# ----------------------------- Run Metadata -----------------------------
def create_run_metadata(
self, run_metadata: RunMetadataRequest
) -> List[RunMetadataResponse]:
"""Creates run metadata.
Args:
run_metadata: The run metadata to create.
Returns:
The created run metadata.
"""
route = f"{WORKSPACES}/{str(run_metadata.workspace)}{RUN_METADATA}"
response_body = self.post(f"{route}", body=run_metadata)
result: List[RunMetadataResponse] = []
if isinstance(response_body, list):
for metadata in response_body or []:
result.append(RunMetadataResponse.parse_obj(metadata))
return result
def get_run_metadata(
self, run_metadata_id: UUID, hydrate: bool = True
) -> RunMetadataResponse:
"""Gets run metadata with the given ID.
Args:
run_metadata_id: The ID of the run metadata to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The run metadata.
"""
return self._get_resource(
resource_id=run_metadata_id,
route=RUN_METADATA,
response_model=RunMetadataResponse,
params={"hydrate": hydrate},
)
def list_run_metadata(
self,
run_metadata_filter_model: RunMetadataFilter,
hydrate: bool = False,
) -> Page[RunMetadataResponse]:
"""List run metadata.
Args:
run_metadata_filter_model: All filter parameters including
pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The run metadata.
"""
return self._list_paginated_resources(
route=RUN_METADATA,
response_model=RunMetadataResponse,
filter_model=run_metadata_filter_model,
params={"hydrate": hydrate},
)
# ----------------------------- Schedules -----------------------------
def create_schedule(self, schedule: ScheduleRequest) -> ScheduleResponse:
"""Creates a new schedule.
Args:
schedule: The schedule to create.
Returns:
The newly created schedule.
"""
return self._create_workspace_scoped_resource(
resource=schedule,
route=SCHEDULES,
response_model=ScheduleResponse,
)
def get_schedule(
self, schedule_id: UUID, hydrate: bool = True
) -> ScheduleResponse:
"""Get a schedule with a given ID.
Args:
schedule_id: ID of the schedule.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The schedule.
"""
return self._get_resource(
resource_id=schedule_id,
route=SCHEDULES,
response_model=ScheduleResponse,
params={"hydrate": hydrate},
)
def list_schedules(
self,
schedule_filter_model: ScheduleFilter,
hydrate: bool = False,
) -> Page[ScheduleResponse]:
"""List all schedules in the workspace.
Args:
schedule_filter_model: All filter parameters including pagination
params
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of schedules.
"""
return self._list_paginated_resources(
route=SCHEDULES,
response_model=ScheduleResponse,
filter_model=schedule_filter_model,
params={"hydrate": hydrate},
)
def update_schedule(
self,
schedule_id: UUID,
schedule_update: ScheduleUpdate,
) -> ScheduleResponse:
"""Updates a schedule.
Args:
schedule_id: The ID of the schedule to be updated.
schedule_update: The update to be applied.
Returns:
The updated schedule.
"""
return self._update_resource(
resource_id=schedule_id,
resource_update=schedule_update,
route=SCHEDULES,
response_model=ScheduleResponse,
)
def delete_schedule(self, schedule_id: UUID) -> None:
"""Deletes a schedule.
Args:
schedule_id: The ID of the schedule to delete.
"""
self._delete_resource(
resource_id=schedule_id,
route=SCHEDULES,
)
# --------------------------- Secrets ---------------------------
def create_secret(self, secret: SecretRequest) -> SecretResponse:
"""Creates a new secret.
The new secret is also validated against the scoping rules enforced in
the secrets store:
- only one workspace-scoped secret with the given name can exist
in the target workspace.
- only one user-scoped secret with the given name can exist in the
target workspace for the target user.
Args:
secret: The secret to create.
Returns:
The newly created secret.
"""
return self._create_workspace_scoped_resource(
resource=secret,
route=SECRETS,
response_model=SecretResponse,
)
def get_secret(
self, secret_id: UUID, hydrate: bool = True
) -> SecretResponse:
"""Get a secret by ID.
Args:
secret_id: The ID of the secret to fetch.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The secret.
"""
return self._get_resource(
resource_id=secret_id,
route=SECRETS,
response_model=SecretResponse,
params={"hydrate": hydrate},
)
def list_secrets(
self, secret_filter_model: SecretFilter, hydrate: bool = False
) -> Page[SecretResponse]:
"""List all secrets matching the given filter criteria.
Note that returned secrets do not include any secret values. To fetch
the secret values, use `get_secret`.
Args:
secret_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all secrets matching the filter criteria, with pagination
information and sorted according to the filter criteria. The
returned secrets do not include any secret values, only metadata. To
fetch the secret values, use `get_secret` individually with each
secret.
"""
return self._list_paginated_resources(
route=SECRETS,
response_model=SecretResponse,
filter_model=secret_filter_model,
params={"hydrate": hydrate},
)
def update_secret(
self, secret_id: UUID, secret_update: SecretUpdate
) -> SecretResponse:
"""Updates a secret.
Secret values that are specified as `None` in the update that are
present in the existing secret are removed from the existing secret.
Values that are present in both secrets are overwritten. All other
values in both the existing secret and the update are kept (merged).
If the update includes a change of name or scope, the scoping rules
enforced in the secrets store are used to validate the update:
- only one workspace-scoped secret with the given name can exist
in the target workspace.
- only one user-scoped secret with the given name can exist in the
target workspace for the target user.
Args:
secret_id: The ID of the secret to be updated.
secret_update: The update to be applied.
Returns:
The updated secret.
"""
return self._update_resource(
resource_id=secret_id,
resource_update=secret_update,
route=SECRETS,
response_model=SecretResponse,
# The default endpoint behavior is to replace all secret values
# with the values in the update. We want to merge the values
# instead.
params=dict(patch_values=True),
)
def delete_secret(self, secret_id: UUID) -> None:
"""Delete a secret.
Args:
secret_id: The id of the secret to delete.
"""
self._delete_resource(
resource_id=secret_id,
route=SECRETS,
)
def backup_secrets(
self, ignore_errors: bool = True, delete_secrets: bool = False
) -> None:
"""Backs up all secrets to the configured backup secrets store.
Args:
ignore_errors: Whether to ignore individual errors during the backup
process and attempt to backup all secrets.
delete_secrets: Whether to delete the secrets that have been
successfully backed up from the primary secrets store. Setting
this flag effectively moves all secrets from the primary secrets
store to the backup secrets store.
"""
params: Dict[str, Any] = {
"ignore_errors": ignore_errors,
"delete_secrets": delete_secrets,
}
self.put(
f"{SECRETS_OPERATIONS}{SECRETS_BACKUP}",
params=params,
)
def restore_secrets(
self, ignore_errors: bool = False, delete_secrets: bool = False
) -> None:
"""Restore all secrets from the configured backup secrets store.
Args:
ignore_errors: Whether to ignore individual errors during the
restore process and attempt to restore all secrets.
delete_secrets: Whether to delete the secrets that have been
successfully restored from the backup secrets store. Setting
this flag effectively moves all secrets from the backup secrets
store to the primary secrets store.
"""
params: Dict[str, Any] = {
"ignore_errors": ignore_errors,
"delete_secrets": delete_secrets,
}
self.put(
f"{SECRETS_OPERATIONS}{SECRETS_RESTORE}",
params=params,
)
# --------------------------- Service Accounts ---------------------------
def create_service_account(
self, service_account: ServiceAccountRequest
) -> ServiceAccountResponse:
"""Creates a new service account.
Args:
service_account: Service account to be created.
Returns:
The newly created service account.
"""
return self._create_resource(
resource=service_account,
route=SERVICE_ACCOUNTS,
response_model=ServiceAccountResponse,
)
def get_service_account(
self,
service_account_name_or_id: Union[str, UUID],
hydrate: bool = True,
) -> ServiceAccountResponse:
"""Gets a specific service account.
Args:
service_account_name_or_id: The name or ID of the service account to
get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested service account, if it was found.
"""
return self._get_resource(
resource_id=service_account_name_or_id,
route=SERVICE_ACCOUNTS,
response_model=ServiceAccountResponse,
params={"hydrate": hydrate},
)
def list_service_accounts(
self, filter_model: ServiceAccountFilter, hydrate: bool = False
) -> Page[ServiceAccountResponse]:
"""List all service accounts.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of filtered service accounts.
"""
return self._list_paginated_resources(
route=SERVICE_ACCOUNTS,
response_model=ServiceAccountResponse,
filter_model=filter_model,
params={"hydrate": hydrate},
)
def update_service_account(
self,
service_account_name_or_id: Union[str, UUID],
service_account_update: ServiceAccountUpdate,
) -> ServiceAccountResponse:
"""Updates an existing service account.
Args:
service_account_name_or_id: The name or the ID of the service
account to update.
service_account_update: The update to be applied to the service
account.
Returns:
The updated service account.
"""
return self._update_resource(
resource_id=service_account_name_or_id,
resource_update=service_account_update,
route=SERVICE_ACCOUNTS,
response_model=ServiceAccountResponse,
)
def delete_service_account(
self,
service_account_name_or_id: Union[str, UUID],
) -> None:
"""Delete a service account.
Args:
service_account_name_or_id: The name or the ID of the service
account to delete.
"""
self._delete_resource(
resource_id=service_account_name_or_id,
route=SERVICE_ACCOUNTS,
)
# --------------------------- Service Connectors ---------------------------
def create_service_connector(
self, service_connector: ServiceConnectorRequest
) -> ServiceConnectorResponse:
"""Creates a new service connector.
Args:
service_connector: Service connector to be created.
Returns:
The newly created service connector.
"""
connector_model = self._create_workspace_scoped_resource(
resource=service_connector,
route=SERVICE_CONNECTORS,
response_model=ServiceConnectorResponse,
)
self._populate_connector_type(connector_model)
return connector_model
def get_service_connector(
self, service_connector_id: UUID, hydrate: bool = True
) -> ServiceConnectorResponse:
"""Gets a specific service connector.
Args:
service_connector_id: The ID of the service connector to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested service connector, if it was found.
"""
connector_model = self._get_resource(
resource_id=service_connector_id,
route=SERVICE_CONNECTORS,
response_model=ServiceConnectorResponse,
params={"expand_secrets": False, "hydrate": hydrate},
)
self._populate_connector_type(connector_model)
return connector_model
def list_service_connectors(
self,
filter_model: ServiceConnectorFilter,
hydrate: bool = False,
) -> Page[ServiceConnectorResponse]:
"""List all service connectors.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all service connectors.
"""
connector_models = self._list_paginated_resources(
route=SERVICE_CONNECTORS,
response_model=ServiceConnectorResponse,
filter_model=filter_model,
params={"expand_secrets": False, "hydrate": hydrate},
)
self._populate_connector_type(*connector_models.items)
return connector_models
def update_service_connector(
self, service_connector_id: UUID, update: ServiceConnectorUpdate
) -> ServiceConnectorResponse:
"""Updates an existing service connector.
The update model contains the fields to be updated. If a field value is
set to None in the model, the field is not updated, but there are
special rules concerning some fields:
* the `configuration` and `secrets` fields together represent a full
valid configuration update, not just a partial update. If either is
set (i.e. not None) in the update, their values are merged together and
will replace the existing configuration and secrets values.
* the `resource_id` field value is also a full replacement value: if set
to `None`, the resource ID is removed from the service connector.
* the `expiration_seconds` field value is also a full replacement value:
if set to `None`, the expiration is removed from the service connector.
* the `secret_id` field value in the update is ignored, given that
secrets are managed internally by the ZenML store.
* the `labels` field is also a full labels update: if set (i.e. not
`None`), all existing labels are removed and replaced by the new labels
in the update.
Args:
service_connector_id: The ID of the service connector to update.
update: The update to be applied to the service connector.
Returns:
The updated service connector.
"""
connector_model = self._update_resource(
resource_id=service_connector_id,
resource_update=update,
response_model=ServiceConnectorResponse,
route=SERVICE_CONNECTORS,
)
self._populate_connector_type(connector_model)
return connector_model
def delete_service_connector(self, service_connector_id: UUID) -> None:
"""Deletes a service connector.
Args:
service_connector_id: The ID of the service connector to delete.
"""
self._delete_resource(
resource_id=service_connector_id, route=SERVICE_CONNECTORS
)
def _populate_connector_type(
self,
*connector_models: Union[
ServiceConnectorResponse, ServiceConnectorResourcesModel
],
) -> None:
"""Populates or updates the connector type of the given connector or resource models.
If the connector type is not locally available, the connector type
field is left as is. The local and remote flags of the connector type
are updated accordingly.
Args:
connector_models: The service connector or resource models to
populate.
"""
for service_connector in connector_models:
# Mark the remote connector type as being only remotely available
if not isinstance(service_connector.connector_type, str):
service_connector.connector_type.local = False
service_connector.connector_type.remote = True
if not service_connector_registry.is_registered(
service_connector.type
):
continue
connector_type = (
service_connector_registry.get_service_connector_type(
service_connector.type
)
)
connector_type.local = True
if not isinstance(service_connector.connector_type, str):
connector_type.remote = True
# TODO: Normally, this could have been handled with setter
# functions over the connector type property in the response
# model. However, pydantic breaks property setter functions.
# We can find a more elegant solution here.
if isinstance(service_connector, ServiceConnectorResponse):
service_connector.set_connector_type(connector_type)
elif isinstance(service_connector, ServiceConnectorResourcesModel):
service_connector.connector_type = connector_type
else:
TypeError(
"The service connector must be an instance of either"
"`ServiceConnectorResponse` or "
"`ServiceConnectorResourcesModel`."
)
def verify_service_connector_config(
self,
service_connector: ServiceConnectorRequest,
list_resources: bool = True,
) -> ServiceConnectorResourcesModel:
"""Verifies if a service connector configuration has access to resources.
Args:
service_connector: The service connector configuration to verify.
list_resources: If True, the list of all resources accessible
through the service connector and matching the supplied resource
type and ID are returned.
Returns:
The list of resources that the service connector configuration has
access to.
"""
response_body = self.post(
f"{SERVICE_CONNECTORS}{SERVICE_CONNECTOR_VERIFY}",
body=service_connector,
params={"list_resources": list_resources},
)
resources = ServiceConnectorResourcesModel.parse_obj(response_body)
self._populate_connector_type(resources)
return resources
def verify_service_connector(
self,
service_connector_id: UUID,
resource_type: Optional[str] = None,
resource_id: Optional[str] = None,
list_resources: bool = True,
) -> ServiceConnectorResourcesModel:
"""Verifies if a service connector instance has access to one or more resources.
Args:
service_connector_id: The ID of the service connector to verify.
resource_type: The type of resource to verify access to.
resource_id: The ID of the resource to verify access to.
list_resources: If True, the list of all resources accessible
through the service connector and matching the supplied resource
type and ID are returned.
Returns:
The list of resources that the service connector has access to,
scoped to the supplied resource type and ID, if provided.
"""
params: Dict[str, Any] = {"list_resources": list_resources}
if resource_type:
params["resource_type"] = resource_type
if resource_id:
params["resource_id"] = resource_id
response_body = self.put(
f"{SERVICE_CONNECTORS}/{str(service_connector_id)}{SERVICE_CONNECTOR_VERIFY}",
params=params,
)
resources = ServiceConnectorResourcesModel.parse_obj(response_body)
self._populate_connector_type(resources)
return resources
def get_service_connector_client(
self,
service_connector_id: UUID,
resource_type: Optional[str] = None,
resource_id: Optional[str] = None,
) -> ServiceConnectorResponse:
"""Get a service connector client for a service connector and given resource.
Args:
service_connector_id: The ID of the base service connector to use.
resource_type: The type of resource to get a client for.
resource_id: The ID of the resource to get a client for.
Returns:
A service connector client that can be used to access the given
resource.
"""
params = {}
if resource_type:
params["resource_type"] = resource_type
if resource_id:
params["resource_id"] = resource_id
response_body = self.get(
f"{SERVICE_CONNECTORS}/{str(service_connector_id)}{SERVICE_CONNECTOR_CLIENT}",
params=params,
)
connector = ServiceConnectorResponse.parse_obj(response_body)
self._populate_connector_type(connector)
return connector
def list_service_connector_resources(
self,
workspace_name_or_id: Union[str, UUID],
connector_type: Optional[str] = None,
resource_type: Optional[str] = None,
resource_id: Optional[str] = None,
) -> List[ServiceConnectorResourcesModel]:
"""List resources that can be accessed by service connectors.
Args:
workspace_name_or_id: The name or ID of the workspace to scope to.
connector_type: The type of service connector to scope to.
resource_type: The type of resource to scope to.
resource_id: The ID of the resource to scope to.
Returns:
The matching list of resources that available service
connectors have access to.
"""
params = {}
if connector_type:
params["connector_type"] = connector_type
if resource_type:
params["resource_type"] = resource_type
if resource_id:
params["resource_id"] = resource_id
response_body = self.get(
f"{WORKSPACES}/{workspace_name_or_id}{SERVICE_CONNECTORS}{SERVICE_CONNECTOR_RESOURCES}",
params=params,
)
assert isinstance(response_body, list)
resource_list = [
ServiceConnectorResourcesModel.parse_obj(item)
for item in response_body
]
self._populate_connector_type(*resource_list)
# For service connectors with types that are only locally available,
# we need to retrieve the resource list locally
for idx, resources in enumerate(resource_list):
if isinstance(resources.connector_type, str):
# Skip connector types that are neither locally nor remotely
# available
continue
if resources.connector_type.remote:
# Skip connector types that are remotely available
continue
# Retrieve the resource list locally
assert resources.id is not None
connector = self.get_service_connector(resources.id)
connector_instance = (
service_connector_registry.instantiate_connector(
model=connector
)
)
try:
local_resources = connector_instance.verify(
resource_type=resource_type,
resource_id=resource_id,
)
except (ValueError, AuthorizationException) as e:
logger.error(
f'Failed to fetch {resource_type or "available"} '
f"resources from service connector {connector.name}/"
f"{connector.id}: {e}"
)
continue
resource_list[idx] = local_resources
return resource_list
def list_service_connector_types(
self,
connector_type: Optional[str] = None,
resource_type: Optional[str] = None,
auth_method: Optional[str] = None,
) -> List[ServiceConnectorTypeModel]:
"""Get a list of service connector types.
Args:
connector_type: Filter by connector type.
resource_type: Filter by resource type.
auth_method: Filter by authentication method.
Returns:
List of service connector types.
"""
params = {}
if connector_type:
params["connector_type"] = connector_type
if resource_type:
params["resource_type"] = resource_type
if auth_method:
params["auth_method"] = auth_method
response_body = self.get(
SERVICE_CONNECTOR_TYPES,
params=params,
)
assert isinstance(response_body, list)
remote_connector_types = [
ServiceConnectorTypeModel.parse_obj(item) for item in response_body
]
# Mark the remote connector types as being only remotely available
for c in remote_connector_types:
c.local = False
c.remote = True
local_connector_types = (
service_connector_registry.list_service_connector_types(
connector_type=connector_type,
resource_type=resource_type,
auth_method=auth_method,
)
)
# Add the connector types in the local registry to the list of
# connector types available remotely. Overwrite those that have
# the same connector type but mark them as being remotely available.
connector_types_map = {
connector_type.connector_type: connector_type
for connector_type in remote_connector_types
}
for connector in local_connector_types:
if connector.connector_type in connector_types_map:
connector.remote = True
connector_types_map[connector.connector_type] = connector
return list(connector_types_map.values())
def get_service_connector_type(
self,
connector_type: str,
) -> ServiceConnectorTypeModel:
"""Returns the requested service connector type.
Args:
connector_type: the service connector type identifier.
Returns:
The requested service connector type.
"""
# Use the local registry to get the service connector type, if it
# exists.
local_connector_type: Optional[ServiceConnectorTypeModel] = None
if service_connector_registry.is_registered(connector_type):
local_connector_type = (
service_connector_registry.get_service_connector_type(
connector_type
)
)
try:
response_body = self.get(
f"{SERVICE_CONNECTOR_TYPES}/{connector_type}",
)
remote_connector_type = ServiceConnectorTypeModel.parse_obj(
response_body
)
if local_connector_type:
# If locally available, return the local connector type but
# mark it as being remotely available.
local_connector_type.remote = True
return local_connector_type
# Mark the remote connector type as being only remotely available
remote_connector_type.local = False
remote_connector_type.remote = True
return remote_connector_type
except KeyError:
# If the service connector type is not found, check the local
# registry.
return service_connector_registry.get_service_connector_type(
connector_type
)
# ----------------------------- Stacks -----------------------------
def create_stack(self, stack: StackRequest) -> StackResponse:
"""Register a new stack.
Args:
stack: The stack to register.
Returns:
The registered stack.
"""
return self._create_workspace_scoped_resource(
resource=stack,
route=STACKS,
response_model=StackResponse,
)
def get_stack(self, stack_id: UUID, hydrate: bool = True) -> StackResponse:
"""Get a stack by its unique ID.
Args:
stack_id: The ID of the stack to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The stack with the given ID.
"""
return self._get_resource(
resource_id=stack_id,
route=STACKS,
response_model=StackResponse,
params={"hydrate": hydrate},
)
def list_stacks(
self, stack_filter_model: StackFilter, hydrate: bool = False
) -> Page[StackResponse]:
"""List all stacks matching the given filter criteria.
Args:
stack_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all stacks matching the filter criteria.
"""
return self._list_paginated_resources(
route=STACKS,
response_model=StackResponse,
filter_model=stack_filter_model,
params={"hydrate": hydrate},
)
def update_stack(
self, stack_id: UUID, stack_update: StackUpdate
) -> StackResponse:
"""Update a stack.
Args:
stack_id: The ID of the stack update.
stack_update: The update request on the stack.
Returns:
The updated stack.
"""
return self._update_resource(
resource_id=stack_id,
resource_update=stack_update,
route=STACKS,
response_model=StackResponse,
)
def delete_stack(self, stack_id: UUID) -> None:
"""Delete a stack.
Args:
stack_id: The ID of the stack to delete.
"""
self._delete_resource(
resource_id=stack_id,
route=STACKS,
)
# ----------------------------- Step runs -----------------------------
def create_run_step(self, step_run: StepRunRequest) -> StepRunResponse:
"""Creates a step run.
Args:
step_run: The step run to create.
Returns:
The created step run.
"""
return self._create_resource(
resource=step_run,
response_model=StepRunResponse,
route=STEPS,
)
def get_run_step(
self, step_run_id: UUID, hydrate: bool = True
) -> StepRunResponse:
"""Get a step run by ID.
Args:
step_run_id: The ID of the step run to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The step run.
"""
return self._get_resource(
resource_id=step_run_id,
route=STEPS,
response_model=StepRunResponse,
params={"hydrate": hydrate},
)
def list_run_steps(
self,
step_run_filter_model: StepRunFilter,
hydrate: bool = False,
) -> Page[StepRunResponse]:
"""List all step runs matching the given filter criteria.
Args:
step_run_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all step runs matching the filter criteria.
"""
return self._list_paginated_resources(
route=STEPS,
response_model=StepRunResponse,
filter_model=step_run_filter_model,
params={"hydrate": hydrate},
)
def update_run_step(
self,
step_run_id: UUID,
step_run_update: StepRunUpdate,
) -> StepRunResponse:
"""Updates a step run.
Args:
step_run_id: The ID of the step to update.
step_run_update: The update to be applied to the step.
Returns:
The updated step run.
"""
return self._update_resource(
resource_id=step_run_id,
resource_update=step_run_update,
response_model=StepRunResponse,
route=STEPS,
)
# -------------------- Triggers --------------------
def create_trigger(self, trigger: TriggerRequest) -> TriggerResponse:
"""Create an trigger.
Args:
trigger: The trigger to create.
Returns:
The created trigger.
"""
return self._create_resource(
resource=trigger,
route=TRIGGERS,
response_model=TriggerResponse,
)
def get_trigger(
self,
trigger_id: UUID,
hydrate: bool = True,
) -> TriggerResponse:
"""Get a trigger by ID.
Args:
trigger_id: The ID of the trigger to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The trigger.
"""
return self._get_resource(
resource_id=trigger_id,
route=TRIGGERS,
response_model=TriggerResponse,
params={"hydrate": hydrate},
)
def list_triggers(
self,
trigger_filter_model: TriggerFilter,
hydrate: bool = False,
) -> Page[TriggerResponse]:
"""List all triggers matching the given filter criteria.
Args:
trigger_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all triggers matching the filter criteria.
"""
return self._list_paginated_resources(
route=TRIGGERS,
response_model=TriggerResponse,
filter_model=trigger_filter_model,
params={"hydrate": hydrate},
)
def update_trigger(
self,
trigger_id: UUID,
trigger_update: TriggerUpdate,
) -> TriggerResponse:
"""Update an existing trigger.
Args:
trigger_id: The ID of the trigger to update.
trigger_update: The update to be applied to the trigger.
Returns:
The updated trigger.
"""
return self._update_resource(
resource_id=trigger_id,
resource_update=trigger_update,
route=TRIGGERS,
response_model=TriggerResponse,
)
def delete_trigger(self, trigger_id: UUID) -> None:
"""Delete an trigger.
Args:
trigger_id: The ID of the trigger to delete.
"""
self._delete_resource(
resource_id=trigger_id,
route=TRIGGERS,
)
# -------------------- Trigger Executions --------------------
def get_trigger_execution(
self,
trigger_execution_id: UUID,
hydrate: bool = True,
) -> TriggerExecutionResponse:
"""Get an trigger execution by ID.
Args:
trigger_execution_id: The ID of the trigger execution to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The trigger execution.
"""
return self._get_resource(
resource_id=trigger_execution_id,
route=TRIGGER_EXECUTIONS,
response_model=TriggerExecutionResponse,
params={"hydrate": hydrate},
)
def list_trigger_executions(
self,
trigger_execution_filter_model: TriggerExecutionFilter,
hydrate: bool = False,
) -> Page[TriggerExecutionResponse]:
"""List all trigger executions matching the given filter criteria.
Args:
trigger_execution_filter_model: All filter parameters including
pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all trigger executions matching the filter criteria.
"""
return self._list_paginated_resources(
route=TRIGGER_EXECUTIONS,
response_model=TriggerExecutionResponse,
filter_model=trigger_execution_filter_model,
params={"hydrate": hydrate},
)
def delete_trigger_execution(self, trigger_execution_id: UUID) -> None:
"""Delete a trigger execution.
Args:
trigger_execution_id: The ID of the trigger execution to delete.
"""
self._delete_resource(
resource_id=trigger_execution_id,
route=TRIGGER_EXECUTIONS,
)
# ----------------------------- Users -----------------------------
def create_user(self, user: UserRequest) -> UserResponse:
"""Creates a new user.
Args:
user: User to be created.
Returns:
The newly created user.
"""
return self._create_resource(
resource=user,
route=USERS,
response_model=UserResponse,
)
def get_user(
self,
user_name_or_id: Optional[Union[str, UUID]] = None,
include_private: bool = False,
hydrate: bool = True,
) -> UserResponse:
"""Gets a specific user, when no id is specified get the active user.
The `include_private` parameter is ignored here as it is handled
implicitly by the /current-user endpoint that is queried when no
user_name_or_id is set. Raises a KeyError in case a user with that id
does not exist.
Args:
user_name_or_id: The name or ID of the user to get.
include_private: Whether to include private user information.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested user, if it was found.
"""
if user_name_or_id:
return self._get_resource(
resource_id=user_name_or_id,
route=USERS,
response_model=UserResponse,
params={"hydrate": hydrate},
)
else:
body = self.get(CURRENT_USER, params={"hydrate": hydrate})
return UserResponse.parse_obj(body)
def list_users(
self,
user_filter_model: UserFilter,
hydrate: bool = False,
) -> Page[UserResponse]:
"""List all users.
Args:
user_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all users.
"""
return self._list_paginated_resources(
route=USERS,
response_model=UserResponse,
filter_model=user_filter_model,
params={"hydrate": hydrate},
)
def update_user(
self, user_id: UUID, user_update: UserUpdate
) -> UserResponse:
"""Updates an existing user.
Args:
user_id: The id of the user to update.
user_update: The update to be applied to the user.
Returns:
The updated user.
"""
return self._update_resource(
resource_id=user_id,
resource_update=user_update,
route=USERS,
response_model=UserResponse,
)
def delete_user(self, user_name_or_id: Union[str, UUID]) -> None:
"""Deletes a user.
Args:
user_name_or_id: The name or ID of the user to delete.
"""
self._delete_resource(
resource_id=user_name_or_id,
route=USERS,
)
# ----------------------------- Workspaces -----------------------------
def create_workspace(
self, workspace: WorkspaceRequest
) -> WorkspaceResponse:
"""Creates a new workspace.
Args:
workspace: The workspace to create.
Returns:
The newly created workspace.
"""
return self._create_resource(
resource=workspace,
route=WORKSPACES,
response_model=WorkspaceResponse,
)
def get_workspace(
self, workspace_name_or_id: Union[UUID, str], hydrate: bool = True
) -> WorkspaceResponse:
"""Get an existing workspace by name or ID.
Args:
workspace_name_or_id: Name or ID of the workspace to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested workspace.
"""
return self._get_resource(
resource_id=workspace_name_or_id,
route=WORKSPACES,
response_model=WorkspaceResponse,
params={"hydrate": hydrate},
)
def list_workspaces(
self,
workspace_filter_model: WorkspaceFilter,
hydrate: bool = False,
) -> Page[WorkspaceResponse]:
"""List all workspace matching the given filter criteria.
Args:
workspace_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all workspace matching the filter criteria.
"""
return self._list_paginated_resources(
route=WORKSPACES,
response_model=WorkspaceResponse,
filter_model=workspace_filter_model,
params={"hydrate": hydrate},
)
def update_workspace(
self, workspace_id: UUID, workspace_update: WorkspaceUpdate
) -> WorkspaceResponse:
"""Update an existing workspace.
Args:
workspace_id: The ID of the workspace to be updated.
workspace_update: The update to be applied to the workspace.
Returns:
The updated workspace.
"""
return self._update_resource(
resource_id=workspace_id,
resource_update=workspace_update,
route=WORKSPACES,
response_model=WorkspaceResponse,
)
def delete_workspace(self, workspace_name_or_id: Union[str, UUID]) -> None:
"""Deletes a workspace.
Args:
workspace_name_or_id: Name or ID of the workspace to delete.
"""
self._delete_resource(
resource_id=workspace_name_or_id,
route=WORKSPACES,
)
# --------------------------- Model ---------------------------
def create_model(self, model: ModelRequest) -> ModelResponse:
"""Creates a new model.
Args:
model: the Model to be created.
Returns:
The newly created model.
"""
return self._create_workspace_scoped_resource(
resource=model,
response_model=ModelResponse,
route=MODELS,
)
def delete_model(self, model_name_or_id: Union[str, UUID]) -> None:
"""Deletes a model.
Args:
model_name_or_id: name or id of the model to be deleted.
"""
self._delete_resource(resource_id=model_name_or_id, route=MODELS)
def update_model(
self,
model_id: UUID,
model_update: ModelUpdate,
) -> ModelResponse:
"""Updates an existing model.
Args:
model_id: UUID of the model to be updated.
model_update: the Model to be updated.
Returns:
The updated model.
"""
return self._update_resource(
resource_id=model_id,
resource_update=model_update,
route=MODELS,
response_model=ModelResponse,
)
def get_model(
self, model_name_or_id: Union[str, UUID], hydrate: bool = True
) -> ModelResponse:
"""Get an existing model.
Args:
model_name_or_id: name or id of the model to be retrieved.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The model of interest.
"""
return self._get_resource(
resource_id=model_name_or_id,
route=MODELS,
response_model=ModelResponse,
params={"hydrate": hydrate},
)
def list_models(
self,
model_filter_model: ModelFilter,
hydrate: bool = False,
) -> Page[ModelResponse]:
"""Get all models by filter.
Args:
model_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all models.
"""
return self._list_paginated_resources(
route=MODELS,
response_model=ModelResponse,
filter_model=model_filter_model,
params={"hydrate": hydrate},
)
# ----------------------------- Model Versions -----------------------------
def create_model_version(
self, model_version: ModelVersionRequest
) -> ModelVersionResponse:
"""Creates a new model version.
Args:
model_version: the Model Version to be created.
Returns:
The newly created model version.
"""
return self._create_workspace_scoped_resource(
resource=model_version,
response_model=ModelVersionResponse,
route=f"{MODELS}/{model_version.model}{MODEL_VERSIONS}",
)
def delete_model_version(
self,
model_version_id: UUID,
) -> None:
"""Deletes a model version.
Args:
model_version_id: name or id of the model version to be deleted.
"""
self._delete_resource(
resource_id=model_version_id,
route=f"{MODEL_VERSIONS}",
)
def get_model_version(
self, model_version_id: UUID, hydrate: bool = True
) -> ModelVersionResponse:
"""Get an existing model version.
Args:
model_version_id: name, id, stage or number of the model version to
be retrieved. If skipped - latest is retrieved.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The model version of interest.
"""
return self._get_resource(
resource_id=model_version_id,
route=MODEL_VERSIONS,
response_model=ModelVersionResponse,
params={"hydrate": hydrate},
)
def list_model_versions(
self,
model_version_filter_model: ModelVersionFilter,
model_name_or_id: Optional[Union[str, UUID]] = None,
hydrate: bool = False,
) -> Page[ModelVersionResponse]:
"""Get all model versions by filter.
Args:
model_name_or_id: name or id of the model containing the model
versions.
model_version_filter_model: All filter parameters including
pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all model versions.
"""
if model_name_or_id:
return self._list_paginated_resources(
route=f"{MODELS}/{model_name_or_id}{MODEL_VERSIONS}",
response_model=ModelVersionResponse,
filter_model=model_version_filter_model,
params={"hydrate": hydrate},
)
else:
return self._list_paginated_resources(
route=MODEL_VERSIONS,
response_model=ModelVersionResponse,
filter_model=model_version_filter_model,
params={"hydrate": hydrate},
)
def update_model_version(
self,
model_version_id: UUID,
model_version_update_model: ModelVersionUpdate,
) -> ModelVersionResponse:
"""Get all model versions by filter.
Args:
model_version_id: The ID of model version to be updated.
model_version_update_model: The model version to be updated.
Returns:
An updated model version.
"""
return self._update_resource(
resource_id=model_version_id,
resource_update=model_version_update_model,
route=MODEL_VERSIONS,
response_model=ModelVersionResponse,
)
# ------------------------ Model Versions Artifacts ------------------------
def create_model_version_artifact_link(
self, model_version_artifact_link: ModelVersionArtifactRequest
) -> ModelVersionArtifactResponse:
"""Creates a new model version link.
Args:
model_version_artifact_link: the Model Version to Artifact Link
to be created.
Returns:
The newly created model version to artifact link.
"""
return self._create_workspace_scoped_resource(
resource=model_version_artifact_link,
response_model=ModelVersionArtifactResponse,
route=f"{MODEL_VERSIONS}/{model_version_artifact_link.model_version}{ARTIFACTS}",
)
def list_model_version_artifact_links(
self,
model_version_artifact_link_filter_model: ModelVersionArtifactFilter,
hydrate: bool = False,
) -> Page[ModelVersionArtifactResponse]:
"""Get all model version to artifact links by filter.
Args:
model_version_artifact_link_filter_model: All filter parameters
including pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all model version to artifact links.
"""
return self._list_paginated_resources(
route=MODEL_VERSION_ARTIFACTS,
response_model=ModelVersionArtifactResponse,
filter_model=model_version_artifact_link_filter_model,
params={"hydrate": hydrate},
)
def delete_model_version_artifact_link(
self,
model_version_id: UUID,
model_version_artifact_link_name_or_id: Union[str, UUID],
) -> None:
"""Deletes a model version to artifact link.
Args:
model_version_id: ID of the model version containing the link.
model_version_artifact_link_name_or_id: name or ID of the model
version to artifact link to be deleted.
"""
self._delete_resource(
resource_id=model_version_artifact_link_name_or_id,
route=f"{MODEL_VERSIONS}/{model_version_id}{ARTIFACTS}",
)
def delete_all_model_version_artifact_links(
self,
model_version_id: UUID,
only_links: bool = True,
) -> None:
"""Deletes all links between model version and an artifact.
Args:
model_version_id: ID of the model version containing the link.
only_links: Flag deciding whether to delete only links or all.
"""
self.delete(
f"{MODEL_VERSIONS}/{model_version_id}{ARTIFACTS}",
params={"only_links": only_links},
)
# ---------------------- Model Versions Pipeline Runs ----------------------
def create_model_version_pipeline_run_link(
self,
model_version_pipeline_run_link: ModelVersionPipelineRunRequest,
) -> ModelVersionPipelineRunResponse:
"""Creates a new model version to pipeline run link.
Args:
model_version_pipeline_run_link: the Model Version to Pipeline Run
Link to be created.
Returns:
- If Model Version to Pipeline Run Link already exists - returns
the existing link.
- Otherwise, returns the newly created model version to pipeline
run link.
"""
return self._create_workspace_scoped_resource(
resource=model_version_pipeline_run_link,
response_model=ModelVersionPipelineRunResponse,
route=f"{MODEL_VERSIONS}/{model_version_pipeline_run_link.model_version}{RUNS}",
)
def list_model_version_pipeline_run_links(
self,
model_version_pipeline_run_link_filter_model: ModelVersionPipelineRunFilter,
hydrate: bool = False,
) -> Page[ModelVersionPipelineRunResponse]:
"""Get all model version to pipeline run links by filter.
Args:
model_version_pipeline_run_link_filter_model: All filter parameters
including pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all model version to pipeline run links.
"""
return self._list_paginated_resources(
route=MODEL_VERSION_PIPELINE_RUNS,
response_model=ModelVersionPipelineRunResponse,
filter_model=model_version_pipeline_run_link_filter_model,
params={"hydrate": hydrate},
)
def delete_model_version_pipeline_run_link(
self,
model_version_id: UUID,
model_version_pipeline_run_link_name_or_id: Union[str, UUID],
) -> None:
"""Deletes a model version to pipeline run link.
Args:
model_version_id: ID of the model version containing the link.
model_version_pipeline_run_link_name_or_id: name or ID of the model version to pipeline run link to be deleted.
"""
self._delete_resource(
resource_id=model_version_pipeline_run_link_name_or_id,
route=f"{MODEL_VERSIONS}/{model_version_id}{RUNS}",
)
# ---------------------------- Devices ----------------------------
def get_authorized_device(
self, device_id: UUID, hydrate: bool = True
) -> OAuthDeviceResponse:
"""Gets a specific OAuth 2.0 authorized device.
Args:
device_id: The ID of the device to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested device, if it was found.
"""
return self._get_resource(
resource_id=device_id,
route=DEVICES,
response_model=OAuthDeviceResponse,
params={"hydrate": hydrate},
)
def list_authorized_devices(
self, filter_model: OAuthDeviceFilter, hydrate: bool = False
) -> Page[OAuthDeviceResponse]:
"""List all OAuth 2.0 authorized devices for a user.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all matching OAuth 2.0 authorized devices.
"""
return self._list_paginated_resources(
route=DEVICES,
response_model=OAuthDeviceResponse,
filter_model=filter_model,
params={"hydrate": hydrate},
)
def update_authorized_device(
self, device_id: UUID, update: OAuthDeviceUpdate
) -> OAuthDeviceResponse:
"""Updates an existing OAuth 2.0 authorized device for internal use.
Args:
device_id: The ID of the device to update.
update: The update to be applied to the device.
Returns:
The updated OAuth 2.0 authorized device.
"""
return self._update_resource(
resource_id=device_id,
resource_update=update,
response_model=OAuthDeviceResponse,
route=DEVICES,
)
def delete_authorized_device(self, device_id: UUID) -> None:
"""Deletes an OAuth 2.0 authorized device.
Args:
device_id: The ID of the device to delete.
"""
self._delete_resource(resource_id=device_id, route=DEVICES)
# -------------------
# Pipeline API Tokens
# -------------------
def get_api_token(
self,
pipeline_id: Optional[UUID] = None,
schedule_id: Optional[UUID] = None,
expires_minutes: Optional[int] = None,
) -> str:
"""Get an API token for a workload.
Args:
pipeline_id: The ID of the pipeline to get a token for.
schedule_id: The ID of the schedule to get a token for.
expires_minutes: The number of minutes for which the token should
be valid. If not provided, the token will be valid indefinitely.
Returns:
The API token.
Raises:
ValueError: if the server response is not valid.
"""
params: Dict[str, Any] = {}
if pipeline_id:
params["pipeline_id"] = pipeline_id
if schedule_id:
params["schedule_id"] = schedule_id
if expires_minutes:
params["expires_minutes"] = expires_minutes
response_body = self.get(API_TOKEN, params=params)
if not isinstance(response_body, str):
raise ValueError(
f"Bad API Response. Expected API token, got "
f"{type(response_body)}"
)
return response_body
#################
# Tags
#################
def create_tag(self, tag: TagRequest) -> TagResponse:
"""Creates a new tag.
Args:
tag: the tag to be created.
Returns:
The newly created tag.
"""
return self._create_resource(
resource=tag,
response_model=TagResponse,
route=TAGS,
)
def delete_tag(
self,
tag_name_or_id: Union[str, UUID],
) -> None:
"""Deletes a tag.
Args:
tag_name_or_id: name or id of the tag to delete.
"""
self._delete_resource(resource_id=tag_name_or_id, route=TAGS)
def get_tag(
self, tag_name_or_id: Union[str, UUID], hydrate: bool = True
) -> TagResponse:
"""Get an existing tag.
Args:
tag_name_or_id: name or id of the tag to be retrieved.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The tag of interest.
"""
return self._get_resource(
resource_id=tag_name_or_id,
route=TAGS,
response_model=TagResponse,
params={"hydrate": hydrate},
)
def list_tags(
self,
tag_filter_model: TagFilter,
hydrate: bool = False,
) -> Page[TagResponse]:
"""Get all tags by filter.
Args:
tag_filter_model: All filter parameters including pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all tags.
"""
return self._list_paginated_resources(
route=TAGS,
response_model=TagResponse,
filter_model=tag_filter_model,
params={"hydrate": hydrate},
)
def update_tag(
self,
tag_name_or_id: Union[str, UUID],
tag_update_model: TagUpdate,
) -> TagResponse:
"""Update tag.
Args:
tag_name_or_id: name or id of the tag to be updated.
tag_update_model: Tag to use for the update.
Returns:
An updated tag.
"""
tag = self.get_tag(tag_name_or_id)
return self._update_resource(
resource_id=tag.id,
resource_update=tag_update_model,
route=TAGS,
response_model=TagResponse,
)
# =======================
# Internal helper methods
# =======================
def _get_auth_token(self) -> str:
"""Get the authentication token for the REST store.
Returns:
The authentication token.
Raises:
ValueError: if the response from the server isn't in the right
format.
"""
if self._api_token is None:
# Check if the API token is already stored in the config
if self.config.api_token:
self._api_token = self.config.api_token
# Check if the username and password are provided in the config
elif (
self.config.username is not None
and self.config.password is not None
or self.config.api_key is not None
):
data: Optional[Dict[str, str]] = None
if self.config.api_key is not None:
data = {
"grant_type": OAuthGrantTypes.ZENML_API_KEY.value,
"password": self.config.api_key,
}
elif (
self.config.username is not None
and self.config.password is not None
):
data = {
"grant_type": OAuthGrantTypes.OAUTH_PASSWORD.value,
"username": self.config.username,
"password": self.config.password,
}
response = self._handle_response(
requests.post(
self.url + API + VERSION_1 + LOGIN,
data=data,
verify=self.config.verify_ssl,
timeout=self.config.http_timeout,
)
)
if (
not isinstance(response, dict)
or "access_token" not in response
):
raise ValueError(
f"Bad API Response. Expected access token dict, got "
f"{type(response)}"
)
self._api_token = response["access_token"]
self.config.api_token = self._api_token
else:
raise ValueError(
"No API token, API key or username/password provided. "
"Please provide either an API token, an API key or a "
"username and password in the ZenML config."
)
return self._api_token
@property
def session(self) -> requests.Session:
"""Authenticate to the ZenML server.
Returns:
A requests session with the authentication token.
"""
if self._session is None:
if self.config.verify_ssl is False:
urllib3.disable_warnings(
urllib3.exceptions.InsecureRequestWarning
)
self._session = requests.Session()
retries = Retry(backoff_factor=0.1, connect=5)
self._session.mount("https://", HTTPAdapter(max_retries=retries))
self._session.mount("http://", HTTPAdapter(max_retries=retries))
self._session.verify = self.config.verify_ssl
token = self._get_auth_token()
self._session.headers.update({"Authorization": "Bearer " + token})
logger.debug("Authenticated to ZenML server.")
return self._session
def clear_session(self) -> None:
"""Clear the authentication session and any cached API tokens."""
self._session = None
self._api_token = None
# Clear the configured API token only if it's possible to fetch a new
# one from the server using other credentials (username/password or
# service account API key).
if (
self.config.username is not None
and self.config.password is not None
or self.config.api_key is not None
):
self.config.api_token = None
@staticmethod
def _handle_response(response: requests.Response) -> Json:
"""Handle API response, translating http status codes to Exception.
Args:
response: The response to handle.
Returns:
The parsed response.
Raises:
ValueError: if the response is not in the right format.
RuntimeError: if an error response is received from the server
and a more specific exception cannot be determined.
exc: the exception converted from an error response, if one
is returned from the server.
"""
if 200 <= response.status_code < 300:
try:
payload: Json = response.json()
return payload
except requests.exceptions.JSONDecodeError:
raise ValueError(
"Bad response from API. Expected json, got\n"
f"{response.text}"
)
elif response.status_code >= 400:
exc = exception_from_response(response)
if exc is not None:
raise exc
else:
raise RuntimeError(
f"{response.status_code} HTTP Error received from server: "
f"{response.text}"
)
else:
raise RuntimeError(
"Error retrieving from API. Got response "
f"{response.status_code} with body:\n{response.text}"
)
def _request(
self,
method: str,
url: str,
params: Optional[Dict[str, Any]] = None,
**kwargs: Any,
) -> Json:
"""Make a request to the REST API.
Args:
method: The HTTP method to use.
url: The URL to request.
params: The query parameters to pass to the endpoint.
kwargs: Additional keyword arguments to pass to the request.
Returns:
The parsed response.
Raises:
AuthorizationException: if the request fails due to an expired
authentication token.
"""
params = {k: str(v) for k, v in params.items()} if params else {}
self.session.headers.update(
{source_context.name: source_context.get().value}
)
try:
return self._handle_response(
self.session.request(
method,
url,
params=params,
verify=self.config.verify_ssl,
timeout=self.config.http_timeout,
**kwargs,
)
)
except AuthorizationException:
# The authentication token could have expired; refresh it and try
# again. This will clear any cached token and trigger a new
# authentication flow.
self.clear_session()
logger.info("Authentication token expired; refreshing...")
try:
return self._handle_response(
self.session.request(
method,
url,
params=params,
verify=self.config.verify_ssl,
timeout=self.config.http_timeout,
**kwargs,
)
)
except AuthorizationException:
logger.info(
"Your authentication token has expired. Please re-authenticate."
)
raise
def get(
self, path: str, params: Optional[Dict[str, Any]] = None, **kwargs: Any
) -> Json:
"""Make a GET request to the given endpoint path.
Args:
path: The path to the endpoint.
params: The query parameters to pass to the endpoint.
kwargs: Additional keyword arguments to pass to the request.
Returns:
The response body.
"""
logger.debug(f"Sending GET request to {path}...")
return self._request(
"GET", self.url + API + VERSION_1 + path, params=params, **kwargs
)
def delete(
self, path: str, params: Optional[Dict[str, Any]] = None, **kwargs: Any
) -> Json:
"""Make a DELETE request to the given endpoint path.
Args:
path: The path to the endpoint.
params: The query parameters to pass to the endpoint.
kwargs: Additional keyword arguments to pass to the request.
Returns:
The response body.
"""
logger.debug(f"Sending DELETE request to {path}...")
return self._request(
"DELETE",
self.url + API + VERSION_1 + path,
params=params,
**kwargs,
)
def post(
self,
path: str,
body: BaseModel,
params: Optional[Dict[str, Any]] = None,
**kwargs: Any,
) -> Json:
"""Make a POST request to the given endpoint path.
Args:
path: The path to the endpoint.
body: The body to send.
params: The query parameters to pass to the endpoint.
kwargs: Additional keyword arguments to pass to the request.
Returns:
The response body.
"""
logger.debug(f"Sending POST request to {path}...")
return self._request(
"POST",
self.url + API + VERSION_1 + path,
data=body.json(),
params=params,
**kwargs,
)
def put(
self,
path: str,
body: Optional[BaseModel] = None,
params: Optional[Dict[str, Any]] = None,
**kwargs: Any,
) -> Json:
"""Make a PUT request to the given endpoint path.
Args:
path: The path to the endpoint.
body: The body to send.
params: The query parameters to pass to the endpoint.
kwargs: Additional keyword arguments to pass to the request.
Returns:
The response body.
"""
logger.debug(f"Sending PUT request to {path}...")
data = body.json(exclude_unset=True) if body else None
return self._request(
"PUT",
self.url + API + VERSION_1 + path,
data=data,
params=params,
**kwargs,
)
def _create_resource(
self,
resource: AnyRequest,
response_model: Type[AnyResponse],
route: str,
params: Optional[Dict[str, Any]] = None,
) -> AnyResponse:
"""Create a new resource.
Args:
resource: The resource to create.
route: The resource REST API route to use.
response_model: Optional model to use to deserialize the response
body. If not provided, the resource class itself will be used.
params: Optional query parameters to pass to the endpoint.
Returns:
The created resource.
"""
response_body = self.post(f"{route}", body=resource, params=params)
return response_model.parse_obj(response_body)
def _create_workspace_scoped_resource(
self,
resource: AnyWorkspaceScopedRequest,
response_model: Type[AnyResponse],
route: str,
params: Optional[Dict[str, Any]] = None,
) -> AnyResponse:
"""Create a new workspace scoped resource.
Args:
resource: The resource to create.
route: The resource REST API route to use.
response_model: Optional model to use to deserialize the response
body. If not provided, the resource class itself will be used.
params: Optional query parameters to pass to the endpoint.
Returns:
The created resource.
"""
return self._create_resource(
resource=resource,
response_model=response_model,
route=f"{WORKSPACES}/{str(resource.workspace)}{route}",
params=params,
)
def _get_or_create_resource(
self,
resource: AnyRequest,
response_model: Type[AnyResponse],
route: str,
params: Optional[Dict[str, Any]] = None,
) -> Tuple[AnyResponse, bool]:
"""Get or create a resource.
Args:
resource: The resource to get or create.
route: The resource REST API route to use.
response_model: Optional model to use to deserialize the response
body. If not provided, the resource class itself will be used.
params: Optional query parameters to pass to the endpoint.
Returns:
The created resource, and a boolean indicating whether the resource
was created or not.
Raises:
ValueError: If the response body is not a list with 2 elements
where the first element is the resource and the second element
a boolean indicating whether the resource was created or not.
"""
response_body = self.post(
f"{route}{GET_OR_CREATE}",
body=resource,
params=params,
)
if not isinstance(response_body, list):
raise ValueError(
f"Expected a list response from the {route}{GET_OR_CREATE} "
f"endpoint but got {type(response_body)} instead."
)
if len(response_body) != 2:
raise ValueError(
f"Expected a list response with 2 elements from the "
f"{route}{GET_OR_CREATE} endpoint but got {len(response_body)} "
f"elements instead."
)
model_json, was_created = response_body
if not isinstance(was_created, bool):
raise ValueError(
f"Expected a boolean as the second element of the list "
f"response from the {route}{GET_OR_CREATE} endpoint but got "
f"{type(was_created)} instead."
)
return response_model.parse_obj(model_json), was_created
def _get_or_create_workspace_scoped_resource(
self,
resource: AnyWorkspaceScopedRequest,
response_model: Type[AnyResponse],
route: str,
params: Optional[Dict[str, Any]] = None,
) -> Tuple[AnyResponse, bool]:
"""Get or create a workspace scoped resource.
Args:
resource: The resource to get or create.
route: The resource REST API route to use.
response_model: Optional model to use to deserialize the response
body. If not provided, the resource class itself will be used.
params: Optional query parameters to pass to the endpoint.
Returns:
The created resource, and a boolean indicating whether the resource
was created or not.
"""
return self._get_or_create_resource(
resource=resource,
response_model=response_model,
route=f"{WORKSPACES}/{str(resource.workspace)}{route}",
params=params,
)
def _get_resource(
self,
resource_id: Union[str, int, UUID],
route: str,
response_model: Type[AnyResponse],
params: Optional[Dict[str, Any]] = None,
) -> AnyResponse:
"""Retrieve a single resource.
Args:
resource_id: The ID of the resource to retrieve.
route: The resource REST API route to use.
response_model: Model to use to serialize the response body.
params: Optional query parameters to pass to the endpoint.
Returns:
The retrieved resource.
"""
body = self.get(f"{route}/{str(resource_id)}", params=params)
return response_model.parse_obj(body)
def _list_paginated_resources(
self,
route: str,
response_model: Type[AnyResponse],
filter_model: BaseFilter,
params: Optional[Dict[str, Any]] = None,
) -> Page[AnyResponse]:
"""Retrieve a list of resources filtered by some criteria.
Args:
route: The resource REST API route to use.
response_model: Model to use to serialize the response body.
filter_model: The filter model to use for the list query.
params: Optional query parameters to pass to the endpoint.
Returns:
List of retrieved resources matching the filter criteria.
Raises:
ValueError: If the value returned by the server is not a list.
"""
# leave out filter params that are not supplied
params = params or {}
params.update(filter_model.dict(exclude_none=True))
body = self.get(f"{route}", params=params)
if not isinstance(body, dict):
raise ValueError(
f"Bad API Response. Expected list, got {type(body)}"
)
# The initial page of items will be of type BaseResponseModel
page_of_items: Page[AnyResponse] = Page.parse_obj(body)
# So these items will be parsed into their correct types like here
page_of_items.items = [
response_model.parse_obj(generic_item)
for generic_item in body["items"]
]
return page_of_items
def _list_resources(
self,
route: str,
response_model: Type[AnyResponse],
**filters: Any,
) -> List[AnyResponse]:
"""Retrieve a list of resources filtered by some criteria.
Args:
route: The resource REST API route to use.
response_model: Model to use to serialize the response body.
filters: Filter parameters to use in the query.
Returns:
List of retrieved resources matching the filter criteria.
Raises:
ValueError: If the value returned by the server is not a list.
"""
# leave out filter params that are not supplied
params = dict(filter(lambda x: x[1] is not None, filters.items()))
body = self.get(f"{route}", params=params)
if not isinstance(body, list):
raise ValueError(
f"Bad API Response. Expected list, got {type(body)}"
)
return [response_model.parse_obj(entry) for entry in body]
def _update_resource(
self,
resource_id: Union[str, int, UUID],
resource_update: BaseModel,
response_model: Type[AnyResponse],
route: str,
params: Optional[Dict[str, Any]] = None,
) -> AnyResponse:
"""Update an existing resource.
Args:
resource_id: The id of the resource to update.
resource_update: The resource update.
response_model: Optional model to use to deserialize the response
body. If not provided, the resource class itself will be used.
route: The resource REST API route to use.
params: Optional query parameters to pass to the endpoint.
Returns:
The updated resource.
"""
response_body = self.put(
f"{route}/{str(resource_id)}", body=resource_update, params=params
)
return response_model.parse_obj(response_body)
def _delete_resource(
self, resource_id: Union[str, UUID], route: str
) -> None:
"""Delete a resource.
Args:
resource_id: The ID of the resource to delete.
route: The resource REST API route to use.
"""
self.delete(f"{route}/{str(resource_id)}")
session: Session
property
readonly
Authenticate to the ZenML server.
Returns:
| Type | Description |
|---|---|
Session |
A requests session with the authentication token. |
CONFIG_TYPE (StoreConfiguration)
pydantic-model
REST ZenML store configuration.
Attributes:
| Name | Type | Description |
|---|---|---|
type |
StoreType |
The type of the store. |
username |
Optional[str] |
The username to use to connect to the Zen server. |
password |
Optional[str] |
The password to use to connect to the Zen server. |
api_key |
Optional[str] |
The service account API key to use to connect to the Zen server. |
api_token |
Optional[str] |
The API token to use to connect to the Zen server. Generated by the client and stored in the configuration file on the first login and every time the API key is refreshed. |
verify_ssl |
Union[bool, str] |
Either a boolean, in which case it controls whether we verify the server's TLS certificate, or a string, in which case it must be a path to a CA bundle to use or the CA bundle value itself. |
http_timeout |
int |
The timeout to use for all requests. |
Source code in zenml/zen_stores/rest_zen_store.py
class RestZenStoreConfiguration(StoreConfiguration):
"""REST ZenML store configuration.
Attributes:
type: The type of the store.
username: The username to use to connect to the Zen server.
password: The password to use to connect to the Zen server.
api_key: The service account API key to use to connect to the Zen
server.
api_token: The API token to use to connect to the Zen server. Generated
by the client and stored in the configuration file on the first
login and every time the API key is refreshed.
verify_ssl: Either a boolean, in which case it controls whether we
verify the server's TLS certificate, or a string, in which case it
must be a path to a CA bundle to use or the CA bundle value itself.
http_timeout: The timeout to use for all requests.
"""
type: StoreType = StoreType.REST
username: Optional[str] = None
password: Optional[str] = None
api_key: Optional[str] = None
api_token: Optional[str] = None
verify_ssl: Union[bool, str] = True
http_timeout: int = DEFAULT_HTTP_TIMEOUT
@root_validator
def validate_credentials(cls, values: Dict[str, Any]) -> Dict[str, Any]:
"""Validates the credentials provided in the values dictionary.
Args:
values: A dictionary containing the values to be validated.
Raises:
ValueError: If neither api_token nor username nor api_key is set.
Returns:
The values dictionary.
"""
# Check if the values dictionary contains either an API token, an API
# key or a username as non-empty strings.
if (
values.get("api_token")
or values.get("username")
or values.get("api_key")
):
return values
raise ValueError(
"Neither api_token nor username nor api_key is set in the "
"store config."
)
@validator("url")
def validate_url(cls, url: str) -> str:
"""Validates that the URL is a well-formed REST store URL.
Args:
url: The URL to be validated.
Returns:
The validated URL without trailing slashes.
Raises:
ValueError: If the URL is not a well-formed REST store URL.
"""
url = url.rstrip("/")
scheme = re.search("^([a-z0-9]+://)", url)
if scheme is None or scheme.group() not in ("https://", "http://"):
raise ValueError(
"Invalid URL for REST store: {url}. Should be in the form "
"https://hostname[:port] or http://hostname[:port]."
)
# When running inside a container, if the URL uses localhost, the
# target service will not be available. We try to replace localhost
# with one of the special Docker or K3D internal hostnames.
url = replace_localhost_with_internal_hostname(url)
return url
@validator("verify_ssl")
def validate_verify_ssl(
cls, verify_ssl: Union[bool, str]
) -> Union[bool, str]:
"""Validates that the verify_ssl either points to a file or is a bool.
Args:
verify_ssl: The verify_ssl value to be validated.
Returns:
The validated verify_ssl value.
"""
secret_folder = Path(
GlobalConfiguration().local_stores_path,
"certificates",
)
if isinstance(verify_ssl, bool) or verify_ssl.startswith(
str(secret_folder)
):
return verify_ssl
if os.path.isfile(verify_ssl):
with open(verify_ssl, "r") as f:
verify_ssl = f.read()
fileio.makedirs(str(secret_folder))
file_path = Path(secret_folder, "ca_bundle.pem")
with open(file_path, "w") as f:
f.write(verify_ssl)
file_path.chmod(0o600)
verify_ssl = str(file_path)
return verify_ssl
@classmethod
def supports_url_scheme(cls, url: str) -> bool:
"""Check if a URL scheme is supported by this store.
Args:
url: The URL to check.
Returns:
True if the URL scheme is supported, False otherwise.
"""
return urlparse(url).scheme in ("http", "https")
def expand_certificates(self) -> None:
"""Expands the certificates in the verify_ssl field."""
# Load the certificate values back into the configuration
if isinstance(self.verify_ssl, str) and os.path.isfile(
self.verify_ssl
):
with open(self.verify_ssl, "r") as f:
self.verify_ssl = f.read()
class Config:
"""Pydantic configuration class."""
# Don't validate attributes when assigning them. This is necessary
# because the `verify_ssl` attribute can be expanded to the contents
# of the certificate file.
validate_assignment = False
# Forbid extra attributes set in the class.
extra = "forbid"
Config
Pydantic configuration class.
Source code in zenml/zen_stores/rest_zen_store.py
class Config:
"""Pydantic configuration class."""
# Don't validate attributes when assigning them. This is necessary
# because the `verify_ssl` attribute can be expanded to the contents
# of the certificate file.
validate_assignment = False
# Forbid extra attributes set in the class.
extra = "forbid"
expand_certificates(self)
Expands the certificates in the verify_ssl field.
Source code in zenml/zen_stores/rest_zen_store.py
def expand_certificates(self) -> None:
"""Expands the certificates in the verify_ssl field."""
# Load the certificate values back into the configuration
if isinstance(self.verify_ssl, str) and os.path.isfile(
self.verify_ssl
):
with open(self.verify_ssl, "r") as f:
self.verify_ssl = f.read()
supports_url_scheme(url)
classmethod
Check if a URL scheme is supported by this store.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
url |
str |
The URL to check. |
required |
Returns:
| Type | Description |
|---|---|
bool |
True if the URL scheme is supported, False otherwise. |
Source code in zenml/zen_stores/rest_zen_store.py
@classmethod
def supports_url_scheme(cls, url: str) -> bool:
"""Check if a URL scheme is supported by this store.
Args:
url: The URL to check.
Returns:
True if the URL scheme is supported, False otherwise.
"""
return urlparse(url).scheme in ("http", "https")
validate_credentials(values)
classmethod
Validates the credentials provided in the values dictionary.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
values |
Dict[str, Any] |
A dictionary containing the values to be validated. |
required |
Exceptions:
| Type | Description |
|---|---|
ValueError |
If neither api_token nor username nor api_key is set. |
Returns:
| Type | Description |
|---|---|
Dict[str, Any] |
The values dictionary. |
Source code in zenml/zen_stores/rest_zen_store.py
@root_validator
def validate_credentials(cls, values: Dict[str, Any]) -> Dict[str, Any]:
"""Validates the credentials provided in the values dictionary.
Args:
values: A dictionary containing the values to be validated.
Raises:
ValueError: If neither api_token nor username nor api_key is set.
Returns:
The values dictionary.
"""
# Check if the values dictionary contains either an API token, an API
# key or a username as non-empty strings.
if (
values.get("api_token")
or values.get("username")
or values.get("api_key")
):
return values
raise ValueError(
"Neither api_token nor username nor api_key is set in the "
"store config."
)
validate_url(url)
classmethod
Validates that the URL is a well-formed REST store URL.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
url |
str |
The URL to be validated. |
required |
Returns:
| Type | Description |
|---|---|
str |
The validated URL without trailing slashes. |
Exceptions:
| Type | Description |
|---|---|
ValueError |
If the URL is not a well-formed REST store URL. |
Source code in zenml/zen_stores/rest_zen_store.py
@validator("url")
def validate_url(cls, url: str) -> str:
"""Validates that the URL is a well-formed REST store URL.
Args:
url: The URL to be validated.
Returns:
The validated URL without trailing slashes.
Raises:
ValueError: If the URL is not a well-formed REST store URL.
"""
url = url.rstrip("/")
scheme = re.search("^([a-z0-9]+://)", url)
if scheme is None or scheme.group() not in ("https://", "http://"):
raise ValueError(
"Invalid URL for REST store: {url}. Should be in the form "
"https://hostname[:port] or http://hostname[:port]."
)
# When running inside a container, if the URL uses localhost, the
# target service will not be available. We try to replace localhost
# with one of the special Docker or K3D internal hostnames.
url = replace_localhost_with_internal_hostname(url)
return url
validate_verify_ssl(verify_ssl)
classmethod
Validates that the verify_ssl either points to a file or is a bool.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
verify_ssl |
Union[bool, str] |
The verify_ssl value to be validated. |
required |
Returns:
| Type | Description |
|---|---|
Union[bool, str] |
The validated verify_ssl value. |
Source code in zenml/zen_stores/rest_zen_store.py
@validator("verify_ssl")
def validate_verify_ssl(
cls, verify_ssl: Union[bool, str]
) -> Union[bool, str]:
"""Validates that the verify_ssl either points to a file or is a bool.
Args:
verify_ssl: The verify_ssl value to be validated.
Returns:
The validated verify_ssl value.
"""
secret_folder = Path(
GlobalConfiguration().local_stores_path,
"certificates",
)
if isinstance(verify_ssl, bool) or verify_ssl.startswith(
str(secret_folder)
):
return verify_ssl
if os.path.isfile(verify_ssl):
with open(verify_ssl, "r") as f:
verify_ssl = f.read()
fileio.makedirs(str(secret_folder))
file_path = Path(secret_folder, "ca_bundle.pem")
with open(file_path, "w") as f:
f.write(verify_ssl)
file_path.chmod(0o600)
verify_ssl = str(file_path)
return verify_ssl
backup_secrets(self, ignore_errors=True, delete_secrets=False)
Backs up all secrets to the configured backup secrets store.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
ignore_errors |
bool |
Whether to ignore individual errors during the backup process and attempt to backup all secrets. |
True |
delete_secrets |
bool |
Whether to delete the secrets that have been successfully backed up from the primary secrets store. Setting this flag effectively moves all secrets from the primary secrets store to the backup secrets store. |
False |
Source code in zenml/zen_stores/rest_zen_store.py
def backup_secrets(
self, ignore_errors: bool = True, delete_secrets: bool = False
) -> None:
"""Backs up all secrets to the configured backup secrets store.
Args:
ignore_errors: Whether to ignore individual errors during the backup
process and attempt to backup all secrets.
delete_secrets: Whether to delete the secrets that have been
successfully backed up from the primary secrets store. Setting
this flag effectively moves all secrets from the primary secrets
store to the backup secrets store.
"""
params: Dict[str, Any] = {
"ignore_errors": ignore_errors,
"delete_secrets": delete_secrets,
}
self.put(
f"{SECRETS_OPERATIONS}{SECRETS_BACKUP}",
params=params,
)
clear_session(self)
Clear the authentication session and any cached API tokens.
Source code in zenml/zen_stores/rest_zen_store.py
def clear_session(self) -> None:
"""Clear the authentication session and any cached API tokens."""
self._session = None
self._api_token = None
# Clear the configured API token only if it's possible to fetch a new
# one from the server using other credentials (username/password or
# service account API key).
if (
self.config.username is not None
and self.config.password is not None
or self.config.api_key is not None
):
self.config.api_token = None
create_api_key(self, service_account_id, api_key)
Create a new API key for a service account.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account_id |
UUID |
The ID of the service account for which to create the API key. |
required |
api_key |
APIKeyRequest |
The API key to create. |
required |
Returns:
| Type | Description |
|---|---|
APIKeyResponse |
The created API key. |
Source code in zenml/zen_stores/rest_zen_store.py
def create_api_key(
self, service_account_id: UUID, api_key: APIKeyRequest
) -> APIKeyResponse:
"""Create a new API key for a service account.
Args:
service_account_id: The ID of the service account for which to
create the API key.
api_key: The API key to create.
Returns:
The created API key.
"""
return self._create_resource(
resource=api_key,
route=f"{SERVICE_ACCOUNTS}/{str(service_account_id)}{API_KEYS}",
response_model=APIKeyResponse,
)
create_artifact(self, artifact)
Creates a new artifact.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact |
ArtifactRequest |
The artifact to create. |
required |
Returns:
| Type | Description |
|---|---|
ArtifactResponse |
The newly created artifact. |
Source code in zenml/zen_stores/rest_zen_store.py
def create_artifact(self, artifact: ArtifactRequest) -> ArtifactResponse:
"""Creates a new artifact.
Args:
artifact: The artifact to create.
Returns:
The newly created artifact.
"""
return self._create_resource(
resource=artifact,
response_model=ArtifactResponse,
route=ARTIFACTS,
)
create_artifact_version(self, artifact_version)
Creates an artifact version.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_version |
ArtifactVersionRequest |
The artifact version to create. |
required |
Returns:
| Type | Description |
|---|---|
ArtifactVersionResponse |
The created artifact version. |
Source code in zenml/zen_stores/rest_zen_store.py
def create_artifact_version(
self, artifact_version: ArtifactVersionRequest
) -> ArtifactVersionResponse:
"""Creates an artifact version.
Args:
artifact_version: The artifact version to create.
Returns:
The created artifact version.
"""
return self._create_resource(
resource=artifact_version,
response_model=ArtifactVersionResponse,
route=ARTIFACT_VERSIONS,
)
create_build(self, build)
Creates a new build in a workspace.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
build |
PipelineBuildRequest |
The build to create. |
required |
Returns:
| Type | Description |
|---|---|
PipelineBuildResponse |
The newly created build. |
Source code in zenml/zen_stores/rest_zen_store.py
def create_build(
self,
build: PipelineBuildRequest,
) -> PipelineBuildResponse:
"""Creates a new build in a workspace.
Args:
build: The build to create.
Returns:
The newly created build.
"""
return self._create_workspace_scoped_resource(
resource=build,
route=PIPELINE_BUILDS,
response_model=PipelineBuildResponse,
)
create_code_repository(self, code_repository)
Creates a new code repository.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
code_repository |
CodeRepositoryRequest |
Code repository to be created. |
required |
Returns:
| Type | Description |
|---|---|
CodeRepositoryResponse |
The newly created code repository. |
Source code in zenml/zen_stores/rest_zen_store.py
def create_code_repository(
self, code_repository: CodeRepositoryRequest
) -> CodeRepositoryResponse:
"""Creates a new code repository.
Args:
code_repository: Code repository to be created.
Returns:
The newly created code repository.
"""
return self._create_workspace_scoped_resource(
resource=code_repository,
response_model=CodeRepositoryResponse,
route=CODE_REPOSITORIES,
)
create_deployment(self, deployment)
Creates a new deployment in a workspace.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
deployment |
PipelineDeploymentRequest |
The deployment to create. |
required |
Returns:
| Type | Description |
|---|---|
PipelineDeploymentResponse |
The newly created deployment. |
Source code in zenml/zen_stores/rest_zen_store.py
def create_deployment(
self,
deployment: PipelineDeploymentRequest,
) -> PipelineDeploymentResponse:
"""Creates a new deployment in a workspace.
Args:
deployment: The deployment to create.
Returns:
The newly created deployment.
"""
return self._create_workspace_scoped_resource(
resource=deployment,
route=PIPELINE_DEPLOYMENTS,
response_model=PipelineDeploymentResponse,
)
create_event_source(self, event_source)
Create an event_source.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
event_source |
EventSourceRequest |
The event_source to create. |
required |
Returns:
| Type | Description |
|---|---|
EventSourceResponse |
The created event_source. |
Source code in zenml/zen_stores/rest_zen_store.py
def create_event_source(
self, event_source: EventSourceRequest
) -> EventSourceResponse:
"""Create an event_source.
Args:
event_source: The event_source to create.
Returns:
The created event_source.
"""
return self._create_resource(
resource=event_source,
route=EVENT_SOURCES,
response_model=EventSourceResponse,
)
create_flavor(self, flavor)
Creates a new stack component flavor.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
flavor |
FlavorRequest |
The stack component flavor to create. |
required |
Returns:
| Type | Description |
|---|---|
FlavorResponse |
The newly created flavor. |
Source code in zenml/zen_stores/rest_zen_store.py
def create_flavor(self, flavor: FlavorRequest) -> FlavorResponse:
"""Creates a new stack component flavor.
Args:
flavor: The stack component flavor to create.
Returns:
The newly created flavor.
"""
return self._create_resource(
resource=flavor,
route=FLAVORS,
response_model=FlavorResponse,
)
create_model(self, model)
Creates a new model.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model |
ModelRequest |
the Model to be created. |
required |
Returns:
| Type | Description |
|---|---|
ModelResponse |
The newly created model. |
Source code in zenml/zen_stores/rest_zen_store.py
def create_model(self, model: ModelRequest) -> ModelResponse:
"""Creates a new model.
Args:
model: the Model to be created.
Returns:
The newly created model.
"""
return self._create_workspace_scoped_resource(
resource=model,
response_model=ModelResponse,
route=MODELS,
)
create_model_version(self, model_version)
Creates a new model version.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version |
ModelVersionRequest |
the Model Version to be created. |
required |
Returns:
| Type | Description |
|---|---|
ModelVersionResponse |
The newly created model version. |
Source code in zenml/zen_stores/rest_zen_store.py
def create_model_version(
self, model_version: ModelVersionRequest
) -> ModelVersionResponse:
"""Creates a new model version.
Args:
model_version: the Model Version to be created.
Returns:
The newly created model version.
"""
return self._create_workspace_scoped_resource(
resource=model_version,
response_model=ModelVersionResponse,
route=f"{MODELS}/{model_version.model}{MODEL_VERSIONS}",
)
create_model_version_artifact_link(self, model_version_artifact_link)
Creates a new model version link.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_artifact_link |
ModelVersionArtifactRequest |
the Model Version to Artifact Link to be created. |
required |
Returns:
| Type | Description |
|---|---|
ModelVersionArtifactResponse |
The newly created model version to artifact link. |
Source code in zenml/zen_stores/rest_zen_store.py
def create_model_version_artifact_link(
self, model_version_artifact_link: ModelVersionArtifactRequest
) -> ModelVersionArtifactResponse:
"""Creates a new model version link.
Args:
model_version_artifact_link: the Model Version to Artifact Link
to be created.
Returns:
The newly created model version to artifact link.
"""
return self._create_workspace_scoped_resource(
resource=model_version_artifact_link,
response_model=ModelVersionArtifactResponse,
route=f"{MODEL_VERSIONS}/{model_version_artifact_link.model_version}{ARTIFACTS}",
)
create_model_version_pipeline_run_link(self, model_version_pipeline_run_link)
Creates a new model version to pipeline run link.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_pipeline_run_link |
ModelVersionPipelineRunRequest |
the Model Version to Pipeline Run Link to be created. |
required |
Returns:
| Type | Description |
|---|---|
ModelVersionPipelineRunResponse |
|
Source code in zenml/zen_stores/rest_zen_store.py
def create_model_version_pipeline_run_link(
self,
model_version_pipeline_run_link: ModelVersionPipelineRunRequest,
) -> ModelVersionPipelineRunResponse:
"""Creates a new model version to pipeline run link.
Args:
model_version_pipeline_run_link: the Model Version to Pipeline Run
Link to be created.
Returns:
- If Model Version to Pipeline Run Link already exists - returns
the existing link.
- Otherwise, returns the newly created model version to pipeline
run link.
"""
return self._create_workspace_scoped_resource(
resource=model_version_pipeline_run_link,
response_model=ModelVersionPipelineRunResponse,
route=f"{MODEL_VERSIONS}/{model_version_pipeline_run_link.model_version}{RUNS}",
)
create_pipeline(self, pipeline)
Creates a new pipeline in a workspace.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
pipeline |
PipelineRequest |
The pipeline to create. |
required |
Returns:
| Type | Description |
|---|---|
PipelineResponse |
The newly created pipeline. |
Source code in zenml/zen_stores/rest_zen_store.py
def create_pipeline(self, pipeline: PipelineRequest) -> PipelineResponse:
"""Creates a new pipeline in a workspace.
Args:
pipeline: The pipeline to create.
Returns:
The newly created pipeline.
"""
return self._create_workspace_scoped_resource(
resource=pipeline,
route=PIPELINES,
response_model=PipelineResponse,
)
create_run(self, pipeline_run)
Creates a pipeline run.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
pipeline_run |
PipelineRunRequest |
The pipeline run to create. |
required |
Returns:
| Type | Description |
|---|---|
PipelineRunResponse |
The created pipeline run. |
Source code in zenml/zen_stores/rest_zen_store.py
def create_run(
self, pipeline_run: PipelineRunRequest
) -> PipelineRunResponse:
"""Creates a pipeline run.
Args:
pipeline_run: The pipeline run to create.
Returns:
The created pipeline run.
"""
return self._create_workspace_scoped_resource(
resource=pipeline_run,
response_model=PipelineRunResponse,
route=RUNS,
)
create_run_metadata(self, run_metadata)
Creates run metadata.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
run_metadata |
RunMetadataRequest |
The run metadata to create. |
required |
Returns:
| Type | Description |
|---|---|
List[zenml.models.v2.core.run_metadata.RunMetadataResponse] |
The created run metadata. |
Source code in zenml/zen_stores/rest_zen_store.py
def create_run_metadata(
self, run_metadata: RunMetadataRequest
) -> List[RunMetadataResponse]:
"""Creates run metadata.
Args:
run_metadata: The run metadata to create.
Returns:
The created run metadata.
"""
route = f"{WORKSPACES}/{str(run_metadata.workspace)}{RUN_METADATA}"
response_body = self.post(f"{route}", body=run_metadata)
result: List[RunMetadataResponse] = []
if isinstance(response_body, list):
for metadata in response_body or []:
result.append(RunMetadataResponse.parse_obj(metadata))
return result
create_run_step(self, step_run)
Creates a step run.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
step_run |
StepRunRequest |
The step run to create. |
required |
Returns:
| Type | Description |
|---|---|
StepRunResponse |
The created step run. |
Source code in zenml/zen_stores/rest_zen_store.py
def create_run_step(self, step_run: StepRunRequest) -> StepRunResponse:
"""Creates a step run.
Args:
step_run: The step run to create.
Returns:
The created step run.
"""
return self._create_resource(
resource=step_run,
response_model=StepRunResponse,
route=STEPS,
)
create_schedule(self, schedule)
Creates a new schedule.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
schedule |
ScheduleRequest |
The schedule to create. |
required |
Returns:
| Type | Description |
|---|---|
ScheduleResponse |
The newly created schedule. |
Source code in zenml/zen_stores/rest_zen_store.py
def create_schedule(self, schedule: ScheduleRequest) -> ScheduleResponse:
"""Creates a new schedule.
Args:
schedule: The schedule to create.
Returns:
The newly created schedule.
"""
return self._create_workspace_scoped_resource(
resource=schedule,
route=SCHEDULES,
response_model=ScheduleResponse,
)
create_secret(self, secret)
Creates a new secret.
The new secret is also validated against the scoping rules enforced in the secrets store:
- only one workspace-scoped secret with the given name can exist in the target workspace.
- only one user-scoped secret with the given name can exist in the target workspace for the target user.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret |
SecretRequest |
The secret to create. |
required |
Returns:
| Type | Description |
|---|---|
SecretResponse |
The newly created secret. |
Source code in zenml/zen_stores/rest_zen_store.py
def create_secret(self, secret: SecretRequest) -> SecretResponse:
"""Creates a new secret.
The new secret is also validated against the scoping rules enforced in
the secrets store:
- only one workspace-scoped secret with the given name can exist
in the target workspace.
- only one user-scoped secret with the given name can exist in the
target workspace for the target user.
Args:
secret: The secret to create.
Returns:
The newly created secret.
"""
return self._create_workspace_scoped_resource(
resource=secret,
route=SECRETS,
response_model=SecretResponse,
)
create_service_account(self, service_account)
Creates a new service account.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account |
ServiceAccountRequest |
Service account to be created. |
required |
Returns:
| Type | Description |
|---|---|
ServiceAccountResponse |
The newly created service account. |
Source code in zenml/zen_stores/rest_zen_store.py
def create_service_account(
self, service_account: ServiceAccountRequest
) -> ServiceAccountResponse:
"""Creates a new service account.
Args:
service_account: Service account to be created.
Returns:
The newly created service account.
"""
return self._create_resource(
resource=service_account,
route=SERVICE_ACCOUNTS,
response_model=ServiceAccountResponse,
)
create_service_connector(self, service_connector)
Creates a new service connector.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_connector |
ServiceConnectorRequest |
Service connector to be created. |
required |
Returns:
| Type | Description |
|---|---|
ServiceConnectorResponse |
The newly created service connector. |
Source code in zenml/zen_stores/rest_zen_store.py
def create_service_connector(
self, service_connector: ServiceConnectorRequest
) -> ServiceConnectorResponse:
"""Creates a new service connector.
Args:
service_connector: Service connector to be created.
Returns:
The newly created service connector.
"""
connector_model = self._create_workspace_scoped_resource(
resource=service_connector,
route=SERVICE_CONNECTORS,
response_model=ServiceConnectorResponse,
)
self._populate_connector_type(connector_model)
return connector_model
create_stack(self, stack)
Register a new stack.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
stack |
StackRequest |
The stack to register. |
required |
Returns:
| Type | Description |
|---|---|
StackResponse |
The registered stack. |
Source code in zenml/zen_stores/rest_zen_store.py
def create_stack(self, stack: StackRequest) -> StackResponse:
"""Register a new stack.
Args:
stack: The stack to register.
Returns:
The registered stack.
"""
return self._create_workspace_scoped_resource(
resource=stack,
route=STACKS,
response_model=StackResponse,
)
create_stack_component(self, component)
Create a stack component.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
component |
ComponentRequest |
The stack component to create. |
required |
Returns:
| Type | Description |
|---|---|
ComponentResponse |
The created stack component. |
Source code in zenml/zen_stores/rest_zen_store.py
def create_stack_component(
self,
component: ComponentRequest,
) -> ComponentResponse:
"""Create a stack component.
Args:
component: The stack component to create.
Returns:
The created stack component.
"""
return self._create_workspace_scoped_resource(
resource=component,
route=STACK_COMPONENTS,
response_model=ComponentResponse,
)
create_tag(self, tag)
Creates a new tag.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
tag |
TagRequest |
the tag to be created. |
required |
Returns:
| Type | Description |
|---|---|
TagResponse |
The newly created tag. |
Source code in zenml/zen_stores/rest_zen_store.py
def create_tag(self, tag: TagRequest) -> TagResponse:
"""Creates a new tag.
Args:
tag: the tag to be created.
Returns:
The newly created tag.
"""
return self._create_resource(
resource=tag,
response_model=TagResponse,
route=TAGS,
)
create_trigger(self, trigger)
Create an trigger.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
trigger |
TriggerRequest |
The trigger to create. |
required |
Returns:
| Type | Description |
|---|---|
TriggerResponse |
The created trigger. |
Source code in zenml/zen_stores/rest_zen_store.py
def create_trigger(self, trigger: TriggerRequest) -> TriggerResponse:
"""Create an trigger.
Args:
trigger: The trigger to create.
Returns:
The created trigger.
"""
return self._create_resource(
resource=trigger,
route=TRIGGERS,
response_model=TriggerResponse,
)
create_user(self, user)
Creates a new user.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
user |
UserRequest |
User to be created. |
required |
Returns:
| Type | Description |
|---|---|
UserResponse |
The newly created user. |
Source code in zenml/zen_stores/rest_zen_store.py
def create_user(self, user: UserRequest) -> UserResponse:
"""Creates a new user.
Args:
user: User to be created.
Returns:
The newly created user.
"""
return self._create_resource(
resource=user,
route=USERS,
response_model=UserResponse,
)
create_workspace(self, workspace)
Creates a new workspace.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
workspace |
WorkspaceRequest |
The workspace to create. |
required |
Returns:
| Type | Description |
|---|---|
WorkspaceResponse |
The newly created workspace. |
Source code in zenml/zen_stores/rest_zen_store.py
def create_workspace(
self, workspace: WorkspaceRequest
) -> WorkspaceResponse:
"""Creates a new workspace.
Args:
workspace: The workspace to create.
Returns:
The newly created workspace.
"""
return self._create_resource(
resource=workspace,
route=WORKSPACES,
response_model=WorkspaceResponse,
)
delete(self, path, params=None, **kwargs)
Make a DELETE request to the given endpoint path.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
path |
str |
The path to the endpoint. |
required |
params |
Optional[Dict[str, Any]] |
The query parameters to pass to the endpoint. |
None |
kwargs |
Any |
Additional keyword arguments to pass to the request. |
{} |
Returns:
| Type | Description |
|---|---|
Union[Dict[str, Any], List[Any], str, int, float, bool] |
The response body. |
Source code in zenml/zen_stores/rest_zen_store.py
def delete(
self, path: str, params: Optional[Dict[str, Any]] = None, **kwargs: Any
) -> Json:
"""Make a DELETE request to the given endpoint path.
Args:
path: The path to the endpoint.
params: The query parameters to pass to the endpoint.
kwargs: Additional keyword arguments to pass to the request.
Returns:
The response body.
"""
logger.debug(f"Sending DELETE request to {path}...")
return self._request(
"DELETE",
self.url + API + VERSION_1 + path,
params=params,
**kwargs,
)
delete_all_model_version_artifact_links(self, model_version_id, only_links=True)
Deletes all links between model version and an artifact.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_id |
UUID |
ID of the model version containing the link. |
required |
only_links |
bool |
Flag deciding whether to delete only links or all. |
True |
Source code in zenml/zen_stores/rest_zen_store.py
def delete_all_model_version_artifact_links(
self,
model_version_id: UUID,
only_links: bool = True,
) -> None:
"""Deletes all links between model version and an artifact.
Args:
model_version_id: ID of the model version containing the link.
only_links: Flag deciding whether to delete only links or all.
"""
self.delete(
f"{MODEL_VERSIONS}/{model_version_id}{ARTIFACTS}",
params={"only_links": only_links},
)
delete_api_key(self, service_account_id, api_key_name_or_id)
Delete an API key for a service account.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account_id |
UUID |
The ID of the service account for which to delete the API key. |
required |
api_key_name_or_id |
Union[str, uuid.UUID] |
The name or ID of the API key to delete. |
required |
Source code in zenml/zen_stores/rest_zen_store.py
def delete_api_key(
self,
service_account_id: UUID,
api_key_name_or_id: Union[str, UUID],
) -> None:
"""Delete an API key for a service account.
Args:
service_account_id: The ID of the service account for which to
delete the API key.
api_key_name_or_id: The name or ID of the API key to delete.
"""
self._delete_resource(
resource_id=api_key_name_or_id,
route=f"{SERVICE_ACCOUNTS}/{str(service_account_id)}{API_KEYS}",
)
delete_artifact(self, artifact_id)
Deletes an artifact.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_id |
UUID |
The ID of the artifact to delete. |
required |
Source code in zenml/zen_stores/rest_zen_store.py
def delete_artifact(self, artifact_id: UUID) -> None:
"""Deletes an artifact.
Args:
artifact_id: The ID of the artifact to delete.
"""
self._delete_resource(resource_id=artifact_id, route=ARTIFACTS)
delete_artifact_version(self, artifact_version_id)
Deletes an artifact version.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_version_id |
UUID |
The ID of the artifact version to delete. |
required |
Source code in zenml/zen_stores/rest_zen_store.py
def delete_artifact_version(self, artifact_version_id: UUID) -> None:
"""Deletes an artifact version.
Args:
artifact_version_id: The ID of the artifact version to delete.
"""
self._delete_resource(
resource_id=artifact_version_id, route=ARTIFACT_VERSIONS
)
delete_authorized_device(self, device_id)
Deletes an OAuth 2.0 authorized device.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
device_id |
UUID |
The ID of the device to delete. |
required |
Source code in zenml/zen_stores/rest_zen_store.py
def delete_authorized_device(self, device_id: UUID) -> None:
"""Deletes an OAuth 2.0 authorized device.
Args:
device_id: The ID of the device to delete.
"""
self._delete_resource(resource_id=device_id, route=DEVICES)
delete_build(self, build_id)
Deletes a build.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
build_id |
UUID |
The ID of the build to delete. |
required |
Source code in zenml/zen_stores/rest_zen_store.py
def delete_build(self, build_id: UUID) -> None:
"""Deletes a build.
Args:
build_id: The ID of the build to delete.
"""
self._delete_resource(
resource_id=build_id,
route=PIPELINE_BUILDS,
)
# ----------------------
# Pipeline Deployments
# ----------------------
delete_code_repository(self, code_repository_id)
Deletes a code repository.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
code_repository_id |
UUID |
The ID of the code repository to delete. |
required |
Source code in zenml/zen_stores/rest_zen_store.py
def delete_code_repository(self, code_repository_id: UUID) -> None:
"""Deletes a code repository.
Args:
code_repository_id: The ID of the code repository to delete.
"""
self._delete_resource(
resource_id=code_repository_id, route=CODE_REPOSITORIES
)
delete_deployment(self, deployment_id)
Deletes a deployment.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
deployment_id |
UUID |
The ID of the deployment to delete. |
required |
Source code in zenml/zen_stores/rest_zen_store.py
def delete_deployment(self, deployment_id: UUID) -> None:
"""Deletes a deployment.
Args:
deployment_id: The ID of the deployment to delete.
"""
self._delete_resource(
resource_id=deployment_id,
route=PIPELINE_DEPLOYMENTS,
)
delete_event_source(self, event_source_id)
Delete an event_source.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
event_source_id |
UUID |
The ID of the event_source to delete. |
required |
Source code in zenml/zen_stores/rest_zen_store.py
def delete_event_source(self, event_source_id: UUID) -> None:
"""Delete an event_source.
Args:
event_source_id: The ID of the event_source to delete.
"""
self._delete_resource(
resource_id=event_source_id,
route=EVENT_SOURCES,
)
delete_flavor(self, flavor_id)
Delete a stack component flavor.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
flavor_id |
UUID |
The ID of the stack component flavor to delete. |
required |
Source code in zenml/zen_stores/rest_zen_store.py
def delete_flavor(self, flavor_id: UUID) -> None:
"""Delete a stack component flavor.
Args:
flavor_id: The ID of the stack component flavor to delete.
"""
self._delete_resource(
resource_id=flavor_id,
route=FLAVORS,
)
delete_model(self, model_name_or_id)
Deletes a model.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_name_or_id |
Union[str, uuid.UUID] |
name or id of the model to be deleted. |
required |
Source code in zenml/zen_stores/rest_zen_store.py
def delete_model(self, model_name_or_id: Union[str, UUID]) -> None:
"""Deletes a model.
Args:
model_name_or_id: name or id of the model to be deleted.
"""
self._delete_resource(resource_id=model_name_or_id, route=MODELS)
delete_model_version(self, model_version_id)
Deletes a model version.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_id |
UUID |
name or id of the model version to be deleted. |
required |
Source code in zenml/zen_stores/rest_zen_store.py
def delete_model_version(
self,
model_version_id: UUID,
) -> None:
"""Deletes a model version.
Args:
model_version_id: name or id of the model version to be deleted.
"""
self._delete_resource(
resource_id=model_version_id,
route=f"{MODEL_VERSIONS}",
)
delete_model_version_artifact_link(self, model_version_id, model_version_artifact_link_name_or_id)
Deletes a model version to artifact link.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_id |
UUID |
ID of the model version containing the link. |
required |
model_version_artifact_link_name_or_id |
Union[str, uuid.UUID] |
name or ID of the model version to artifact link to be deleted. |
required |
Source code in zenml/zen_stores/rest_zen_store.py
def delete_model_version_artifact_link(
self,
model_version_id: UUID,
model_version_artifact_link_name_or_id: Union[str, UUID],
) -> None:
"""Deletes a model version to artifact link.
Args:
model_version_id: ID of the model version containing the link.
model_version_artifact_link_name_or_id: name or ID of the model
version to artifact link to be deleted.
"""
self._delete_resource(
resource_id=model_version_artifact_link_name_or_id,
route=f"{MODEL_VERSIONS}/{model_version_id}{ARTIFACTS}",
)
delete_model_version_pipeline_run_link(self, model_version_id, model_version_pipeline_run_link_name_or_id)
Deletes a model version to pipeline run link.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_id |
UUID |
ID of the model version containing the link. |
required |
model_version_pipeline_run_link_name_or_id |
Union[str, uuid.UUID] |
name or ID of the model version to pipeline run link to be deleted. |
required |
Source code in zenml/zen_stores/rest_zen_store.py
def delete_model_version_pipeline_run_link(
self,
model_version_id: UUID,
model_version_pipeline_run_link_name_or_id: Union[str, UUID],
) -> None:
"""Deletes a model version to pipeline run link.
Args:
model_version_id: ID of the model version containing the link.
model_version_pipeline_run_link_name_or_id: name or ID of the model version to pipeline run link to be deleted.
"""
self._delete_resource(
resource_id=model_version_pipeline_run_link_name_or_id,
route=f"{MODEL_VERSIONS}/{model_version_id}{RUNS}",
)
delete_pipeline(self, pipeline_id)
Deletes a pipeline.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
pipeline_id |
UUID |
The ID of the pipeline to delete. |
required |
Source code in zenml/zen_stores/rest_zen_store.py
def delete_pipeline(self, pipeline_id: UUID) -> None:
"""Deletes a pipeline.
Args:
pipeline_id: The ID of the pipeline to delete.
"""
self._delete_resource(
resource_id=pipeline_id,
route=PIPELINES,
)
delete_run(self, run_id)
Deletes a pipeline run.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
run_id |
UUID |
The ID of the pipeline run to delete. |
required |
Source code in zenml/zen_stores/rest_zen_store.py
def delete_run(self, run_id: UUID) -> None:
"""Deletes a pipeline run.
Args:
run_id: The ID of the pipeline run to delete.
"""
self._delete_resource(
resource_id=run_id,
route=RUNS,
)
delete_schedule(self, schedule_id)
Deletes a schedule.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
schedule_id |
UUID |
The ID of the schedule to delete. |
required |
Source code in zenml/zen_stores/rest_zen_store.py
def delete_schedule(self, schedule_id: UUID) -> None:
"""Deletes a schedule.
Args:
schedule_id: The ID of the schedule to delete.
"""
self._delete_resource(
resource_id=schedule_id,
route=SCHEDULES,
)
delete_secret(self, secret_id)
Delete a secret.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
The id of the secret to delete. |
required |
Source code in zenml/zen_stores/rest_zen_store.py
def delete_secret(self, secret_id: UUID) -> None:
"""Delete a secret.
Args:
secret_id: The id of the secret to delete.
"""
self._delete_resource(
resource_id=secret_id,
route=SECRETS,
)
delete_service_account(self, service_account_name_or_id)
Delete a service account.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account_name_or_id |
Union[str, uuid.UUID] |
The name or the ID of the service account to delete. |
required |
Source code in zenml/zen_stores/rest_zen_store.py
def delete_service_account(
self,
service_account_name_or_id: Union[str, UUID],
) -> None:
"""Delete a service account.
Args:
service_account_name_or_id: The name or the ID of the service
account to delete.
"""
self._delete_resource(
resource_id=service_account_name_or_id,
route=SERVICE_ACCOUNTS,
)
delete_service_connector(self, service_connector_id)
Deletes a service connector.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_connector_id |
UUID |
The ID of the service connector to delete. |
required |
Source code in zenml/zen_stores/rest_zen_store.py
def delete_service_connector(self, service_connector_id: UUID) -> None:
"""Deletes a service connector.
Args:
service_connector_id: The ID of the service connector to delete.
"""
self._delete_resource(
resource_id=service_connector_id, route=SERVICE_CONNECTORS
)
delete_stack(self, stack_id)
Delete a stack.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
stack_id |
UUID |
The ID of the stack to delete. |
required |
Source code in zenml/zen_stores/rest_zen_store.py
def delete_stack(self, stack_id: UUID) -> None:
"""Delete a stack.
Args:
stack_id: The ID of the stack to delete.
"""
self._delete_resource(
resource_id=stack_id,
route=STACKS,
)
delete_stack_component(self, component_id)
Delete a stack component.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
component_id |
UUID |
The ID of the stack component to delete. |
required |
Source code in zenml/zen_stores/rest_zen_store.py
def delete_stack_component(self, component_id: UUID) -> None:
"""Delete a stack component.
Args:
component_id: The ID of the stack component to delete.
"""
self._delete_resource(
resource_id=component_id,
route=STACK_COMPONENTS,
)
delete_tag(self, tag_name_or_id)
Deletes a tag.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
tag_name_or_id |
Union[str, uuid.UUID] |
name or id of the tag to delete. |
required |
Source code in zenml/zen_stores/rest_zen_store.py
def delete_tag(
self,
tag_name_or_id: Union[str, UUID],
) -> None:
"""Deletes a tag.
Args:
tag_name_or_id: name or id of the tag to delete.
"""
self._delete_resource(resource_id=tag_name_or_id, route=TAGS)
delete_trigger(self, trigger_id)
Delete an trigger.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
trigger_id |
UUID |
The ID of the trigger to delete. |
required |
Source code in zenml/zen_stores/rest_zen_store.py
def delete_trigger(self, trigger_id: UUID) -> None:
"""Delete an trigger.
Args:
trigger_id: The ID of the trigger to delete.
"""
self._delete_resource(
resource_id=trigger_id,
route=TRIGGERS,
)
delete_trigger_execution(self, trigger_execution_id)
Delete a trigger execution.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
trigger_execution_id |
UUID |
The ID of the trigger execution to delete. |
required |
Source code in zenml/zen_stores/rest_zen_store.py
def delete_trigger_execution(self, trigger_execution_id: UUID) -> None:
"""Delete a trigger execution.
Args:
trigger_execution_id: The ID of the trigger execution to delete.
"""
self._delete_resource(
resource_id=trigger_execution_id,
route=TRIGGER_EXECUTIONS,
)
delete_user(self, user_name_or_id)
Deletes a user.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
user_name_or_id |
Union[str, uuid.UUID] |
The name or ID of the user to delete. |
required |
Source code in zenml/zen_stores/rest_zen_store.py
def delete_user(self, user_name_or_id: Union[str, UUID]) -> None:
"""Deletes a user.
Args:
user_name_or_id: The name or ID of the user to delete.
"""
self._delete_resource(
resource_id=user_name_or_id,
route=USERS,
)
delete_workspace(self, workspace_name_or_id)
Deletes a workspace.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
workspace_name_or_id |
Union[str, uuid.UUID] |
Name or ID of the workspace to delete. |
required |
Source code in zenml/zen_stores/rest_zen_store.py
def delete_workspace(self, workspace_name_or_id: Union[str, UUID]) -> None:
"""Deletes a workspace.
Args:
workspace_name_or_id: Name or ID of the workspace to delete.
"""
self._delete_resource(
resource_id=workspace_name_or_id,
route=WORKSPACES,
)
get(self, path, params=None, **kwargs)
Make a GET request to the given endpoint path.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
path |
str |
The path to the endpoint. |
required |
params |
Optional[Dict[str, Any]] |
The query parameters to pass to the endpoint. |
None |
kwargs |
Any |
Additional keyword arguments to pass to the request. |
{} |
Returns:
| Type | Description |
|---|---|
Union[Dict[str, Any], List[Any], str, int, float, bool] |
The response body. |
Source code in zenml/zen_stores/rest_zen_store.py
def get(
self, path: str, params: Optional[Dict[str, Any]] = None, **kwargs: Any
) -> Json:
"""Make a GET request to the given endpoint path.
Args:
path: The path to the endpoint.
params: The query parameters to pass to the endpoint.
kwargs: Additional keyword arguments to pass to the request.
Returns:
The response body.
"""
logger.debug(f"Sending GET request to {path}...")
return self._request(
"GET", self.url + API + VERSION_1 + path, params=params, **kwargs
)
get_api_key(self, service_account_id, api_key_name_or_id, hydrate=True)
Get an API key for a service account.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account_id |
UUID |
The ID of the service account for which to fetch the API key. |
required |
api_key_name_or_id |
Union[str, uuid.UUID] |
The name or ID of the API key to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
APIKeyResponse |
The API key with the given ID. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_api_key(
self,
service_account_id: UUID,
api_key_name_or_id: Union[str, UUID],
hydrate: bool = True,
) -> APIKeyResponse:
"""Get an API key for a service account.
Args:
service_account_id: The ID of the service account for which to fetch
the API key.
api_key_name_or_id: The name or ID of the API key to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The API key with the given ID.
"""
return self._get_resource(
resource_id=api_key_name_or_id,
route=f"{SERVICE_ACCOUNTS}/{str(service_account_id)}{API_KEYS}",
response_model=APIKeyResponse,
params={"hydrate": hydrate},
)
get_api_token(self, pipeline_id=None, schedule_id=None, expires_minutes=None)
Get an API token for a workload.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
pipeline_id |
Optional[uuid.UUID] |
The ID of the pipeline to get a token for. |
None |
schedule_id |
Optional[uuid.UUID] |
The ID of the schedule to get a token for. |
None |
expires_minutes |
Optional[int] |
The number of minutes for which the token should be valid. If not provided, the token will be valid indefinitely. |
None |
Returns:
| Type | Description |
|---|---|
str |
The API token. |
Exceptions:
| Type | Description |
|---|---|
ValueError |
if the server response is not valid. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_api_token(
self,
pipeline_id: Optional[UUID] = None,
schedule_id: Optional[UUID] = None,
expires_minutes: Optional[int] = None,
) -> str:
"""Get an API token for a workload.
Args:
pipeline_id: The ID of the pipeline to get a token for.
schedule_id: The ID of the schedule to get a token for.
expires_minutes: The number of minutes for which the token should
be valid. If not provided, the token will be valid indefinitely.
Returns:
The API token.
Raises:
ValueError: if the server response is not valid.
"""
params: Dict[str, Any] = {}
if pipeline_id:
params["pipeline_id"] = pipeline_id
if schedule_id:
params["schedule_id"] = schedule_id
if expires_minutes:
params["expires_minutes"] = expires_minutes
response_body = self.get(API_TOKEN, params=params)
if not isinstance(response_body, str):
raise ValueError(
f"Bad API Response. Expected API token, got "
f"{type(response_body)}"
)
return response_body
get_artifact(self, artifact_id, hydrate=True)
Gets an artifact.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_id |
UUID |
The ID of the artifact to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
ArtifactResponse |
The artifact. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_artifact(
self, artifact_id: UUID, hydrate: bool = True
) -> ArtifactResponse:
"""Gets an artifact.
Args:
artifact_id: The ID of the artifact to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The artifact.
"""
return self._get_resource(
resource_id=artifact_id,
route=ARTIFACTS,
response_model=ArtifactResponse,
params={"hydrate": hydrate},
)
get_artifact_version(self, artifact_version_id, hydrate=True)
Gets an artifact.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_version_id |
UUID |
The ID of the artifact version to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
ArtifactVersionResponse |
The artifact version. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_artifact_version(
self, artifact_version_id: UUID, hydrate: bool = True
) -> ArtifactVersionResponse:
"""Gets an artifact.
Args:
artifact_version_id: The ID of the artifact version to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The artifact version.
"""
return self._get_resource(
resource_id=artifact_version_id,
route=ARTIFACT_VERSIONS,
response_model=ArtifactVersionResponse,
params={"hydrate": hydrate},
)
get_artifact_visualization(self, artifact_visualization_id, hydrate=True)
Gets an artifact visualization.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_visualization_id |
UUID |
The ID of the artifact visualization to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
ArtifactVisualizationResponse |
The artifact visualization. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_artifact_visualization(
self, artifact_visualization_id: UUID, hydrate: bool = True
) -> ArtifactVisualizationResponse:
"""Gets an artifact visualization.
Args:
artifact_visualization_id: The ID of the artifact visualization to
get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The artifact visualization.
"""
return self._get_resource(
resource_id=artifact_visualization_id,
route=ARTIFACT_VISUALIZATIONS,
response_model=ArtifactVisualizationResponse,
params={"hydrate": hydrate},
)
get_authorized_device(self, device_id, hydrate=True)
Gets a specific OAuth 2.0 authorized device.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
device_id |
UUID |
The ID of the device to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
OAuthDeviceResponse |
The requested device, if it was found. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_authorized_device(
self, device_id: UUID, hydrate: bool = True
) -> OAuthDeviceResponse:
"""Gets a specific OAuth 2.0 authorized device.
Args:
device_id: The ID of the device to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested device, if it was found.
"""
return self._get_resource(
resource_id=device_id,
route=DEVICES,
response_model=OAuthDeviceResponse,
params={"hydrate": hydrate},
)
get_build(self, build_id, hydrate=True)
Get a build with a given ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
build_id |
UUID |
ID of the build. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
PipelineBuildResponse |
The build. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_build(
self, build_id: UUID, hydrate: bool = True
) -> PipelineBuildResponse:
"""Get a build with a given ID.
Args:
build_id: ID of the build.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The build.
"""
return self._get_resource(
resource_id=build_id,
route=PIPELINE_BUILDS,
response_model=PipelineBuildResponse,
params={"hydrate": hydrate},
)
get_code_reference(self, code_reference_id, hydrate=True)
Gets a code reference.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
code_reference_id |
UUID |
The ID of the code reference to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
CodeReferenceResponse |
The code reference. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_code_reference(
self, code_reference_id: UUID, hydrate: bool = True
) -> CodeReferenceResponse:
"""Gets a code reference.
Args:
code_reference_id: The ID of the code reference to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The code reference.
"""
return self._get_resource(
resource_id=code_reference_id,
route=CODE_REFERENCES,
response_model=CodeReferenceResponse,
params={"hydrate": hydrate},
)
get_code_repository(self, code_repository_id, hydrate=True)
Gets a specific code repository.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
code_repository_id |
UUID |
The ID of the code repository to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
CodeRepositoryResponse |
The requested code repository, if it was found. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_code_repository(
self, code_repository_id: UUID, hydrate: bool = True
) -> CodeRepositoryResponse:
"""Gets a specific code repository.
Args:
code_repository_id: The ID of the code repository to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested code repository, if it was found.
"""
return self._get_resource(
resource_id=code_repository_id,
route=CODE_REPOSITORIES,
response_model=CodeRepositoryResponse,
params={"hydrate": hydrate},
)
get_deployment(self, deployment_id, hydrate=True)
Get a deployment with a given ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
deployment_id |
UUID |
ID of the deployment. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
PipelineDeploymentResponse |
The deployment. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_deployment(
self, deployment_id: UUID, hydrate: bool = True
) -> PipelineDeploymentResponse:
"""Get a deployment with a given ID.
Args:
deployment_id: ID of the deployment.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The deployment.
"""
return self._get_resource(
resource_id=deployment_id,
route=PIPELINE_DEPLOYMENTS,
response_model=PipelineDeploymentResponse,
params={"hydrate": hydrate},
)
get_deployment_id(self)
Get the ID of the deployment.
Returns:
| Type | Description |
|---|---|
UUID |
The ID of the deployment. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_deployment_id(self) -> UUID:
"""Get the ID of the deployment.
Returns:
The ID of the deployment.
"""
return self.get_store_info().id
get_event_source(self, event_source_id, hydrate=True)
Get an event_source by ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
event_source_id |
UUID |
The ID of the event_source to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
EventSourceResponse |
The event_source. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_event_source(
self,
event_source_id: UUID,
hydrate: bool = True,
) -> EventSourceResponse:
"""Get an event_source by ID.
Args:
event_source_id: The ID of the event_source to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The event_source.
"""
return self._get_resource(
resource_id=event_source_id,
route=EVENT_SOURCES,
response_model=EventSourceResponse,
params={"hydrate": hydrate},
)
get_flavor(self, flavor_id, hydrate=True)
Get a stack component flavor by ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
flavor_id |
UUID |
The ID of the stack component flavor to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
FlavorResponse |
The stack component flavor. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_flavor(
self, flavor_id: UUID, hydrate: bool = True
) -> FlavorResponse:
"""Get a stack component flavor by ID.
Args:
flavor_id: The ID of the stack component flavor to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The stack component flavor.
"""
return self._get_resource(
resource_id=flavor_id,
route=FLAVORS,
response_model=FlavorResponse,
params={"hydrate": hydrate},
)
get_logs(self, logs_id, hydrate=True)
Gets logs with the given ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
logs_id |
UUID |
The ID of the logs to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
LogsResponse |
The logs. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_logs(self, logs_id: UUID, hydrate: bool = True) -> LogsResponse:
"""Gets logs with the given ID.
Args:
logs_id: The ID of the logs to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The logs.
"""
return self._get_resource(
resource_id=logs_id,
route=LOGS,
response_model=LogsResponse,
params={"hydrate": hydrate},
)
get_model(self, model_name_or_id, hydrate=True)
Get an existing model.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_name_or_id |
Union[str, uuid.UUID] |
name or id of the model to be retrieved. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
ModelResponse |
The model of interest. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_model(
self, model_name_or_id: Union[str, UUID], hydrate: bool = True
) -> ModelResponse:
"""Get an existing model.
Args:
model_name_or_id: name or id of the model to be retrieved.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The model of interest.
"""
return self._get_resource(
resource_id=model_name_or_id,
route=MODELS,
response_model=ModelResponse,
params={"hydrate": hydrate},
)
get_model_version(self, model_version_id, hydrate=True)
Get an existing model version.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_id |
UUID |
name, id, stage or number of the model version to be retrieved. If skipped - latest is retrieved. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
ModelVersionResponse |
The model version of interest. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_model_version(
self, model_version_id: UUID, hydrate: bool = True
) -> ModelVersionResponse:
"""Get an existing model version.
Args:
model_version_id: name, id, stage or number of the model version to
be retrieved. If skipped - latest is retrieved.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The model version of interest.
"""
return self._get_resource(
resource_id=model_version_id,
route=MODEL_VERSIONS,
response_model=ModelVersionResponse,
params={"hydrate": hydrate},
)
get_or_create_run(self, pipeline_run)
Gets or creates a pipeline run.
If a run with the same ID or name already exists, it is returned. Otherwise, a new run is created.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
pipeline_run |
PipelineRunRequest |
The pipeline run to get or create. |
required |
Returns:
| Type | Description |
|---|---|
Tuple[zenml.models.v2.core.pipeline_run.PipelineRunResponse, bool] |
The pipeline run, and a boolean indicating whether the run was created or not. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_or_create_run(
self, pipeline_run: PipelineRunRequest
) -> Tuple[PipelineRunResponse, bool]:
"""Gets or creates a pipeline run.
If a run with the same ID or name already exists, it is returned.
Otherwise, a new run is created.
Args:
pipeline_run: The pipeline run to get or create.
Returns:
The pipeline run, and a boolean indicating whether the run was
created or not.
"""
return self._get_or_create_workspace_scoped_resource(
resource=pipeline_run,
route=RUNS,
response_model=PipelineRunResponse,
)
get_pipeline(self, pipeline_id, hydrate=True)
Get a pipeline with a given ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
pipeline_id |
UUID |
ID of the pipeline. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
PipelineResponse |
The pipeline. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_pipeline(
self, pipeline_id: UUID, hydrate: bool = True
) -> PipelineResponse:
"""Get a pipeline with a given ID.
Args:
pipeline_id: ID of the pipeline.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The pipeline.
"""
return self._get_resource(
resource_id=pipeline_id,
route=PIPELINES,
response_model=PipelineResponse,
params={"hydrate": hydrate},
)
get_run(self, run_name_or_id, hydrate=True)
Gets a pipeline run.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
run_name_or_id |
Union[uuid.UUID, str] |
The name or ID of the pipeline run to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
PipelineRunResponse |
The pipeline run. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_run(
self, run_name_or_id: Union[UUID, str], hydrate: bool = True
) -> PipelineRunResponse:
"""Gets a pipeline run.
Args:
run_name_or_id: The name or ID of the pipeline run to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The pipeline run.
"""
return self._get_resource(
resource_id=run_name_or_id,
route=RUNS,
response_model=PipelineRunResponse,
params={"hydrate": hydrate},
)
get_run_metadata(self, run_metadata_id, hydrate=True)
Gets run metadata with the given ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
run_metadata_id |
UUID |
The ID of the run metadata to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
RunMetadataResponse |
The run metadata. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_run_metadata(
self, run_metadata_id: UUID, hydrate: bool = True
) -> RunMetadataResponse:
"""Gets run metadata with the given ID.
Args:
run_metadata_id: The ID of the run metadata to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The run metadata.
"""
return self._get_resource(
resource_id=run_metadata_id,
route=RUN_METADATA,
response_model=RunMetadataResponse,
params={"hydrate": hydrate},
)
get_run_step(self, step_run_id, hydrate=True)
Get a step run by ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
step_run_id |
UUID |
The ID of the step run to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
StepRunResponse |
The step run. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_run_step(
self, step_run_id: UUID, hydrate: bool = True
) -> StepRunResponse:
"""Get a step run by ID.
Args:
step_run_id: The ID of the step run to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The step run.
"""
return self._get_resource(
resource_id=step_run_id,
route=STEPS,
response_model=StepRunResponse,
params={"hydrate": hydrate},
)
get_schedule(self, schedule_id, hydrate=True)
Get a schedule with a given ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
schedule_id |
UUID |
ID of the schedule. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
ScheduleResponse |
The schedule. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_schedule(
self, schedule_id: UUID, hydrate: bool = True
) -> ScheduleResponse:
"""Get a schedule with a given ID.
Args:
schedule_id: ID of the schedule.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The schedule.
"""
return self._get_resource(
resource_id=schedule_id,
route=SCHEDULES,
response_model=ScheduleResponse,
params={"hydrate": hydrate},
)
get_secret(self, secret_id, hydrate=True)
Get a secret by ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
The ID of the secret to fetch. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
SecretResponse |
The secret. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_secret(
self, secret_id: UUID, hydrate: bool = True
) -> SecretResponse:
"""Get a secret by ID.
Args:
secret_id: The ID of the secret to fetch.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The secret.
"""
return self._get_resource(
resource_id=secret_id,
route=SECRETS,
response_model=SecretResponse,
params={"hydrate": hydrate},
)
get_service_account(self, service_account_name_or_id, hydrate=True)
Gets a specific service account.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account_name_or_id |
Union[str, uuid.UUID] |
The name or ID of the service account to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
ServiceAccountResponse |
The requested service account, if it was found. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_service_account(
self,
service_account_name_or_id: Union[str, UUID],
hydrate: bool = True,
) -> ServiceAccountResponse:
"""Gets a specific service account.
Args:
service_account_name_or_id: The name or ID of the service account to
get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested service account, if it was found.
"""
return self._get_resource(
resource_id=service_account_name_or_id,
route=SERVICE_ACCOUNTS,
response_model=ServiceAccountResponse,
params={"hydrate": hydrate},
)
get_service_connector(self, service_connector_id, hydrate=True)
Gets a specific service connector.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_connector_id |
UUID |
The ID of the service connector to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
ServiceConnectorResponse |
The requested service connector, if it was found. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_service_connector(
self, service_connector_id: UUID, hydrate: bool = True
) -> ServiceConnectorResponse:
"""Gets a specific service connector.
Args:
service_connector_id: The ID of the service connector to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested service connector, if it was found.
"""
connector_model = self._get_resource(
resource_id=service_connector_id,
route=SERVICE_CONNECTORS,
response_model=ServiceConnectorResponse,
params={"expand_secrets": False, "hydrate": hydrate},
)
self._populate_connector_type(connector_model)
return connector_model
get_service_connector_client(self, service_connector_id, resource_type=None, resource_id=None)
Get a service connector client for a service connector and given resource.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_connector_id |
UUID |
The ID of the base service connector to use. |
required |
resource_type |
Optional[str] |
The type of resource to get a client for. |
None |
resource_id |
Optional[str] |
The ID of the resource to get a client for. |
None |
Returns:
| Type | Description |
|---|---|
ServiceConnectorResponse |
A service connector client that can be used to access the given resource. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_service_connector_client(
self,
service_connector_id: UUID,
resource_type: Optional[str] = None,
resource_id: Optional[str] = None,
) -> ServiceConnectorResponse:
"""Get a service connector client for a service connector and given resource.
Args:
service_connector_id: The ID of the base service connector to use.
resource_type: The type of resource to get a client for.
resource_id: The ID of the resource to get a client for.
Returns:
A service connector client that can be used to access the given
resource.
"""
params = {}
if resource_type:
params["resource_type"] = resource_type
if resource_id:
params["resource_id"] = resource_id
response_body = self.get(
f"{SERVICE_CONNECTORS}/{str(service_connector_id)}{SERVICE_CONNECTOR_CLIENT}",
params=params,
)
connector = ServiceConnectorResponse.parse_obj(response_body)
self._populate_connector_type(connector)
return connector
get_service_connector_type(self, connector_type)
Returns the requested service connector type.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
connector_type |
str |
the service connector type identifier. |
required |
Returns:
| Type | Description |
|---|---|
ServiceConnectorTypeModel |
The requested service connector type. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_service_connector_type(
self,
connector_type: str,
) -> ServiceConnectorTypeModel:
"""Returns the requested service connector type.
Args:
connector_type: the service connector type identifier.
Returns:
The requested service connector type.
"""
# Use the local registry to get the service connector type, if it
# exists.
local_connector_type: Optional[ServiceConnectorTypeModel] = None
if service_connector_registry.is_registered(connector_type):
local_connector_type = (
service_connector_registry.get_service_connector_type(
connector_type
)
)
try:
response_body = self.get(
f"{SERVICE_CONNECTOR_TYPES}/{connector_type}",
)
remote_connector_type = ServiceConnectorTypeModel.parse_obj(
response_body
)
if local_connector_type:
# If locally available, return the local connector type but
# mark it as being remotely available.
local_connector_type.remote = True
return local_connector_type
# Mark the remote connector type as being only remotely available
remote_connector_type.local = False
remote_connector_type.remote = True
return remote_connector_type
except KeyError:
# If the service connector type is not found, check the local
# registry.
return service_connector_registry.get_service_connector_type(
connector_type
)
get_stack(self, stack_id, hydrate=True)
Get a stack by its unique ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
stack_id |
UUID |
The ID of the stack to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
StackResponse |
The stack with the given ID. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_stack(self, stack_id: UUID, hydrate: bool = True) -> StackResponse:
"""Get a stack by its unique ID.
Args:
stack_id: The ID of the stack to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The stack with the given ID.
"""
return self._get_resource(
resource_id=stack_id,
route=STACKS,
response_model=StackResponse,
params={"hydrate": hydrate},
)
get_stack_component(self, component_id, hydrate=True)
Get a stack component by ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
component_id |
UUID |
The ID of the stack component to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
ComponentResponse |
The stack component. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_stack_component(
self, component_id: UUID, hydrate: bool = True
) -> ComponentResponse:
"""Get a stack component by ID.
Args:
component_id: The ID of the stack component to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The stack component.
"""
return self._get_resource(
resource_id=component_id,
route=STACK_COMPONENTS,
response_model=ComponentResponse,
params={"hydrate": hydrate},
)
get_store_info(self)
Get information about the server.
Returns:
| Type | Description |
|---|---|
ServerModel |
Information about the server. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_store_info(self) -> ServerModel:
"""Get information about the server.
Returns:
Information about the server.
"""
body = self.get(INFO)
return ServerModel.parse_obj(body)
get_tag(self, tag_name_or_id, hydrate=True)
Get an existing tag.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
tag_name_or_id |
Union[str, uuid.UUID] |
name or id of the tag to be retrieved. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
TagResponse |
The tag of interest. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_tag(
self, tag_name_or_id: Union[str, UUID], hydrate: bool = True
) -> TagResponse:
"""Get an existing tag.
Args:
tag_name_or_id: name or id of the tag to be retrieved.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The tag of interest.
"""
return self._get_resource(
resource_id=tag_name_or_id,
route=TAGS,
response_model=TagResponse,
params={"hydrate": hydrate},
)
get_trigger(self, trigger_id, hydrate=True)
Get a trigger by ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
trigger_id |
UUID |
The ID of the trigger to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
TriggerResponse |
The trigger. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_trigger(
self,
trigger_id: UUID,
hydrate: bool = True,
) -> TriggerResponse:
"""Get a trigger by ID.
Args:
trigger_id: The ID of the trigger to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The trigger.
"""
return self._get_resource(
resource_id=trigger_id,
route=TRIGGERS,
response_model=TriggerResponse,
params={"hydrate": hydrate},
)
get_trigger_execution(self, trigger_execution_id, hydrate=True)
Get an trigger execution by ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
trigger_execution_id |
UUID |
The ID of the trigger execution to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
TriggerExecutionResponse |
The trigger execution. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_trigger_execution(
self,
trigger_execution_id: UUID,
hydrate: bool = True,
) -> TriggerExecutionResponse:
"""Get an trigger execution by ID.
Args:
trigger_execution_id: The ID of the trigger execution to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The trigger execution.
"""
return self._get_resource(
resource_id=trigger_execution_id,
route=TRIGGER_EXECUTIONS,
response_model=TriggerExecutionResponse,
params={"hydrate": hydrate},
)
get_user(self, user_name_or_id=None, include_private=False, hydrate=True)
Gets a specific user, when no id is specified get the active user.
The include_private parameter is ignored here as it is handled
implicitly by the /current-user endpoint that is queried when no
user_name_or_id is set. Raises a KeyError in case a user with that id
does not exist.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
user_name_or_id |
Union[str, uuid.UUID] |
The name or ID of the user to get. |
None |
include_private |
bool |
Whether to include private user information. |
False |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
UserResponse |
The requested user, if it was found. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_user(
self,
user_name_or_id: Optional[Union[str, UUID]] = None,
include_private: bool = False,
hydrate: bool = True,
) -> UserResponse:
"""Gets a specific user, when no id is specified get the active user.
The `include_private` parameter is ignored here as it is handled
implicitly by the /current-user endpoint that is queried when no
user_name_or_id is set. Raises a KeyError in case a user with that id
does not exist.
Args:
user_name_or_id: The name or ID of the user to get.
include_private: Whether to include private user information.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested user, if it was found.
"""
if user_name_or_id:
return self._get_resource(
resource_id=user_name_or_id,
route=USERS,
response_model=UserResponse,
params={"hydrate": hydrate},
)
else:
body = self.get(CURRENT_USER, params={"hydrate": hydrate})
return UserResponse.parse_obj(body)
get_workspace(self, workspace_name_or_id, hydrate=True)
Get an existing workspace by name or ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
workspace_name_or_id |
Union[uuid.UUID, str] |
Name or ID of the workspace to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
WorkspaceResponse |
The requested workspace. |
Source code in zenml/zen_stores/rest_zen_store.py
def get_workspace(
self, workspace_name_or_id: Union[UUID, str], hydrate: bool = True
) -> WorkspaceResponse:
"""Get an existing workspace by name or ID.
Args:
workspace_name_or_id: Name or ID of the workspace to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested workspace.
"""
return self._get_resource(
resource_id=workspace_name_or_id,
route=WORKSPACES,
response_model=WorkspaceResponse,
params={"hydrate": hydrate},
)
list_api_keys(self, service_account_id, filter_model, hydrate=False)
List all API keys for a service account matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account_id |
UUID |
The ID of the service account for which to list the API keys. |
required |
filter_model |
APIKeyFilter |
All filter parameters including pagination params |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[APIKeyResponse] |
A list of all API keys matching the filter criteria. |
Source code in zenml/zen_stores/rest_zen_store.py
def list_api_keys(
self,
service_account_id: UUID,
filter_model: APIKeyFilter,
hydrate: bool = False,
) -> Page[APIKeyResponse]:
"""List all API keys for a service account matching the given filter criteria.
Args:
service_account_id: The ID of the service account for which to list
the API keys.
filter_model: All filter parameters including pagination
params
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all API keys matching the filter criteria.
"""
return self._list_paginated_resources(
route=f"{SERVICE_ACCOUNTS}/{str(service_account_id)}{API_KEYS}",
response_model=APIKeyResponse,
filter_model=filter_model,
params={"hydrate": hydrate},
)
list_artifact_versions(self, artifact_version_filter_model, hydrate=False)
List all artifact versions matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_version_filter_model |
ArtifactVersionFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[ArtifactVersionResponse] |
A list of all artifact versions matching the filter criteria. |
Source code in zenml/zen_stores/rest_zen_store.py
def list_artifact_versions(
self,
artifact_version_filter_model: ArtifactVersionFilter,
hydrate: bool = False,
) -> Page[ArtifactVersionResponse]:
"""List all artifact versions matching the given filter criteria.
Args:
artifact_version_filter_model: All filter parameters including
pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all artifact versions matching the filter criteria.
"""
return self._list_paginated_resources(
route=ARTIFACT_VERSIONS,
response_model=ArtifactVersionResponse,
filter_model=artifact_version_filter_model,
params={"hydrate": hydrate},
)
list_artifacts(self, filter_model, hydrate=False)
List all artifacts matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
filter_model |
ArtifactFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[ArtifactResponse] |
A list of all artifacts matching the filter criteria. |
Source code in zenml/zen_stores/rest_zen_store.py
def list_artifacts(
self, filter_model: ArtifactFilter, hydrate: bool = False
) -> Page[ArtifactResponse]:
"""List all artifacts matching the given filter criteria.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all artifacts matching the filter criteria.
"""
return self._list_paginated_resources(
route=ARTIFACTS,
response_model=ArtifactResponse,
filter_model=filter_model,
params={"hydrate": hydrate},
)
list_authorized_devices(self, filter_model, hydrate=False)
List all OAuth 2.0 authorized devices for a user.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
filter_model |
OAuthDeviceFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[OAuthDeviceResponse] |
A page of all matching OAuth 2.0 authorized devices. |
Source code in zenml/zen_stores/rest_zen_store.py
def list_authorized_devices(
self, filter_model: OAuthDeviceFilter, hydrate: bool = False
) -> Page[OAuthDeviceResponse]:
"""List all OAuth 2.0 authorized devices for a user.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all matching OAuth 2.0 authorized devices.
"""
return self._list_paginated_resources(
route=DEVICES,
response_model=OAuthDeviceResponse,
filter_model=filter_model,
params={"hydrate": hydrate},
)
list_builds(self, build_filter_model, hydrate=False)
List all builds matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
build_filter_model |
PipelineBuildFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[PipelineBuildResponse] |
A page of all builds matching the filter criteria. |
Source code in zenml/zen_stores/rest_zen_store.py
def list_builds(
self,
build_filter_model: PipelineBuildFilter,
hydrate: bool = False,
) -> Page[PipelineBuildResponse]:
"""List all builds matching the given filter criteria.
Args:
build_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all builds matching the filter criteria.
"""
return self._list_paginated_resources(
route=PIPELINE_BUILDS,
response_model=PipelineBuildResponse,
filter_model=build_filter_model,
params={"hydrate": hydrate},
)
list_code_repositories(self, filter_model, hydrate=False)
List all code repositories.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
filter_model |
CodeRepositoryFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[CodeRepositoryResponse] |
A page of all code repositories. |
Source code in zenml/zen_stores/rest_zen_store.py
def list_code_repositories(
self,
filter_model: CodeRepositoryFilter,
hydrate: bool = False,
) -> Page[CodeRepositoryResponse]:
"""List all code repositories.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all code repositories.
"""
return self._list_paginated_resources(
route=CODE_REPOSITORIES,
response_model=CodeRepositoryResponse,
filter_model=filter_model,
params={"hydrate": hydrate},
)
list_deployments(self, deployment_filter_model, hydrate=False)
List all deployments matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
deployment_filter_model |
PipelineDeploymentFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[PipelineDeploymentResponse] |
A page of all deployments matching the filter criteria. |
Source code in zenml/zen_stores/rest_zen_store.py
def list_deployments(
self,
deployment_filter_model: PipelineDeploymentFilter,
hydrate: bool = False,
) -> Page[PipelineDeploymentResponse]:
"""List all deployments matching the given filter criteria.
Args:
deployment_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all deployments matching the filter criteria.
"""
return self._list_paginated_resources(
route=PIPELINE_DEPLOYMENTS,
response_model=PipelineDeploymentResponse,
filter_model=deployment_filter_model,
params={"hydrate": hydrate},
)
list_event_sources(self, event_source_filter_model, hydrate=False)
List all event_sources matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
event_source_filter_model |
EventSourceFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[EventSourceResponse] |
A list of all event_sources matching the filter criteria. |
Source code in zenml/zen_stores/rest_zen_store.py
def list_event_sources(
self,
event_source_filter_model: EventSourceFilter,
hydrate: bool = False,
) -> Page[EventSourceResponse]:
"""List all event_sources matching the given filter criteria.
Args:
event_source_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all event_sources matching the filter criteria.
"""
return self._list_paginated_resources(
route=EVENT_SOURCES,
response_model=EventSourceResponse,
filter_model=event_source_filter_model,
params={"hydrate": hydrate},
)
list_flavors(self, flavor_filter_model, hydrate=False)
List all stack component flavors matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
flavor_filter_model |
FlavorFilter |
All filter parameters including pagination params |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[FlavorResponse] |
List of all the stack component flavors matching the given criteria. |
Source code in zenml/zen_stores/rest_zen_store.py
def list_flavors(
self,
flavor_filter_model: FlavorFilter,
hydrate: bool = False,
) -> Page[FlavorResponse]:
"""List all stack component flavors matching the given filter criteria.
Args:
flavor_filter_model: All filter parameters including pagination
params
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
List of all the stack component flavors matching the given criteria.
"""
return self._list_paginated_resources(
route=FLAVORS,
response_model=FlavorResponse,
filter_model=flavor_filter_model,
params={"hydrate": hydrate},
)
list_model_version_artifact_links(self, model_version_artifact_link_filter_model, hydrate=False)
Get all model version to artifact links by filter.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_artifact_link_filter_model |
ModelVersionArtifactFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[ModelVersionArtifactResponse] |
A page of all model version to artifact links. |
Source code in zenml/zen_stores/rest_zen_store.py
def list_model_version_artifact_links(
self,
model_version_artifact_link_filter_model: ModelVersionArtifactFilter,
hydrate: bool = False,
) -> Page[ModelVersionArtifactResponse]:
"""Get all model version to artifact links by filter.
Args:
model_version_artifact_link_filter_model: All filter parameters
including pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all model version to artifact links.
"""
return self._list_paginated_resources(
route=MODEL_VERSION_ARTIFACTS,
response_model=ModelVersionArtifactResponse,
filter_model=model_version_artifact_link_filter_model,
params={"hydrate": hydrate},
)
list_model_version_pipeline_run_links(self, model_version_pipeline_run_link_filter_model, hydrate=False)
Get all model version to pipeline run links by filter.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_pipeline_run_link_filter_model |
ModelVersionPipelineRunFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[ModelVersionPipelineRunResponse] |
A page of all model version to pipeline run links. |
Source code in zenml/zen_stores/rest_zen_store.py
def list_model_version_pipeline_run_links(
self,
model_version_pipeline_run_link_filter_model: ModelVersionPipelineRunFilter,
hydrate: bool = False,
) -> Page[ModelVersionPipelineRunResponse]:
"""Get all model version to pipeline run links by filter.
Args:
model_version_pipeline_run_link_filter_model: All filter parameters
including pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all model version to pipeline run links.
"""
return self._list_paginated_resources(
route=MODEL_VERSION_PIPELINE_RUNS,
response_model=ModelVersionPipelineRunResponse,
filter_model=model_version_pipeline_run_link_filter_model,
params={"hydrate": hydrate},
)
list_model_versions(self, model_version_filter_model, model_name_or_id=None, hydrate=False)
Get all model versions by filter.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_name_or_id |
Union[str, uuid.UUID] |
name or id of the model containing the model versions. |
None |
model_version_filter_model |
ModelVersionFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[ModelVersionResponse] |
A page of all model versions. |
Source code in zenml/zen_stores/rest_zen_store.py
def list_model_versions(
self,
model_version_filter_model: ModelVersionFilter,
model_name_or_id: Optional[Union[str, UUID]] = None,
hydrate: bool = False,
) -> Page[ModelVersionResponse]:
"""Get all model versions by filter.
Args:
model_name_or_id: name or id of the model containing the model
versions.
model_version_filter_model: All filter parameters including
pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all model versions.
"""
if model_name_or_id:
return self._list_paginated_resources(
route=f"{MODELS}/{model_name_or_id}{MODEL_VERSIONS}",
response_model=ModelVersionResponse,
filter_model=model_version_filter_model,
params={"hydrate": hydrate},
)
else:
return self._list_paginated_resources(
route=MODEL_VERSIONS,
response_model=ModelVersionResponse,
filter_model=model_version_filter_model,
params={"hydrate": hydrate},
)
list_models(self, model_filter_model, hydrate=False)
Get all models by filter.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_filter_model |
ModelFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[ModelResponse] |
A page of all models. |
Source code in zenml/zen_stores/rest_zen_store.py
def list_models(
self,
model_filter_model: ModelFilter,
hydrate: bool = False,
) -> Page[ModelResponse]:
"""Get all models by filter.
Args:
model_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all models.
"""
return self._list_paginated_resources(
route=MODELS,
response_model=ModelResponse,
filter_model=model_filter_model,
params={"hydrate": hydrate},
)
list_pipelines(self, pipeline_filter_model, hydrate=False)
List all pipelines matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
pipeline_filter_model |
PipelineFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[PipelineResponse] |
A list of all pipelines matching the filter criteria. |
Source code in zenml/zen_stores/rest_zen_store.py
def list_pipelines(
self,
pipeline_filter_model: PipelineFilter,
hydrate: bool = False,
) -> Page[PipelineResponse]:
"""List all pipelines matching the given filter criteria.
Args:
pipeline_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all pipelines matching the filter criteria.
"""
return self._list_paginated_resources(
route=PIPELINES,
response_model=PipelineResponse,
filter_model=pipeline_filter_model,
params={"hydrate": hydrate},
)
list_run_metadata(self, run_metadata_filter_model, hydrate=False)
List run metadata.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
run_metadata_filter_model |
RunMetadataFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[RunMetadataResponse] |
The run metadata. |
Source code in zenml/zen_stores/rest_zen_store.py
def list_run_metadata(
self,
run_metadata_filter_model: RunMetadataFilter,
hydrate: bool = False,
) -> Page[RunMetadataResponse]:
"""List run metadata.
Args:
run_metadata_filter_model: All filter parameters including
pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The run metadata.
"""
return self._list_paginated_resources(
route=RUN_METADATA,
response_model=RunMetadataResponse,
filter_model=run_metadata_filter_model,
params={"hydrate": hydrate},
)
list_run_steps(self, step_run_filter_model, hydrate=False)
List all step runs matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
step_run_filter_model |
StepRunFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[StepRunResponse] |
A list of all step runs matching the filter criteria. |
Source code in zenml/zen_stores/rest_zen_store.py
def list_run_steps(
self,
step_run_filter_model: StepRunFilter,
hydrate: bool = False,
) -> Page[StepRunResponse]:
"""List all step runs matching the given filter criteria.
Args:
step_run_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all step runs matching the filter criteria.
"""
return self._list_paginated_resources(
route=STEPS,
response_model=StepRunResponse,
filter_model=step_run_filter_model,
params={"hydrate": hydrate},
)
list_runs(self, runs_filter_model, hydrate=False)
List all pipeline runs matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
runs_filter_model |
PipelineRunFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[PipelineRunResponse] |
A list of all pipeline runs matching the filter criteria. |
Source code in zenml/zen_stores/rest_zen_store.py
def list_runs(
self,
runs_filter_model: PipelineRunFilter,
hydrate: bool = False,
) -> Page[PipelineRunResponse]:
"""List all pipeline runs matching the given filter criteria.
Args:
runs_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all pipeline runs matching the filter criteria.
"""
return self._list_paginated_resources(
route=RUNS,
response_model=PipelineRunResponse,
filter_model=runs_filter_model,
params={"hydrate": hydrate},
)
list_schedules(self, schedule_filter_model, hydrate=False)
List all schedules in the workspace.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
schedule_filter_model |
ScheduleFilter |
All filter parameters including pagination params |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[ScheduleResponse] |
A list of schedules. |
Source code in zenml/zen_stores/rest_zen_store.py
def list_schedules(
self,
schedule_filter_model: ScheduleFilter,
hydrate: bool = False,
) -> Page[ScheduleResponse]:
"""List all schedules in the workspace.
Args:
schedule_filter_model: All filter parameters including pagination
params
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of schedules.
"""
return self._list_paginated_resources(
route=SCHEDULES,
response_model=ScheduleResponse,
filter_model=schedule_filter_model,
params={"hydrate": hydrate},
)
list_secrets(self, secret_filter_model, hydrate=False)
List all secrets matching the given filter criteria.
Note that returned secrets do not include any secret values. To fetch
the secret values, use get_secret.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_filter_model |
SecretFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[SecretResponse] |
A list of all secrets matching the filter criteria, with pagination
information and sorted according to the filter criteria. The
returned secrets do not include any secret values, only metadata. To
fetch the secret values, use |
Source code in zenml/zen_stores/rest_zen_store.py
def list_secrets(
self, secret_filter_model: SecretFilter, hydrate: bool = False
) -> Page[SecretResponse]:
"""List all secrets matching the given filter criteria.
Note that returned secrets do not include any secret values. To fetch
the secret values, use `get_secret`.
Args:
secret_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all secrets matching the filter criteria, with pagination
information and sorted according to the filter criteria. The
returned secrets do not include any secret values, only metadata. To
fetch the secret values, use `get_secret` individually with each
secret.
"""
return self._list_paginated_resources(
route=SECRETS,
response_model=SecretResponse,
filter_model=secret_filter_model,
params={"hydrate": hydrate},
)
list_service_accounts(self, filter_model, hydrate=False)
List all service accounts.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
filter_model |
ServiceAccountFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[ServiceAccountResponse] |
A list of filtered service accounts. |
Source code in zenml/zen_stores/rest_zen_store.py
def list_service_accounts(
self, filter_model: ServiceAccountFilter, hydrate: bool = False
) -> Page[ServiceAccountResponse]:
"""List all service accounts.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of filtered service accounts.
"""
return self._list_paginated_resources(
route=SERVICE_ACCOUNTS,
response_model=ServiceAccountResponse,
filter_model=filter_model,
params={"hydrate": hydrate},
)
list_service_connector_resources(self, workspace_name_or_id, connector_type=None, resource_type=None, resource_id=None)
List resources that can be accessed by service connectors.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
workspace_name_or_id |
Union[str, uuid.UUID] |
The name or ID of the workspace to scope to. |
required |
connector_type |
Optional[str] |
The type of service connector to scope to. |
None |
resource_type |
Optional[str] |
The type of resource to scope to. |
None |
resource_id |
Optional[str] |
The ID of the resource to scope to. |
None |
Returns:
| Type | Description |
|---|---|
List[zenml.models.v2.misc.service_connector_type.ServiceConnectorResourcesModel] |
The matching list of resources that available service connectors have access to. |
Source code in zenml/zen_stores/rest_zen_store.py
def list_service_connector_resources(
self,
workspace_name_or_id: Union[str, UUID],
connector_type: Optional[str] = None,
resource_type: Optional[str] = None,
resource_id: Optional[str] = None,
) -> List[ServiceConnectorResourcesModel]:
"""List resources that can be accessed by service connectors.
Args:
workspace_name_or_id: The name or ID of the workspace to scope to.
connector_type: The type of service connector to scope to.
resource_type: The type of resource to scope to.
resource_id: The ID of the resource to scope to.
Returns:
The matching list of resources that available service
connectors have access to.
"""
params = {}
if connector_type:
params["connector_type"] = connector_type
if resource_type:
params["resource_type"] = resource_type
if resource_id:
params["resource_id"] = resource_id
response_body = self.get(
f"{WORKSPACES}/{workspace_name_or_id}{SERVICE_CONNECTORS}{SERVICE_CONNECTOR_RESOURCES}",
params=params,
)
assert isinstance(response_body, list)
resource_list = [
ServiceConnectorResourcesModel.parse_obj(item)
for item in response_body
]
self._populate_connector_type(*resource_list)
# For service connectors with types that are only locally available,
# we need to retrieve the resource list locally
for idx, resources in enumerate(resource_list):
if isinstance(resources.connector_type, str):
# Skip connector types that are neither locally nor remotely
# available
continue
if resources.connector_type.remote:
# Skip connector types that are remotely available
continue
# Retrieve the resource list locally
assert resources.id is not None
connector = self.get_service_connector(resources.id)
connector_instance = (
service_connector_registry.instantiate_connector(
model=connector
)
)
try:
local_resources = connector_instance.verify(
resource_type=resource_type,
resource_id=resource_id,
)
except (ValueError, AuthorizationException) as e:
logger.error(
f'Failed to fetch {resource_type or "available"} '
f"resources from service connector {connector.name}/"
f"{connector.id}: {e}"
)
continue
resource_list[idx] = local_resources
return resource_list
list_service_connector_types(self, connector_type=None, resource_type=None, auth_method=None)
Get a list of service connector types.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
connector_type |
Optional[str] |
Filter by connector type. |
None |
resource_type |
Optional[str] |
Filter by resource type. |
None |
auth_method |
Optional[str] |
Filter by authentication method. |
None |
Returns:
| Type | Description |
|---|---|
List[zenml.models.v2.misc.service_connector_type.ServiceConnectorTypeModel] |
List of service connector types. |
Source code in zenml/zen_stores/rest_zen_store.py
def list_service_connector_types(
self,
connector_type: Optional[str] = None,
resource_type: Optional[str] = None,
auth_method: Optional[str] = None,
) -> List[ServiceConnectorTypeModel]:
"""Get a list of service connector types.
Args:
connector_type: Filter by connector type.
resource_type: Filter by resource type.
auth_method: Filter by authentication method.
Returns:
List of service connector types.
"""
params = {}
if connector_type:
params["connector_type"] = connector_type
if resource_type:
params["resource_type"] = resource_type
if auth_method:
params["auth_method"] = auth_method
response_body = self.get(
SERVICE_CONNECTOR_TYPES,
params=params,
)
assert isinstance(response_body, list)
remote_connector_types = [
ServiceConnectorTypeModel.parse_obj(item) for item in response_body
]
# Mark the remote connector types as being only remotely available
for c in remote_connector_types:
c.local = False
c.remote = True
local_connector_types = (
service_connector_registry.list_service_connector_types(
connector_type=connector_type,
resource_type=resource_type,
auth_method=auth_method,
)
)
# Add the connector types in the local registry to the list of
# connector types available remotely. Overwrite those that have
# the same connector type but mark them as being remotely available.
connector_types_map = {
connector_type.connector_type: connector_type
for connector_type in remote_connector_types
}
for connector in local_connector_types:
if connector.connector_type in connector_types_map:
connector.remote = True
connector_types_map[connector.connector_type] = connector
return list(connector_types_map.values())
list_service_connectors(self, filter_model, hydrate=False)
List all service connectors.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
filter_model |
ServiceConnectorFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[ServiceConnectorResponse] |
A page of all service connectors. |
Source code in zenml/zen_stores/rest_zen_store.py
def list_service_connectors(
self,
filter_model: ServiceConnectorFilter,
hydrate: bool = False,
) -> Page[ServiceConnectorResponse]:
"""List all service connectors.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all service connectors.
"""
connector_models = self._list_paginated_resources(
route=SERVICE_CONNECTORS,
response_model=ServiceConnectorResponse,
filter_model=filter_model,
params={"expand_secrets": False, "hydrate": hydrate},
)
self._populate_connector_type(*connector_models.items)
return connector_models
list_stack_components(self, component_filter_model, hydrate=False)
List all stack components matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
component_filter_model |
ComponentFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[ComponentResponse] |
A list of all stack components matching the filter criteria. |
Source code in zenml/zen_stores/rest_zen_store.py
def list_stack_components(
self,
component_filter_model: ComponentFilter,
hydrate: bool = False,
) -> Page[ComponentResponse]:
"""List all stack components matching the given filter criteria.
Args:
component_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all stack components matching the filter criteria.
"""
return self._list_paginated_resources(
route=STACK_COMPONENTS,
response_model=ComponentResponse,
filter_model=component_filter_model,
params={"hydrate": hydrate},
)
list_stacks(self, stack_filter_model, hydrate=False)
List all stacks matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
stack_filter_model |
StackFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[StackResponse] |
A list of all stacks matching the filter criteria. |
Source code in zenml/zen_stores/rest_zen_store.py
def list_stacks(
self, stack_filter_model: StackFilter, hydrate: bool = False
) -> Page[StackResponse]:
"""List all stacks matching the given filter criteria.
Args:
stack_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all stacks matching the filter criteria.
"""
return self._list_paginated_resources(
route=STACKS,
response_model=StackResponse,
filter_model=stack_filter_model,
params={"hydrate": hydrate},
)
list_tags(self, tag_filter_model, hydrate=False)
Get all tags by filter.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
tag_filter_model |
TagFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[TagResponse] |
A page of all tags. |
Source code in zenml/zen_stores/rest_zen_store.py
def list_tags(
self,
tag_filter_model: TagFilter,
hydrate: bool = False,
) -> Page[TagResponse]:
"""Get all tags by filter.
Args:
tag_filter_model: All filter parameters including pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all tags.
"""
return self._list_paginated_resources(
route=TAGS,
response_model=TagResponse,
filter_model=tag_filter_model,
params={"hydrate": hydrate},
)
list_trigger_executions(self, trigger_execution_filter_model, hydrate=False)
List all trigger executions matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
trigger_execution_filter_model |
TriggerExecutionFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[TriggerExecutionResponse] |
A list of all trigger executions matching the filter criteria. |
Source code in zenml/zen_stores/rest_zen_store.py
def list_trigger_executions(
self,
trigger_execution_filter_model: TriggerExecutionFilter,
hydrate: bool = False,
) -> Page[TriggerExecutionResponse]:
"""List all trigger executions matching the given filter criteria.
Args:
trigger_execution_filter_model: All filter parameters including
pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all trigger executions matching the filter criteria.
"""
return self._list_paginated_resources(
route=TRIGGER_EXECUTIONS,
response_model=TriggerExecutionResponse,
filter_model=trigger_execution_filter_model,
params={"hydrate": hydrate},
)
list_triggers(self, trigger_filter_model, hydrate=False)
List all triggers matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
trigger_filter_model |
TriggerFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[TriggerResponse] |
A list of all triggers matching the filter criteria. |
Source code in zenml/zen_stores/rest_zen_store.py
def list_triggers(
self,
trigger_filter_model: TriggerFilter,
hydrate: bool = False,
) -> Page[TriggerResponse]:
"""List all triggers matching the given filter criteria.
Args:
trigger_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all triggers matching the filter criteria.
"""
return self._list_paginated_resources(
route=TRIGGERS,
response_model=TriggerResponse,
filter_model=trigger_filter_model,
params={"hydrate": hydrate},
)
list_users(self, user_filter_model, hydrate=False)
List all users.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
user_filter_model |
UserFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[UserResponse] |
A list of all users. |
Source code in zenml/zen_stores/rest_zen_store.py
def list_users(
self,
user_filter_model: UserFilter,
hydrate: bool = False,
) -> Page[UserResponse]:
"""List all users.
Args:
user_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all users.
"""
return self._list_paginated_resources(
route=USERS,
response_model=UserResponse,
filter_model=user_filter_model,
params={"hydrate": hydrate},
)
list_workspaces(self, workspace_filter_model, hydrate=False)
List all workspace matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
workspace_filter_model |
WorkspaceFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[WorkspaceResponse] |
A list of all workspace matching the filter criteria. |
Source code in zenml/zen_stores/rest_zen_store.py
def list_workspaces(
self,
workspace_filter_model: WorkspaceFilter,
hydrate: bool = False,
) -> Page[WorkspaceResponse]:
"""List all workspace matching the given filter criteria.
Args:
workspace_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all workspace matching the filter criteria.
"""
return self._list_paginated_resources(
route=WORKSPACES,
response_model=WorkspaceResponse,
filter_model=workspace_filter_model,
params={"hydrate": hydrate},
)
post(self, path, body, params=None, **kwargs)
Make a POST request to the given endpoint path.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
path |
str |
The path to the endpoint. |
required |
body |
BaseModel |
The body to send. |
required |
params |
Optional[Dict[str, Any]] |
The query parameters to pass to the endpoint. |
None |
kwargs |
Any |
Additional keyword arguments to pass to the request. |
{} |
Returns:
| Type | Description |
|---|---|
Union[Dict[str, Any], List[Any], str, int, float, bool] |
The response body. |
Source code in zenml/zen_stores/rest_zen_store.py
def post(
self,
path: str,
body: BaseModel,
params: Optional[Dict[str, Any]] = None,
**kwargs: Any,
) -> Json:
"""Make a POST request to the given endpoint path.
Args:
path: The path to the endpoint.
body: The body to send.
params: The query parameters to pass to the endpoint.
kwargs: Additional keyword arguments to pass to the request.
Returns:
The response body.
"""
logger.debug(f"Sending POST request to {path}...")
return self._request(
"POST",
self.url + API + VERSION_1 + path,
data=body.json(),
params=params,
**kwargs,
)
prune_artifact_versions(self, only_versions=True)
Prunes unused artifact versions and their artifacts.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
only_versions |
bool |
Only delete artifact versions, keeping artifacts |
True |
Source code in zenml/zen_stores/rest_zen_store.py
def prune_artifact_versions(
self,
only_versions: bool = True,
) -> None:
"""Prunes unused artifact versions and their artifacts.
Args:
only_versions: Only delete artifact versions, keeping artifacts
"""
self.delete(
path=ARTIFACT_VERSIONS, params={"only_versions": only_versions}
)
put(self, path, body=None, params=None, **kwargs)
Make a PUT request to the given endpoint path.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
path |
str |
The path to the endpoint. |
required |
body |
Optional[pydantic.main.BaseModel] |
The body to send. |
None |
params |
Optional[Dict[str, Any]] |
The query parameters to pass to the endpoint. |
None |
kwargs |
Any |
Additional keyword arguments to pass to the request. |
{} |
Returns:
| Type | Description |
|---|---|
Union[Dict[str, Any], List[Any], str, int, float, bool] |
The response body. |
Source code in zenml/zen_stores/rest_zen_store.py
def put(
self,
path: str,
body: Optional[BaseModel] = None,
params: Optional[Dict[str, Any]] = None,
**kwargs: Any,
) -> Json:
"""Make a PUT request to the given endpoint path.
Args:
path: The path to the endpoint.
body: The body to send.
params: The query parameters to pass to the endpoint.
kwargs: Additional keyword arguments to pass to the request.
Returns:
The response body.
"""
logger.debug(f"Sending PUT request to {path}...")
data = body.json(exclude_unset=True) if body else None
return self._request(
"PUT",
self.url + API + VERSION_1 + path,
data=data,
params=params,
**kwargs,
)
restore_secrets(self, ignore_errors=False, delete_secrets=False)
Restore all secrets from the configured backup secrets store.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
ignore_errors |
bool |
Whether to ignore individual errors during the restore process and attempt to restore all secrets. |
False |
delete_secrets |
bool |
Whether to delete the secrets that have been successfully restored from the backup secrets store. Setting this flag effectively moves all secrets from the backup secrets store to the primary secrets store. |
False |
Source code in zenml/zen_stores/rest_zen_store.py
def restore_secrets(
self, ignore_errors: bool = False, delete_secrets: bool = False
) -> None:
"""Restore all secrets from the configured backup secrets store.
Args:
ignore_errors: Whether to ignore individual errors during the
restore process and attempt to restore all secrets.
delete_secrets: Whether to delete the secrets that have been
successfully restored from the backup secrets store. Setting
this flag effectively moves all secrets from the backup secrets
store to the primary secrets store.
"""
params: Dict[str, Any] = {
"ignore_errors": ignore_errors,
"delete_secrets": delete_secrets,
}
self.put(
f"{SECRETS_OPERATIONS}{SECRETS_RESTORE}",
params=params,
)
rotate_api_key(self, service_account_id, api_key_name_or_id, rotate_request)
Rotate an API key for a service account.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account_id |
UUID |
The ID of the service account for which to rotate the API key. |
required |
api_key_name_or_id |
Union[str, uuid.UUID] |
The name or ID of the API key to rotate. |
required |
rotate_request |
APIKeyRotateRequest |
The rotate request on the API key. |
required |
Returns:
| Type | Description |
|---|---|
APIKeyResponse |
The updated API key. |
Source code in zenml/zen_stores/rest_zen_store.py
def rotate_api_key(
self,
service_account_id: UUID,
api_key_name_or_id: Union[str, UUID],
rotate_request: APIKeyRotateRequest,
) -> APIKeyResponse:
"""Rotate an API key for a service account.
Args:
service_account_id: The ID of the service account for which to
rotate the API key.
api_key_name_or_id: The name or ID of the API key to rotate.
rotate_request: The rotate request on the API key.
Returns:
The updated API key.
"""
response_body = self.put(
f"{SERVICE_ACCOUNTS}/{str(service_account_id)}{API_KEYS}/{str(api_key_name_or_id)}{API_KEY_ROTATE}",
body=rotate_request,
)
return APIKeyResponse.parse_obj(response_body)
set_api_key(self, api_key)
Set the API key to use for authentication.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
api_key |
str |
The API key to use for authentication. |
required |
Source code in zenml/zen_stores/rest_zen_store.py
def set_api_key(self, api_key: str) -> None:
"""Set the API key to use for authentication.
Args:
api_key: The API key to use for authentication.
"""
self.config.api_key = api_key
self.clear_session()
# TODO: find a way to persist the API key in the configuration file
# without calling _write_config() here.
# This is the only place where we need to explicitly call
# _write_config() to persist the global configuration.
GlobalConfiguration()._write_config()
update_api_key(self, service_account_id, api_key_name_or_id, api_key_update)
Update an API key for a service account.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account_id |
UUID |
The ID of the service account for which to update the API key. |
required |
api_key_name_or_id |
Union[str, uuid.UUID] |
The name or ID of the API key to update. |
required |
api_key_update |
APIKeyUpdate |
The update request on the API key. |
required |
Returns:
| Type | Description |
|---|---|
APIKeyResponse |
The updated API key. |
Source code in zenml/zen_stores/rest_zen_store.py
def update_api_key(
self,
service_account_id: UUID,
api_key_name_or_id: Union[str, UUID],
api_key_update: APIKeyUpdate,
) -> APIKeyResponse:
"""Update an API key for a service account.
Args:
service_account_id: The ID of the service account for which to
update the API key.
api_key_name_or_id: The name or ID of the API key to update.
api_key_update: The update request on the API key.
Returns:
The updated API key.
"""
return self._update_resource(
resource_id=api_key_name_or_id,
resource_update=api_key_update,
route=f"{SERVICE_ACCOUNTS}/{str(service_account_id)}{API_KEYS}",
response_model=APIKeyResponse,
)
update_artifact(self, artifact_id, artifact_update)
Updates an artifact.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_id |
UUID |
The ID of the artifact to update. |
required |
artifact_update |
ArtifactUpdate |
The update to be applied to the artifact. |
required |
Returns:
| Type | Description |
|---|---|
ArtifactResponse |
The updated artifact. |
Source code in zenml/zen_stores/rest_zen_store.py
def update_artifact(
self, artifact_id: UUID, artifact_update: ArtifactUpdate
) -> ArtifactResponse:
"""Updates an artifact.
Args:
artifact_id: The ID of the artifact to update.
artifact_update: The update to be applied to the artifact.
Returns:
The updated artifact.
"""
return self._update_resource(
resource_id=artifact_id,
resource_update=artifact_update,
response_model=ArtifactResponse,
route=ARTIFACTS,
)
update_artifact_version(self, artifact_version_id, artifact_version_update)
Updates an artifact version.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_version_id |
UUID |
The ID of the artifact version to update. |
required |
artifact_version_update |
ArtifactVersionUpdate |
The update to be applied to the artifact version. |
required |
Returns:
| Type | Description |
|---|---|
ArtifactVersionResponse |
The updated artifact version. |
Source code in zenml/zen_stores/rest_zen_store.py
def update_artifact_version(
self,
artifact_version_id: UUID,
artifact_version_update: ArtifactVersionUpdate,
) -> ArtifactVersionResponse:
"""Updates an artifact version.
Args:
artifact_version_id: The ID of the artifact version to update.
artifact_version_update: The update to be applied to the artifact
version.
Returns:
The updated artifact version.
"""
return self._update_resource(
resource_id=artifact_version_id,
resource_update=artifact_version_update,
response_model=ArtifactVersionResponse,
route=ARTIFACT_VERSIONS,
)
update_authorized_device(self, device_id, update)
Updates an existing OAuth 2.0 authorized device for internal use.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
device_id |
UUID |
The ID of the device to update. |
required |
update |
OAuthDeviceUpdate |
The update to be applied to the device. |
required |
Returns:
| Type | Description |
|---|---|
OAuthDeviceResponse |
The updated OAuth 2.0 authorized device. |
Source code in zenml/zen_stores/rest_zen_store.py
def update_authorized_device(
self, device_id: UUID, update: OAuthDeviceUpdate
) -> OAuthDeviceResponse:
"""Updates an existing OAuth 2.0 authorized device for internal use.
Args:
device_id: The ID of the device to update.
update: The update to be applied to the device.
Returns:
The updated OAuth 2.0 authorized device.
"""
return self._update_resource(
resource_id=device_id,
resource_update=update,
response_model=OAuthDeviceResponse,
route=DEVICES,
)
update_code_repository(self, code_repository_id, update)
Updates an existing code repository.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
code_repository_id |
UUID |
The ID of the code repository to update. |
required |
update |
CodeRepositoryUpdate |
The update to be applied to the code repository. |
required |
Returns:
| Type | Description |
|---|---|
CodeRepositoryResponse |
The updated code repository. |
Source code in zenml/zen_stores/rest_zen_store.py
def update_code_repository(
self, code_repository_id: UUID, update: CodeRepositoryUpdate
) -> CodeRepositoryResponse:
"""Updates an existing code repository.
Args:
code_repository_id: The ID of the code repository to update.
update: The update to be applied to the code repository.
Returns:
The updated code repository.
"""
return self._update_resource(
resource_id=code_repository_id,
resource_update=update,
response_model=CodeRepositoryResponse,
route=CODE_REPOSITORIES,
)
update_event_source(self, event_source_id, event_source_update)
Update an existing event_source.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
event_source_id |
UUID |
The ID of the event_source to update. |
required |
event_source_update |
EventSourceUpdate |
The update to be applied to the event_source. |
required |
Returns:
| Type | Description |
|---|---|
EventSourceResponse |
The updated event_source. |
Source code in zenml/zen_stores/rest_zen_store.py
def update_event_source(
self,
event_source_id: UUID,
event_source_update: EventSourceUpdate,
) -> EventSourceResponse:
"""Update an existing event_source.
Args:
event_source_id: The ID of the event_source to update.
event_source_update: The update to be applied to the event_source.
Returns:
The updated event_source.
"""
return self._update_resource(
resource_id=event_source_id,
resource_update=event_source_update,
route=EVENT_SOURCES,
response_model=EventSourceResponse,
)
update_flavor(self, flavor_id, flavor_update)
Updates an existing user.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
flavor_id |
UUID |
The id of the flavor to update. |
required |
flavor_update |
FlavorUpdate |
The update to be applied to the flavor. |
required |
Returns:
| Type | Description |
|---|---|
FlavorResponse |
The updated flavor. |
Source code in zenml/zen_stores/rest_zen_store.py
def update_flavor(
self, flavor_id: UUID, flavor_update: FlavorUpdate
) -> FlavorResponse:
"""Updates an existing user.
Args:
flavor_id: The id of the flavor to update.
flavor_update: The update to be applied to the flavor.
Returns:
The updated flavor.
"""
return self._update_resource(
resource_id=flavor_id,
resource_update=flavor_update,
route=FLAVORS,
response_model=FlavorResponse,
)
update_model(self, model_id, model_update)
Updates an existing model.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_id |
UUID |
UUID of the model to be updated. |
required |
model_update |
ModelUpdate |
the Model to be updated. |
required |
Returns:
| Type | Description |
|---|---|
ModelResponse |
The updated model. |
Source code in zenml/zen_stores/rest_zen_store.py
def update_model(
self,
model_id: UUID,
model_update: ModelUpdate,
) -> ModelResponse:
"""Updates an existing model.
Args:
model_id: UUID of the model to be updated.
model_update: the Model to be updated.
Returns:
The updated model.
"""
return self._update_resource(
resource_id=model_id,
resource_update=model_update,
route=MODELS,
response_model=ModelResponse,
)
update_model_version(self, model_version_id, model_version_update_model)
Get all model versions by filter.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_id |
UUID |
The ID of model version to be updated. |
required |
model_version_update_model |
ModelVersionUpdate |
The model version to be updated. |
required |
Returns:
| Type | Description |
|---|---|
ModelVersionResponse |
An updated model version. |
Source code in zenml/zen_stores/rest_zen_store.py
def update_model_version(
self,
model_version_id: UUID,
model_version_update_model: ModelVersionUpdate,
) -> ModelVersionResponse:
"""Get all model versions by filter.
Args:
model_version_id: The ID of model version to be updated.
model_version_update_model: The model version to be updated.
Returns:
An updated model version.
"""
return self._update_resource(
resource_id=model_version_id,
resource_update=model_version_update_model,
route=MODEL_VERSIONS,
response_model=ModelVersionResponse,
)
update_pipeline(self, pipeline_id, pipeline_update)
Updates a pipeline.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
pipeline_id |
UUID |
The ID of the pipeline to be updated. |
required |
pipeline_update |
PipelineUpdate |
The update to be applied. |
required |
Returns:
| Type | Description |
|---|---|
PipelineResponse |
The updated pipeline. |
Source code in zenml/zen_stores/rest_zen_store.py
def update_pipeline(
self, pipeline_id: UUID, pipeline_update: PipelineUpdate
) -> PipelineResponse:
"""Updates a pipeline.
Args:
pipeline_id: The ID of the pipeline to be updated.
pipeline_update: The update to be applied.
Returns:
The updated pipeline.
"""
return self._update_resource(
resource_id=pipeline_id,
resource_update=pipeline_update,
route=PIPELINES,
response_model=PipelineResponse,
)
update_run(self, run_id, run_update)
Updates a pipeline run.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
run_id |
UUID |
The ID of the pipeline run to update. |
required |
run_update |
PipelineRunUpdate |
The update to be applied to the pipeline run. |
required |
Returns:
| Type | Description |
|---|---|
PipelineRunResponse |
The updated pipeline run. |
Source code in zenml/zen_stores/rest_zen_store.py
def update_run(
self, run_id: UUID, run_update: PipelineRunUpdate
) -> PipelineRunResponse:
"""Updates a pipeline run.
Args:
run_id: The ID of the pipeline run to update.
run_update: The update to be applied to the pipeline run.
Returns:
The updated pipeline run.
"""
return self._update_resource(
resource_id=run_id,
resource_update=run_update,
response_model=PipelineRunResponse,
route=RUNS,
)
update_run_step(self, step_run_id, step_run_update)
Updates a step run.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
step_run_id |
UUID |
The ID of the step to update. |
required |
step_run_update |
StepRunUpdate |
The update to be applied to the step. |
required |
Returns:
| Type | Description |
|---|---|
StepRunResponse |
The updated step run. |
Source code in zenml/zen_stores/rest_zen_store.py
def update_run_step(
self,
step_run_id: UUID,
step_run_update: StepRunUpdate,
) -> StepRunResponse:
"""Updates a step run.
Args:
step_run_id: The ID of the step to update.
step_run_update: The update to be applied to the step.
Returns:
The updated step run.
"""
return self._update_resource(
resource_id=step_run_id,
resource_update=step_run_update,
response_model=StepRunResponse,
route=STEPS,
)
update_schedule(self, schedule_id, schedule_update)
Updates a schedule.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
schedule_id |
UUID |
The ID of the schedule to be updated. |
required |
schedule_update |
ScheduleUpdate |
The update to be applied. |
required |
Returns:
| Type | Description |
|---|---|
ScheduleResponse |
The updated schedule. |
Source code in zenml/zen_stores/rest_zen_store.py
def update_schedule(
self,
schedule_id: UUID,
schedule_update: ScheduleUpdate,
) -> ScheduleResponse:
"""Updates a schedule.
Args:
schedule_id: The ID of the schedule to be updated.
schedule_update: The update to be applied.
Returns:
The updated schedule.
"""
return self._update_resource(
resource_id=schedule_id,
resource_update=schedule_update,
route=SCHEDULES,
response_model=ScheduleResponse,
)
update_secret(self, secret_id, secret_update)
Updates a secret.
Secret values that are specified as None in the update that are
present in the existing secret are removed from the existing secret.
Values that are present in both secrets are overwritten. All other
values in both the existing secret and the update are kept (merged).
If the update includes a change of name or scope, the scoping rules enforced in the secrets store are used to validate the update:
- only one workspace-scoped secret with the given name can exist in the target workspace.
- only one user-scoped secret with the given name can exist in the target workspace for the target user.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
The ID of the secret to be updated. |
required |
secret_update |
SecretUpdate |
The update to be applied. |
required |
Returns:
| Type | Description |
|---|---|
SecretResponse |
The updated secret. |
Source code in zenml/zen_stores/rest_zen_store.py
def update_secret(
self, secret_id: UUID, secret_update: SecretUpdate
) -> SecretResponse:
"""Updates a secret.
Secret values that are specified as `None` in the update that are
present in the existing secret are removed from the existing secret.
Values that are present in both secrets are overwritten. All other
values in both the existing secret and the update are kept (merged).
If the update includes a change of name or scope, the scoping rules
enforced in the secrets store are used to validate the update:
- only one workspace-scoped secret with the given name can exist
in the target workspace.
- only one user-scoped secret with the given name can exist in the
target workspace for the target user.
Args:
secret_id: The ID of the secret to be updated.
secret_update: The update to be applied.
Returns:
The updated secret.
"""
return self._update_resource(
resource_id=secret_id,
resource_update=secret_update,
route=SECRETS,
response_model=SecretResponse,
# The default endpoint behavior is to replace all secret values
# with the values in the update. We want to merge the values
# instead.
params=dict(patch_values=True),
)
update_service_account(self, service_account_name_or_id, service_account_update)
Updates an existing service account.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account_name_or_id |
Union[str, uuid.UUID] |
The name or the ID of the service account to update. |
required |
service_account_update |
ServiceAccountUpdate |
The update to be applied to the service account. |
required |
Returns:
| Type | Description |
|---|---|
ServiceAccountResponse |
The updated service account. |
Source code in zenml/zen_stores/rest_zen_store.py
def update_service_account(
self,
service_account_name_or_id: Union[str, UUID],
service_account_update: ServiceAccountUpdate,
) -> ServiceAccountResponse:
"""Updates an existing service account.
Args:
service_account_name_or_id: The name or the ID of the service
account to update.
service_account_update: The update to be applied to the service
account.
Returns:
The updated service account.
"""
return self._update_resource(
resource_id=service_account_name_or_id,
resource_update=service_account_update,
route=SERVICE_ACCOUNTS,
response_model=ServiceAccountResponse,
)
update_service_connector(self, service_connector_id, update)
Updates an existing service connector.
The update model contains the fields to be updated. If a field value is set to None in the model, the field is not updated, but there are special rules concerning some fields:
- the
configurationandsecretsfields together represent a full valid configuration update, not just a partial update. If either is set (i.e. not None) in the update, their values are merged together and will replace the existing configuration and secrets values. - the
resource_idfield value is also a full replacement value: if set toNone, the resource ID is removed from the service connector. - the
expiration_secondsfield value is also a full replacement value: if set toNone, the expiration is removed from the service connector. - the
secret_idfield value in the update is ignored, given that secrets are managed internally by the ZenML store. - the
labelsfield is also a full labels update: if set (i.e. notNone), all existing labels are removed and replaced by the new labels in the update.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_connector_id |
UUID |
The ID of the service connector to update. |
required |
update |
ServiceConnectorUpdate |
The update to be applied to the service connector. |
required |
Returns:
| Type | Description |
|---|---|
ServiceConnectorResponse |
The updated service connector. |
Source code in zenml/zen_stores/rest_zen_store.py
def update_service_connector(
self, service_connector_id: UUID, update: ServiceConnectorUpdate
) -> ServiceConnectorResponse:
"""Updates an existing service connector.
The update model contains the fields to be updated. If a field value is
set to None in the model, the field is not updated, but there are
special rules concerning some fields:
* the `configuration` and `secrets` fields together represent a full
valid configuration update, not just a partial update. If either is
set (i.e. not None) in the update, their values are merged together and
will replace the existing configuration and secrets values.
* the `resource_id` field value is also a full replacement value: if set
to `None`, the resource ID is removed from the service connector.
* the `expiration_seconds` field value is also a full replacement value:
if set to `None`, the expiration is removed from the service connector.
* the `secret_id` field value in the update is ignored, given that
secrets are managed internally by the ZenML store.
* the `labels` field is also a full labels update: if set (i.e. not
`None`), all existing labels are removed and replaced by the new labels
in the update.
Args:
service_connector_id: The ID of the service connector to update.
update: The update to be applied to the service connector.
Returns:
The updated service connector.
"""
connector_model = self._update_resource(
resource_id=service_connector_id,
resource_update=update,
response_model=ServiceConnectorResponse,
route=SERVICE_CONNECTORS,
)
self._populate_connector_type(connector_model)
return connector_model
update_stack(self, stack_id, stack_update)
Update a stack.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
stack_id |
UUID |
The ID of the stack update. |
required |
stack_update |
StackUpdate |
The update request on the stack. |
required |
Returns:
| Type | Description |
|---|---|
StackResponse |
The updated stack. |
Source code in zenml/zen_stores/rest_zen_store.py
def update_stack(
self, stack_id: UUID, stack_update: StackUpdate
) -> StackResponse:
"""Update a stack.
Args:
stack_id: The ID of the stack update.
stack_update: The update request on the stack.
Returns:
The updated stack.
"""
return self._update_resource(
resource_id=stack_id,
resource_update=stack_update,
route=STACKS,
response_model=StackResponse,
)
update_stack_component(self, component_id, component_update)
Update an existing stack component.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
component_id |
UUID |
The ID of the stack component to update. |
required |
component_update |
ComponentUpdate |
The update to be applied to the stack component. |
required |
Returns:
| Type | Description |
|---|---|
ComponentResponse |
The updated stack component. |
Source code in zenml/zen_stores/rest_zen_store.py
def update_stack_component(
self,
component_id: UUID,
component_update: ComponentUpdate,
) -> ComponentResponse:
"""Update an existing stack component.
Args:
component_id: The ID of the stack component to update.
component_update: The update to be applied to the stack component.
Returns:
The updated stack component.
"""
return self._update_resource(
resource_id=component_id,
resource_update=component_update,
route=STACK_COMPONENTS,
response_model=ComponentResponse,
)
update_tag(self, tag_name_or_id, tag_update_model)
Update tag.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
tag_name_or_id |
Union[str, uuid.UUID] |
name or id of the tag to be updated. |
required |
tag_update_model |
TagUpdate |
Tag to use for the update. |
required |
Returns:
| Type | Description |
|---|---|
TagResponse |
An updated tag. |
Source code in zenml/zen_stores/rest_zen_store.py
def update_tag(
self,
tag_name_or_id: Union[str, UUID],
tag_update_model: TagUpdate,
) -> TagResponse:
"""Update tag.
Args:
tag_name_or_id: name or id of the tag to be updated.
tag_update_model: Tag to use for the update.
Returns:
An updated tag.
"""
tag = self.get_tag(tag_name_or_id)
return self._update_resource(
resource_id=tag.id,
resource_update=tag_update_model,
route=TAGS,
response_model=TagResponse,
)
update_trigger(self, trigger_id, trigger_update)
Update an existing trigger.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
trigger_id |
UUID |
The ID of the trigger to update. |
required |
trigger_update |
TriggerUpdate |
The update to be applied to the trigger. |
required |
Returns:
| Type | Description |
|---|---|
TriggerResponse |
The updated trigger. |
Source code in zenml/zen_stores/rest_zen_store.py
def update_trigger(
self,
trigger_id: UUID,
trigger_update: TriggerUpdate,
) -> TriggerResponse:
"""Update an existing trigger.
Args:
trigger_id: The ID of the trigger to update.
trigger_update: The update to be applied to the trigger.
Returns:
The updated trigger.
"""
return self._update_resource(
resource_id=trigger_id,
resource_update=trigger_update,
route=TRIGGERS,
response_model=TriggerResponse,
)
update_user(self, user_id, user_update)
Updates an existing user.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
user_id |
UUID |
The id of the user to update. |
required |
user_update |
UserUpdate |
The update to be applied to the user. |
required |
Returns:
| Type | Description |
|---|---|
UserResponse |
The updated user. |
Source code in zenml/zen_stores/rest_zen_store.py
def update_user(
self, user_id: UUID, user_update: UserUpdate
) -> UserResponse:
"""Updates an existing user.
Args:
user_id: The id of the user to update.
user_update: The update to be applied to the user.
Returns:
The updated user.
"""
return self._update_resource(
resource_id=user_id,
resource_update=user_update,
route=USERS,
response_model=UserResponse,
)
update_workspace(self, workspace_id, workspace_update)
Update an existing workspace.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
workspace_id |
UUID |
The ID of the workspace to be updated. |
required |
workspace_update |
WorkspaceUpdate |
The update to be applied to the workspace. |
required |
Returns:
| Type | Description |
|---|---|
WorkspaceResponse |
The updated workspace. |
Source code in zenml/zen_stores/rest_zen_store.py
def update_workspace(
self, workspace_id: UUID, workspace_update: WorkspaceUpdate
) -> WorkspaceResponse:
"""Update an existing workspace.
Args:
workspace_id: The ID of the workspace to be updated.
workspace_update: The update to be applied to the workspace.
Returns:
The updated workspace.
"""
return self._update_resource(
resource_id=workspace_id,
resource_update=workspace_update,
route=WORKSPACES,
response_model=WorkspaceResponse,
)
verify_service_connector(self, service_connector_id, resource_type=None, resource_id=None, list_resources=True)
Verifies if a service connector instance has access to one or more resources.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_connector_id |
UUID |
The ID of the service connector to verify. |
required |
resource_type |
Optional[str] |
The type of resource to verify access to. |
None |
resource_id |
Optional[str] |
The ID of the resource to verify access to. |
None |
list_resources |
bool |
If True, the list of all resources accessible through the service connector and matching the supplied resource type and ID are returned. |
True |
Returns:
| Type | Description |
|---|---|
ServiceConnectorResourcesModel |
The list of resources that the service connector has access to, scoped to the supplied resource type and ID, if provided. |
Source code in zenml/zen_stores/rest_zen_store.py
def verify_service_connector(
self,
service_connector_id: UUID,
resource_type: Optional[str] = None,
resource_id: Optional[str] = None,
list_resources: bool = True,
) -> ServiceConnectorResourcesModel:
"""Verifies if a service connector instance has access to one or more resources.
Args:
service_connector_id: The ID of the service connector to verify.
resource_type: The type of resource to verify access to.
resource_id: The ID of the resource to verify access to.
list_resources: If True, the list of all resources accessible
through the service connector and matching the supplied resource
type and ID are returned.
Returns:
The list of resources that the service connector has access to,
scoped to the supplied resource type and ID, if provided.
"""
params: Dict[str, Any] = {"list_resources": list_resources}
if resource_type:
params["resource_type"] = resource_type
if resource_id:
params["resource_id"] = resource_id
response_body = self.put(
f"{SERVICE_CONNECTORS}/{str(service_connector_id)}{SERVICE_CONNECTOR_VERIFY}",
params=params,
)
resources = ServiceConnectorResourcesModel.parse_obj(response_body)
self._populate_connector_type(resources)
return resources
verify_service_connector_config(self, service_connector, list_resources=True)
Verifies if a service connector configuration has access to resources.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_connector |
ServiceConnectorRequest |
The service connector configuration to verify. |
required |
list_resources |
bool |
If True, the list of all resources accessible through the service connector and matching the supplied resource type and ID are returned. |
True |
Returns:
| Type | Description |
|---|---|
ServiceConnectorResourcesModel |
The list of resources that the service connector configuration has access to. |
Source code in zenml/zen_stores/rest_zen_store.py
def verify_service_connector_config(
self,
service_connector: ServiceConnectorRequest,
list_resources: bool = True,
) -> ServiceConnectorResourcesModel:
"""Verifies if a service connector configuration has access to resources.
Args:
service_connector: The service connector configuration to verify.
list_resources: If True, the list of all resources accessible
through the service connector and matching the supplied resource
type and ID are returned.
Returns:
The list of resources that the service connector configuration has
access to.
"""
response_body = self.post(
f"{SERVICE_CONNECTORS}{SERVICE_CONNECTOR_VERIFY}",
body=service_connector,
params={"list_resources": list_resources},
)
resources = ServiceConnectorResourcesModel.parse_obj(response_body)
self._populate_connector_type(resources)
return resources
RestZenStoreConfiguration (StoreConfiguration)
pydantic-model
REST ZenML store configuration.
Attributes:
| Name | Type | Description |
|---|---|---|
type |
StoreType |
The type of the store. |
username |
Optional[str] |
The username to use to connect to the Zen server. |
password |
Optional[str] |
The password to use to connect to the Zen server. |
api_key |
Optional[str] |
The service account API key to use to connect to the Zen server. |
api_token |
Optional[str] |
The API token to use to connect to the Zen server. Generated by the client and stored in the configuration file on the first login and every time the API key is refreshed. |
verify_ssl |
Union[bool, str] |
Either a boolean, in which case it controls whether we verify the server's TLS certificate, or a string, in which case it must be a path to a CA bundle to use or the CA bundle value itself. |
http_timeout |
int |
The timeout to use for all requests. |
Source code in zenml/zen_stores/rest_zen_store.py
class RestZenStoreConfiguration(StoreConfiguration):
"""REST ZenML store configuration.
Attributes:
type: The type of the store.
username: The username to use to connect to the Zen server.
password: The password to use to connect to the Zen server.
api_key: The service account API key to use to connect to the Zen
server.
api_token: The API token to use to connect to the Zen server. Generated
by the client and stored in the configuration file on the first
login and every time the API key is refreshed.
verify_ssl: Either a boolean, in which case it controls whether we
verify the server's TLS certificate, or a string, in which case it
must be a path to a CA bundle to use or the CA bundle value itself.
http_timeout: The timeout to use for all requests.
"""
type: StoreType = StoreType.REST
username: Optional[str] = None
password: Optional[str] = None
api_key: Optional[str] = None
api_token: Optional[str] = None
verify_ssl: Union[bool, str] = True
http_timeout: int = DEFAULT_HTTP_TIMEOUT
@root_validator
def validate_credentials(cls, values: Dict[str, Any]) -> Dict[str, Any]:
"""Validates the credentials provided in the values dictionary.
Args:
values: A dictionary containing the values to be validated.
Raises:
ValueError: If neither api_token nor username nor api_key is set.
Returns:
The values dictionary.
"""
# Check if the values dictionary contains either an API token, an API
# key or a username as non-empty strings.
if (
values.get("api_token")
or values.get("username")
or values.get("api_key")
):
return values
raise ValueError(
"Neither api_token nor username nor api_key is set in the "
"store config."
)
@validator("url")
def validate_url(cls, url: str) -> str:
"""Validates that the URL is a well-formed REST store URL.
Args:
url: The URL to be validated.
Returns:
The validated URL without trailing slashes.
Raises:
ValueError: If the URL is not a well-formed REST store URL.
"""
url = url.rstrip("/")
scheme = re.search("^([a-z0-9]+://)", url)
if scheme is None or scheme.group() not in ("https://", "http://"):
raise ValueError(
"Invalid URL for REST store: {url}. Should be in the form "
"https://hostname[:port] or http://hostname[:port]."
)
# When running inside a container, if the URL uses localhost, the
# target service will not be available. We try to replace localhost
# with one of the special Docker or K3D internal hostnames.
url = replace_localhost_with_internal_hostname(url)
return url
@validator("verify_ssl")
def validate_verify_ssl(
cls, verify_ssl: Union[bool, str]
) -> Union[bool, str]:
"""Validates that the verify_ssl either points to a file or is a bool.
Args:
verify_ssl: The verify_ssl value to be validated.
Returns:
The validated verify_ssl value.
"""
secret_folder = Path(
GlobalConfiguration().local_stores_path,
"certificates",
)
if isinstance(verify_ssl, bool) or verify_ssl.startswith(
str(secret_folder)
):
return verify_ssl
if os.path.isfile(verify_ssl):
with open(verify_ssl, "r") as f:
verify_ssl = f.read()
fileio.makedirs(str(secret_folder))
file_path = Path(secret_folder, "ca_bundle.pem")
with open(file_path, "w") as f:
f.write(verify_ssl)
file_path.chmod(0o600)
verify_ssl = str(file_path)
return verify_ssl
@classmethod
def supports_url_scheme(cls, url: str) -> bool:
"""Check if a URL scheme is supported by this store.
Args:
url: The URL to check.
Returns:
True if the URL scheme is supported, False otherwise.
"""
return urlparse(url).scheme in ("http", "https")
def expand_certificates(self) -> None:
"""Expands the certificates in the verify_ssl field."""
# Load the certificate values back into the configuration
if isinstance(self.verify_ssl, str) and os.path.isfile(
self.verify_ssl
):
with open(self.verify_ssl, "r") as f:
self.verify_ssl = f.read()
class Config:
"""Pydantic configuration class."""
# Don't validate attributes when assigning them. This is necessary
# because the `verify_ssl` attribute can be expanded to the contents
# of the certificate file.
validate_assignment = False
# Forbid extra attributes set in the class.
extra = "forbid"
Config
Pydantic configuration class.
Source code in zenml/zen_stores/rest_zen_store.py
class Config:
"""Pydantic configuration class."""
# Don't validate attributes when assigning them. This is necessary
# because the `verify_ssl` attribute can be expanded to the contents
# of the certificate file.
validate_assignment = False
# Forbid extra attributes set in the class.
extra = "forbid"
expand_certificates(self)
Expands the certificates in the verify_ssl field.
Source code in zenml/zen_stores/rest_zen_store.py
def expand_certificates(self) -> None:
"""Expands the certificates in the verify_ssl field."""
# Load the certificate values back into the configuration
if isinstance(self.verify_ssl, str) and os.path.isfile(
self.verify_ssl
):
with open(self.verify_ssl, "r") as f:
self.verify_ssl = f.read()
supports_url_scheme(url)
classmethod
Check if a URL scheme is supported by this store.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
url |
str |
The URL to check. |
required |
Returns:
| Type | Description |
|---|---|
bool |
True if the URL scheme is supported, False otherwise. |
Source code in zenml/zen_stores/rest_zen_store.py
@classmethod
def supports_url_scheme(cls, url: str) -> bool:
"""Check if a URL scheme is supported by this store.
Args:
url: The URL to check.
Returns:
True if the URL scheme is supported, False otherwise.
"""
return urlparse(url).scheme in ("http", "https")
validate_credentials(values)
classmethod
Validates the credentials provided in the values dictionary.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
values |
Dict[str, Any] |
A dictionary containing the values to be validated. |
required |
Exceptions:
| Type | Description |
|---|---|
ValueError |
If neither api_token nor username nor api_key is set. |
Returns:
| Type | Description |
|---|---|
Dict[str, Any] |
The values dictionary. |
Source code in zenml/zen_stores/rest_zen_store.py
@root_validator
def validate_credentials(cls, values: Dict[str, Any]) -> Dict[str, Any]:
"""Validates the credentials provided in the values dictionary.
Args:
values: A dictionary containing the values to be validated.
Raises:
ValueError: If neither api_token nor username nor api_key is set.
Returns:
The values dictionary.
"""
# Check if the values dictionary contains either an API token, an API
# key or a username as non-empty strings.
if (
values.get("api_token")
or values.get("username")
or values.get("api_key")
):
return values
raise ValueError(
"Neither api_token nor username nor api_key is set in the "
"store config."
)
validate_url(url)
classmethod
Validates that the URL is a well-formed REST store URL.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
url |
str |
The URL to be validated. |
required |
Returns:
| Type | Description |
|---|---|
str |
The validated URL without trailing slashes. |
Exceptions:
| Type | Description |
|---|---|
ValueError |
If the URL is not a well-formed REST store URL. |
Source code in zenml/zen_stores/rest_zen_store.py
@validator("url")
def validate_url(cls, url: str) -> str:
"""Validates that the URL is a well-formed REST store URL.
Args:
url: The URL to be validated.
Returns:
The validated URL without trailing slashes.
Raises:
ValueError: If the URL is not a well-formed REST store URL.
"""
url = url.rstrip("/")
scheme = re.search("^([a-z0-9]+://)", url)
if scheme is None or scheme.group() not in ("https://", "http://"):
raise ValueError(
"Invalid URL for REST store: {url}. Should be in the form "
"https://hostname[:port] or http://hostname[:port]."
)
# When running inside a container, if the URL uses localhost, the
# target service will not be available. We try to replace localhost
# with one of the special Docker or K3D internal hostnames.
url = replace_localhost_with_internal_hostname(url)
return url
validate_verify_ssl(verify_ssl)
classmethod
Validates that the verify_ssl either points to a file or is a bool.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
verify_ssl |
Union[bool, str] |
The verify_ssl value to be validated. |
required |
Returns:
| Type | Description |
|---|---|
Union[bool, str] |
The validated verify_ssl value. |
Source code in zenml/zen_stores/rest_zen_store.py
@validator("verify_ssl")
def validate_verify_ssl(
cls, verify_ssl: Union[bool, str]
) -> Union[bool, str]:
"""Validates that the verify_ssl either points to a file or is a bool.
Args:
verify_ssl: The verify_ssl value to be validated.
Returns:
The validated verify_ssl value.
"""
secret_folder = Path(
GlobalConfiguration().local_stores_path,
"certificates",
)
if isinstance(verify_ssl, bool) or verify_ssl.startswith(
str(secret_folder)
):
return verify_ssl
if os.path.isfile(verify_ssl):
with open(verify_ssl, "r") as f:
verify_ssl = f.read()
fileio.makedirs(str(secret_folder))
file_path = Path(secret_folder, "ca_bundle.pem")
with open(file_path, "w") as f:
f.write(verify_ssl)
file_path.chmod(0o600)
verify_ssl = str(file_path)
return verify_ssl
schemas
special
SQL Model Implementations.
api_key_schemas
SQLModel implementation of user tables.
APIKeySchema (NamedSchema)
pydantic-model
SQL Model for API keys.
Source code in zenml/zen_stores/schemas/api_key_schemas.py
class APIKeySchema(NamedSchema, table=True):
"""SQL Model for API keys."""
__tablename__ = "api_key"
description: str = Field(sa_column=Column(TEXT))
key: str
previous_key: Optional[str] = Field(default=None, nullable=True)
retain_period: int = Field(default=0)
active: bool = Field(default=True)
last_login: Optional[datetime] = None
last_rotated: Optional[datetime] = None
service_account_id: UUID = build_foreign_key_field(
source=__tablename__,
target=UserSchema.__tablename__,
source_column="service_account_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
service_account: "UserSchema" = Relationship(back_populates="api_keys")
@classmethod
def _generate_jwt_secret_key(cls) -> str:
"""Generate a random API key.
Returns:
A random API key.
"""
return token_hex(32)
@classmethod
def _get_hashed_key(cls, key: str) -> str:
"""Hashes the input key and returns the hash value.
Args:
key: The key value to hash.
Returns:
The key hash value.
"""
context = CryptContext(schemes=["bcrypt"], deprecated="auto")
return context.hash(key)
@classmethod
def from_request(
cls,
service_account_id: UUID,
request: APIKeyRequest,
) -> Tuple["APIKeySchema", str]:
"""Convert a `APIKeyRequest` to a `APIKeySchema`.
Args:
service_account_id: The service account id to associate the key
with.
request: The request model to convert.
Returns:
The converted schema and the un-hashed API key.
"""
key = cls._generate_jwt_secret_key()
hashed_key = cls._get_hashed_key(key)
now = datetime.utcnow()
return (
cls(
name=request.name,
description=request.description or "",
key=hashed_key,
service_account_id=service_account_id,
created=now,
updated=now,
),
key,
)
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> APIKeyResponse:
"""Convert a `APIKeySchema` to an `APIKeyResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
**kwargs: Keyword arguments to filter models.
Returns:
The created APIKeyResponse.
"""
metadata = None
if include_metadata:
metadata = APIKeyResponseMetadata(
description=self.description,
retain_period_minutes=self.retain_period,
last_login=self.last_login,
last_rotated=self.last_rotated,
)
body = APIKeyResponseBody(
created=self.created,
updated=self.updated,
active=self.active,
service_account=self.service_account.to_service_account_model(),
)
return APIKeyResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
)
def to_internal_model(
self, hydrate: bool = False
) -> APIKeyInternalResponse:
"""Convert a `APIKeySchema` to an `APIKeyInternalResponse`.
The internal response model includes the hashed key values.
Args:
hydrate: bool to decide whether to return a hydrated version of the
model.
Returns:
The created APIKeyInternalResponse.
"""
model = self.to_model(include_metadata=hydrate)
model.get_body().key = self.key
return APIKeyInternalResponse(
id=self.id,
name=self.name,
previous_key=self.previous_key,
body=model.body,
metadata=model.metadata,
)
def update(self, update: APIKeyUpdate) -> "APIKeySchema":
"""Update an `APIKeySchema` with an `APIKeyUpdate`.
Args:
update: The update model.
Returns:
The updated `APIKeySchema`.
"""
for field, value in update.dict(exclude_none=True).items():
if hasattr(self, field):
setattr(self, field, value)
self.updated = datetime.utcnow()
return self
def internal_update(self, update: APIKeyInternalUpdate) -> "APIKeySchema":
"""Update an `APIKeySchema` with an `APIKeyInternalUpdate`.
The internal update can also update the last used timestamp.
Args:
update: The update model.
Returns:
The updated `APIKeySchema`.
"""
self.update(update)
if update.update_last_login:
self.last_login = self.updated
return self
def rotate(
self,
rotate_request: APIKeyRotateRequest,
) -> Tuple["APIKeySchema", str]:
"""Rotate the key for an `APIKeySchema`.
Args:
rotate_request: The rotate request model.
Returns:
The updated `APIKeySchema` and the new un-hashed key.
"""
self.updated = datetime.utcnow()
self.previous_key = self.key
self.retain_period = rotate_request.retain_period_minutes
new_key = self._generate_jwt_secret_key()
self.key = self._get_hashed_key(new_key)
self.last_rotated = self.updated
return self, new_key
from_request(service_account_id, request)
classmethod
Convert a APIKeyRequest to a APIKeySchema.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account_id |
UUID |
The service account id to associate the key with. |
required |
request |
APIKeyRequest |
The request model to convert. |
required |
Returns:
| Type | Description |
|---|---|
Tuple[APIKeySchema, str] |
The converted schema and the un-hashed API key. |
Source code in zenml/zen_stores/schemas/api_key_schemas.py
@classmethod
def from_request(
cls,
service_account_id: UUID,
request: APIKeyRequest,
) -> Tuple["APIKeySchema", str]:
"""Convert a `APIKeyRequest` to a `APIKeySchema`.
Args:
service_account_id: The service account id to associate the key
with.
request: The request model to convert.
Returns:
The converted schema and the un-hashed API key.
"""
key = cls._generate_jwt_secret_key()
hashed_key = cls._get_hashed_key(key)
now = datetime.utcnow()
return (
cls(
name=request.name,
description=request.description or "",
key=hashed_key,
service_account_id=service_account_id,
created=now,
updated=now,
),
key,
)
internal_update(self, update)
Update an APIKeySchema with an APIKeyInternalUpdate.
The internal update can also update the last used timestamp.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
update |
APIKeyInternalUpdate |
The update model. |
required |
Returns:
| Type | Description |
|---|---|
APIKeySchema |
The updated |
Source code in zenml/zen_stores/schemas/api_key_schemas.py
def internal_update(self, update: APIKeyInternalUpdate) -> "APIKeySchema":
"""Update an `APIKeySchema` with an `APIKeyInternalUpdate`.
The internal update can also update the last used timestamp.
Args:
update: The update model.
Returns:
The updated `APIKeySchema`.
"""
self.update(update)
if update.update_last_login:
self.last_login = self.updated
return self
rotate(self, rotate_request)
Rotate the key for an APIKeySchema.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
rotate_request |
APIKeyRotateRequest |
The rotate request model. |
required |
Returns:
| Type | Description |
|---|---|
Tuple[APIKeySchema, str] |
The updated |
Source code in zenml/zen_stores/schemas/api_key_schemas.py
def rotate(
self,
rotate_request: APIKeyRotateRequest,
) -> Tuple["APIKeySchema", str]:
"""Rotate the key for an `APIKeySchema`.
Args:
rotate_request: The rotate request model.
Returns:
The updated `APIKeySchema` and the new un-hashed key.
"""
self.updated = datetime.utcnow()
self.previous_key = self.key
self.retain_period = rotate_request.retain_period_minutes
new_key = self._generate_jwt_secret_key()
self.key = self._get_hashed_key(new_key)
self.last_rotated = self.updated
return self, new_key
to_internal_model(self, hydrate=False)
Convert a APIKeySchema to an APIKeyInternalResponse.
The internal response model includes the hashed key values.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
hydrate |
bool |
bool to decide whether to return a hydrated version of the model. |
False |
Returns:
| Type | Description |
|---|---|
APIKeyInternalResponse |
The created APIKeyInternalResponse. |
Source code in zenml/zen_stores/schemas/api_key_schemas.py
def to_internal_model(
self, hydrate: bool = False
) -> APIKeyInternalResponse:
"""Convert a `APIKeySchema` to an `APIKeyInternalResponse`.
The internal response model includes the hashed key values.
Args:
hydrate: bool to decide whether to return a hydrated version of the
model.
Returns:
The created APIKeyInternalResponse.
"""
model = self.to_model(include_metadata=hydrate)
model.get_body().key = self.key
return APIKeyInternalResponse(
id=self.id,
name=self.name,
previous_key=self.previous_key,
body=model.body,
metadata=model.metadata,
)
to_model(self, include_metadata=False, include_resources=False, **kwargs)
Convert a APIKeySchema to an APIKeyResponse.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
**kwargs |
Any |
Keyword arguments to filter models. |
{} |
Returns:
| Type | Description |
|---|---|
APIKeyResponse |
The created APIKeyResponse. |
Source code in zenml/zen_stores/schemas/api_key_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> APIKeyResponse:
"""Convert a `APIKeySchema` to an `APIKeyResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
**kwargs: Keyword arguments to filter models.
Returns:
The created APIKeyResponse.
"""
metadata = None
if include_metadata:
metadata = APIKeyResponseMetadata(
description=self.description,
retain_period_minutes=self.retain_period,
last_login=self.last_login,
last_rotated=self.last_rotated,
)
body = APIKeyResponseBody(
created=self.created,
updated=self.updated,
active=self.active,
service_account=self.service_account.to_service_account_model(),
)
return APIKeyResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
)
update(self, update)
Update an APIKeySchema with an APIKeyUpdate.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
update |
APIKeyUpdate |
The update model. |
required |
Returns:
| Type | Description |
|---|---|
APIKeySchema |
The updated |
Source code in zenml/zen_stores/schemas/api_key_schemas.py
def update(self, update: APIKeyUpdate) -> "APIKeySchema":
"""Update an `APIKeySchema` with an `APIKeyUpdate`.
Args:
update: The update model.
Returns:
The updated `APIKeySchema`.
"""
for field, value in update.dict(exclude_none=True).items():
if hasattr(self, field):
setattr(self, field, value)
self.updated = datetime.utcnow()
return self
artifact_schemas
SQLModel implementation of artifact table.
ArtifactSchema (NamedSchema)
pydantic-model
SQL Model for artifacts.
Source code in zenml/zen_stores/schemas/artifact_schemas.py
class ArtifactSchema(NamedSchema, table=True):
"""SQL Model for artifacts."""
__tablename__ = "artifact"
# Fields
has_custom_name: bool
versions: List["ArtifactVersionSchema"] = Relationship(
back_populates="artifact",
sa_relationship_kwargs={"cascade": "delete"},
)
tags: List["TagResourceSchema"] = Relationship(
back_populates="artifact",
sa_relationship_kwargs=dict(
primaryjoin=f"and_(TagResourceSchema.resource_type=='{TaggableResourceTypes.ARTIFACT.value}', foreign(TagResourceSchema.resource_id)==ArtifactSchema.id)",
cascade="delete",
overlaps="tags",
),
)
@classmethod
def from_request(
cls,
artifact_request: ArtifactRequest,
) -> "ArtifactSchema":
"""Convert an `ArtifactRequest` to an `ArtifactSchema`.
Args:
artifact_request: The request model to convert.
Returns:
The converted schema.
"""
return cls(
name=artifact_request.name,
has_custom_name=artifact_request.has_custom_name,
)
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> ArtifactResponse:
"""Convert an `ArtifactSchema` to an `ArtifactResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created `ArtifactResponse`.
"""
latest_id, latest_name = None, None
if self.versions:
latest_version = max(self.versions, key=lambda x: x.created)
latest_id, latest_name = latest_version.id, latest_version.version
# Create the body of the model
body = ArtifactResponseBody(
created=self.created,
updated=self.updated,
tags=[t.tag.to_model() for t in self.tags],
latest_version_name=latest_name,
latest_version_id=latest_id,
)
# Create the metadata of the model
metadata = None
if include_metadata:
metadata = ArtifactResponseMetadata(
has_custom_name=self.has_custom_name,
)
return ArtifactResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
)
def update(self, artifact_update: ArtifactUpdate) -> "ArtifactSchema":
"""Update an `ArtifactSchema` with an `ArtifactUpdate`.
Args:
artifact_update: The update model to apply.
Returns:
The updated `ArtifactSchema`.
"""
self.updated = datetime.utcnow()
if artifact_update.name:
self.name = artifact_update.name
self.has_custom_name = True
if artifact_update.has_custom_name is not None:
self.has_custom_name = artifact_update.has_custom_name
return self
from_request(artifact_request)
classmethod
Convert an ArtifactRequest to an ArtifactSchema.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_request |
ArtifactRequest |
The request model to convert. |
required |
Returns:
| Type | Description |
|---|---|
ArtifactSchema |
The converted schema. |
Source code in zenml/zen_stores/schemas/artifact_schemas.py
@classmethod
def from_request(
cls,
artifact_request: ArtifactRequest,
) -> "ArtifactSchema":
"""Convert an `ArtifactRequest` to an `ArtifactSchema`.
Args:
artifact_request: The request model to convert.
Returns:
The converted schema.
"""
return cls(
name=artifact_request.name,
has_custom_name=artifact_request.has_custom_name,
)
to_model(self, include_metadata=False, include_resources=False, **kwargs)
Convert an ArtifactSchema to an ArtifactResponse.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
Returns:
| Type | Description |
|---|---|
ArtifactResponse |
The created |
Source code in zenml/zen_stores/schemas/artifact_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> ArtifactResponse:
"""Convert an `ArtifactSchema` to an `ArtifactResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created `ArtifactResponse`.
"""
latest_id, latest_name = None, None
if self.versions:
latest_version = max(self.versions, key=lambda x: x.created)
latest_id, latest_name = latest_version.id, latest_version.version
# Create the body of the model
body = ArtifactResponseBody(
created=self.created,
updated=self.updated,
tags=[t.tag.to_model() for t in self.tags],
latest_version_name=latest_name,
latest_version_id=latest_id,
)
# Create the metadata of the model
metadata = None
if include_metadata:
metadata = ArtifactResponseMetadata(
has_custom_name=self.has_custom_name,
)
return ArtifactResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
)
update(self, artifact_update)
Update an ArtifactSchema with an ArtifactUpdate.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_update |
ArtifactUpdate |
The update model to apply. |
required |
Returns:
| Type | Description |
|---|---|
ArtifactSchema |
The updated |
Source code in zenml/zen_stores/schemas/artifact_schemas.py
def update(self, artifact_update: ArtifactUpdate) -> "ArtifactSchema":
"""Update an `ArtifactSchema` with an `ArtifactUpdate`.
Args:
artifact_update: The update model to apply.
Returns:
The updated `ArtifactSchema`.
"""
self.updated = datetime.utcnow()
if artifact_update.name:
self.name = artifact_update.name
self.has_custom_name = True
if artifact_update.has_custom_name is not None:
self.has_custom_name = artifact_update.has_custom_name
return self
ArtifactVersionSchema (BaseSchema)
pydantic-model
SQL Model for artifact versions.
Source code in zenml/zen_stores/schemas/artifact_schemas.py
class ArtifactVersionSchema(BaseSchema, table=True):
"""SQL Model for artifact versions."""
__tablename__ = "artifact_version"
# Fields
version: str
version_number: Optional[int]
type: ArtifactType
uri: str = Field(sa_column=Column(TEXT, nullable=False))
materializer: str = Field(sa_column=Column(TEXT, nullable=False))
data_type: str = Field(sa_column=Column(TEXT, nullable=False))
tags: List["TagResourceSchema"] = Relationship(
back_populates="artifact_version",
sa_relationship_kwargs=dict(
primaryjoin=f"and_(TagResourceSchema.resource_type=='{TaggableResourceTypes.ARTIFACT_VERSION.value}', foreign(TagResourceSchema.resource_id)==ArtifactVersionSchema.id)",
cascade="delete",
overlaps="tags",
),
)
# Foreign keys
artifact_id: UUID = build_foreign_key_field(
source=__tablename__,
target=ArtifactSchema.__tablename__,
source_column="artifact_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
artifact_store_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=StackComponentSchema.__tablename__,
source_column="artifact_store_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
user_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=UserSchema.__tablename__,
source_column="user_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
workspace_id: UUID = build_foreign_key_field(
source=__tablename__,
target=WorkspaceSchema.__tablename__,
source_column="workspace_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
# Relationships
artifact: "ArtifactSchema" = Relationship(back_populates="versions")
user: Optional["UserSchema"] = Relationship(
back_populates="artifact_versions"
)
workspace: "WorkspaceSchema" = Relationship(
back_populates="artifact_versions"
)
run_metadata: List["RunMetadataSchema"] = Relationship(
back_populates="artifact_version",
sa_relationship_kwargs=dict(
primaryjoin=f"and_(RunMetadataSchema.resource_type=='{MetadataResourceTypes.ARTIFACT_VERSION.value}', foreign(RunMetadataSchema.resource_id)==ArtifactVersionSchema.id)",
cascade="delete",
overlaps="run_metadata",
),
)
output_of_step_runs: List["StepRunOutputArtifactSchema"] = Relationship(
back_populates="artifact_version",
sa_relationship_kwargs={"cascade": "delete"},
)
input_of_step_runs: List["StepRunInputArtifactSchema"] = Relationship(
back_populates="artifact_version",
sa_relationship_kwargs={"cascade": "delete"},
)
visualizations: List["ArtifactVisualizationSchema"] = Relationship(
back_populates="artifact_version",
sa_relationship_kwargs={"cascade": "delete"},
)
model_versions_artifacts_links: List["ModelVersionArtifactSchema"] = (
Relationship(
back_populates="artifact_version",
sa_relationship_kwargs={"cascade": "delete"},
)
)
@classmethod
def from_request(
cls,
artifact_version_request: ArtifactVersionRequest,
) -> "ArtifactVersionSchema":
"""Convert an `ArtifactVersionRequest` to an `ArtifactVersionSchema`.
Args:
artifact_version_request: The request model to convert.
Returns:
The converted schema.
"""
try:
version_number = int(artifact_version_request.version)
except ValueError:
version_number = None
return cls(
artifact_id=artifact_version_request.artifact_id,
version=str(artifact_version_request.version),
version_number=version_number,
artifact_store_id=artifact_version_request.artifact_store_id,
workspace_id=artifact_version_request.workspace,
user_id=artifact_version_request.user,
type=artifact_version_request.type,
uri=artifact_version_request.uri,
materializer=artifact_version_request.materializer.json(),
data_type=artifact_version_request.data_type.json(),
)
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> ArtifactVersionResponse:
"""Convert an `ArtifactVersionSchema` to an `ArtifactVersionResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created `ArtifactVersionResponse`.
"""
try:
materializer = Source.parse_raw(self.materializer)
except ValidationError:
# This is an old source which was an importable source path
materializer = Source.from_import_path(self.materializer)
try:
data_type = Source.parse_raw(self.data_type)
except ValidationError:
# This is an old source which was an importable source path
data_type = Source.from_import_path(self.data_type)
producer_step_run_id, producer_pipeline_run_id = None, None
if self.output_of_step_runs:
step_run = self.output_of_step_runs[0].step_run
if step_run.status == ExecutionStatus.COMPLETED:
producer_step_run_id = step_run.id
producer_pipeline_run_id = step_run.pipeline_run_id
else:
producer_step_run_id = step_run.original_step_run_id
# Create the body of the model
body = ArtifactVersionResponseBody(
artifact=self.artifact.to_model(),
version=self.version_number or self.version,
user=self.user.to_model() if self.user else None,
uri=self.uri,
type=self.type,
materializer=materializer,
data_type=data_type,
created=self.created,
updated=self.updated,
tags=[t.tag.to_model() for t in self.tags],
producer_pipeline_run_id=producer_pipeline_run_id,
)
# Create the metadata of the model
metadata = None
if include_metadata:
metadata = ArtifactVersionResponseMetadata(
workspace=self.workspace.to_model(),
artifact_store_id=self.artifact_store_id,
producer_step_run_id=producer_step_run_id,
visualizations=[v.to_model() for v in self.visualizations],
run_metadata={m.key: m.to_model() for m in self.run_metadata},
)
return ArtifactVersionResponse(
id=self.id,
body=body,
metadata=metadata,
)
def update(
self, artifact_version_update: ArtifactVersionUpdate
) -> "ArtifactVersionSchema":
"""Update an `ArtifactVersionSchema` with an `ArtifactVersionUpdate`.
Args:
artifact_version_update: The update model to apply.
Returns:
The updated `ArtifactVersionSchema`.
"""
self.updated = datetime.utcnow()
return self
from_request(artifact_version_request)
classmethod
Convert an ArtifactVersionRequest to an ArtifactVersionSchema.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_version_request |
ArtifactVersionRequest |
The request model to convert. |
required |
Returns:
| Type | Description |
|---|---|
ArtifactVersionSchema |
The converted schema. |
Source code in zenml/zen_stores/schemas/artifact_schemas.py
@classmethod
def from_request(
cls,
artifact_version_request: ArtifactVersionRequest,
) -> "ArtifactVersionSchema":
"""Convert an `ArtifactVersionRequest` to an `ArtifactVersionSchema`.
Args:
artifact_version_request: The request model to convert.
Returns:
The converted schema.
"""
try:
version_number = int(artifact_version_request.version)
except ValueError:
version_number = None
return cls(
artifact_id=artifact_version_request.artifact_id,
version=str(artifact_version_request.version),
version_number=version_number,
artifact_store_id=artifact_version_request.artifact_store_id,
workspace_id=artifact_version_request.workspace,
user_id=artifact_version_request.user,
type=artifact_version_request.type,
uri=artifact_version_request.uri,
materializer=artifact_version_request.materializer.json(),
data_type=artifact_version_request.data_type.json(),
)
to_model(self, include_metadata=False, include_resources=False, **kwargs)
Convert an ArtifactVersionSchema to an ArtifactVersionResponse.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
Returns:
| Type | Description |
|---|---|
ArtifactVersionResponse |
The created |
Source code in zenml/zen_stores/schemas/artifact_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> ArtifactVersionResponse:
"""Convert an `ArtifactVersionSchema` to an `ArtifactVersionResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created `ArtifactVersionResponse`.
"""
try:
materializer = Source.parse_raw(self.materializer)
except ValidationError:
# This is an old source which was an importable source path
materializer = Source.from_import_path(self.materializer)
try:
data_type = Source.parse_raw(self.data_type)
except ValidationError:
# This is an old source which was an importable source path
data_type = Source.from_import_path(self.data_type)
producer_step_run_id, producer_pipeline_run_id = None, None
if self.output_of_step_runs:
step_run = self.output_of_step_runs[0].step_run
if step_run.status == ExecutionStatus.COMPLETED:
producer_step_run_id = step_run.id
producer_pipeline_run_id = step_run.pipeline_run_id
else:
producer_step_run_id = step_run.original_step_run_id
# Create the body of the model
body = ArtifactVersionResponseBody(
artifact=self.artifact.to_model(),
version=self.version_number or self.version,
user=self.user.to_model() if self.user else None,
uri=self.uri,
type=self.type,
materializer=materializer,
data_type=data_type,
created=self.created,
updated=self.updated,
tags=[t.tag.to_model() for t in self.tags],
producer_pipeline_run_id=producer_pipeline_run_id,
)
# Create the metadata of the model
metadata = None
if include_metadata:
metadata = ArtifactVersionResponseMetadata(
workspace=self.workspace.to_model(),
artifact_store_id=self.artifact_store_id,
producer_step_run_id=producer_step_run_id,
visualizations=[v.to_model() for v in self.visualizations],
run_metadata={m.key: m.to_model() for m in self.run_metadata},
)
return ArtifactVersionResponse(
id=self.id,
body=body,
metadata=metadata,
)
update(self, artifact_version_update)
Update an ArtifactVersionSchema with an ArtifactVersionUpdate.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_version_update |
ArtifactVersionUpdate |
The update model to apply. |
required |
Returns:
| Type | Description |
|---|---|
ArtifactVersionSchema |
The updated |
Source code in zenml/zen_stores/schemas/artifact_schemas.py
def update(
self, artifact_version_update: ArtifactVersionUpdate
) -> "ArtifactVersionSchema":
"""Update an `ArtifactVersionSchema` with an `ArtifactVersionUpdate`.
Args:
artifact_version_update: The update model to apply.
Returns:
The updated `ArtifactVersionSchema`.
"""
self.updated = datetime.utcnow()
return self
artifact_visualization_schemas
SQLModel implementation of artifact visualization table.
ArtifactVisualizationSchema (BaseSchema)
pydantic-model
SQL Model for visualizations of artifacts.
Source code in zenml/zen_stores/schemas/artifact_visualization_schemas.py
class ArtifactVisualizationSchema(BaseSchema, table=True):
"""SQL Model for visualizations of artifacts."""
__tablename__ = "artifact_visualization"
# Fields
type: VisualizationType
uri: str = Field(sa_column=Column(TEXT, nullable=False))
# Foreign Keys
artifact_version_id: UUID = build_foreign_key_field(
source=__tablename__,
target=ArtifactVersionSchema.__tablename__,
source_column="artifact_version_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
# Relationships
artifact_version: ArtifactVersionSchema = Relationship(
back_populates="visualizations"
)
@classmethod
def from_model(
cls,
artifact_visualization_request: ArtifactVisualizationRequest,
artifact_version_id: UUID,
) -> "ArtifactVisualizationSchema":
"""Convert a `ArtifactVisualizationRequest` to a `ArtifactVisualizationSchema`.
Args:
artifact_visualization_request: The visualization.
artifact_version_id: The UUID of the artifact version.
Returns:
The `ArtifactVisualizationSchema`.
"""
return cls(
type=artifact_visualization_request.type,
uri=artifact_visualization_request.uri,
artifact_version_id=artifact_version_id,
)
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> ArtifactVisualizationResponse:
"""Convert an `ArtifactVisualizationSchema` to a `Visualization`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The `Visualization`.
"""
body = ArtifactVisualizationResponseBody(
type=self.type,
uri=self.uri,
created=self.created,
updated=self.updated,
)
metadata = None
if include_metadata:
metadata = ArtifactVisualizationResponseMetadata(
artifact_version_id=self.artifact_version_id,
)
return ArtifactVisualizationResponse(
id=self.id,
body=body,
metadata=metadata,
)
from_model(artifact_visualization_request, artifact_version_id)
classmethod
Convert a ArtifactVisualizationRequest to a ArtifactVisualizationSchema.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_visualization_request |
ArtifactVisualizationRequest |
The visualization. |
required |
artifact_version_id |
UUID |
The UUID of the artifact version. |
required |
Returns:
| Type | Description |
|---|---|
ArtifactVisualizationSchema |
The |
Source code in zenml/zen_stores/schemas/artifact_visualization_schemas.py
@classmethod
def from_model(
cls,
artifact_visualization_request: ArtifactVisualizationRequest,
artifact_version_id: UUID,
) -> "ArtifactVisualizationSchema":
"""Convert a `ArtifactVisualizationRequest` to a `ArtifactVisualizationSchema`.
Args:
artifact_visualization_request: The visualization.
artifact_version_id: The UUID of the artifact version.
Returns:
The `ArtifactVisualizationSchema`.
"""
return cls(
type=artifact_visualization_request.type,
uri=artifact_visualization_request.uri,
artifact_version_id=artifact_version_id,
)
to_model(self, include_metadata=False, include_resources=False, **kwargs)
Convert an ArtifactVisualizationSchema to a Visualization.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
Returns:
| Type | Description |
|---|---|
ArtifactVisualizationResponse |
The |
Source code in zenml/zen_stores/schemas/artifact_visualization_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> ArtifactVisualizationResponse:
"""Convert an `ArtifactVisualizationSchema` to a `Visualization`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The `Visualization`.
"""
body = ArtifactVisualizationResponseBody(
type=self.type,
uri=self.uri,
created=self.created,
updated=self.updated,
)
metadata = None
if include_metadata:
metadata = ArtifactVisualizationResponseMetadata(
artifact_version_id=self.artifact_version_id,
)
return ArtifactVisualizationResponse(
id=self.id,
body=body,
metadata=metadata,
)
base_schemas
Base classes for SQLModel schemas.
BaseSchema (SQLModel)
pydantic-model
Base SQL Model for ZenML entities.
Source code in zenml/zen_stores/schemas/base_schemas.py
class BaseSchema(SQLModel):
"""Base SQL Model for ZenML entities."""
id: UUID = Field(default_factory=uuid4, primary_key=True)
created: datetime = Field(default_factory=datetime.utcnow)
updated: datetime = Field(default_factory=datetime.utcnow)
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> Any:
"""In case the Schema has a corresponding Model, this allows conversion to that model.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Raises:
NotImplementedError: When the base class fails to implement this.
"""
raise NotImplementedError(
"No 'to_model()' method implemented for this"
f"schema: '{self.__class__.__name__}'."
)
to_model(self, include_metadata=False, include_resources=False, **kwargs)
In case the Schema has a corresponding Model, this allows conversion to that model.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
Exceptions:
| Type | Description |
|---|---|
NotImplementedError |
When the base class fails to implement this. |
Source code in zenml/zen_stores/schemas/base_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> Any:
"""In case the Schema has a corresponding Model, this allows conversion to that model.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Raises:
NotImplementedError: When the base class fails to implement this.
"""
raise NotImplementedError(
"No 'to_model()' method implemented for this"
f"schema: '{self.__class__.__name__}'."
)
NamedSchema (BaseSchema)
pydantic-model
Base Named SQL Model.
Source code in zenml/zen_stores/schemas/base_schemas.py
class NamedSchema(BaseSchema):
"""Base Named SQL Model."""
name: str
code_repository_schemas
SQL Model Implementations for code repositories.
CodeReferenceSchema (BaseSchema)
pydantic-model
SQL Model for code references.
Source code in zenml/zen_stores/schemas/code_repository_schemas.py
class CodeReferenceSchema(BaseSchema, table=True):
"""SQL Model for code references."""
__tablename__ = "code_reference"
workspace_id: UUID = build_foreign_key_field(
source=__tablename__,
target=WorkspaceSchema.__tablename__,
source_column="workspace_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
workspace: "WorkspaceSchema" = Relationship()
code_repository_id: UUID = build_foreign_key_field(
source=__tablename__,
target=CodeRepositorySchema.__tablename__,
source_column="code_repository_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
code_repository: "CodeRepositorySchema" = Relationship()
commit: str
subdirectory: str
@classmethod
def from_request(
cls, request: "CodeReferenceRequest", workspace_id: UUID
) -> "CodeReferenceSchema":
"""Convert a `CodeReferenceRequest` to a `CodeReferenceSchema`.
Args:
request: The request model to convert.
workspace_id: The workspace ID.
Returns:
The converted schema.
"""
return cls(
workspace_id=workspace_id,
commit=request.commit,
subdirectory=request.subdirectory,
code_repository_id=request.code_repository,
)
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> "CodeReferenceResponse":
"""Convert a `CodeReferenceSchema` to a `CodeReferenceResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
kwargs: Additional keyword arguments.
Returns:
The converted model.
"""
body = CodeReferenceResponseBody(
commit=self.commit,
subdirectory=self.subdirectory,
code_repository=self.code_repository.to_model(),
created=self.created,
updated=self.updated,
)
metadata = None
if include_metadata:
metadata = CodeReferenceResponseMetadata()
return CodeReferenceResponse(
id=self.id,
body=body,
metadata=metadata,
)
from_request(request, workspace_id)
classmethod
Convert a CodeReferenceRequest to a CodeReferenceSchema.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
request |
CodeReferenceRequest |
The request model to convert. |
required |
workspace_id |
UUID |
The workspace ID. |
required |
Returns:
| Type | Description |
|---|---|
CodeReferenceSchema |
The converted schema. |
Source code in zenml/zen_stores/schemas/code_repository_schemas.py
@classmethod
def from_request(
cls, request: "CodeReferenceRequest", workspace_id: UUID
) -> "CodeReferenceSchema":
"""Convert a `CodeReferenceRequest` to a `CodeReferenceSchema`.
Args:
request: The request model to convert.
workspace_id: The workspace ID.
Returns:
The converted schema.
"""
return cls(
workspace_id=workspace_id,
commit=request.commit,
subdirectory=request.subdirectory,
code_repository_id=request.code_repository,
)
to_model(self, include_metadata=False, include_resources=False, **kwargs)
Convert a CodeReferenceSchema to a CodeReferenceResponse.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
kwargs |
Any |
Additional keyword arguments. |
{} |
Returns:
| Type | Description |
|---|---|
CodeReferenceResponse |
The converted model. |
Source code in zenml/zen_stores/schemas/code_repository_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> "CodeReferenceResponse":
"""Convert a `CodeReferenceSchema` to a `CodeReferenceResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
kwargs: Additional keyword arguments.
Returns:
The converted model.
"""
body = CodeReferenceResponseBody(
commit=self.commit,
subdirectory=self.subdirectory,
code_repository=self.code_repository.to_model(),
created=self.created,
updated=self.updated,
)
metadata = None
if include_metadata:
metadata = CodeReferenceResponseMetadata()
return CodeReferenceResponse(
id=self.id,
body=body,
metadata=metadata,
)
CodeRepositorySchema (NamedSchema)
pydantic-model
SQL Model for code repositories.
Source code in zenml/zen_stores/schemas/code_repository_schemas.py
class CodeRepositorySchema(NamedSchema, table=True):
"""SQL Model for code repositories."""
__tablename__ = "code_repository"
workspace_id: UUID = build_foreign_key_field(
source=__tablename__,
target=WorkspaceSchema.__tablename__,
source_column="workspace_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
workspace: "WorkspaceSchema" = Relationship(
back_populates="code_repositories"
)
user_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=UserSchema.__tablename__,
source_column="user_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
user: Optional["UserSchema"] = Relationship(
back_populates="code_repositories"
)
config: str = Field(sa_column=Column(TEXT, nullable=False))
source: str = Field(sa_column=Column(TEXT, nullable=False))
logo_url: Optional[str] = Field()
description: Optional[str] = Field(sa_column=Column(TEXT, nullable=True))
@classmethod
def from_request(
cls, request: "CodeRepositoryRequest"
) -> "CodeRepositorySchema":
"""Convert a `CodeRepositoryRequest` to a `CodeRepositorySchema`.
Args:
request: The request model to convert.
Returns:
The converted schema.
"""
return cls(
name=request.name,
workspace_id=request.workspace,
user_id=request.user,
config=json.dumps(request.config),
source=request.source.json(),
description=request.description,
logo_url=request.logo_url,
)
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> "CodeRepositoryResponse":
"""Convert a `CodeRepositorySchema` to a `CodeRepositoryResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created CodeRepositoryResponse.
"""
body = CodeRepositoryResponseBody(
user=self.user.to_model() if self.user else None,
source=json.loads(self.source),
logo_url=self.logo_url,
created=self.created,
updated=self.updated,
)
metadata = None
if include_metadata:
metadata = CodeRepositoryResponseMetadata(
workspace=self.workspace.to_model(),
config=json.loads(self.config),
description=self.description,
)
return CodeRepositoryResponse(
id=self.id,
name=self.name,
metadata=metadata,
body=body,
)
def update(self, update: "CodeRepositoryUpdate") -> "CodeRepositorySchema":
"""Update a `CodeRepositorySchema` with a `CodeRepositoryUpdate`.
Args:
update: The update model.
Returns:
The updated `CodeRepositorySchema`.
"""
if update.name:
self.name = update.name
if update.description:
self.description = update.description
if update.logo_url:
self.logo_url = update.logo_url
self.updated = datetime.utcnow()
return self
from_request(request)
classmethod
Convert a CodeRepositoryRequest to a CodeRepositorySchema.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
request |
CodeRepositoryRequest |
The request model to convert. |
required |
Returns:
| Type | Description |
|---|---|
CodeRepositorySchema |
The converted schema. |
Source code in zenml/zen_stores/schemas/code_repository_schemas.py
@classmethod
def from_request(
cls, request: "CodeRepositoryRequest"
) -> "CodeRepositorySchema":
"""Convert a `CodeRepositoryRequest` to a `CodeRepositorySchema`.
Args:
request: The request model to convert.
Returns:
The converted schema.
"""
return cls(
name=request.name,
workspace_id=request.workspace,
user_id=request.user,
config=json.dumps(request.config),
source=request.source.json(),
description=request.description,
logo_url=request.logo_url,
)
to_model(self, include_metadata=False, include_resources=False, **kwargs)
Convert a CodeRepositorySchema to a CodeRepositoryResponse.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
Returns:
| Type | Description |
|---|---|
CodeRepositoryResponse |
The created CodeRepositoryResponse. |
Source code in zenml/zen_stores/schemas/code_repository_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> "CodeRepositoryResponse":
"""Convert a `CodeRepositorySchema` to a `CodeRepositoryResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created CodeRepositoryResponse.
"""
body = CodeRepositoryResponseBody(
user=self.user.to_model() if self.user else None,
source=json.loads(self.source),
logo_url=self.logo_url,
created=self.created,
updated=self.updated,
)
metadata = None
if include_metadata:
metadata = CodeRepositoryResponseMetadata(
workspace=self.workspace.to_model(),
config=json.loads(self.config),
description=self.description,
)
return CodeRepositoryResponse(
id=self.id,
name=self.name,
metadata=metadata,
body=body,
)
update(self, update)
Update a CodeRepositorySchema with a CodeRepositoryUpdate.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
update |
CodeRepositoryUpdate |
The update model. |
required |
Returns:
| Type | Description |
|---|---|
CodeRepositorySchema |
The updated |
Source code in zenml/zen_stores/schemas/code_repository_schemas.py
def update(self, update: "CodeRepositoryUpdate") -> "CodeRepositorySchema":
"""Update a `CodeRepositorySchema` with a `CodeRepositoryUpdate`.
Args:
update: The update model.
Returns:
The updated `CodeRepositorySchema`.
"""
if update.name:
self.name = update.name
if update.description:
self.description = update.description
if update.logo_url:
self.logo_url = update.logo_url
self.updated = datetime.utcnow()
return self
component_schemas
SQL Model Implementations for Stack Components.
StackComponentSchema (NamedSchema)
pydantic-model
SQL Model for stack components.
Source code in zenml/zen_stores/schemas/component_schemas.py
class StackComponentSchema(NamedSchema, table=True):
"""SQL Model for stack components."""
__tablename__ = "stack_component"
type: StackComponentType
flavor: str
configuration: bytes
labels: Optional[bytes]
component_spec_path: Optional[str]
workspace_id: UUID = build_foreign_key_field(
source=__tablename__,
target=WorkspaceSchema.__tablename__,
source_column="workspace_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
workspace: "WorkspaceSchema" = Relationship(back_populates="components")
user_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=UserSchema.__tablename__,
source_column="user_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
user: Optional["UserSchema"] = Relationship(back_populates="components")
stacks: List["StackSchema"] = Relationship(
back_populates="components", link_model=StackCompositionSchema
)
schedules: List["ScheduleSchema"] = Relationship(
back_populates="orchestrator",
)
run_metadata: List["RunMetadataSchema"] = Relationship(
back_populates="stack_component",
)
run_or_step_logs: List["LogsSchema"] = Relationship(
back_populates="artifact_store",
sa_relationship_kwargs={"cascade": "delete", "uselist": True},
)
connector_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=ServiceConnectorSchema.__tablename__,
source_column="connector_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
connector: Optional["ServiceConnectorSchema"] = Relationship(
back_populates="components"
)
connector_resource_id: Optional[str]
def update(
self, component_update: "ComponentUpdate"
) -> "StackComponentSchema":
"""Updates a `StackComponentSchema` from a `ComponentUpdate`.
Args:
component_update: The `ComponentUpdate` to update from.
Returns:
The updated `StackComponentSchema`.
"""
for field, value in component_update.dict(
exclude_unset=True, exclude={"workspace", "user", "connector"}
).items():
if field == "configuration":
self.configuration = base64.b64encode(
json.dumps(component_update.configuration).encode("utf-8")
)
elif field == "labels":
self.labels = base64.b64encode(
json.dumps(component_update.labels).encode("utf-8")
)
else:
setattr(self, field, value)
self.updated = datetime.utcnow()
return self
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> "ComponentResponse":
"""Creates a `ComponentModel` from an instance of a `StackComponentSchema`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
A `ComponentModel`
"""
body = ComponentResponseBody(
type=self.type,
flavor=self.flavor,
user=self.user.to_model() if self.user else None,
created=self.created,
updated=self.updated,
)
metadata = None
if include_metadata:
metadata = ComponentResponseMetadata(
workspace=self.workspace.to_model(),
configuration=json.loads(
base64.b64decode(self.configuration).decode()
),
labels=json.loads(base64.b64decode(self.labels).decode())
if self.labels
else None,
component_spec_path=self.component_spec_path,
connector_resource_id=self.connector_resource_id,
connector=self.connector.to_model()
if self.connector
else None,
)
return ComponentResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
)
to_model(self, include_metadata=False, include_resources=False, **kwargs)
Creates a ComponentModel from an instance of a StackComponentSchema.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
Returns:
| Type | Description |
|---|---|
ComponentResponse |
A |
Source code in zenml/zen_stores/schemas/component_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> "ComponentResponse":
"""Creates a `ComponentModel` from an instance of a `StackComponentSchema`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
A `ComponentModel`
"""
body = ComponentResponseBody(
type=self.type,
flavor=self.flavor,
user=self.user.to_model() if self.user else None,
created=self.created,
updated=self.updated,
)
metadata = None
if include_metadata:
metadata = ComponentResponseMetadata(
workspace=self.workspace.to_model(),
configuration=json.loads(
base64.b64decode(self.configuration).decode()
),
labels=json.loads(base64.b64decode(self.labels).decode())
if self.labels
else None,
component_spec_path=self.component_spec_path,
connector_resource_id=self.connector_resource_id,
connector=self.connector.to_model()
if self.connector
else None,
)
return ComponentResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
)
update(self, component_update)
Updates a StackComponentSchema from a ComponentUpdate.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
component_update |
ComponentUpdate |
The |
required |
Returns:
| Type | Description |
|---|---|
StackComponentSchema |
The updated |
Source code in zenml/zen_stores/schemas/component_schemas.py
def update(
self, component_update: "ComponentUpdate"
) -> "StackComponentSchema":
"""Updates a `StackComponentSchema` from a `ComponentUpdate`.
Args:
component_update: The `ComponentUpdate` to update from.
Returns:
The updated `StackComponentSchema`.
"""
for field, value in component_update.dict(
exclude_unset=True, exclude={"workspace", "user", "connector"}
).items():
if field == "configuration":
self.configuration = base64.b64encode(
json.dumps(component_update.configuration).encode("utf-8")
)
elif field == "labels":
self.labels = base64.b64encode(
json.dumps(component_update.labels).encode("utf-8")
)
else:
setattr(self, field, value)
self.updated = datetime.utcnow()
return self
device_schemas
SQLModel implementation for authorized OAuth2 devices.
OAuthDeviceSchema (BaseSchema)
pydantic-model
SQL Model for authorized OAuth2 devices.
Source code in zenml/zen_stores/schemas/device_schemas.py
class OAuthDeviceSchema(BaseSchema, table=True):
"""SQL Model for authorized OAuth2 devices."""
__tablename__ = "auth_devices"
client_id: UUID
user_code: str
device_code: str
status: OAuthDeviceStatus
failed_auth_attempts: int = 0
expires: Optional[datetime] = None
last_login: Optional[datetime] = None
trusted_device: bool = False
os: Optional[str] = None
ip_address: Optional[str] = None
hostname: Optional[str] = None
python_version: Optional[str] = None
zenml_version: Optional[str] = None
city: Optional[str] = None
region: Optional[str] = None
country: Optional[str] = None
user_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=UserSchema.__tablename__,
source_column="user_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
user: Optional["UserSchema"] = Relationship(back_populates="auth_devices")
@classmethod
def _generate_user_code(cls) -> str:
"""Generate a user code for an OAuth2 device.
Returns:
The generated user code.
"""
return token_hex(16)
@classmethod
def _generate_device_code(cls) -> str:
"""Generate a device code.
Returns:
The generated device code.
"""
return token_hex(32)
@classmethod
def _get_hashed_code(cls, code: str) -> str:
"""Hashes the input code and returns the hash value.
Args:
code: The code value to hash.
Returns:
The code hash value.
"""
context = CryptContext(schemes=["bcrypt"], deprecated="auto")
return context.hash(code)
@classmethod
def from_request(
cls, request: OAuthDeviceInternalRequest
) -> Tuple["OAuthDeviceSchema", str, str]:
"""Create an authorized device DB entry from a device authorization request.
Args:
request: The device authorization request.
Returns:
The created `OAuthDeviceSchema`, the user code and the device code.
"""
user_code = cls._generate_user_code()
device_code = cls._generate_device_code()
hashed_user_code = cls._get_hashed_code(user_code)
hashed_device_code = cls._get_hashed_code(device_code)
now = datetime.utcnow()
return (
cls(
client_id=request.client_id,
user_code=hashed_user_code,
device_code=hashed_device_code,
status=OAuthDeviceStatus.PENDING,
failed_auth_attempts=0,
expires=now + timedelta(seconds=request.expires_in),
os=request.os,
ip_address=request.ip_address,
hostname=request.hostname,
python_version=request.python_version,
zenml_version=request.zenml_version,
city=request.city,
region=request.region,
country=request.country,
created=now,
updated=now,
),
user_code,
device_code,
)
def update(self, device_update: OAuthDeviceUpdate) -> "OAuthDeviceSchema":
"""Update an authorized device from a device update model.
Args:
device_update: The device update model.
Returns:
The updated `OAuthDeviceSchema`.
"""
for field, value in device_update.dict(exclude_none=True).items():
if hasattr(self, field):
setattr(self, field, value)
if device_update.locked is True:
self.status = OAuthDeviceStatus.LOCKED
elif device_update.locked is False:
self.status = OAuthDeviceStatus.ACTIVE
self.updated = datetime.utcnow()
return self
def internal_update(
self, device_update: OAuthDeviceInternalUpdate
) -> Tuple["OAuthDeviceSchema", Optional[str], Optional[str]]:
"""Update an authorized device from an internal device update model.
Args:
device_update: The internal device update model.
Returns:
The updated `OAuthDeviceSchema` and the new user code and device
code, if they were generated.
"""
now = datetime.utcnow()
user_code: Optional[str] = None
device_code: Optional[str] = None
# This call also takes care of setting fields that have the same
# name in the internal model and the schema.
self.update(device_update)
if device_update.expires_in is not None:
if device_update.expires_in <= 0:
self.expires = None
else:
self.expires = now + timedelta(
seconds=device_update.expires_in
)
if device_update.update_last_login:
self.last_login = now
if device_update.generate_new_codes:
user_code = self._generate_user_code()
device_code = self._generate_device_code()
self.user_code = self._get_hashed_code(user_code)
self.device_code = self._get_hashed_code(device_code)
self.updated = now
return self, user_code, device_code
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> OAuthDeviceResponse:
"""Convert a device schema to a device response model.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The converted device response model.
"""
metadata = None
if include_metadata:
metadata = OAuthDeviceResponseMetadata(
python_version=self.python_version,
zenml_version=self.zenml_version,
city=self.city,
region=self.region,
country=self.country,
failed_auth_attempts=self.failed_auth_attempts,
last_login=self.last_login,
)
body = OAuthDeviceResponseBody(
user=self.user.to_model() if self.user else None,
created=self.created,
updated=self.updated,
client_id=self.client_id,
expires=self.expires,
trusted_device=self.trusted_device,
status=self.status,
os=self.os,
ip_address=self.ip_address,
hostname=self.hostname,
)
return OAuthDeviceResponse(
id=self.id,
body=body,
metadata=metadata,
)
def to_internal_model(
self, hydrate: bool = False
) -> OAuthDeviceInternalResponse:
"""Convert a device schema to an internal device response model.
Args:
hydrate: bool to decide whether to return a hydrated version of the
model.
Returns:
The converted internal device response model.
"""
device_model = self.to_model(include_metadata=hydrate)
return OAuthDeviceInternalResponse(
id=device_model.id,
body=device_model.body,
metadata=device_model.metadata,
user_code=self.user_code,
device_code=self.device_code,
)
from_request(request)
classmethod
Create an authorized device DB entry from a device authorization request.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
request |
OAuthDeviceInternalRequest |
The device authorization request. |
required |
Returns:
| Type | Description |
|---|---|
Tuple[OAuthDeviceSchema, str, str] |
The created |
Source code in zenml/zen_stores/schemas/device_schemas.py
@classmethod
def from_request(
cls, request: OAuthDeviceInternalRequest
) -> Tuple["OAuthDeviceSchema", str, str]:
"""Create an authorized device DB entry from a device authorization request.
Args:
request: The device authorization request.
Returns:
The created `OAuthDeviceSchema`, the user code and the device code.
"""
user_code = cls._generate_user_code()
device_code = cls._generate_device_code()
hashed_user_code = cls._get_hashed_code(user_code)
hashed_device_code = cls._get_hashed_code(device_code)
now = datetime.utcnow()
return (
cls(
client_id=request.client_id,
user_code=hashed_user_code,
device_code=hashed_device_code,
status=OAuthDeviceStatus.PENDING,
failed_auth_attempts=0,
expires=now + timedelta(seconds=request.expires_in),
os=request.os,
ip_address=request.ip_address,
hostname=request.hostname,
python_version=request.python_version,
zenml_version=request.zenml_version,
city=request.city,
region=request.region,
country=request.country,
created=now,
updated=now,
),
user_code,
device_code,
)
internal_update(self, device_update)
Update an authorized device from an internal device update model.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
device_update |
OAuthDeviceInternalUpdate |
The internal device update model. |
required |
Returns:
| Type | Description |
|---|---|
Tuple[OAuthDeviceSchema, Optional[str], Optional[str]] |
The updated |
Source code in zenml/zen_stores/schemas/device_schemas.py
def internal_update(
self, device_update: OAuthDeviceInternalUpdate
) -> Tuple["OAuthDeviceSchema", Optional[str], Optional[str]]:
"""Update an authorized device from an internal device update model.
Args:
device_update: The internal device update model.
Returns:
The updated `OAuthDeviceSchema` and the new user code and device
code, if they were generated.
"""
now = datetime.utcnow()
user_code: Optional[str] = None
device_code: Optional[str] = None
# This call also takes care of setting fields that have the same
# name in the internal model and the schema.
self.update(device_update)
if device_update.expires_in is not None:
if device_update.expires_in <= 0:
self.expires = None
else:
self.expires = now + timedelta(
seconds=device_update.expires_in
)
if device_update.update_last_login:
self.last_login = now
if device_update.generate_new_codes:
user_code = self._generate_user_code()
device_code = self._generate_device_code()
self.user_code = self._get_hashed_code(user_code)
self.device_code = self._get_hashed_code(device_code)
self.updated = now
return self, user_code, device_code
to_internal_model(self, hydrate=False)
Convert a device schema to an internal device response model.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
hydrate |
bool |
bool to decide whether to return a hydrated version of the model. |
False |
Returns:
| Type | Description |
|---|---|
OAuthDeviceInternalResponse |
The converted internal device response model. |
Source code in zenml/zen_stores/schemas/device_schemas.py
def to_internal_model(
self, hydrate: bool = False
) -> OAuthDeviceInternalResponse:
"""Convert a device schema to an internal device response model.
Args:
hydrate: bool to decide whether to return a hydrated version of the
model.
Returns:
The converted internal device response model.
"""
device_model = self.to_model(include_metadata=hydrate)
return OAuthDeviceInternalResponse(
id=device_model.id,
body=device_model.body,
metadata=device_model.metadata,
user_code=self.user_code,
device_code=self.device_code,
)
to_model(self, include_metadata=False, include_resources=False, **kwargs)
Convert a device schema to a device response model.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
Returns:
| Type | Description |
|---|---|
OAuthDeviceResponse |
The converted device response model. |
Source code in zenml/zen_stores/schemas/device_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> OAuthDeviceResponse:
"""Convert a device schema to a device response model.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The converted device response model.
"""
metadata = None
if include_metadata:
metadata = OAuthDeviceResponseMetadata(
python_version=self.python_version,
zenml_version=self.zenml_version,
city=self.city,
region=self.region,
country=self.country,
failed_auth_attempts=self.failed_auth_attempts,
last_login=self.last_login,
)
body = OAuthDeviceResponseBody(
user=self.user.to_model() if self.user else None,
created=self.created,
updated=self.updated,
client_id=self.client_id,
expires=self.expires,
trusted_device=self.trusted_device,
status=self.status,
os=self.os,
ip_address=self.ip_address,
hostname=self.hostname,
)
return OAuthDeviceResponse(
id=self.id,
body=body,
metadata=metadata,
)
update(self, device_update)
Update an authorized device from a device update model.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
device_update |
OAuthDeviceUpdate |
The device update model. |
required |
Returns:
| Type | Description |
|---|---|
OAuthDeviceSchema |
The updated |
Source code in zenml/zen_stores/schemas/device_schemas.py
def update(self, device_update: OAuthDeviceUpdate) -> "OAuthDeviceSchema":
"""Update an authorized device from a device update model.
Args:
device_update: The device update model.
Returns:
The updated `OAuthDeviceSchema`.
"""
for field, value in device_update.dict(exclude_none=True).items():
if hasattr(self, field):
setattr(self, field, value)
if device_update.locked is True:
self.status = OAuthDeviceStatus.LOCKED
elif device_update.locked is False:
self.status = OAuthDeviceStatus.ACTIVE
self.updated = datetime.utcnow()
return self
event_source_schemas
SQL Model Implementations for event sources.
EventSourceSchema (NamedSchema)
pydantic-model
SQL Model for tag.
Source code in zenml/zen_stores/schemas/event_source_schemas.py
class EventSourceSchema(NamedSchema, table=True):
"""SQL Model for tag."""
__tablename__ = "event_source"
workspace_id: UUID = build_foreign_key_field(
source=__tablename__,
target=WorkspaceSchema.__tablename__,
source_column="workspace_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
workspace: "WorkspaceSchema" = Relationship(back_populates="event_sources")
user_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=UserSchema.__tablename__,
source_column="user_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
user: Optional["UserSchema"] = Relationship(back_populates="event_sources")
triggers: List["TriggerSchema"] = Relationship(
back_populates="event_source"
)
flavor: str = Field(nullable=False)
plugin_subtype: str = Field(nullable=False)
description: str = Field(sa_column=Column(TEXT, nullable=True))
configuration: bytes
is_active: bool = Field(nullable=False)
@classmethod
def from_request(cls, request: EventSourceRequest) -> "EventSourceSchema":
"""Convert an `EventSourceRequest` to an `EventSourceSchema`.
Args:
request: The request model to convert.
Returns:
The converted schema.
"""
return cls(
workspace_id=request.workspace,
user_id=request.user,
flavor=request.flavor,
plugin_subtype=request.plugin_subtype,
name=request.name,
description=request.description,
configuration=base64.b64encode(
json.dumps(
request.configuration,
sort_keys=False,
default=pydantic_encoder,
).encode("utf-8")
),
is_active=True, # Makes no sense to create an inactive event source
)
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> EventSourceResponse:
"""Convert an `EventSourceSchema` to an `EventSourceResponse`.
Args:
include_metadata: Flag deciding whether to include the output model(s)
metadata fields in the response.
include_resources: Flag deciding whether to include the output model(s)
metadata fields in the response.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created `EventSourceResponse`.
"""
from zenml.models import TriggerResponse
body = EventSourceResponseBody(
created=self.created,
updated=self.updated,
user=self.user.to_model() if self.user else None,
flavor=self.flavor,
plugin_subtype=self.plugin_subtype,
is_active=self.is_active,
)
resources = None
if include_resources:
triggers = cast(
Page[TriggerResponse],
get_page_from_list(
items_list=self.triggers,
response_model=TriggerResponse,
include_resources=include_resources,
include_metadata=include_metadata,
),
)
resources = EventSourceResponseResources(
triggers=triggers,
)
metadata = None
if include_metadata:
metadata = EventSourceResponseMetadata(
workspace=self.workspace.to_model(),
description=self.description,
configuration=json.loads(
base64.b64decode(self.configuration).decode()
),
)
return EventSourceResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
resources=resources,
)
def update(self, update: EventSourceUpdate) -> "EventSourceSchema":
"""Updates a `EventSourceSchema` from a `EventSourceUpdate`.
Args:
update: The `EventSourceUpdate` to update from.
Returns:
The updated `EventSourceSchema`.
"""
for field, value in update.dict(
exclude_unset=True, exclude_none=True
).items():
if field == "configuration":
self.configuration = base64.b64encode(
json.dumps(
update.configuration, default=pydantic_encoder
).encode("utf-8")
)
else:
setattr(self, field, value)
self.updated = datetime.utcnow()
return self
from_request(request)
classmethod
Convert an EventSourceRequest to an EventSourceSchema.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
request |
EventSourceRequest |
The request model to convert. |
required |
Returns:
| Type | Description |
|---|---|
EventSourceSchema |
The converted schema. |
Source code in zenml/zen_stores/schemas/event_source_schemas.py
@classmethod
def from_request(cls, request: EventSourceRequest) -> "EventSourceSchema":
"""Convert an `EventSourceRequest` to an `EventSourceSchema`.
Args:
request: The request model to convert.
Returns:
The converted schema.
"""
return cls(
workspace_id=request.workspace,
user_id=request.user,
flavor=request.flavor,
plugin_subtype=request.plugin_subtype,
name=request.name,
description=request.description,
configuration=base64.b64encode(
json.dumps(
request.configuration,
sort_keys=False,
default=pydantic_encoder,
).encode("utf-8")
),
is_active=True, # Makes no sense to create an inactive event source
)
to_model(self, include_metadata=False, include_resources=False, **kwargs)
Convert an EventSourceSchema to an EventSourceResponse.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Flag deciding whether to include the output model(s) metadata fields in the response. |
False |
include_resources |
bool |
Flag deciding whether to include the output model(s) metadata fields in the response. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
Returns:
| Type | Description |
|---|---|
EventSourceResponse |
The created |
Source code in zenml/zen_stores/schemas/event_source_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> EventSourceResponse:
"""Convert an `EventSourceSchema` to an `EventSourceResponse`.
Args:
include_metadata: Flag deciding whether to include the output model(s)
metadata fields in the response.
include_resources: Flag deciding whether to include the output model(s)
metadata fields in the response.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created `EventSourceResponse`.
"""
from zenml.models import TriggerResponse
body = EventSourceResponseBody(
created=self.created,
updated=self.updated,
user=self.user.to_model() if self.user else None,
flavor=self.flavor,
plugin_subtype=self.plugin_subtype,
is_active=self.is_active,
)
resources = None
if include_resources:
triggers = cast(
Page[TriggerResponse],
get_page_from_list(
items_list=self.triggers,
response_model=TriggerResponse,
include_resources=include_resources,
include_metadata=include_metadata,
),
)
resources = EventSourceResponseResources(
triggers=triggers,
)
metadata = None
if include_metadata:
metadata = EventSourceResponseMetadata(
workspace=self.workspace.to_model(),
description=self.description,
configuration=json.loads(
base64.b64decode(self.configuration).decode()
),
)
return EventSourceResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
resources=resources,
)
update(self, update)
Updates a EventSourceSchema from a EventSourceUpdate.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
update |
EventSourceUpdate |
The |
required |
Returns:
| Type | Description |
|---|---|
EventSourceSchema |
The updated |
Source code in zenml/zen_stores/schemas/event_source_schemas.py
def update(self, update: EventSourceUpdate) -> "EventSourceSchema":
"""Updates a `EventSourceSchema` from a `EventSourceUpdate`.
Args:
update: The `EventSourceUpdate` to update from.
Returns:
The updated `EventSourceSchema`.
"""
for field, value in update.dict(
exclude_unset=True, exclude_none=True
).items():
if field == "configuration":
self.configuration = base64.b64encode(
json.dumps(
update.configuration, default=pydantic_encoder
).encode("utf-8")
)
else:
setattr(self, field, value)
self.updated = datetime.utcnow()
return self
flavor_schemas
SQL Model Implementations for Flavors.
FlavorSchema (NamedSchema)
pydantic-model
SQL Model for flavors.
Attributes:
| Name | Type | Description |
|---|---|---|
type |
StackComponentType |
The type of the flavor. |
source |
str |
The source of the flavor. |
config_schema |
str |
The config schema of the flavor. |
integration |
Optional[str] |
The integration associated with the flavor. |
Source code in zenml/zen_stores/schemas/flavor_schemas.py
class FlavorSchema(NamedSchema, table=True):
"""SQL Model for flavors.
Attributes:
type: The type of the flavor.
source: The source of the flavor.
config_schema: The config schema of the flavor.
integration: The integration associated with the flavor.
"""
__tablename__ = "flavor"
type: StackComponentType
source: str
config_schema: str = Field(sa_column=Column(TEXT, nullable=False))
integration: Optional[str] = Field(default="")
connector_type: Optional[str]
connector_resource_type: Optional[str]
connector_resource_id_attr: Optional[str]
workspace_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=WorkspaceSchema.__tablename__,
source_column="workspace_id",
target_column="id",
ondelete="CASCADE",
nullable=True,
)
workspace: Optional["WorkspaceSchema"] = Relationship(
back_populates="flavors"
)
user_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=UserSchema.__tablename__,
source_column="user_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
user: Optional["UserSchema"] = Relationship(back_populates="flavors")
logo_url: Optional[str] = Field()
docs_url: Optional[str] = Field()
sdk_docs_url: Optional[str] = Field()
is_custom: bool = Field(default=True)
def update(self, flavor_update: "FlavorUpdate") -> "FlavorSchema":
"""Update a `FlavorSchema` from a `FlavorUpdate`.
Args:
flavor_update: The `FlavorUpdate` from which to update the schema.
Returns:
The updated `FlavorSchema`.
"""
for field, value in flavor_update.dict(
exclude_unset=True, exclude={"workspace", "user"}
).items():
if field == "config_schema":
setattr(self, field, json.dumps(value))
else:
setattr(self, field, value)
self.updated = datetime.utcnow()
return self
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> "FlavorResponse":
"""Converts a flavor schema to a flavor model.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The flavor model.
"""
body = FlavorResponseBody(
user=self.user.to_model() if self.user else None,
type=self.type,
integration=self.integration,
logo_url=self.logo_url,
created=self.created,
updated=self.updated,
)
metadata = None
if include_metadata:
metadata = FlavorResponseMetadata(
workspace=self.workspace.to_model()
if self.workspace
else None,
config_schema=json.loads(self.config_schema),
connector_type=self.connector_type,
connector_resource_type=self.connector_resource_type,
connector_resource_id_attr=self.connector_resource_id_attr,
source=self.source,
docs_url=self.docs_url,
sdk_docs_url=self.sdk_docs_url,
is_custom=self.is_custom,
)
return FlavorResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
)
to_model(self, include_metadata=False, include_resources=False, **kwargs)
Converts a flavor schema to a flavor model.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
Returns:
| Type | Description |
|---|---|
FlavorResponse |
The flavor model. |
Source code in zenml/zen_stores/schemas/flavor_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> "FlavorResponse":
"""Converts a flavor schema to a flavor model.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The flavor model.
"""
body = FlavorResponseBody(
user=self.user.to_model() if self.user else None,
type=self.type,
integration=self.integration,
logo_url=self.logo_url,
created=self.created,
updated=self.updated,
)
metadata = None
if include_metadata:
metadata = FlavorResponseMetadata(
workspace=self.workspace.to_model()
if self.workspace
else None,
config_schema=json.loads(self.config_schema),
connector_type=self.connector_type,
connector_resource_type=self.connector_resource_type,
connector_resource_id_attr=self.connector_resource_id_attr,
source=self.source,
docs_url=self.docs_url,
sdk_docs_url=self.sdk_docs_url,
is_custom=self.is_custom,
)
return FlavorResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
)
update(self, flavor_update)
Update a FlavorSchema from a FlavorUpdate.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
flavor_update |
FlavorUpdate |
The |
required |
Returns:
| Type | Description |
|---|---|
FlavorSchema |
The updated |
Source code in zenml/zen_stores/schemas/flavor_schemas.py
def update(self, flavor_update: "FlavorUpdate") -> "FlavorSchema":
"""Update a `FlavorSchema` from a `FlavorUpdate`.
Args:
flavor_update: The `FlavorUpdate` from which to update the schema.
Returns:
The updated `FlavorSchema`.
"""
for field, value in flavor_update.dict(
exclude_unset=True, exclude={"workspace", "user"}
).items():
if field == "config_schema":
setattr(self, field, json.dumps(value))
else:
setattr(self, field, value)
self.updated = datetime.utcnow()
return self
identity_schemas
SQLModel implementation for the server information table.
IdentitySchema (SQLModel)
pydantic-model
SQL Model for the client/server identity.
Source code in zenml/zen_stores/schemas/identity_schemas.py
class IdentitySchema(SQLModel, table=True):
"""SQL Model for the client/server identity."""
__tablename__ = "identity"
id: UUID = Field(primary_key=True)
logs_schemas
SQLModel implementation of pipeline logs tables.
LogsSchema (BaseSchema)
pydantic-model
SQL Model for logs.
Source code in zenml/zen_stores/schemas/logs_schemas.py
class LogsSchema(BaseSchema, table=True):
"""SQL Model for logs."""
__tablename__ = "logs"
# Fields
uri: str = Field(sa_column=Column(TEXT, nullable=False))
# Foreign Keys
pipeline_run_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=PipelineRunSchema.__tablename__,
source_column="pipeline_run_id",
target_column="id",
ondelete="CASCADE",
nullable=True,
)
step_run_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=StepRunSchema.__tablename__,
source_column="step_run_id",
target_column="id",
ondelete="CASCADE",
nullable=True,
)
artifact_store_id: UUID = build_foreign_key_field(
source=__tablename__,
target=StackComponentSchema.__tablename__,
source_column="stack_component_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
# Relationships
artifact_store: Optional["StackComponentSchema"] = Relationship(
back_populates="run_or_step_logs"
)
pipeline_run: Optional["PipelineRunSchema"] = Relationship(
back_populates="logs"
)
step_run: Optional["StepRunSchema"] = Relationship(back_populates="logs")
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> "LogsResponse":
"""Convert a `LogsSchema` to a `LogsResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created `LogsResponse`.
"""
body = LogsResponseBody(
uri=self.uri,
created=self.created,
updated=self.updated,
)
metadata = None
if include_metadata:
metadata = LogsResponseMetadata(
step_run_id=self.step_run_id,
pipeline_run_id=self.pipeline_run_id,
artifact_store_id=self.artifact_store_id,
)
return LogsResponse(
id=self.id,
body=body,
metadata=metadata,
)
to_model(self, include_metadata=False, include_resources=False, **kwargs)
Convert a LogsSchema to a LogsResponse.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
Returns:
| Type | Description |
|---|---|
LogsResponse |
The created |
Source code in zenml/zen_stores/schemas/logs_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> "LogsResponse":
"""Convert a `LogsSchema` to a `LogsResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created `LogsResponse`.
"""
body = LogsResponseBody(
uri=self.uri,
created=self.created,
updated=self.updated,
)
metadata = None
if include_metadata:
metadata = LogsResponseMetadata(
step_run_id=self.step_run_id,
pipeline_run_id=self.pipeline_run_id,
artifact_store_id=self.artifact_store_id,
)
return LogsResponse(
id=self.id,
body=body,
metadata=metadata,
)
model_schemas
SQLModel implementation of model tables.
ModelSchema (NamedSchema)
pydantic-model
SQL Model for model.
Source code in zenml/zen_stores/schemas/model_schemas.py
class ModelSchema(NamedSchema, table=True):
"""SQL Model for model."""
__tablename__ = "model"
workspace_id: UUID = build_foreign_key_field(
source=__tablename__,
target=WorkspaceSchema.__tablename__,
source_column="workspace_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
workspace: "WorkspaceSchema" = Relationship(back_populates="models")
user_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=UserSchema.__tablename__,
source_column="user_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
user: Optional["UserSchema"] = Relationship(back_populates="models")
license: str = Field(sa_column=Column(TEXT, nullable=True))
description: str = Field(sa_column=Column(TEXT, nullable=True))
audience: str = Field(sa_column=Column(TEXT, nullable=True))
use_cases: str = Field(sa_column=Column(TEXT, nullable=True))
limitations: str = Field(sa_column=Column(TEXT, nullable=True))
trade_offs: str = Field(sa_column=Column(TEXT, nullable=True))
ethics: str = Field(sa_column=Column(TEXT, nullable=True))
save_models_to_registry: bool = Field(
sa_column=Column(BOOLEAN, nullable=False)
)
tags: List["TagResourceSchema"] = Relationship(
back_populates="model",
sa_relationship_kwargs=dict(
primaryjoin=f"and_(TagResourceSchema.resource_type=='{TaggableResourceTypes.MODEL.value}', foreign(TagResourceSchema.resource_id)==ModelSchema.id)",
cascade="delete",
overlaps="tags",
),
)
model_versions: List["ModelVersionSchema"] = Relationship(
back_populates="model",
sa_relationship_kwargs={"cascade": "delete"},
)
artifact_links: List["ModelVersionArtifactSchema"] = Relationship(
back_populates="model",
sa_relationship_kwargs={"cascade": "delete"},
)
pipeline_run_links: List["ModelVersionPipelineRunSchema"] = Relationship(
back_populates="model",
sa_relationship_kwargs={"cascade": "delete"},
)
@classmethod
def from_request(cls, model_request: ModelRequest) -> "ModelSchema":
"""Convert an `ModelRequest` to an `ModelSchema`.
Args:
model_request: The request model to convert.
Returns:
The converted schema.
"""
return cls(
name=model_request.name,
workspace_id=model_request.workspace,
user_id=model_request.user,
license=model_request.license,
description=model_request.description,
audience=model_request.audience,
use_cases=model_request.use_cases,
limitations=model_request.limitations,
trade_offs=model_request.trade_offs,
ethics=model_request.ethics,
save_models_to_registry=model_request.save_models_to_registry,
)
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> ModelResponse:
"""Convert an `ModelSchema` to an `ModelResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created `ModelResponse`.
"""
tags = [t.tag.to_model() for t in self.tags]
if self.model_versions:
version_numbers = [mv.number for mv in self.model_versions]
latest_version_idx = version_numbers.index(max(version_numbers))
latest_version_name = self.model_versions[latest_version_idx].name
latest_version_id = self.model_versions[latest_version_idx].id
else:
latest_version_name = None
latest_version_id = None
metadata = None
if include_metadata:
metadata = ModelResponseMetadata(
workspace=self.workspace.to_model(),
license=self.license,
description=self.description,
audience=self.audience,
use_cases=self.use_cases,
limitations=self.limitations,
trade_offs=self.trade_offs,
ethics=self.ethics,
save_models_to_registry=self.save_models_to_registry,
)
body = ModelResponseBody(
user=self.user.to_model() if self.user else None,
workspace=self.workspace.to_model(),
created=self.created,
updated=self.updated,
tags=tags,
latest_version_name=latest_version_name,
latest_version_id=latest_version_id,
)
return ModelResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
)
def update(
self,
model_update: ModelUpdate,
) -> "ModelSchema":
"""Updates a `ModelSchema` from a `ModelUpdate`.
Args:
model_update: The `ModelUpdate` to update from.
Returns:
The updated `ModelSchema`.
"""
for field, value in model_update.dict(
exclude_unset=True, exclude_none=True
).items():
setattr(self, field, value)
self.updated = datetime.utcnow()
return self
from_request(model_request)
classmethod
Convert an ModelRequest to an ModelSchema.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_request |
ModelRequest |
The request model to convert. |
required |
Returns:
| Type | Description |
|---|---|
ModelSchema |
The converted schema. |
Source code in zenml/zen_stores/schemas/model_schemas.py
@classmethod
def from_request(cls, model_request: ModelRequest) -> "ModelSchema":
"""Convert an `ModelRequest` to an `ModelSchema`.
Args:
model_request: The request model to convert.
Returns:
The converted schema.
"""
return cls(
name=model_request.name,
workspace_id=model_request.workspace,
user_id=model_request.user,
license=model_request.license,
description=model_request.description,
audience=model_request.audience,
use_cases=model_request.use_cases,
limitations=model_request.limitations,
trade_offs=model_request.trade_offs,
ethics=model_request.ethics,
save_models_to_registry=model_request.save_models_to_registry,
)
to_model(self, include_metadata=False, include_resources=False, **kwargs)
Convert an ModelSchema to an ModelResponse.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
Returns:
| Type | Description |
|---|---|
ModelResponse |
The created |
Source code in zenml/zen_stores/schemas/model_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> ModelResponse:
"""Convert an `ModelSchema` to an `ModelResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created `ModelResponse`.
"""
tags = [t.tag.to_model() for t in self.tags]
if self.model_versions:
version_numbers = [mv.number for mv in self.model_versions]
latest_version_idx = version_numbers.index(max(version_numbers))
latest_version_name = self.model_versions[latest_version_idx].name
latest_version_id = self.model_versions[latest_version_idx].id
else:
latest_version_name = None
latest_version_id = None
metadata = None
if include_metadata:
metadata = ModelResponseMetadata(
workspace=self.workspace.to_model(),
license=self.license,
description=self.description,
audience=self.audience,
use_cases=self.use_cases,
limitations=self.limitations,
trade_offs=self.trade_offs,
ethics=self.ethics,
save_models_to_registry=self.save_models_to_registry,
)
body = ModelResponseBody(
user=self.user.to_model() if self.user else None,
workspace=self.workspace.to_model(),
created=self.created,
updated=self.updated,
tags=tags,
latest_version_name=latest_version_name,
latest_version_id=latest_version_id,
)
return ModelResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
)
update(self, model_update)
Updates a ModelSchema from a ModelUpdate.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_update |
ModelUpdate |
The |
required |
Returns:
| Type | Description |
|---|---|
ModelSchema |
The updated |
Source code in zenml/zen_stores/schemas/model_schemas.py
def update(
self,
model_update: ModelUpdate,
) -> "ModelSchema":
"""Updates a `ModelSchema` from a `ModelUpdate`.
Args:
model_update: The `ModelUpdate` to update from.
Returns:
The updated `ModelSchema`.
"""
for field, value in model_update.dict(
exclude_unset=True, exclude_none=True
).items():
setattr(self, field, value)
self.updated = datetime.utcnow()
return self
ModelVersionArtifactSchema (BaseSchema)
pydantic-model
SQL Model for linking of Model Versions and Artifacts M:M.
Source code in zenml/zen_stores/schemas/model_schemas.py
class ModelVersionArtifactSchema(BaseSchema, table=True):
"""SQL Model for linking of Model Versions and Artifacts M:M."""
__tablename__ = "model_versions_artifacts"
workspace_id: UUID = build_foreign_key_field(
source=__tablename__,
target=WorkspaceSchema.__tablename__,
source_column="workspace_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
workspace: "WorkspaceSchema" = Relationship(
back_populates="model_versions_artifacts_links"
)
user_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=UserSchema.__tablename__,
source_column="user_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
user: Optional["UserSchema"] = Relationship(
back_populates="model_versions_artifacts_links"
)
model_id: UUID = build_foreign_key_field(
source=__tablename__,
target=ModelSchema.__tablename__,
source_column="model_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
model: "ModelSchema" = Relationship(back_populates="artifact_links")
model_version_id: UUID = build_foreign_key_field(
source=__tablename__,
target=ModelVersionSchema.__tablename__,
source_column="model_version_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
model_version: "ModelVersionSchema" = Relationship(
back_populates="artifact_links"
)
artifact_version_id: UUID = build_foreign_key_field(
source=__tablename__,
target=ArtifactVersionSchema.__tablename__,
source_column="artifact_version_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
artifact_version: "ArtifactVersionSchema" = Relationship(
back_populates="model_versions_artifacts_links"
)
is_model_artifact: bool = Field(sa_column=Column(BOOLEAN, nullable=True))
is_deployment_artifact: bool = Field(
sa_column=Column(BOOLEAN, nullable=True)
)
@classmethod
def from_request(
cls,
model_version_artifact_request: ModelVersionArtifactRequest,
) -> "ModelVersionArtifactSchema":
"""Convert an `ModelVersionArtifactRequest` to a `ModelVersionArtifactSchema`.
Args:
model_version_artifact_request: The request link to convert.
Returns:
The converted schema.
"""
return cls(
workspace_id=model_version_artifact_request.workspace,
user_id=model_version_artifact_request.user,
model_id=model_version_artifact_request.model,
model_version_id=model_version_artifact_request.model_version,
artifact_version_id=model_version_artifact_request.artifact_version,
is_model_artifact=model_version_artifact_request.is_model_artifact,
is_deployment_artifact=model_version_artifact_request.is_deployment_artifact,
)
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> ModelVersionArtifactResponse:
"""Convert an `ModelVersionArtifactSchema` to an `ModelVersionArtifactResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created `ModelVersionArtifactResponseModel`.
"""
return ModelVersionArtifactResponse(
id=self.id,
body=ModelVersionArtifactResponseBody(
created=self.created,
updated=self.updated,
model=self.model_id,
model_version=self.model_version_id,
artifact_version=self.artifact_version.to_model(),
is_model_artifact=self.is_model_artifact,
is_deployment_artifact=self.is_deployment_artifact,
),
metadata=BaseResponseMetadata() if include_metadata else None,
)
from_request(model_version_artifact_request)
classmethod
Convert an ModelVersionArtifactRequest to a ModelVersionArtifactSchema.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_artifact_request |
ModelVersionArtifactRequest |
The request link to convert. |
required |
Returns:
| Type | Description |
|---|---|
ModelVersionArtifactSchema |
The converted schema. |
Source code in zenml/zen_stores/schemas/model_schemas.py
@classmethod
def from_request(
cls,
model_version_artifact_request: ModelVersionArtifactRequest,
) -> "ModelVersionArtifactSchema":
"""Convert an `ModelVersionArtifactRequest` to a `ModelVersionArtifactSchema`.
Args:
model_version_artifact_request: The request link to convert.
Returns:
The converted schema.
"""
return cls(
workspace_id=model_version_artifact_request.workspace,
user_id=model_version_artifact_request.user,
model_id=model_version_artifact_request.model,
model_version_id=model_version_artifact_request.model_version,
artifact_version_id=model_version_artifact_request.artifact_version,
is_model_artifact=model_version_artifact_request.is_model_artifact,
is_deployment_artifact=model_version_artifact_request.is_deployment_artifact,
)
to_model(self, include_metadata=False, include_resources=False, **kwargs)
Convert an ModelVersionArtifactSchema to an ModelVersionArtifactResponse.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
Returns:
| Type | Description |
|---|---|
ModelVersionArtifactResponse |
The created |
Source code in zenml/zen_stores/schemas/model_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> ModelVersionArtifactResponse:
"""Convert an `ModelVersionArtifactSchema` to an `ModelVersionArtifactResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created `ModelVersionArtifactResponseModel`.
"""
return ModelVersionArtifactResponse(
id=self.id,
body=ModelVersionArtifactResponseBody(
created=self.created,
updated=self.updated,
model=self.model_id,
model_version=self.model_version_id,
artifact_version=self.artifact_version.to_model(),
is_model_artifact=self.is_model_artifact,
is_deployment_artifact=self.is_deployment_artifact,
),
metadata=BaseResponseMetadata() if include_metadata else None,
)
ModelVersionPipelineRunSchema (BaseSchema)
pydantic-model
SQL Model for linking of Model Versions and Pipeline Runs M:M.
Source code in zenml/zen_stores/schemas/model_schemas.py
class ModelVersionPipelineRunSchema(BaseSchema, table=True):
"""SQL Model for linking of Model Versions and Pipeline Runs M:M."""
__tablename__ = "model_versions_runs"
workspace_id: UUID = build_foreign_key_field(
source=__tablename__,
target=WorkspaceSchema.__tablename__,
source_column="workspace_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
workspace: "WorkspaceSchema" = Relationship(
back_populates="model_versions_pipeline_runs_links"
)
user_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=UserSchema.__tablename__,
source_column="user_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
user: Optional["UserSchema"] = Relationship(
back_populates="model_versions_pipeline_runs_links"
)
model_id: UUID = build_foreign_key_field(
source=__tablename__,
target=ModelSchema.__tablename__,
source_column="model_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
model: "ModelSchema" = Relationship(back_populates="pipeline_run_links")
model_version_id: UUID = build_foreign_key_field(
source=__tablename__,
target=ModelVersionSchema.__tablename__,
source_column="model_version_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
model_version: "ModelVersionSchema" = Relationship(
back_populates="pipeline_run_links"
)
pipeline_run_id: UUID = build_foreign_key_field(
source=__tablename__,
target=PipelineRunSchema.__tablename__,
source_column="pipeline_run_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
pipeline_run: "PipelineRunSchema" = Relationship(
back_populates="model_versions_pipeline_runs_links"
)
@classmethod
def from_request(
cls,
model_version_pipeline_run_request: ModelVersionPipelineRunRequest,
) -> "ModelVersionPipelineRunSchema":
"""Convert an `ModelVersionPipelineRunRequest` to an `ModelVersionPipelineRunSchema`.
Args:
model_version_pipeline_run_request: The request link to convert.
Returns:
The converted schema.
"""
return cls(
workspace_id=model_version_pipeline_run_request.workspace,
user_id=model_version_pipeline_run_request.user,
model_id=model_version_pipeline_run_request.model,
model_version_id=model_version_pipeline_run_request.model_version,
pipeline_run_id=model_version_pipeline_run_request.pipeline_run,
)
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> ModelVersionPipelineRunResponse:
"""Convert an `ModelVersionPipelineRunSchema` to an `ModelVersionPipelineRunResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created `ModelVersionPipelineRunResponse`.
"""
return ModelVersionPipelineRunResponse(
id=self.id,
body=ModelVersionPipelineRunResponseBody(
created=self.created,
updated=self.updated,
model=self.model_id,
model_version=self.model_version_id,
pipeline_run=self.pipeline_run.to_model(),
),
metadata=BaseResponseMetadata() if include_metadata else None,
)
from_request(model_version_pipeline_run_request)
classmethod
Convert an ModelVersionPipelineRunRequest to an ModelVersionPipelineRunSchema.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_pipeline_run_request |
ModelVersionPipelineRunRequest |
The request link to convert. |
required |
Returns:
| Type | Description |
|---|---|
ModelVersionPipelineRunSchema |
The converted schema. |
Source code in zenml/zen_stores/schemas/model_schemas.py
@classmethod
def from_request(
cls,
model_version_pipeline_run_request: ModelVersionPipelineRunRequest,
) -> "ModelVersionPipelineRunSchema":
"""Convert an `ModelVersionPipelineRunRequest` to an `ModelVersionPipelineRunSchema`.
Args:
model_version_pipeline_run_request: The request link to convert.
Returns:
The converted schema.
"""
return cls(
workspace_id=model_version_pipeline_run_request.workspace,
user_id=model_version_pipeline_run_request.user,
model_id=model_version_pipeline_run_request.model,
model_version_id=model_version_pipeline_run_request.model_version,
pipeline_run_id=model_version_pipeline_run_request.pipeline_run,
)
to_model(self, include_metadata=False, include_resources=False, **kwargs)
Convert an ModelVersionPipelineRunSchema to an ModelVersionPipelineRunResponse.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
Returns:
| Type | Description |
|---|---|
ModelVersionPipelineRunResponse |
The created |
Source code in zenml/zen_stores/schemas/model_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> ModelVersionPipelineRunResponse:
"""Convert an `ModelVersionPipelineRunSchema` to an `ModelVersionPipelineRunResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created `ModelVersionPipelineRunResponse`.
"""
return ModelVersionPipelineRunResponse(
id=self.id,
body=ModelVersionPipelineRunResponseBody(
created=self.created,
updated=self.updated,
model=self.model_id,
model_version=self.model_version_id,
pipeline_run=self.pipeline_run.to_model(),
),
metadata=BaseResponseMetadata() if include_metadata else None,
)
ModelVersionSchema (NamedSchema)
pydantic-model
SQL Model for model version.
Source code in zenml/zen_stores/schemas/model_schemas.py
class ModelVersionSchema(NamedSchema, table=True):
"""SQL Model for model version."""
__tablename__ = "model_version"
workspace_id: UUID = build_foreign_key_field(
source=__tablename__,
target=WorkspaceSchema.__tablename__,
source_column="workspace_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
workspace: "WorkspaceSchema" = Relationship(
back_populates="model_versions"
)
user_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=UserSchema.__tablename__,
source_column="user_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
user: Optional["UserSchema"] = Relationship(
back_populates="model_versions"
)
model_id: UUID = build_foreign_key_field(
source=__tablename__,
target=ModelSchema.__tablename__,
source_column="model_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
model: "ModelSchema" = Relationship(back_populates="model_versions")
artifact_links: List["ModelVersionArtifactSchema"] = Relationship(
back_populates="model_version",
sa_relationship_kwargs={"cascade": "delete"},
)
pipeline_run_links: List["ModelVersionPipelineRunSchema"] = Relationship(
back_populates="model_version",
sa_relationship_kwargs={"cascade": "delete"},
)
tags: List["TagResourceSchema"] = Relationship(
back_populates="model_version",
sa_relationship_kwargs=dict(
primaryjoin=f"and_(TagResourceSchema.resource_type=='{TaggableResourceTypes.MODEL_VERSION.value}', foreign(TagResourceSchema.resource_id)==ModelVersionSchema.id)",
cascade="delete",
overlaps="tags",
),
)
number: int = Field(sa_column=Column(INTEGER, nullable=False))
description: str = Field(sa_column=Column(TEXT, nullable=True))
stage: str = Field(sa_column=Column(TEXT, nullable=True))
run_metadata: List["RunMetadataSchema"] = Relationship(
back_populates="model_version",
sa_relationship_kwargs=dict(
primaryjoin=f"and_(RunMetadataSchema.resource_type=='{MetadataResourceTypes.MODEL_VERSION.value}', foreign(RunMetadataSchema.resource_id)==ModelVersionSchema.id)",
cascade="delete",
overlaps="run_metadata",
),
)
@classmethod
def from_request(
cls, model_version_request: ModelVersionRequest
) -> "ModelVersionSchema":
"""Convert an `ModelVersionRequest` to an `ModelVersionSchema`.
Args:
model_version_request: The request model version to convert.
Returns:
The converted schema.
"""
return cls(
workspace_id=model_version_request.workspace,
user_id=model_version_request.user,
model_id=model_version_request.model,
name=model_version_request.name,
number=model_version_request.number,
description=model_version_request.description,
stage=model_version_request.stage,
)
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> ModelVersionResponse:
"""Convert an `ModelVersionSchema` to an `ModelVersionResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created `ModelVersionResponse`.
"""
# Construct {name: {version: id}} dicts for all linked artifacts
model_artifact_ids: Dict[str, Dict[str, UUID]] = {}
deployment_artifact_ids: Dict[str, Dict[str, UUID]] = {}
data_artifact_ids: Dict[str, Dict[str, UUID]] = {}
for artifact_link in self.artifact_links:
if not artifact_link.artifact_version:
continue
artifact_name = artifact_link.artifact_version.artifact.name
artifact_version = str(artifact_link.artifact_version.version)
artifact_version_id = artifact_link.artifact_version.id
if artifact_link.is_model_artifact:
model_artifact_ids.setdefault(artifact_name, {}).update(
{str(artifact_version): artifact_version_id}
)
elif artifact_link.is_deployment_artifact:
deployment_artifact_ids.setdefault(artifact_name, {}).update(
{str(artifact_version): artifact_version_id}
)
else:
data_artifact_ids.setdefault(artifact_name, {}).update(
{str(artifact_version): artifact_version_id}
)
# Construct {name: id} dict for all linked pipeline runs
pipeline_run_ids: Dict[str, UUID] = {}
for pipeline_run_link in self.pipeline_run_links:
if not pipeline_run_link.pipeline_run:
continue
pipeline_run = pipeline_run_link.pipeline_run
pipeline_run_ids[pipeline_run.name] = pipeline_run.id
metadata = None
if include_metadata:
metadata = ModelVersionResponseMetadata(
workspace=self.workspace.to_model(),
description=self.description,
run_metadata={
rm.key: rm.to_model(include_metadata=True)
for rm in self.run_metadata
},
)
body = ModelVersionResponseBody(
user=self.user.to_model() if self.user else None,
created=self.created,
updated=self.updated,
stage=self.stage,
number=self.number,
model=self.model.to_model(),
model_artifact_ids=model_artifact_ids,
data_artifact_ids=data_artifact_ids,
deployment_artifact_ids=deployment_artifact_ids,
pipeline_run_ids=pipeline_run_ids,
tags=[t.tag.to_model() for t in self.tags],
)
return ModelVersionResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
)
def update(
self,
target_stage: Optional[str] = None,
target_name: Optional[str] = None,
target_description: Optional[str] = None,
) -> "ModelVersionSchema":
"""Updates a `ModelVersionSchema` to a target stage.
Args:
target_stage: The stage to be updated.
target_name: The version name to be updated.
target_description: The version description to be updated.
Returns:
The updated `ModelVersionSchema`.
"""
if target_stage is not None:
self.stage = target_stage
if target_name is not None:
self.name = target_name
if target_description is not None:
self.description = target_description
self.updated = datetime.utcnow()
return self
from_request(model_version_request)
classmethod
Convert an ModelVersionRequest to an ModelVersionSchema.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_request |
ModelVersionRequest |
The request model version to convert. |
required |
Returns:
| Type | Description |
|---|---|
ModelVersionSchema |
The converted schema. |
Source code in zenml/zen_stores/schemas/model_schemas.py
@classmethod
def from_request(
cls, model_version_request: ModelVersionRequest
) -> "ModelVersionSchema":
"""Convert an `ModelVersionRequest` to an `ModelVersionSchema`.
Args:
model_version_request: The request model version to convert.
Returns:
The converted schema.
"""
return cls(
workspace_id=model_version_request.workspace,
user_id=model_version_request.user,
model_id=model_version_request.model,
name=model_version_request.name,
number=model_version_request.number,
description=model_version_request.description,
stage=model_version_request.stage,
)
to_model(self, include_metadata=False, include_resources=False, **kwargs)
Convert an ModelVersionSchema to an ModelVersionResponse.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
Returns:
| Type | Description |
|---|---|
ModelVersionResponse |
The created |
Source code in zenml/zen_stores/schemas/model_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> ModelVersionResponse:
"""Convert an `ModelVersionSchema` to an `ModelVersionResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created `ModelVersionResponse`.
"""
# Construct {name: {version: id}} dicts for all linked artifacts
model_artifact_ids: Dict[str, Dict[str, UUID]] = {}
deployment_artifact_ids: Dict[str, Dict[str, UUID]] = {}
data_artifact_ids: Dict[str, Dict[str, UUID]] = {}
for artifact_link in self.artifact_links:
if not artifact_link.artifact_version:
continue
artifact_name = artifact_link.artifact_version.artifact.name
artifact_version = str(artifact_link.artifact_version.version)
artifact_version_id = artifact_link.artifact_version.id
if artifact_link.is_model_artifact:
model_artifact_ids.setdefault(artifact_name, {}).update(
{str(artifact_version): artifact_version_id}
)
elif artifact_link.is_deployment_artifact:
deployment_artifact_ids.setdefault(artifact_name, {}).update(
{str(artifact_version): artifact_version_id}
)
else:
data_artifact_ids.setdefault(artifact_name, {}).update(
{str(artifact_version): artifact_version_id}
)
# Construct {name: id} dict for all linked pipeline runs
pipeline_run_ids: Dict[str, UUID] = {}
for pipeline_run_link in self.pipeline_run_links:
if not pipeline_run_link.pipeline_run:
continue
pipeline_run = pipeline_run_link.pipeline_run
pipeline_run_ids[pipeline_run.name] = pipeline_run.id
metadata = None
if include_metadata:
metadata = ModelVersionResponseMetadata(
workspace=self.workspace.to_model(),
description=self.description,
run_metadata={
rm.key: rm.to_model(include_metadata=True)
for rm in self.run_metadata
},
)
body = ModelVersionResponseBody(
user=self.user.to_model() if self.user else None,
created=self.created,
updated=self.updated,
stage=self.stage,
number=self.number,
model=self.model.to_model(),
model_artifact_ids=model_artifact_ids,
data_artifact_ids=data_artifact_ids,
deployment_artifact_ids=deployment_artifact_ids,
pipeline_run_ids=pipeline_run_ids,
tags=[t.tag.to_model() for t in self.tags],
)
return ModelVersionResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
)
update(self, target_stage=None, target_name=None, target_description=None)
Updates a ModelVersionSchema to a target stage.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
target_stage |
Optional[str] |
The stage to be updated. |
None |
target_name |
Optional[str] |
The version name to be updated. |
None |
target_description |
Optional[str] |
The version description to be updated. |
None |
Returns:
| Type | Description |
|---|---|
ModelVersionSchema |
The updated |
Source code in zenml/zen_stores/schemas/model_schemas.py
def update(
self,
target_stage: Optional[str] = None,
target_name: Optional[str] = None,
target_description: Optional[str] = None,
) -> "ModelVersionSchema":
"""Updates a `ModelVersionSchema` to a target stage.
Args:
target_stage: The stage to be updated.
target_name: The version name to be updated.
target_description: The version description to be updated.
Returns:
The updated `ModelVersionSchema`.
"""
if target_stage is not None:
self.stage = target_stage
if target_name is not None:
self.name = target_name
if target_description is not None:
self.description = target_description
self.updated = datetime.utcnow()
return self
pipeline_build_schemas
SQLModel implementation of pipeline build tables.
PipelineBuildSchema (BaseSchema)
pydantic-model
SQL Model for pipeline builds.
Source code in zenml/zen_stores/schemas/pipeline_build_schemas.py
class PipelineBuildSchema(BaseSchema, table=True):
"""SQL Model for pipeline builds."""
__tablename__ = "pipeline_build"
user_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=UserSchema.__tablename__,
source_column="user_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
user: Optional["UserSchema"] = Relationship(back_populates="builds")
workspace_id: UUID = build_foreign_key_field(
source=__tablename__,
target=WorkspaceSchema.__tablename__,
source_column="workspace_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
workspace: "WorkspaceSchema" = Relationship(back_populates="builds")
stack_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=StackSchema.__tablename__,
source_column="stack_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
stack: Optional["StackSchema"] = Relationship(back_populates="builds")
pipeline_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=PipelineSchema.__tablename__,
source_column="pipeline_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
pipeline: Optional["PipelineSchema"] = Relationship(
back_populates="builds"
)
template_deployment_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target="pipeline_deployment",
source_column="template_deployment_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
images: str = Field(
sa_column=Column(
String(length=MEDIUMTEXT_MAX_LENGTH).with_variant(
MEDIUMTEXT, "mysql"
),
nullable=False,
)
)
is_local: bool
contains_code: bool
zenml_version: Optional[str]
python_version: Optional[str]
checksum: Optional[str]
@classmethod
def from_request(
cls, request: PipelineBuildRequest
) -> "PipelineBuildSchema":
"""Convert a `PipelineBuildRequest` to a `PipelineBuildSchema`.
Args:
request: The request to convert.
Returns:
The created `PipelineBuildSchema`.
"""
return cls(
stack_id=request.stack,
workspace_id=request.workspace,
user_id=request.user,
pipeline_id=request.pipeline,
images=json.dumps(request.images, default=pydantic_encoder),
is_local=request.is_local,
contains_code=request.contains_code,
zenml_version=request.zenml_version,
python_version=request.python_version,
checksum=request.checksum,
template_deployment_id=request.template_deployment_id,
)
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> PipelineBuildResponse:
"""Convert a `PipelineBuildSchema` to a `PipelineBuildResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created `PipelineBuildResponse`.
"""
body = PipelineBuildResponseBody(
user=self.user.to_model() if self.user else None,
created=self.created,
updated=self.updated,
)
metadata = None
if include_metadata:
metadata = PipelineBuildResponseMetadata(
workspace=self.workspace.to_model(),
pipeline=self.pipeline.to_model() if self.pipeline else None,
stack=self.stack.to_model() if self.stack else None,
images=json.loads(self.images),
zenml_version=self.zenml_version,
python_version=self.python_version,
checksum=self.checksum,
is_local=self.is_local,
contains_code=self.contains_code,
template_deployment_id=self.template_deployment_id,
)
return PipelineBuildResponse(
id=self.id,
body=body,
metadata=metadata,
)
from_request(request)
classmethod
Convert a PipelineBuildRequest to a PipelineBuildSchema.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
request |
PipelineBuildRequest |
The request to convert. |
required |
Returns:
| Type | Description |
|---|---|
PipelineBuildSchema |
The created |
Source code in zenml/zen_stores/schemas/pipeline_build_schemas.py
@classmethod
def from_request(
cls, request: PipelineBuildRequest
) -> "PipelineBuildSchema":
"""Convert a `PipelineBuildRequest` to a `PipelineBuildSchema`.
Args:
request: The request to convert.
Returns:
The created `PipelineBuildSchema`.
"""
return cls(
stack_id=request.stack,
workspace_id=request.workspace,
user_id=request.user,
pipeline_id=request.pipeline,
images=json.dumps(request.images, default=pydantic_encoder),
is_local=request.is_local,
contains_code=request.contains_code,
zenml_version=request.zenml_version,
python_version=request.python_version,
checksum=request.checksum,
template_deployment_id=request.template_deployment_id,
)
to_model(self, include_metadata=False, include_resources=False, **kwargs)
Convert a PipelineBuildSchema to a PipelineBuildResponse.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
Returns:
| Type | Description |
|---|---|
PipelineBuildResponse |
The created |
Source code in zenml/zen_stores/schemas/pipeline_build_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> PipelineBuildResponse:
"""Convert a `PipelineBuildSchema` to a `PipelineBuildResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created `PipelineBuildResponse`.
"""
body = PipelineBuildResponseBody(
user=self.user.to_model() if self.user else None,
created=self.created,
updated=self.updated,
)
metadata = None
if include_metadata:
metadata = PipelineBuildResponseMetadata(
workspace=self.workspace.to_model(),
pipeline=self.pipeline.to_model() if self.pipeline else None,
stack=self.stack.to_model() if self.stack else None,
images=json.loads(self.images),
zenml_version=self.zenml_version,
python_version=self.python_version,
checksum=self.checksum,
is_local=self.is_local,
contains_code=self.contains_code,
template_deployment_id=self.template_deployment_id,
)
return PipelineBuildResponse(
id=self.id,
body=body,
metadata=metadata,
)
pipeline_deployment_schemas
SQLModel implementation of pipeline deployment tables.
PipelineDeploymentSchema (BaseSchema)
pydantic-model
SQL Model for pipeline deployments.
Source code in zenml/zen_stores/schemas/pipeline_deployment_schemas.py
class PipelineDeploymentSchema(BaseSchema, table=True):
"""SQL Model for pipeline deployments."""
__tablename__ = "pipeline_deployment"
# Fields
pipeline_configuration: str = Field(
sa_column=Column(
String(length=MEDIUMTEXT_MAX_LENGTH).with_variant(
MEDIUMTEXT, "mysql"
),
nullable=False,
)
)
step_configurations: str = Field(
sa_column=Column(
String(length=MEDIUMTEXT_MAX_LENGTH).with_variant(
MEDIUMTEXT, "mysql"
),
nullable=False,
)
)
client_environment: str = Field(sa_column=Column(TEXT, nullable=False))
run_name_template: str = Field(nullable=False)
client_version: str = Field(nullable=True)
server_version: str = Field(nullable=True)
# Foreign keys
user_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=UserSchema.__tablename__,
source_column="user_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
workspace_id: UUID = build_foreign_key_field(
source=__tablename__,
target=WorkspaceSchema.__tablename__,
source_column="workspace_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
stack_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=StackSchema.__tablename__,
source_column="stack_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
pipeline_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=PipelineSchema.__tablename__,
source_column="pipeline_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
schedule_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=ScheduleSchema.__tablename__,
source_column="schedule_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
build_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=PipelineBuildSchema.__tablename__,
source_column="build_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
code_reference_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=CodeReferenceSchema.__tablename__,
source_column="code_reference_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
# SQLModel Relationships
user: Optional["UserSchema"] = Relationship()
workspace: "WorkspaceSchema" = Relationship()
stack: "StackSchema" = Relationship()
pipeline: "PipelineSchema" = Relationship()
schedule: Optional["ScheduleSchema"] = Relationship()
build: Optional["PipelineBuildSchema"] = Relationship(
sa_relationship_kwargs={
"foreign_keys": "[PipelineDeploymentSchema.build_id]"
}
)
code_reference: Optional["CodeReferenceSchema"] = Relationship()
pipeline_runs: List["PipelineRunSchema"] = Relationship(
sa_relationship_kwargs={"cascade": "delete"}
)
step_runs: List["StepRunSchema"] = Relationship(
sa_relationship_kwargs={"cascade": "delete"}
)
@classmethod
def from_request(
cls,
request: PipelineDeploymentRequest,
code_reference_id: Optional[UUID],
) -> "PipelineDeploymentSchema":
"""Convert a `PipelineDeploymentRequest` to a `PipelineDeploymentSchema`.
Args:
request: The request to convert.
code_reference_id: Optional ID of the code reference for the
deployment.
Returns:
The created `PipelineDeploymentSchema`.
"""
return cls(
stack_id=request.stack,
workspace_id=request.workspace,
pipeline_id=request.pipeline,
build_id=request.build,
user_id=request.user,
schedule_id=request.schedule,
code_reference_id=code_reference_id,
run_name_template=request.run_name_template,
pipeline_configuration=request.pipeline_configuration.json(),
step_configurations=json.dumps(
request.step_configurations,
sort_keys=False,
default=pydantic_encoder,
),
client_environment=json.dumps(request.client_environment),
client_version=request.client_version,
server_version=request.server_version,
)
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> PipelineDeploymentResponse:
"""Convert a `PipelineDeploymentSchema` to a `PipelineDeploymentResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created `PipelineDeploymentResponse`.
"""
pipeline_configuration = PipelineConfiguration.parse_raw(
self.pipeline_configuration
)
step_configurations = json.loads(self.step_configurations)
for s, c in step_configurations.items():
step_configurations[s] = Step.parse_obj(c)
body = PipelineDeploymentResponseBody(
user=self.user.to_model() if self.user else None,
created=self.created,
updated=self.updated,
)
metadata = None
if include_metadata:
metadata = PipelineDeploymentResponseMetadata(
workspace=self.workspace.to_model(),
run_name_template=self.run_name_template,
pipeline_configuration=pipeline_configuration,
step_configurations=step_configurations,
client_environment=json.loads(self.client_environment),
client_version=self.client_version,
server_version=self.server_version,
pipeline=self.pipeline.to_model() if self.pipeline else None,
stack=self.stack.to_model() if self.stack else None,
build=self.build.to_model() if self.build else None,
schedule=self.schedule.to_model() if self.schedule else None,
code_reference=self.code_reference.to_model()
if self.code_reference
else None,
)
return PipelineDeploymentResponse(
id=self.id,
body=body,
metadata=metadata,
)
from_request(request, code_reference_id)
classmethod
Convert a PipelineDeploymentRequest to a PipelineDeploymentSchema.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
request |
PipelineDeploymentRequest |
The request to convert. |
required |
code_reference_id |
Optional[uuid.UUID] |
Optional ID of the code reference for the deployment. |
required |
Returns:
| Type | Description |
|---|---|
PipelineDeploymentSchema |
The created |
Source code in zenml/zen_stores/schemas/pipeline_deployment_schemas.py
@classmethod
def from_request(
cls,
request: PipelineDeploymentRequest,
code_reference_id: Optional[UUID],
) -> "PipelineDeploymentSchema":
"""Convert a `PipelineDeploymentRequest` to a `PipelineDeploymentSchema`.
Args:
request: The request to convert.
code_reference_id: Optional ID of the code reference for the
deployment.
Returns:
The created `PipelineDeploymentSchema`.
"""
return cls(
stack_id=request.stack,
workspace_id=request.workspace,
pipeline_id=request.pipeline,
build_id=request.build,
user_id=request.user,
schedule_id=request.schedule,
code_reference_id=code_reference_id,
run_name_template=request.run_name_template,
pipeline_configuration=request.pipeline_configuration.json(),
step_configurations=json.dumps(
request.step_configurations,
sort_keys=False,
default=pydantic_encoder,
),
client_environment=json.dumps(request.client_environment),
client_version=request.client_version,
server_version=request.server_version,
)
to_model(self, include_metadata=False, include_resources=False, **kwargs)
Convert a PipelineDeploymentSchema to a PipelineDeploymentResponse.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
Returns:
| Type | Description |
|---|---|
PipelineDeploymentResponse |
The created |
Source code in zenml/zen_stores/schemas/pipeline_deployment_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> PipelineDeploymentResponse:
"""Convert a `PipelineDeploymentSchema` to a `PipelineDeploymentResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created `PipelineDeploymentResponse`.
"""
pipeline_configuration = PipelineConfiguration.parse_raw(
self.pipeline_configuration
)
step_configurations = json.loads(self.step_configurations)
for s, c in step_configurations.items():
step_configurations[s] = Step.parse_obj(c)
body = PipelineDeploymentResponseBody(
user=self.user.to_model() if self.user else None,
created=self.created,
updated=self.updated,
)
metadata = None
if include_metadata:
metadata = PipelineDeploymentResponseMetadata(
workspace=self.workspace.to_model(),
run_name_template=self.run_name_template,
pipeline_configuration=pipeline_configuration,
step_configurations=step_configurations,
client_environment=json.loads(self.client_environment),
client_version=self.client_version,
server_version=self.server_version,
pipeline=self.pipeline.to_model() if self.pipeline else None,
stack=self.stack.to_model() if self.stack else None,
build=self.build.to_model() if self.build else None,
schedule=self.schedule.to_model() if self.schedule else None,
code_reference=self.code_reference.to_model()
if self.code_reference
else None,
)
return PipelineDeploymentResponse(
id=self.id,
body=body,
metadata=metadata,
)
pipeline_run_schemas
SQLModel implementation of pipeline run tables.
PipelineRunSchema (NamedSchema)
pydantic-model
SQL Model for pipeline runs.
Source code in zenml/zen_stores/schemas/pipeline_run_schemas.py
class PipelineRunSchema(NamedSchema, table=True):
"""SQL Model for pipeline runs."""
__tablename__ = "pipeline_run"
__table_args__ = (
UniqueConstraint(
"deployment_id",
"orchestrator_run_id",
name="unique_orchestrator_run_id_for_deployment_id",
),
)
# Fields
orchestrator_run_id: Optional[str] = Field(nullable=True)
start_time: Optional[datetime] = Field(nullable=True)
end_time: Optional[datetime] = Field(nullable=True, default=None)
status: ExecutionStatus = Field(nullable=False)
orchestrator_environment: Optional[str] = Field(
sa_column=Column(TEXT, nullable=True)
)
# Foreign keys
deployment_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=PipelineDeploymentSchema.__tablename__,
source_column="deployment_id",
target_column="id",
ondelete="CASCADE",
nullable=True,
)
user_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=UserSchema.__tablename__,
source_column="user_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
workspace_id: UUID = build_foreign_key_field(
source=__tablename__,
target=WorkspaceSchema.__tablename__,
source_column="workspace_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
pipeline_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=PipelineSchema.__tablename__,
source_column="pipeline_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
# Relationships
deployment: Optional["PipelineDeploymentSchema"] = Relationship(
back_populates="pipeline_runs"
)
workspace: "WorkspaceSchema" = Relationship(back_populates="runs")
user: Optional["UserSchema"] = Relationship(back_populates="runs")
run_metadata: List["RunMetadataSchema"] = Relationship(
back_populates="pipeline_run",
sa_relationship_kwargs=dict(
primaryjoin=f"and_(RunMetadataSchema.resource_type=='{MetadataResourceTypes.PIPELINE_RUN.value}', foreign(RunMetadataSchema.resource_id)==PipelineRunSchema.id)",
cascade="delete",
overlaps="run_metadata",
),
)
logs: Optional["LogsSchema"] = Relationship(
back_populates="pipeline_run",
sa_relationship_kwargs={"cascade": "delete", "uselist": False},
)
model_versions_pipeline_runs_links: List[
"ModelVersionPipelineRunSchema"
] = Relationship(
back_populates="pipeline_run",
sa_relationship_kwargs={"cascade": "delete"},
)
step_runs: List["StepRunSchema"] = Relationship(
sa_relationship_kwargs={"cascade": "delete"},
)
# Temporary fields and foreign keys to be deprecated
pipeline_configuration: Optional[str] = Field(
sa_column=Column(TEXT, nullable=True)
)
client_environment: Optional[str] = Field(
sa_column=Column(TEXT, nullable=True)
)
stack_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=StackSchema.__tablename__,
source_column="stack_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
build_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=PipelineBuildSchema.__tablename__,
source_column="build_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
schedule_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=ScheduleSchema.__tablename__,
source_column="schedule_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
trigger_execution_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=TriggerExecutionSchema.__tablename__,
source_column="trigger_execution_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
stack: Optional["StackSchema"] = Relationship()
build: Optional["PipelineBuildSchema"] = Relationship()
schedule: Optional["ScheduleSchema"] = Relationship()
pipeline: Optional["PipelineSchema"] = Relationship(back_populates="runs")
trigger_execution: Optional["TriggerExecutionSchema"] = Relationship()
@classmethod
def from_request(
cls, request: "PipelineRunRequest"
) -> "PipelineRunSchema":
"""Convert a `PipelineRunRequest` to a `PipelineRunSchema`.
Args:
request: The request to convert.
Returns:
The created `PipelineRunSchema`.
"""
orchestrator_environment = json.dumps(request.orchestrator_environment)
return cls(
workspace_id=request.workspace,
user_id=request.user,
name=request.name,
orchestrator_run_id=request.orchestrator_run_id,
orchestrator_environment=orchestrator_environment,
start_time=request.start_time,
status=request.status,
pipeline_id=request.pipeline,
deployment_id=request.deployment,
trigger_execution_id=request.trigger_execution_id,
)
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> "PipelineRunResponse":
"""Convert a `PipelineRunSchema` to a `PipelineRunResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created `PipelineRunResponse`.
Raises:
RuntimeError: if the model creation fails.
"""
orchestrator_environment = (
json.loads(self.orchestrator_environment)
if self.orchestrator_environment
else {}
)
run_metadata = {
metadata_schema.key: metadata_schema.to_model()
for metadata_schema in self.run_metadata
}
if self.deployment is not None:
deployment = self.deployment.to_model()
config = deployment.pipeline_configuration
client_environment = deployment.client_environment
stack = deployment.stack
pipeline = deployment.pipeline
build = deployment.build
schedule = deployment.schedule
code_reference = deployment.code_reference
elif self.pipeline_configuration is not None:
config = PipelineConfiguration.parse_raw(
self.pipeline_configuration
)
client_environment = (
json.loads(self.client_environment)
if self.client_environment
else {}
)
stack = self.stack.to_model() if self.stack else None
pipeline = self.pipeline.to_model() if self.pipeline else None
build = self.build.to_model() if self.build else None
schedule = self.schedule.to_model() if self.schedule else None
code_reference = None
else:
raise RuntimeError(
"Pipeline run model creation has failed. Each pipeline run "
"entry should either have a deployment_id or "
"pipeline_configuration."
)
body = PipelineRunResponseBody(
user=self.user.to_model() if self.user else None,
status=self.status,
stack=stack,
pipeline=pipeline,
build=build,
schedule=schedule,
code_reference=code_reference,
trigger_execution=self.trigger_execution.to_model()
if self.trigger_execution
else None,
created=self.created,
updated=self.updated,
deployment_id=self.deployment_id,
)
metadata = None
if include_metadata:
steps = {step.name: step.to_model() for step in self.step_runs}
metadata = PipelineRunResponseMetadata(
workspace=self.workspace.to_model(),
run_metadata=run_metadata,
config=config,
steps=steps,
start_time=self.start_time,
end_time=self.end_time,
client_environment=client_environment,
orchestrator_environment=orchestrator_environment,
orchestrator_run_id=self.orchestrator_run_id,
)
return PipelineRunResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
)
def update(self, run_update: "PipelineRunUpdate") -> "PipelineRunSchema":
"""Update a `PipelineRunSchema` with a `PipelineRunUpdate`.
Args:
run_update: The `PipelineRunUpdate` to update with.
Returns:
The updated `PipelineRunSchema`.
"""
if run_update.status:
self.status = run_update.status
self.end_time = run_update.end_time
self.updated = datetime.utcnow()
return self
def update_placeholder(
self, request: "PipelineRunRequest"
) -> "PipelineRunSchema":
"""Update a placeholder run.
Args:
request: The pipeline run request which should replace the
placeholder.
Raises:
RuntimeError: If the DB entry does not represent a placeholder run.
ValueError: If the run request does not match the deployment or
pipeline ID of the placeholder run.
Returns:
The updated `PipelineRunSchema`.
"""
if (
self.orchestrator_run_id
or self.status != ExecutionStatus.INITIALIZING
):
raise RuntimeError(
f"Unable to replace pipeline run {self.id} which is not a "
"placeholder run."
)
if (
self.deployment_id != request.deployment
or self.pipeline_id != request.pipeline
):
raise ValueError(
"Deployment or orchestrator run ID of placeholder run do not "
"match the IDs of the run request."
)
orchestrator_environment = json.dumps(request.orchestrator_environment)
self.orchestrator_run_id = request.orchestrator_run_id
self.orchestrator_environment = orchestrator_environment
self.status = request.status
self.updated = datetime.utcnow()
return self
from_request(request)
classmethod
Convert a PipelineRunRequest to a PipelineRunSchema.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
request |
PipelineRunRequest |
The request to convert. |
required |
Returns:
| Type | Description |
|---|---|
PipelineRunSchema |
The created |
Source code in zenml/zen_stores/schemas/pipeline_run_schemas.py
@classmethod
def from_request(
cls, request: "PipelineRunRequest"
) -> "PipelineRunSchema":
"""Convert a `PipelineRunRequest` to a `PipelineRunSchema`.
Args:
request: The request to convert.
Returns:
The created `PipelineRunSchema`.
"""
orchestrator_environment = json.dumps(request.orchestrator_environment)
return cls(
workspace_id=request.workspace,
user_id=request.user,
name=request.name,
orchestrator_run_id=request.orchestrator_run_id,
orchestrator_environment=orchestrator_environment,
start_time=request.start_time,
status=request.status,
pipeline_id=request.pipeline,
deployment_id=request.deployment,
trigger_execution_id=request.trigger_execution_id,
)
to_model(self, include_metadata=False, include_resources=False, **kwargs)
Convert a PipelineRunSchema to a PipelineRunResponse.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
Returns:
| Type | Description |
|---|---|
PipelineRunResponse |
The created |
Exceptions:
| Type | Description |
|---|---|
RuntimeError |
if the model creation fails. |
Source code in zenml/zen_stores/schemas/pipeline_run_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> "PipelineRunResponse":
"""Convert a `PipelineRunSchema` to a `PipelineRunResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created `PipelineRunResponse`.
Raises:
RuntimeError: if the model creation fails.
"""
orchestrator_environment = (
json.loads(self.orchestrator_environment)
if self.orchestrator_environment
else {}
)
run_metadata = {
metadata_schema.key: metadata_schema.to_model()
for metadata_schema in self.run_metadata
}
if self.deployment is not None:
deployment = self.deployment.to_model()
config = deployment.pipeline_configuration
client_environment = deployment.client_environment
stack = deployment.stack
pipeline = deployment.pipeline
build = deployment.build
schedule = deployment.schedule
code_reference = deployment.code_reference
elif self.pipeline_configuration is not None:
config = PipelineConfiguration.parse_raw(
self.pipeline_configuration
)
client_environment = (
json.loads(self.client_environment)
if self.client_environment
else {}
)
stack = self.stack.to_model() if self.stack else None
pipeline = self.pipeline.to_model() if self.pipeline else None
build = self.build.to_model() if self.build else None
schedule = self.schedule.to_model() if self.schedule else None
code_reference = None
else:
raise RuntimeError(
"Pipeline run model creation has failed. Each pipeline run "
"entry should either have a deployment_id or "
"pipeline_configuration."
)
body = PipelineRunResponseBody(
user=self.user.to_model() if self.user else None,
status=self.status,
stack=stack,
pipeline=pipeline,
build=build,
schedule=schedule,
code_reference=code_reference,
trigger_execution=self.trigger_execution.to_model()
if self.trigger_execution
else None,
created=self.created,
updated=self.updated,
deployment_id=self.deployment_id,
)
metadata = None
if include_metadata:
steps = {step.name: step.to_model() for step in self.step_runs}
metadata = PipelineRunResponseMetadata(
workspace=self.workspace.to_model(),
run_metadata=run_metadata,
config=config,
steps=steps,
start_time=self.start_time,
end_time=self.end_time,
client_environment=client_environment,
orchestrator_environment=orchestrator_environment,
orchestrator_run_id=self.orchestrator_run_id,
)
return PipelineRunResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
)
update(self, run_update)
Update a PipelineRunSchema with a PipelineRunUpdate.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
run_update |
PipelineRunUpdate |
The |
required |
Returns:
| Type | Description |
|---|---|
PipelineRunSchema |
The updated |
Source code in zenml/zen_stores/schemas/pipeline_run_schemas.py
def update(self, run_update: "PipelineRunUpdate") -> "PipelineRunSchema":
"""Update a `PipelineRunSchema` with a `PipelineRunUpdate`.
Args:
run_update: The `PipelineRunUpdate` to update with.
Returns:
The updated `PipelineRunSchema`.
"""
if run_update.status:
self.status = run_update.status
self.end_time = run_update.end_time
self.updated = datetime.utcnow()
return self
update_placeholder(self, request)
Update a placeholder run.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
request |
PipelineRunRequest |
The pipeline run request which should replace the placeholder. |
required |
Exceptions:
| Type | Description |
|---|---|
RuntimeError |
If the DB entry does not represent a placeholder run. |
ValueError |
If the run request does not match the deployment or pipeline ID of the placeholder run. |
Returns:
| Type | Description |
|---|---|
PipelineRunSchema |
The updated |
Source code in zenml/zen_stores/schemas/pipeline_run_schemas.py
def update_placeholder(
self, request: "PipelineRunRequest"
) -> "PipelineRunSchema":
"""Update a placeholder run.
Args:
request: The pipeline run request which should replace the
placeholder.
Raises:
RuntimeError: If the DB entry does not represent a placeholder run.
ValueError: If the run request does not match the deployment or
pipeline ID of the placeholder run.
Returns:
The updated `PipelineRunSchema`.
"""
if (
self.orchestrator_run_id
or self.status != ExecutionStatus.INITIALIZING
):
raise RuntimeError(
f"Unable to replace pipeline run {self.id} which is not a "
"placeholder run."
)
if (
self.deployment_id != request.deployment
or self.pipeline_id != request.pipeline
):
raise ValueError(
"Deployment or orchestrator run ID of placeholder run do not "
"match the IDs of the run request."
)
orchestrator_environment = json.dumps(request.orchestrator_environment)
self.orchestrator_run_id = request.orchestrator_run_id
self.orchestrator_environment = orchestrator_environment
self.status = request.status
self.updated = datetime.utcnow()
return self
pipeline_schemas
SQL Model Implementations for Pipelines and Pipeline Runs.
PipelineSchema (NamedSchema)
pydantic-model
SQL Model for pipelines.
Source code in zenml/zen_stores/schemas/pipeline_schemas.py
class PipelineSchema(NamedSchema, table=True):
"""SQL Model for pipelines."""
__tablename__ = "pipeline"
# Fields
version: str
version_hash: str
docstring: Optional[str] = Field(sa_column=Column(TEXT, nullable=True))
spec: str = Field(
sa_column=Column(
String(length=MEDIUMTEXT_MAX_LENGTH).with_variant(
MEDIUMTEXT, "mysql"
),
nullable=False,
)
)
# Foreign keys
workspace_id: UUID = build_foreign_key_field(
source=__tablename__,
target=WorkspaceSchema.__tablename__,
source_column="workspace_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
user_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=UserSchema.__tablename__,
source_column="user_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
# Relationships
user: Optional["UserSchema"] = Relationship(back_populates="pipelines")
workspace: "WorkspaceSchema" = Relationship(back_populates="pipelines")
schedules: List["ScheduleSchema"] = Relationship(
back_populates="pipeline",
)
runs: List["PipelineRunSchema"] = Relationship(back_populates="pipeline")
builds: List["PipelineBuildSchema"] = Relationship(
back_populates="pipeline"
)
deployments: List["PipelineDeploymentSchema"] = Relationship(
back_populates="pipeline",
)
@classmethod
def from_request(
cls,
pipeline_request: "PipelineRequest",
) -> "PipelineSchema":
"""Convert a `PipelineRequest` to a `PipelineSchema`.
Args:
pipeline_request: The request model to convert.
Returns:
The converted schema.
"""
return cls(
name=pipeline_request.name,
version=pipeline_request.version,
version_hash=pipeline_request.version_hash,
workspace_id=pipeline_request.workspace,
user_id=pipeline_request.user,
docstring=pipeline_request.docstring,
spec=pipeline_request.spec.json(sort_keys=True),
)
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
last_x_runs: int = 3,
**kwargs: Any,
) -> "PipelineResponse":
"""Convert a `PipelineSchema` to a `PipelineResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
last_x_runs: How many runs to use for the execution status
Returns:
The created PipelineResponse.
"""
body = PipelineResponseBody(
user=self.user.to_model() if self.user else None,
status=[run.status for run in self.runs[:last_x_runs]],
created=self.created,
updated=self.updated,
version=self.version,
)
metadata = None
if include_metadata:
metadata = PipelineResponseMetadata(
workspace=self.workspace.to_model(),
version_hash=self.version_hash,
spec=PipelineSpec.parse_raw(self.spec),
docstring=self.docstring,
)
return PipelineResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
)
def update(self, pipeline_update: "PipelineUpdate") -> "PipelineSchema":
"""Update a `PipelineSchema` with a `PipelineUpdate`.
Args:
pipeline_update: The update model.
Returns:
The updated `PipelineSchema`.
"""
self.updated = datetime.utcnow()
return self
from_request(pipeline_request)
classmethod
Convert a PipelineRequest to a PipelineSchema.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
pipeline_request |
PipelineRequest |
The request model to convert. |
required |
Returns:
| Type | Description |
|---|---|
PipelineSchema |
The converted schema. |
Source code in zenml/zen_stores/schemas/pipeline_schemas.py
@classmethod
def from_request(
cls,
pipeline_request: "PipelineRequest",
) -> "PipelineSchema":
"""Convert a `PipelineRequest` to a `PipelineSchema`.
Args:
pipeline_request: The request model to convert.
Returns:
The converted schema.
"""
return cls(
name=pipeline_request.name,
version=pipeline_request.version,
version_hash=pipeline_request.version_hash,
workspace_id=pipeline_request.workspace,
user_id=pipeline_request.user,
docstring=pipeline_request.docstring,
spec=pipeline_request.spec.json(sort_keys=True),
)
to_model(self, include_metadata=False, include_resources=False, last_x_runs=3, **kwargs)
Convert a PipelineSchema to a PipelineResponse.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
last_x_runs |
int |
How many runs to use for the execution status |
3 |
Returns:
| Type | Description |
|---|---|
PipelineResponse |
The created PipelineResponse. |
Source code in zenml/zen_stores/schemas/pipeline_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
last_x_runs: int = 3,
**kwargs: Any,
) -> "PipelineResponse":
"""Convert a `PipelineSchema` to a `PipelineResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
last_x_runs: How many runs to use for the execution status
Returns:
The created PipelineResponse.
"""
body = PipelineResponseBody(
user=self.user.to_model() if self.user else None,
status=[run.status for run in self.runs[:last_x_runs]],
created=self.created,
updated=self.updated,
version=self.version,
)
metadata = None
if include_metadata:
metadata = PipelineResponseMetadata(
workspace=self.workspace.to_model(),
version_hash=self.version_hash,
spec=PipelineSpec.parse_raw(self.spec),
docstring=self.docstring,
)
return PipelineResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
)
update(self, pipeline_update)
Update a PipelineSchema with a PipelineUpdate.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
pipeline_update |
PipelineUpdate |
The update model. |
required |
Returns:
| Type | Description |
|---|---|
PipelineSchema |
The updated |
Source code in zenml/zen_stores/schemas/pipeline_schemas.py
def update(self, pipeline_update: "PipelineUpdate") -> "PipelineSchema":
"""Update a `PipelineSchema` with a `PipelineUpdate`.
Args:
pipeline_update: The update model.
Returns:
The updated `PipelineSchema`.
"""
self.updated = datetime.utcnow()
return self
run_metadata_schemas
SQLModel implementation of pipeline run metadata tables.
RunMetadataSchema (BaseSchema)
pydantic-model
SQL Model for run metadata.
Source code in zenml/zen_stores/schemas/run_metadata_schemas.py
class RunMetadataSchema(BaseSchema, table=True):
"""SQL Model for run metadata."""
__tablename__ = "run_metadata"
resource_id: UUID
resource_type: str = Field(sa_column=Column(VARCHAR(255), nullable=False))
pipeline_run: List["PipelineRunSchema"] = Relationship(
back_populates="run_metadata",
sa_relationship_kwargs=dict(
primaryjoin=f"and_(RunMetadataSchema.resource_type=='{MetadataResourceTypes.PIPELINE_RUN.value}', foreign(RunMetadataSchema.resource_id)==PipelineRunSchema.id)",
overlaps="run_metadata,step_run,artifact_version,model_version",
),
)
step_run: List["StepRunSchema"] = Relationship(
back_populates="run_metadata",
sa_relationship_kwargs=dict(
primaryjoin=f"and_(RunMetadataSchema.resource_type=='{MetadataResourceTypes.STEP_RUN.value}', foreign(RunMetadataSchema.resource_id)==StepRunSchema.id)",
overlaps="run_metadata,pipeline_run,artifact_version,model_version",
),
)
artifact_version: List["ArtifactVersionSchema"] = Relationship(
back_populates="run_metadata",
sa_relationship_kwargs=dict(
primaryjoin=f"and_(RunMetadataSchema.resource_type=='{MetadataResourceTypes.ARTIFACT_VERSION.value}', foreign(RunMetadataSchema.resource_id)==ArtifactVersionSchema.id)",
overlaps="run_metadata,pipeline_run,step_run,model_version",
),
)
model_version: List["ModelVersionSchema"] = Relationship(
back_populates="run_metadata",
sa_relationship_kwargs=dict(
primaryjoin=f"and_(RunMetadataSchema.resource_type=='{MetadataResourceTypes.MODEL_VERSION.value}', foreign(RunMetadataSchema.resource_id)==ModelVersionSchema.id)",
overlaps="run_metadata,pipeline_run,step_run,artifact_version",
),
)
stack_component_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=StackComponentSchema.__tablename__,
source_column="stack_component_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
stack_component: Optional["StackComponentSchema"] = Relationship(
back_populates="run_metadata"
)
user_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=UserSchema.__tablename__,
source_column="user_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
user: Optional["UserSchema"] = Relationship(back_populates="run_metadata")
workspace_id: UUID = build_foreign_key_field(
source=__tablename__,
target=WorkspaceSchema.__tablename__,
source_column="workspace_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
workspace: "WorkspaceSchema" = Relationship(back_populates="run_metadata")
key: str
value: str = Field(sa_column=Column(TEXT, nullable=False))
type: MetadataTypeEnum
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> "RunMetadataResponse":
"""Convert a `RunMetadataSchema` to a `RunMetadataResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created `RunMetadataResponse`.
"""
body = RunMetadataResponseBody(
user=self.user.to_model() if self.user else None,
key=self.key,
created=self.created,
updated=self.updated,
value=json.loads(self.value),
type=self.type,
)
metadata = None
if include_metadata:
metadata = RunMetadataResponseMetadata(
workspace=self.workspace.to_model(),
resource_id=self.resource_id,
resource_type=MetadataResourceTypes(self.resource_type),
stack_component_id=self.stack_component_id,
)
return RunMetadataResponse(
id=self.id,
body=body,
metadata=metadata,
)
to_model(self, include_metadata=False, include_resources=False, **kwargs)
Convert a RunMetadataSchema to a RunMetadataResponse.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
Returns:
| Type | Description |
|---|---|
RunMetadataResponse |
The created |
Source code in zenml/zen_stores/schemas/run_metadata_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> "RunMetadataResponse":
"""Convert a `RunMetadataSchema` to a `RunMetadataResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created `RunMetadataResponse`.
"""
body = RunMetadataResponseBody(
user=self.user.to_model() if self.user else None,
key=self.key,
created=self.created,
updated=self.updated,
value=json.loads(self.value),
type=self.type,
)
metadata = None
if include_metadata:
metadata = RunMetadataResponseMetadata(
workspace=self.workspace.to_model(),
resource_id=self.resource_id,
resource_type=MetadataResourceTypes(self.resource_type),
stack_component_id=self.stack_component_id,
)
return RunMetadataResponse(
id=self.id,
body=body,
metadata=metadata,
)
schedule_schema
SQL Model Implementations for Pipeline Schedules.
ScheduleSchema (NamedSchema)
pydantic-model
SQL Model for schedules.
Source code in zenml/zen_stores/schemas/schedule_schema.py
class ScheduleSchema(NamedSchema, table=True):
"""SQL Model for schedules."""
__tablename__ = "schedule"
workspace_id: UUID = build_foreign_key_field(
source=__tablename__,
target=WorkspaceSchema.__tablename__,
source_column="workspace_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
workspace: "WorkspaceSchema" = Relationship(back_populates="schedules")
user_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=UserSchema.__tablename__,
source_column="user_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
user: Optional["UserSchema"] = Relationship(back_populates="schedules")
pipeline_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=PipelineSchema.__tablename__,
source_column="pipeline_id",
target_column="id",
ondelete="CASCADE",
nullable=True,
)
pipeline: "PipelineSchema" = Relationship(back_populates="schedules")
deployment: Optional["PipelineDeploymentSchema"] = Relationship(
back_populates="schedule"
)
orchestrator_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=StackComponentSchema.__tablename__,
source_column="orchestrator_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
orchestrator: "StackComponentSchema" = Relationship(
back_populates="schedules"
)
active: bool
cron_expression: Optional[str] = Field(nullable=True)
start_time: Optional[datetime] = Field(nullable=True)
end_time: Optional[datetime] = Field(nullable=True)
interval_second: Optional[float] = Field(nullable=True)
catchup: bool
@classmethod
def from_request(
cls, schedule_request: ScheduleRequest
) -> "ScheduleSchema":
"""Create a `ScheduleSchema` from a `ScheduleRequest`.
Args:
schedule_request: The `ScheduleRequest` to create the schema from.
Returns:
The created `ScheduleSchema`.
"""
if schedule_request.interval_second is not None:
interval_second = schedule_request.interval_second.total_seconds()
else:
interval_second = None
return cls(
name=schedule_request.name,
workspace_id=schedule_request.workspace,
user_id=schedule_request.user,
pipeline_id=schedule_request.pipeline_id,
orchestrator_id=schedule_request.orchestrator_id,
active=schedule_request.active,
cron_expression=schedule_request.cron_expression,
start_time=schedule_request.start_time,
end_time=schedule_request.end_time,
interval_second=interval_second,
catchup=schedule_request.catchup,
)
def update(self, schedule_update: ScheduleUpdate) -> "ScheduleSchema":
"""Update a `ScheduleSchema` from a `ScheduleUpdateModel`.
Args:
schedule_update: The `ScheduleUpdateModel` to update the schema from.
Returns:
The updated `ScheduleSchema`.
"""
if schedule_update.name is not None:
self.name = schedule_update.name
if schedule_update.active is not None:
self.active = schedule_update.active
if schedule_update.cron_expression is not None:
self.cron_expression = schedule_update.cron_expression
if schedule_update.start_time is not None:
self.start_time = schedule_update.start_time
if schedule_update.end_time is not None:
self.end_time = schedule_update.end_time
if schedule_update.interval_second is not None:
self.interval_second = (
schedule_update.interval_second.total_seconds()
)
if schedule_update.catchup is not None:
self.catchup = schedule_update.catchup
self.updated = datetime.utcnow()
return self
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> ScheduleResponse:
"""Convert a `ScheduleSchema` to a `ScheduleResponseModel`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created `ScheduleResponseModel`.
"""
if self.interval_second is not None:
interval_second = timedelta(seconds=self.interval_second)
else:
interval_second = None
body = ScheduleResponseBody(
user=self.user.to_model() if self.user else None,
active=self.active,
cron_expression=self.cron_expression,
start_time=self.start_time,
end_time=self.end_time,
interval_second=interval_second,
catchup=self.catchup,
updated=self.updated,
created=self.created,
)
metadata = None
if include_metadata:
metadata = ScheduleResponseMetadata(
workspace=self.workspace.to_model(),
pipeline_id=self.pipeline_id,
orchestrator_id=self.orchestrator_id,
)
return ScheduleResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
)
from_request(schedule_request)
classmethod
Create a ScheduleSchema from a ScheduleRequest.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
schedule_request |
ScheduleRequest |
The |
required |
Returns:
| Type | Description |
|---|---|
ScheduleSchema |
The created |
Source code in zenml/zen_stores/schemas/schedule_schema.py
@classmethod
def from_request(
cls, schedule_request: ScheduleRequest
) -> "ScheduleSchema":
"""Create a `ScheduleSchema` from a `ScheduleRequest`.
Args:
schedule_request: The `ScheduleRequest` to create the schema from.
Returns:
The created `ScheduleSchema`.
"""
if schedule_request.interval_second is not None:
interval_second = schedule_request.interval_second.total_seconds()
else:
interval_second = None
return cls(
name=schedule_request.name,
workspace_id=schedule_request.workspace,
user_id=schedule_request.user,
pipeline_id=schedule_request.pipeline_id,
orchestrator_id=schedule_request.orchestrator_id,
active=schedule_request.active,
cron_expression=schedule_request.cron_expression,
start_time=schedule_request.start_time,
end_time=schedule_request.end_time,
interval_second=interval_second,
catchup=schedule_request.catchup,
)
to_model(self, include_metadata=False, include_resources=False, **kwargs)
Convert a ScheduleSchema to a ScheduleResponseModel.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
Returns:
| Type | Description |
|---|---|
ScheduleResponse |
The created |
Source code in zenml/zen_stores/schemas/schedule_schema.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> ScheduleResponse:
"""Convert a `ScheduleSchema` to a `ScheduleResponseModel`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created `ScheduleResponseModel`.
"""
if self.interval_second is not None:
interval_second = timedelta(seconds=self.interval_second)
else:
interval_second = None
body = ScheduleResponseBody(
user=self.user.to_model() if self.user else None,
active=self.active,
cron_expression=self.cron_expression,
start_time=self.start_time,
end_time=self.end_time,
interval_second=interval_second,
catchup=self.catchup,
updated=self.updated,
created=self.created,
)
metadata = None
if include_metadata:
metadata = ScheduleResponseMetadata(
workspace=self.workspace.to_model(),
pipeline_id=self.pipeline_id,
orchestrator_id=self.orchestrator_id,
)
return ScheduleResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
)
update(self, schedule_update)
Update a ScheduleSchema from a ScheduleUpdateModel.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
schedule_update |
ScheduleUpdate |
The |
required |
Returns:
| Type | Description |
|---|---|
ScheduleSchema |
The updated |
Source code in zenml/zen_stores/schemas/schedule_schema.py
def update(self, schedule_update: ScheduleUpdate) -> "ScheduleSchema":
"""Update a `ScheduleSchema` from a `ScheduleUpdateModel`.
Args:
schedule_update: The `ScheduleUpdateModel` to update the schema from.
Returns:
The updated `ScheduleSchema`.
"""
if schedule_update.name is not None:
self.name = schedule_update.name
if schedule_update.active is not None:
self.active = schedule_update.active
if schedule_update.cron_expression is not None:
self.cron_expression = schedule_update.cron_expression
if schedule_update.start_time is not None:
self.start_time = schedule_update.start_time
if schedule_update.end_time is not None:
self.end_time = schedule_update.end_time
if schedule_update.interval_second is not None:
self.interval_second = (
schedule_update.interval_second.total_seconds()
)
if schedule_update.catchup is not None:
self.catchup = schedule_update.catchup
self.updated = datetime.utcnow()
return self
schema_utils
Utility functions for SQLModel schemas.
build_foreign_key_field(source, target, source_column, target_column, ondelete, nullable, **sa_column_kwargs)
Build a SQLModel foreign key field.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
source |
str |
Source table name. |
required |
target |
str |
Target table name. |
required |
source_column |
str |
Source column name. |
required |
target_column |
str |
Target column name. |
required |
ondelete |
str |
On delete behavior. |
required |
nullable |
bool |
Whether the field is nullable. |
required |
**sa_column_kwargs |
Any |
Keyword arguments for the SQLAlchemy column. |
{} |
Returns:
| Type | Description |
|---|---|
Any |
SQLModel foreign key field. |
Exceptions:
| Type | Description |
|---|---|
ValueError |
If the ondelete and nullable arguments are not compatible. |
Source code in zenml/zen_stores/schemas/schema_utils.py
def build_foreign_key_field(
source: str,
target: str,
source_column: str,
target_column: str,
ondelete: str,
nullable: bool,
**sa_column_kwargs: Any,
) -> Any:
"""Build a SQLModel foreign key field.
Args:
source: Source table name.
target: Target table name.
source_column: Source column name.
target_column: Target column name.
ondelete: On delete behavior.
nullable: Whether the field is nullable.
**sa_column_kwargs: Keyword arguments for the SQLAlchemy column.
Returns:
SQLModel foreign key field.
Raises:
ValueError: If the ondelete and nullable arguments are not compatible.
"""
if not nullable and ondelete == "SET NULL":
raise ValueError(
"Cannot set ondelete to SET NULL if the field is not nullable."
)
constraint_name = foreign_key_constraint_name(
source=source,
target=target,
source_column=source_column,
)
return Field(
sa_column=Column(
ForeignKey(
f"{target}.{target_column}",
name=constraint_name,
ondelete=ondelete,
),
nullable=nullable,
**sa_column_kwargs,
),
)
foreign_key_constraint_name(source, target, source_column)
Defines the name of a foreign key constraint.
For simplicity, we use the naming convention used by alembic here: https://alembic.sqlalchemy.org/en/latest/batch.html#dropping-unnamed-or-named-foreign-key-constraints.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
source |
str |
Source table name. |
required |
target |
str |
Target table name. |
required |
source_column |
str |
Source column name. |
required |
Returns:
| Type | Description |
|---|---|
str |
Name of the foreign key constraint. |
Source code in zenml/zen_stores/schemas/schema_utils.py
def foreign_key_constraint_name(
source: str, target: str, source_column: str
) -> str:
"""Defines the name of a foreign key constraint.
For simplicity, we use the naming convention used by alembic here:
https://alembic.sqlalchemy.org/en/latest/batch.html#dropping-unnamed-or-named-foreign-key-constraints.
Args:
source: Source table name.
target: Target table name.
source_column: Source column name.
Returns:
Name of the foreign key constraint.
"""
return f"fk_{source}_{source_column}_{target}"
secret_schemas
SQL Model Implementations for Secrets.
SecretDecodeError (Exception)
Raised when a secret cannot be decoded or decrypted.
Source code in zenml/zen_stores/schemas/secret_schemas.py
class SecretDecodeError(Exception):
"""Raised when a secret cannot be decoded or decrypted."""
SecretSchema (NamedSchema)
pydantic-model
SQL Model for secrets.
Attributes:
| Name | Type | Description |
|---|---|---|
name |
str |
The name of the secret. |
values |
Optional[bytes] |
The values of the secret. |
Source code in zenml/zen_stores/schemas/secret_schemas.py
class SecretSchema(NamedSchema, table=True):
"""SQL Model for secrets.
Attributes:
name: The name of the secret.
values: The values of the secret.
"""
__tablename__ = "secret"
scope: SecretScope
values: Optional[bytes] = Field(sa_column=Column(TEXT, nullable=True))
workspace_id: UUID = build_foreign_key_field(
source=__tablename__,
target=WorkspaceSchema.__tablename__,
source_column="workspace_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
workspace: "WorkspaceSchema" = Relationship(back_populates="secrets")
user_id: UUID = build_foreign_key_field(
source=__tablename__,
target=UserSchema.__tablename__,
source_column="user_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
user: "UserSchema" = Relationship(back_populates="secrets")
@classmethod
def _dump_secret_values(
cls, values: Dict[str, str], encryption_engine: Optional[AesGcmEngine]
) -> bytes:
"""Dump the secret values to a string.
Args:
values: The secret values to dump.
encryption_engine: The encryption engine to use to encrypt the
secret values. If None, the values will be base64 encoded.
Raises:
ValueError: If the secret values do not fit in the database field.
Returns:
The serialized encrypted secret values.
"""
serialized_values = json.dumps(values)
if encryption_engine is None:
encrypted_values = base64.b64encode(
serialized_values.encode("utf-8")
)
else:
encrypted_values = encryption_engine.encrypt(serialized_values)
if len(encrypted_values) > TEXT_FIELD_MAX_LENGTH:
raise ValueError(
"Database representation of secret values exceeds max "
"length. Please use fewer values or consider using shorter "
"secret keys and/or values."
)
return encrypted_values
@classmethod
def _load_secret_values(
cls,
encrypted_values: bytes,
encryption_engine: Optional[AesGcmEngine] = None,
) -> Dict[str, str]:
"""Load the secret values from a base64 encoded byte string.
Args:
encrypted_values: The serialized encrypted secret values.
encryption_engine: The encryption engine to use to decrypt the
secret values. If None, the values will be base64 decoded.
Returns:
The loaded secret values.
Raises:
SecretDecodeError: If the secret values cannot be decoded or
decrypted.
"""
if encryption_engine is None:
try:
serialized_values = base64.b64decode(encrypted_values).decode()
except ValueError as e:
raise SecretDecodeError(
"Could not decode base64 encoded secret values: {str(e)}"
) from e
else:
try:
serialized_values = encryption_engine.decrypt(encrypted_values)
except (ValueError, InvalidCiphertextError) as e:
raise SecretDecodeError(
"Could not decrypt secret values. Please check that the "
f"encryption key is correct: {str(e)}"
) from e
try:
return cast(
Dict[str, str],
json.loads(serialized_values),
)
except json.JSONDecodeError as e:
raise SecretDecodeError(
"Could not decode secret values. Please check that the "
f"secret values are valid JSON: {str(e)}"
) from e
@classmethod
def from_request(
cls,
secret: SecretRequest,
) -> "SecretSchema":
"""Create a `SecretSchema` from a `SecretRequest`.
Args:
secret: The `SecretRequest` from which to create the schema.
Returns:
The created `SecretSchema`.
"""
assert secret.user is not None, "User must be set for secret creation."
return cls(
name=secret.name,
scope=secret.scope,
workspace_id=secret.workspace,
user_id=secret.user,
# Don't store secret values implicitly in the secret. The
# SQL secret store will call `store_secret_values` to store the
# values separately if SQL is used as the secrets store.
values=None,
)
def update(
self,
secret_update: SecretUpdate,
) -> "SecretSchema":
"""Update a `SecretSchema` from a `SecretUpdate`.
Args:
secret_update: The `SecretUpdate` from which to update the schema.
Returns:
The updated `SecretSchema`.
"""
# Don't update the secret values implicitly in the secret. The
# SQL secret store will call `set_secret_values` to update the
# values separately if SQL is used as the secrets store.
for field, value in secret_update.dict(
exclude_unset=True, exclude={"workspace", "user", "values"}
).items():
setattr(self, field, value)
self.updated = datetime.utcnow()
return self
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> SecretResponse:
"""Converts a secret schema to a secret model.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The secret model.
"""
metadata = None
if include_metadata:
metadata = SecretResponseMetadata(
workspace=self.workspace.to_model(),
)
# Don't load the secret values implicitly in the secret. The
# SQL secret store will call `get_secret_values` to load the
# values separately if SQL is used as the secrets store.
body = SecretResponseBody(
user=self.user.to_model() if self.user else None,
created=self.created,
updated=self.updated,
scope=self.scope,
)
return SecretResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
)
def get_secret_values(
self,
encryption_engine: Optional[AesGcmEngine] = None,
) -> Dict[str, str]:
"""Get the secret values for this secret.
This method is used by the SQL secrets store to load the secret values
from the database.
Args:
encryption_engine: The encryption engine to use to decrypt the
secret values. If None, the values will be base64 decoded.
Returns:
The secret values
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
"""
if not self.values:
raise KeyError(
f"Secret values for secret {self.id} have not been stored in "
f"the SQL secrets store."
)
return self._load_secret_values(self.values, encryption_engine)
def set_secret_values(
self,
secret_values: Dict[str, str],
encryption_engine: Optional[AesGcmEngine] = None,
) -> None:
"""Create a `SecretSchema` from a `SecretRequest`.
This method is used by the SQL secrets store to store the secret values
in the database.
Args:
secret_values: The new secret values.
encryption_engine: The encryption engine to use to encrypt the
secret values. If None, the values will be base64 encoded.
"""
self.values = self._dump_secret_values(
secret_values, encryption_engine
)
from_request(secret)
classmethod
Create a SecretSchema from a SecretRequest.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret |
SecretRequest |
The |
required |
Returns:
| Type | Description |
|---|---|
SecretSchema |
The created |
Source code in zenml/zen_stores/schemas/secret_schemas.py
@classmethod
def from_request(
cls,
secret: SecretRequest,
) -> "SecretSchema":
"""Create a `SecretSchema` from a `SecretRequest`.
Args:
secret: The `SecretRequest` from which to create the schema.
Returns:
The created `SecretSchema`.
"""
assert secret.user is not None, "User must be set for secret creation."
return cls(
name=secret.name,
scope=secret.scope,
workspace_id=secret.workspace,
user_id=secret.user,
# Don't store secret values implicitly in the secret. The
# SQL secret store will call `store_secret_values` to store the
# values separately if SQL is used as the secrets store.
values=None,
)
get_secret_values(self, encryption_engine=None)
Get the secret values for this secret.
This method is used by the SQL secrets store to load the secret values from the database.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
encryption_engine |
Optional[sqlalchemy_utils.types.encrypted.encrypted_type.AesGcmEngine] |
The encryption engine to use to decrypt the secret values. If None, the values will be base64 decoded. |
None |
Returns:
| Type | Description |
|---|---|
Dict[str, str] |
The secret values |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if no secret values for the given ID are stored in the secrets store. |
Source code in zenml/zen_stores/schemas/secret_schemas.py
def get_secret_values(
self,
encryption_engine: Optional[AesGcmEngine] = None,
) -> Dict[str, str]:
"""Get the secret values for this secret.
This method is used by the SQL secrets store to load the secret values
from the database.
Args:
encryption_engine: The encryption engine to use to decrypt the
secret values. If None, the values will be base64 decoded.
Returns:
The secret values
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
"""
if not self.values:
raise KeyError(
f"Secret values for secret {self.id} have not been stored in "
f"the SQL secrets store."
)
return self._load_secret_values(self.values, encryption_engine)
set_secret_values(self, secret_values, encryption_engine=None)
Create a SecretSchema from a SecretRequest.
This method is used by the SQL secrets store to store the secret values in the database.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_values |
Dict[str, str] |
The new secret values. |
required |
encryption_engine |
Optional[sqlalchemy_utils.types.encrypted.encrypted_type.AesGcmEngine] |
The encryption engine to use to encrypt the secret values. If None, the values will be base64 encoded. |
None |
Source code in zenml/zen_stores/schemas/secret_schemas.py
def set_secret_values(
self,
secret_values: Dict[str, str],
encryption_engine: Optional[AesGcmEngine] = None,
) -> None:
"""Create a `SecretSchema` from a `SecretRequest`.
This method is used by the SQL secrets store to store the secret values
in the database.
Args:
secret_values: The new secret values.
encryption_engine: The encryption engine to use to encrypt the
secret values. If None, the values will be base64 encoded.
"""
self.values = self._dump_secret_values(
secret_values, encryption_engine
)
to_model(self, include_metadata=False, include_resources=False, **kwargs)
Converts a secret schema to a secret model.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
Returns:
| Type | Description |
|---|---|
SecretResponse |
The secret model. |
Source code in zenml/zen_stores/schemas/secret_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> SecretResponse:
"""Converts a secret schema to a secret model.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The secret model.
"""
metadata = None
if include_metadata:
metadata = SecretResponseMetadata(
workspace=self.workspace.to_model(),
)
# Don't load the secret values implicitly in the secret. The
# SQL secret store will call `get_secret_values` to load the
# values separately if SQL is used as the secrets store.
body = SecretResponseBody(
user=self.user.to_model() if self.user else None,
created=self.created,
updated=self.updated,
scope=self.scope,
)
return SecretResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
)
update(self, secret_update)
Update a SecretSchema from a SecretUpdate.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_update |
SecretUpdate |
The |
required |
Returns:
| Type | Description |
|---|---|
SecretSchema |
The updated |
Source code in zenml/zen_stores/schemas/secret_schemas.py
def update(
self,
secret_update: SecretUpdate,
) -> "SecretSchema":
"""Update a `SecretSchema` from a `SecretUpdate`.
Args:
secret_update: The `SecretUpdate` from which to update the schema.
Returns:
The updated `SecretSchema`.
"""
# Don't update the secret values implicitly in the secret. The
# SQL secret store will call `set_secret_values` to update the
# values separately if SQL is used as the secrets store.
for field, value in secret_update.dict(
exclude_unset=True, exclude={"workspace", "user", "values"}
).items():
setattr(self, field, value)
self.updated = datetime.utcnow()
return self
service_connector_schemas
SQL Model Implementations for Service Connectors.
ServiceConnectorSchema (NamedSchema)
pydantic-model
SQL Model for service connectors.
Source code in zenml/zen_stores/schemas/service_connector_schemas.py
class ServiceConnectorSchema(NamedSchema, table=True):
"""SQL Model for service connectors."""
__tablename__ = "service_connector"
connector_type: str = Field(sa_column=Column(TEXT))
description: str
auth_method: str = Field(sa_column=Column(TEXT))
resource_types: bytes
resource_id: Optional[str] = Field(sa_column=Column(TEXT, nullable=True))
supports_instances: bool
configuration: Optional[bytes]
secret_id: Optional[UUID]
expires_at: Optional[datetime]
expires_skew_tolerance: Optional[int]
expiration_seconds: Optional[int]
labels: Optional[bytes]
workspace_id: UUID = build_foreign_key_field(
source=__tablename__,
target=WorkspaceSchema.__tablename__,
source_column="workspace_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
workspace: "WorkspaceSchema" = Relationship(
back_populates="service_connectors"
)
user_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=UserSchema.__tablename__,
source_column="user_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
user: Optional["UserSchema"] = Relationship(
back_populates="service_connectors"
)
components: List["StackComponentSchema"] = Relationship(
back_populates="connector",
)
@property
def resource_types_list(self) -> List[str]:
"""Returns the resource types as a list.
Returns:
The resource types as a list.
"""
resource_types = json.loads(
base64.b64decode(self.resource_types).decode()
)
assert isinstance(resource_types, list)
return resource_types
@property
def labels_dict(self) -> Dict[str, str]:
"""Returns the labels as a dictionary.
Returns:
The labels as a dictionary.
"""
if self.labels is None:
return {}
labels_dict = json.loads(base64.b64decode(self.labels).decode())
return cast(Dict[str, str], labels_dict)
def has_labels(self, labels: Dict[str, Optional[str]]) -> bool:
"""Checks if the connector has the given labels.
Args:
labels: The labels to check for.
Returns:
Whether the connector has the given labels.
"""
return all(
self.labels_dict.get(key, None) == value
for key, value in labels.items()
if value is not None
) and all(
key in self.labels_dict
for key, value in labels.items()
if value is None
)
@classmethod
def from_request(
cls,
connector_request: ServiceConnectorRequest,
secret_id: Optional[UUID] = None,
) -> "ServiceConnectorSchema":
"""Create a `ServiceConnectorSchema` from a `ServiceConnectorRequest`.
Args:
connector_request: The `ServiceConnectorRequest` from which to
create the schema.
secret_id: The ID of the secret to use for this connector.
Returns:
The created `ServiceConnectorSchema`.
"""
assert connector_request.user is not None, "User must be set."
return cls(
workspace_id=connector_request.workspace,
user_id=connector_request.user,
name=connector_request.name,
description=connector_request.description,
connector_type=connector_request.type,
auth_method=connector_request.auth_method,
resource_types=base64.b64encode(
json.dumps(connector_request.resource_types).encode("utf-8")
),
resource_id=connector_request.resource_id,
supports_instances=connector_request.supports_instances,
configuration=base64.b64encode(
json.dumps(connector_request.configuration).encode("utf-8")
)
if connector_request.configuration
else None,
secret_id=secret_id,
expires_at=connector_request.expires_at,
expires_skew_tolerance=connector_request.expires_skew_tolerance,
expiration_seconds=connector_request.expiration_seconds,
labels=base64.b64encode(
json.dumps(connector_request.labels).encode("utf-8")
)
if connector_request.labels
else None,
)
def update(
self,
connector_update: ServiceConnectorUpdate,
secret_id: Optional[UUID] = None,
) -> "ServiceConnectorSchema":
"""Updates a `ServiceConnectorSchema` from a `ServiceConnectorUpdate`.
Args:
connector_update: The `ServiceConnectorUpdate` to update from.
secret_id: The ID of the secret to use for this connector.
Returns:
The updated `ServiceConnectorSchema`.
"""
for field, value in connector_update.dict(
exclude_unset=False,
exclude={"workspace", "user", "secrets"},
).items():
if value is None:
if field == "resource_id":
# The resource ID field in the update is special: if set
# to None in the update, it triggers the existing resource
# ID to be cleared.
self.resource_id = None
if field == "expiration_seconds":
# The expiration_seconds field in the update is special:
# if set to None in the update, it triggers the existing
# expiration_seconds to be cleared.
self.expiration_seconds = None
continue
if field == "configuration":
self.configuration = (
base64.b64encode(
json.dumps(connector_update.configuration).encode(
"utf-8"
)
)
if connector_update.configuration
else None
)
elif field == "resource_types":
self.resource_types = base64.b64encode(
json.dumps(connector_update.resource_types).encode("utf-8")
)
elif field == "labels":
self.labels = (
base64.b64encode(
json.dumps(connector_update.labels).encode("utf-8")
)
if connector_update.labels
else None
)
else:
setattr(self, field, value)
self.secret_id = secret_id
self.updated = datetime.utcnow()
return self
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> "ServiceConnectorResponse":
"""Creates a `ServiceConnector` from a `ServiceConnectorSchema`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
A `ServiceConnectorModel`
"""
body = ServiceConnectorResponseBody(
user=self.user.to_model() if self.user else None,
created=self.created,
updated=self.updated,
description=self.description,
connector_type=self.connector_type,
auth_method=self.auth_method,
resource_types=self.resource_types_list,
resource_id=self.resource_id,
supports_instances=self.supports_instances,
expires_at=self.expires_at,
expires_skew_tolerance=self.expires_skew_tolerance,
)
metadata = None
if include_metadata:
metadata = ServiceConnectorResponseMetadata(
workspace=self.workspace.to_model(),
configuration=json.loads(
base64.b64decode(self.configuration).decode()
)
if self.configuration
else {},
secret_id=self.secret_id,
expiration_seconds=self.expiration_seconds,
labels=self.labels_dict,
)
return ServiceConnectorResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
)
labels_dict: Dict[str, str]
property
readonly
Returns the labels as a dictionary.
Returns:
| Type | Description |
|---|---|
Dict[str, str] |
The labels as a dictionary. |
resource_types_list: List[str]
property
readonly
Returns the resource types as a list.
Returns:
| Type | Description |
|---|---|
List[str] |
The resource types as a list. |
from_request(connector_request, secret_id=None)
classmethod
Create a ServiceConnectorSchema from a ServiceConnectorRequest.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
connector_request |
ServiceConnectorRequest |
The |
required |
secret_id |
Optional[uuid.UUID] |
The ID of the secret to use for this connector. |
None |
Returns:
| Type | Description |
|---|---|
ServiceConnectorSchema |
The created |
Source code in zenml/zen_stores/schemas/service_connector_schemas.py
@classmethod
def from_request(
cls,
connector_request: ServiceConnectorRequest,
secret_id: Optional[UUID] = None,
) -> "ServiceConnectorSchema":
"""Create a `ServiceConnectorSchema` from a `ServiceConnectorRequest`.
Args:
connector_request: The `ServiceConnectorRequest` from which to
create the schema.
secret_id: The ID of the secret to use for this connector.
Returns:
The created `ServiceConnectorSchema`.
"""
assert connector_request.user is not None, "User must be set."
return cls(
workspace_id=connector_request.workspace,
user_id=connector_request.user,
name=connector_request.name,
description=connector_request.description,
connector_type=connector_request.type,
auth_method=connector_request.auth_method,
resource_types=base64.b64encode(
json.dumps(connector_request.resource_types).encode("utf-8")
),
resource_id=connector_request.resource_id,
supports_instances=connector_request.supports_instances,
configuration=base64.b64encode(
json.dumps(connector_request.configuration).encode("utf-8")
)
if connector_request.configuration
else None,
secret_id=secret_id,
expires_at=connector_request.expires_at,
expires_skew_tolerance=connector_request.expires_skew_tolerance,
expiration_seconds=connector_request.expiration_seconds,
labels=base64.b64encode(
json.dumps(connector_request.labels).encode("utf-8")
)
if connector_request.labels
else None,
)
has_labels(self, labels)
Checks if the connector has the given labels.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
labels |
Dict[str, Optional[str]] |
The labels to check for. |
required |
Returns:
| Type | Description |
|---|---|
bool |
Whether the connector has the given labels. |
Source code in zenml/zen_stores/schemas/service_connector_schemas.py
def has_labels(self, labels: Dict[str, Optional[str]]) -> bool:
"""Checks if the connector has the given labels.
Args:
labels: The labels to check for.
Returns:
Whether the connector has the given labels.
"""
return all(
self.labels_dict.get(key, None) == value
for key, value in labels.items()
if value is not None
) and all(
key in self.labels_dict
for key, value in labels.items()
if value is None
)
to_model(self, include_metadata=False, include_resources=False, **kwargs)
Creates a ServiceConnector from a ServiceConnectorSchema.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
Returns:
| Type | Description |
|---|---|
ServiceConnectorResponse |
A |
Source code in zenml/zen_stores/schemas/service_connector_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> "ServiceConnectorResponse":
"""Creates a `ServiceConnector` from a `ServiceConnectorSchema`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
A `ServiceConnectorModel`
"""
body = ServiceConnectorResponseBody(
user=self.user.to_model() if self.user else None,
created=self.created,
updated=self.updated,
description=self.description,
connector_type=self.connector_type,
auth_method=self.auth_method,
resource_types=self.resource_types_list,
resource_id=self.resource_id,
supports_instances=self.supports_instances,
expires_at=self.expires_at,
expires_skew_tolerance=self.expires_skew_tolerance,
)
metadata = None
if include_metadata:
metadata = ServiceConnectorResponseMetadata(
workspace=self.workspace.to_model(),
configuration=json.loads(
base64.b64decode(self.configuration).decode()
)
if self.configuration
else {},
secret_id=self.secret_id,
expiration_seconds=self.expiration_seconds,
labels=self.labels_dict,
)
return ServiceConnectorResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
)
update(self, connector_update, secret_id=None)
Updates a ServiceConnectorSchema from a ServiceConnectorUpdate.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
connector_update |
ServiceConnectorUpdate |
The |
required |
secret_id |
Optional[uuid.UUID] |
The ID of the secret to use for this connector. |
None |
Returns:
| Type | Description |
|---|---|
ServiceConnectorSchema |
The updated |
Source code in zenml/zen_stores/schemas/service_connector_schemas.py
def update(
self,
connector_update: ServiceConnectorUpdate,
secret_id: Optional[UUID] = None,
) -> "ServiceConnectorSchema":
"""Updates a `ServiceConnectorSchema` from a `ServiceConnectorUpdate`.
Args:
connector_update: The `ServiceConnectorUpdate` to update from.
secret_id: The ID of the secret to use for this connector.
Returns:
The updated `ServiceConnectorSchema`.
"""
for field, value in connector_update.dict(
exclude_unset=False,
exclude={"workspace", "user", "secrets"},
).items():
if value is None:
if field == "resource_id":
# The resource ID field in the update is special: if set
# to None in the update, it triggers the existing resource
# ID to be cleared.
self.resource_id = None
if field == "expiration_seconds":
# The expiration_seconds field in the update is special:
# if set to None in the update, it triggers the existing
# expiration_seconds to be cleared.
self.expiration_seconds = None
continue
if field == "configuration":
self.configuration = (
base64.b64encode(
json.dumps(connector_update.configuration).encode(
"utf-8"
)
)
if connector_update.configuration
else None
)
elif field == "resource_types":
self.resource_types = base64.b64encode(
json.dumps(connector_update.resource_types).encode("utf-8")
)
elif field == "labels":
self.labels = (
base64.b64encode(
json.dumps(connector_update.labels).encode("utf-8")
)
if connector_update.labels
else None
)
else:
setattr(self, field, value)
self.secret_id = secret_id
self.updated = datetime.utcnow()
return self
stack_schemas
SQL Model Implementations for Stacks.
StackCompositionSchema (SQLModel)
pydantic-model
SQL Model for stack definitions.
Join table between Stacks and StackComponents.
Source code in zenml/zen_stores/schemas/stack_schemas.py
class StackCompositionSchema(SQLModel, table=True):
"""SQL Model for stack definitions.
Join table between Stacks and StackComponents.
"""
__tablename__ = "stack_composition"
stack_id: UUID = build_foreign_key_field(
source=__tablename__,
target="stack",
source_column="stack_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
primary_key=True,
)
component_id: UUID = build_foreign_key_field(
source=__tablename__,
target="stack_component",
source_column="component_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
primary_key=True,
)
StackSchema (NamedSchema)
pydantic-model
SQL Model for stacks.
Source code in zenml/zen_stores/schemas/stack_schemas.py
class StackSchema(NamedSchema, table=True):
"""SQL Model for stacks."""
__tablename__ = "stack"
stack_spec_path: Optional[str]
workspace_id: UUID = build_foreign_key_field(
source=__tablename__,
target=WorkspaceSchema.__tablename__,
source_column="workspace_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
workspace: "WorkspaceSchema" = Relationship(back_populates="stacks")
user_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=UserSchema.__tablename__,
source_column="user_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
user: Optional["UserSchema"] = Relationship(back_populates="stacks")
components: List["StackComponentSchema"] = Relationship(
back_populates="stacks",
link_model=StackCompositionSchema,
)
builds: List["PipelineBuildSchema"] = Relationship(back_populates="stack")
deployments: List["PipelineDeploymentSchema"] = Relationship(
back_populates="stack",
)
def update(
self,
stack_update: "StackUpdate",
components: List["StackComponentSchema"],
) -> "StackSchema":
"""Updates a stack schema with a stack update model.
Args:
stack_update: `StackUpdate` to update the stack with.
components: List of `StackComponentSchema` to update the stack with.
Returns:
The updated StackSchema.
"""
for field, value in stack_update.dict(
exclude_unset=True, exclude={"workspace", "user"}
).items():
if field == "components":
self.components = components
else:
setattr(self, field, value)
self.updated = datetime.utcnow()
return self
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> "StackResponse":
"""Converts the schema to a model.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The converted model.
"""
body = StackResponseBody(
user=self.user.to_model() if self.user else None,
created=self.created,
updated=self.updated,
)
metadata = None
if include_metadata:
metadata = StackResponseMetadata(
workspace=self.workspace.to_model(),
components={c.type: [c.to_model()] for c in self.components},
stack_spec_path=self.stack_spec_path,
)
return StackResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
)
to_model(self, include_metadata=False, include_resources=False, **kwargs)
Converts the schema to a model.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
Returns:
| Type | Description |
|---|---|
StackResponse |
The converted model. |
Source code in zenml/zen_stores/schemas/stack_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> "StackResponse":
"""Converts the schema to a model.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The converted model.
"""
body = StackResponseBody(
user=self.user.to_model() if self.user else None,
created=self.created,
updated=self.updated,
)
metadata = None
if include_metadata:
metadata = StackResponseMetadata(
workspace=self.workspace.to_model(),
components={c.type: [c.to_model()] for c in self.components},
stack_spec_path=self.stack_spec_path,
)
return StackResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
)
update(self, stack_update, components)
Updates a stack schema with a stack update model.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
stack_update |
StackUpdate |
|
required |
components |
List[StackComponentSchema] |
List of |
required |
Returns:
| Type | Description |
|---|---|
StackSchema |
The updated StackSchema. |
Source code in zenml/zen_stores/schemas/stack_schemas.py
def update(
self,
stack_update: "StackUpdate",
components: List["StackComponentSchema"],
) -> "StackSchema":
"""Updates a stack schema with a stack update model.
Args:
stack_update: `StackUpdate` to update the stack with.
components: List of `StackComponentSchema` to update the stack with.
Returns:
The updated StackSchema.
"""
for field, value in stack_update.dict(
exclude_unset=True, exclude={"workspace", "user"}
).items():
if field == "components":
self.components = components
else:
setattr(self, field, value)
self.updated = datetime.utcnow()
return self
step_run_schemas
SQLModel implementation of step run tables.
StepRunInputArtifactSchema (SQLModel)
pydantic-model
SQL Model that defines which artifacts are inputs to which step.
Source code in zenml/zen_stores/schemas/step_run_schemas.py
class StepRunInputArtifactSchema(SQLModel, table=True):
"""SQL Model that defines which artifacts are inputs to which step."""
__tablename__ = "step_run_input_artifact"
# Fields
name: str = Field(nullable=False, primary_key=True)
type: StepRunInputArtifactType
# Foreign keys
step_id: UUID = build_foreign_key_field(
source=__tablename__,
target=StepRunSchema.__tablename__,
source_column="step_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
primary_key=True,
)
# Note: We keep the name artifact_id instead of artifact_version_id here to
# avoid having to drop and recreate the primary key constraint.
artifact_id: UUID = build_foreign_key_field(
source=__tablename__,
target="artifact_version",
source_column="artifact_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
primary_key=True,
)
# Relationships
step_run: "StepRunSchema" = Relationship(back_populates="input_artifacts")
artifact_version: "ArtifactVersionSchema" = Relationship()
StepRunOutputArtifactSchema (SQLModel)
pydantic-model
SQL Model that defines which artifacts are outputs of which step.
Source code in zenml/zen_stores/schemas/step_run_schemas.py
class StepRunOutputArtifactSchema(SQLModel, table=True):
"""SQL Model that defines which artifacts are outputs of which step."""
__tablename__ = "step_run_output_artifact"
# Fields
name: str
type: StepRunOutputArtifactType
# Foreign keys
step_id: UUID = build_foreign_key_field(
source=__tablename__,
target=StepRunSchema.__tablename__,
source_column="step_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
primary_key=True,
)
# Note: we keep the name artifact_id instead of artifact_version_id here to
# avoid having to drop and recreate the primary key constraint.
artifact_id: UUID = build_foreign_key_field(
source=__tablename__,
target="artifact_version",
source_column="artifact_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
primary_key=True,
)
# Relationship
step_run: "StepRunSchema" = Relationship(back_populates="output_artifacts")
artifact_version: "ArtifactVersionSchema" = Relationship(
back_populates="output_of_step_runs"
)
StepRunParentsSchema (SQLModel)
pydantic-model
SQL Model that defines the order of steps.
Source code in zenml/zen_stores/schemas/step_run_schemas.py
class StepRunParentsSchema(SQLModel, table=True):
"""SQL Model that defines the order of steps."""
__tablename__ = "step_run_parents"
# Foreign Keys
parent_id: UUID = build_foreign_key_field(
source=__tablename__,
target=StepRunSchema.__tablename__,
source_column="parent_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
primary_key=True,
)
child_id: UUID = build_foreign_key_field(
source=__tablename__,
target=StepRunSchema.__tablename__,
source_column="child_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
primary_key=True,
)
StepRunSchema (NamedSchema)
pydantic-model
SQL Model for steps of pipeline runs.
Source code in zenml/zen_stores/schemas/step_run_schemas.py
class StepRunSchema(NamedSchema, table=True):
"""SQL Model for steps of pipeline runs."""
__tablename__ = "step_run"
# Fields
start_time: Optional[datetime] = Field(nullable=True)
end_time: Optional[datetime] = Field(nullable=True)
status: ExecutionStatus = Field(nullable=False)
docstring: Optional[str] = Field(sa_column=Column(TEXT, nullable=True))
cache_key: Optional[str] = Field(nullable=True)
source_code: Optional[str] = Field(sa_column=Column(TEXT, nullable=True))
code_hash: Optional[str] = Field(nullable=True)
step_configuration: str = Field(
sa_column=Column(
String(length=MEDIUMTEXT_MAX_LENGTH).with_variant(
MEDIUMTEXT, "mysql"
),
nullable=True,
)
)
# Foreign keys
original_step_run_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=__tablename__,
source_column="original_step_run_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
deployment_id: UUID = build_foreign_key_field(
source=__tablename__,
target=PipelineDeploymentSchema.__tablename__,
source_column="deployment_id",
target_column="id",
ondelete="CASCADE",
nullable=True,
)
pipeline_run_id: UUID = build_foreign_key_field(
source=__tablename__,
target=PipelineRunSchema.__tablename__,
source_column="pipeline_run_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
user_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=UserSchema.__tablename__,
source_column="user_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
workspace_id: UUID = build_foreign_key_field(
source=__tablename__,
target=WorkspaceSchema.__tablename__,
source_column="workspace_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
# Relationships
workspace: "WorkspaceSchema" = Relationship(back_populates="step_runs")
user: Optional["UserSchema"] = Relationship(back_populates="step_runs")
deployment: Optional["PipelineDeploymentSchema"] = Relationship(
back_populates="step_runs"
)
run_metadata: List["RunMetadataSchema"] = Relationship(
back_populates="step_run",
sa_relationship_kwargs=dict(
primaryjoin=f"and_(RunMetadataSchema.resource_type=='{MetadataResourceTypes.STEP_RUN.value}', foreign(RunMetadataSchema.resource_id)==StepRunSchema.id)",
cascade="delete",
overlaps="run_metadata",
),
)
input_artifacts: List["StepRunInputArtifactSchema"] = Relationship(
sa_relationship_kwargs={"cascade": "delete"}
)
output_artifacts: List["StepRunOutputArtifactSchema"] = Relationship(
sa_relationship_kwargs={"cascade": "delete"}
)
logs: Optional["LogsSchema"] = Relationship(
back_populates="step_run",
sa_relationship_kwargs={"cascade": "delete", "uselist": False},
)
parents: List["StepRunParentsSchema"] = Relationship(
sa_relationship_kwargs={
"cascade": "delete",
"primaryjoin": "StepRunParentsSchema.child_id == StepRunSchema.id",
},
)
@classmethod
def from_request(cls, request: StepRunRequest) -> "StepRunSchema":
"""Create a step run schema from a step run request model.
Args:
request: The step run request model.
Returns:
The step run schema.
"""
return cls(
name=request.name,
workspace_id=request.workspace,
user_id=request.user,
start_time=request.start_time,
end_time=request.end_time,
status=request.status,
original_step_run_id=request.original_step_run_id,
pipeline_run_id=request.pipeline_run_id,
deployment_id=request.deployment,
docstring=request.docstring,
cache_key=request.cache_key,
code_hash=request.code_hash,
source_code=request.source_code,
)
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> StepRunResponse:
"""Convert a `StepRunSchema` to a `StepRunResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created StepRunResponse.
Raises:
RuntimeError: If the step run schema does not have a deployment_id
or a step_configuration.
"""
run_metadata = {
metadata_schema.key: metadata_schema.to_model()
for metadata_schema in self.run_metadata
}
input_artifacts = {
artifact.name: artifact.artifact_version.to_model()
for artifact in self.input_artifacts
}
output_artifacts = {
artifact.name: artifact.artifact_version.to_model()
for artifact in self.output_artifacts
}
if self.deployment is not None:
full_step_config = Step.parse_obj(
json.loads(self.deployment.step_configurations)[self.name]
)
elif self.step_configuration is not None:
full_step_config = Step.parse_raw(self.step_configuration)
else:
raise RuntimeError(
"Step run model creation has failed. Each step run entry "
"should either have a deployment_id or step_configuration."
)
body = StepRunResponseBody(
user=self.user.to_model() if self.user else None,
status=self.status,
inputs=input_artifacts,
outputs=output_artifacts,
created=self.created,
updated=self.updated,
)
metadata = None
if include_metadata:
metadata = StepRunResponseMetadata(
workspace=self.workspace.to_model(),
config=full_step_config.config,
spec=full_step_config.spec,
cache_key=self.cache_key,
code_hash=self.code_hash,
docstring=self.docstring,
source_code=self.source_code,
start_time=self.start_time,
end_time=self.end_time,
logs=self.logs.to_model() if self.logs else None,
deployment_id=self.deployment_id,
pipeline_run_id=self.pipeline_run_id,
original_step_run_id=self.original_step_run_id,
parent_step_ids=[p.parent_id for p in self.parents],
run_metadata=run_metadata,
)
return StepRunResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
)
def update(self, step_update: "StepRunUpdate") -> "StepRunSchema":
"""Update a step run schema with a step run update model.
Args:
step_update: The step run update model.
Returns:
The updated step run schema.
"""
for key, value in step_update.dict(
exclude_unset=True, exclude_none=True
).items():
if key == "status":
self.status = value
if key == "end_time":
self.end_time = value
self.updated = datetime.utcnow()
return self
from_request(request)
classmethod
Create a step run schema from a step run request model.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
request |
StepRunRequest |
The step run request model. |
required |
Returns:
| Type | Description |
|---|---|
StepRunSchema |
The step run schema. |
Source code in zenml/zen_stores/schemas/step_run_schemas.py
@classmethod
def from_request(cls, request: StepRunRequest) -> "StepRunSchema":
"""Create a step run schema from a step run request model.
Args:
request: The step run request model.
Returns:
The step run schema.
"""
return cls(
name=request.name,
workspace_id=request.workspace,
user_id=request.user,
start_time=request.start_time,
end_time=request.end_time,
status=request.status,
original_step_run_id=request.original_step_run_id,
pipeline_run_id=request.pipeline_run_id,
deployment_id=request.deployment,
docstring=request.docstring,
cache_key=request.cache_key,
code_hash=request.code_hash,
source_code=request.source_code,
)
to_model(self, include_metadata=False, include_resources=False, **kwargs)
Convert a StepRunSchema to a StepRunResponse.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
Returns:
| Type | Description |
|---|---|
StepRunResponse |
The created StepRunResponse. |
Exceptions:
| Type | Description |
|---|---|
RuntimeError |
If the step run schema does not have a deployment_id or a step_configuration. |
Source code in zenml/zen_stores/schemas/step_run_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> StepRunResponse:
"""Convert a `StepRunSchema` to a `StepRunResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created StepRunResponse.
Raises:
RuntimeError: If the step run schema does not have a deployment_id
or a step_configuration.
"""
run_metadata = {
metadata_schema.key: metadata_schema.to_model()
for metadata_schema in self.run_metadata
}
input_artifacts = {
artifact.name: artifact.artifact_version.to_model()
for artifact in self.input_artifacts
}
output_artifacts = {
artifact.name: artifact.artifact_version.to_model()
for artifact in self.output_artifacts
}
if self.deployment is not None:
full_step_config = Step.parse_obj(
json.loads(self.deployment.step_configurations)[self.name]
)
elif self.step_configuration is not None:
full_step_config = Step.parse_raw(self.step_configuration)
else:
raise RuntimeError(
"Step run model creation has failed. Each step run entry "
"should either have a deployment_id or step_configuration."
)
body = StepRunResponseBody(
user=self.user.to_model() if self.user else None,
status=self.status,
inputs=input_artifacts,
outputs=output_artifacts,
created=self.created,
updated=self.updated,
)
metadata = None
if include_metadata:
metadata = StepRunResponseMetadata(
workspace=self.workspace.to_model(),
config=full_step_config.config,
spec=full_step_config.spec,
cache_key=self.cache_key,
code_hash=self.code_hash,
docstring=self.docstring,
source_code=self.source_code,
start_time=self.start_time,
end_time=self.end_time,
logs=self.logs.to_model() if self.logs else None,
deployment_id=self.deployment_id,
pipeline_run_id=self.pipeline_run_id,
original_step_run_id=self.original_step_run_id,
parent_step_ids=[p.parent_id for p in self.parents],
run_metadata=run_metadata,
)
return StepRunResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
)
update(self, step_update)
Update a step run schema with a step run update model.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
step_update |
StepRunUpdate |
The step run update model. |
required |
Returns:
| Type | Description |
|---|---|
StepRunSchema |
The updated step run schema. |
Source code in zenml/zen_stores/schemas/step_run_schemas.py
def update(self, step_update: "StepRunUpdate") -> "StepRunSchema":
"""Update a step run schema with a step run update model.
Args:
step_update: The step run update model.
Returns:
The updated step run schema.
"""
for key, value in step_update.dict(
exclude_unset=True, exclude_none=True
).items():
if key == "status":
self.status = value
if key == "end_time":
self.end_time = value
self.updated = datetime.utcnow()
return self
tag_schemas
SQLModel implementation of tag tables.
TagResourceSchema (BaseSchema)
pydantic-model
SQL Model for tag resource relationship.
Source code in zenml/zen_stores/schemas/tag_schemas.py
class TagResourceSchema(BaseSchema, table=True):
"""SQL Model for tag resource relationship."""
__tablename__ = "tag_resource"
tag_id: UUID = build_foreign_key_field(
source=__tablename__,
target=TagSchema.__tablename__,
source_column="tag_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
tag: "TagSchema" = Relationship(back_populates="links")
resource_id: UUID
resource_type: str = Field(sa_column=Column(VARCHAR(255), nullable=False))
artifact: List["ArtifactSchema"] = Relationship(
back_populates="tags",
sa_relationship_kwargs=dict(
primaryjoin=f"and_(TagResourceSchema.resource_type=='{TaggableResourceTypes.ARTIFACT.value}', foreign(TagResourceSchema.resource_id)==ArtifactSchema.id)",
overlaps="tags,model,artifact_version,model_version",
),
)
artifact_version: List["ArtifactVersionSchema"] = Relationship(
back_populates="tags",
sa_relationship_kwargs=dict(
primaryjoin=f"and_(TagResourceSchema.resource_type=='{TaggableResourceTypes.ARTIFACT_VERSION.value}', foreign(TagResourceSchema.resource_id)==ArtifactVersionSchema.id)",
overlaps="tags,model,artifact,model_version",
),
)
model: List["ModelSchema"] = Relationship(
back_populates="tags",
sa_relationship_kwargs=dict(
primaryjoin=f"and_(TagResourceSchema.resource_type=='{TaggableResourceTypes.MODEL.value}', foreign(TagResourceSchema.resource_id)==ModelSchema.id)",
overlaps="tags,artifact,artifact_version,model_version",
),
)
model_version: List["ModelVersionSchema"] = Relationship(
back_populates="tags",
sa_relationship_kwargs=dict(
primaryjoin=f"and_(TagResourceSchema.resource_type=='{TaggableResourceTypes.MODEL_VERSION.value}', foreign(TagResourceSchema.resource_id)==ModelVersionSchema.id)",
overlaps="tags,model,artifact,artifact_version",
),
)
@classmethod
def from_request(cls, request: TagResourceRequest) -> "TagResourceSchema":
"""Convert an `TagResourceRequest` to an `TagResourceSchema`.
Args:
request: The request model version to convert.
Returns:
The converted schema.
"""
return cls(
tag_id=request.tag_id,
resource_id=request.resource_id,
resource_type=request.resource_type.value,
)
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> TagResourceResponse:
"""Convert an `TagResourceSchema` to an `TagResourceResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created `TagResourceResponse`.
"""
return TagResourceResponse(
id=self.id,
body=TagResourceResponseBody(
tag_id=self.tag_id,
resource_id=self.resource_id,
created=self.created,
updated=self.updated,
resource_type=TaggableResourceTypes(self.resource_type),
),
)
from_request(request)
classmethod
Convert an TagResourceRequest to an TagResourceSchema.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
request |
TagResourceRequest |
The request model version to convert. |
required |
Returns:
| Type | Description |
|---|---|
TagResourceSchema |
The converted schema. |
Source code in zenml/zen_stores/schemas/tag_schemas.py
@classmethod
def from_request(cls, request: TagResourceRequest) -> "TagResourceSchema":
"""Convert an `TagResourceRequest` to an `TagResourceSchema`.
Args:
request: The request model version to convert.
Returns:
The converted schema.
"""
return cls(
tag_id=request.tag_id,
resource_id=request.resource_id,
resource_type=request.resource_type.value,
)
to_model(self, include_metadata=False, include_resources=False, **kwargs)
Convert an TagResourceSchema to an TagResourceResponse.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
Returns:
| Type | Description |
|---|---|
TagResourceResponse |
The created |
Source code in zenml/zen_stores/schemas/tag_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> TagResourceResponse:
"""Convert an `TagResourceSchema` to an `TagResourceResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created `TagResourceResponse`.
"""
return TagResourceResponse(
id=self.id,
body=TagResourceResponseBody(
tag_id=self.tag_id,
resource_id=self.resource_id,
created=self.created,
updated=self.updated,
resource_type=TaggableResourceTypes(self.resource_type),
),
)
TagSchema (NamedSchema)
pydantic-model
SQL Model for tag.
Source code in zenml/zen_stores/schemas/tag_schemas.py
class TagSchema(NamedSchema, table=True):
"""SQL Model for tag."""
__tablename__ = "tag"
color: str = Field(sa_column=Column(VARCHAR(255), nullable=False))
links: List["TagResourceSchema"] = Relationship(
back_populates="tag",
sa_relationship_kwargs={"cascade": "delete"},
)
@classmethod
def from_request(cls, request: TagRequest) -> "TagSchema":
"""Convert an `TagRequest` to an `TagSchema`.
Args:
request: The request model to convert.
Returns:
The converted schema.
"""
return cls(
name=request.name,
color=request.color.value,
)
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> TagResponse:
"""Convert an `TagSchema` to an `TagResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created `TagResponse`.
"""
return TagResponse(
id=self.id,
name=self.name,
body=TagResponseBody(
created=self.created,
updated=self.updated,
color=ColorVariants(self.color),
tagged_count=len(self.links),
),
)
def update(self, update: TagUpdate) -> "TagSchema":
"""Updates a `TagSchema` from a `TagUpdate`.
Args:
update: The `TagUpdate` to update from.
Returns:
The updated `TagSchema`.
"""
for field, value in update.dict(exclude_unset=True).items():
setattr(self, field, value)
self.updated = datetime.utcnow()
return self
from_request(request)
classmethod
Convert an TagRequest to an TagSchema.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
request |
TagRequest |
The request model to convert. |
required |
Returns:
| Type | Description |
|---|---|
TagSchema |
The converted schema. |
Source code in zenml/zen_stores/schemas/tag_schemas.py
@classmethod
def from_request(cls, request: TagRequest) -> "TagSchema":
"""Convert an `TagRequest` to an `TagSchema`.
Args:
request: The request model to convert.
Returns:
The converted schema.
"""
return cls(
name=request.name,
color=request.color.value,
)
to_model(self, include_metadata=False, include_resources=False, **kwargs)
Convert an TagSchema to an TagResponse.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
Returns:
| Type | Description |
|---|---|
TagResponse |
The created |
Source code in zenml/zen_stores/schemas/tag_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> TagResponse:
"""Convert an `TagSchema` to an `TagResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The created `TagResponse`.
"""
return TagResponse(
id=self.id,
name=self.name,
body=TagResponseBody(
created=self.created,
updated=self.updated,
color=ColorVariants(self.color),
tagged_count=len(self.links),
),
)
update(self, update)
Updates a TagSchema from a TagUpdate.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
update |
TagUpdate |
The |
required |
Returns:
| Type | Description |
|---|---|
TagSchema |
The updated |
Source code in zenml/zen_stores/schemas/tag_schemas.py
def update(self, update: TagUpdate) -> "TagSchema":
"""Updates a `TagSchema` from a `TagUpdate`.
Args:
update: The `TagUpdate` to update from.
Returns:
The updated `TagSchema`.
"""
for field, value in update.dict(exclude_unset=True).items():
setattr(self, field, value)
self.updated = datetime.utcnow()
return self
trigger_schemas
SQL Model Implementations for Triggers.
TriggerExecutionSchema (BaseSchema)
pydantic-model
SQL Model for trigger executions.
Source code in zenml/zen_stores/schemas/trigger_schemas.py
class TriggerExecutionSchema(BaseSchema, table=True):
"""SQL Model for trigger executions."""
__tablename__ = "trigger_execution"
trigger_id: UUID = build_foreign_key_field(
source=__tablename__,
target=TriggerSchema.__tablename__,
source_column="trigger_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
trigger: TriggerSchema = Relationship(back_populates="executions")
event_metadata: Optional[bytes] = None
@classmethod
def from_request(
cls, request: "TriggerExecutionRequest"
) -> "TriggerExecutionSchema":
"""Convert a `TriggerExecutionRequest` to a `TriggerExecutionSchema`.
Args:
request: The request model to convert.
Returns:
The converted schema.
"""
return cls(
trigger_id=request.trigger,
event_metadata=base64.b64encode(
json.dumps(request.event_metadata).encode("utf-8")
),
)
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> "TriggerExecutionResponse":
"""Converts the schema to a model.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The converted model.
"""
body = TriggerExecutionResponseBody(
created=self.created,
updated=self.updated,
)
metadata = None
if include_metadata:
metadata = TriggerExecutionResponseMetadata(
event_metadata=json.loads(
base64.b64decode(self.event_metadata).decode()
)
if self.event_metadata
else {},
)
resources = None
if include_resources:
resources = TriggerExecutionResponseResources(
trigger=self.trigger.to_model(),
)
return TriggerExecutionResponse(
id=self.id, body=body, metadata=metadata, resources=resources
)
from_request(request)
classmethod
Convert a TriggerExecutionRequest to a TriggerExecutionSchema.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
request |
TriggerExecutionRequest |
The request model to convert. |
required |
Returns:
| Type | Description |
|---|---|
TriggerExecutionSchema |
The converted schema. |
Source code in zenml/zen_stores/schemas/trigger_schemas.py
@classmethod
def from_request(
cls, request: "TriggerExecutionRequest"
) -> "TriggerExecutionSchema":
"""Convert a `TriggerExecutionRequest` to a `TriggerExecutionSchema`.
Args:
request: The request model to convert.
Returns:
The converted schema.
"""
return cls(
trigger_id=request.trigger,
event_metadata=base64.b64encode(
json.dumps(request.event_metadata).encode("utf-8")
),
)
to_model(self, include_metadata=False, include_resources=False, **kwargs)
Converts the schema to a model.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
Returns:
| Type | Description |
|---|---|
TriggerExecutionResponse |
The converted model. |
Source code in zenml/zen_stores/schemas/trigger_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> "TriggerExecutionResponse":
"""Converts the schema to a model.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The converted model.
"""
body = TriggerExecutionResponseBody(
created=self.created,
updated=self.updated,
)
metadata = None
if include_metadata:
metadata = TriggerExecutionResponseMetadata(
event_metadata=json.loads(
base64.b64decode(self.event_metadata).decode()
)
if self.event_metadata
else {},
)
resources = None
if include_resources:
resources = TriggerExecutionResponseResources(
trigger=self.trigger.to_model(),
)
return TriggerExecutionResponse(
id=self.id, body=body, metadata=metadata, resources=resources
)
TriggerSchema (NamedSchema)
pydantic-model
SQL Model for triggers.
Source code in zenml/zen_stores/schemas/trigger_schemas.py
class TriggerSchema(NamedSchema, table=True):
"""SQL Model for triggers."""
__tablename__ = "trigger"
workspace_id: UUID = build_foreign_key_field(
source=__tablename__,
target=WorkspaceSchema.__tablename__,
source_column="workspace_id",
target_column="id",
ondelete="CASCADE",
nullable=False,
)
workspace: "WorkspaceSchema" = Relationship(back_populates="triggers")
user_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=UserSchema.__tablename__,
source_column="user_id",
target_column="id",
ondelete="SET NULL",
nullable=True,
)
user: Optional["UserSchema"] = Relationship(
back_populates="triggers",
sa_relationship_kwargs={"foreign_keys": "[TriggerSchema.user_id]"},
)
event_source_id: Optional[UUID] = build_foreign_key_field(
source=__tablename__,
target=EventSourceSchema.__tablename__,
source_column="event_source_id",
target_column="id",
ondelete="CASCADE", # TODO: this should be set null and the trigger should be deactivated
nullable=False,
)
event_source: "EventSourceSchema" = Relationship(back_populates="triggers")
executions: List["TriggerExecutionSchema"] = Relationship(
back_populates="trigger"
)
service_account_id: UUID = build_foreign_key_field(
source=__tablename__,
target=UserSchema.__tablename__,
source_column="service_account_id",
target_column="id",
ondelete="CASCADE", # TODO: this should be set null and the trigger should be deactivated
nullable=False,
)
service_account: UserSchema = Relationship(
back_populates="auth_triggers",
sa_relationship_kwargs={
"foreign_keys": "[TriggerSchema.service_account_id]"
},
)
auth_window: int
event_filter: bytes
action: bytes
action_flavor: str # <- "builtin"
action_subtype: str # <- "PipelineRun"
description: str = Field(sa_column=Column(TEXT, nullable=True))
is_active: bool = Field(nullable=False)
def update(self, trigger_update: "TriggerUpdate") -> "TriggerSchema":
"""Updates a trigger schema with a trigger update model.
Args:
trigger_update: `TriggerUpdate` to update the trigger with.
Returns:
The updated TriggerSchema.
"""
for field, value in trigger_update.dict(
exclude_unset=True,
exclude_none=True,
).items():
if field == "event_filter":
self.event_filter = base64.b64encode(
json.dumps(
trigger_update.event_filter, default=pydantic_encoder
).encode("utf-8")
)
elif field == "action":
self.action = base64.b64encode(
json.dumps(
trigger_update.action, default=pydantic_encoder
).encode("utf-8")
)
else:
setattr(self, field, value)
self.updated = datetime.utcnow()
return self
@classmethod
def from_request(cls, request: "TriggerRequest") -> "TriggerSchema":
"""Convert a `TriggerRequest` to a `TriggerSchema`.
Args:
request: The request model to convert.
Returns:
The converted schema.
Raises:
ValueError: If `auth_window` is not set.
"""
if request.auth_window is None:
raise ValueError("auth_window must be set")
return cls(
name=request.name,
workspace_id=request.workspace,
user_id=request.user,
action=base64.b64encode(
json.dumps(request.action, default=pydantic_encoder).encode(
"utf-8"
),
),
action_flavor=request.action_flavor,
action_subtype=request.action_subtype,
event_source_id=request.event_source_id,
service_account_id=request.service_account_id,
auth_window=request.auth_window,
event_filter=base64.b64encode(
json.dumps(
request.event_filter, default=pydantic_encoder
).encode("utf-8")
),
description=request.description,
is_active=True, # Makes no sense for it to be created inactive
)
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> "TriggerResponse":
"""Converts the schema to a model.
Args:
include_metadata: Flag deciding whether to include the output model(s)
metadata fields in the response.
include_resources: Flag deciding whether to include the output model(s)
metadata fields in the response.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The converted model.
"""
from zenml.models import TriggerExecutionResponse
body = TriggerResponseBody(
user=self.user.to_model() if self.user else None,
created=self.created,
updated=self.updated,
action_flavor=self.action_flavor,
action_subtype=self.action_subtype,
event_source_flavor=self.event_source.flavor,
is_active=self.is_active,
)
metadata = None
if include_metadata:
metadata = TriggerResponseMetadata(
workspace=self.workspace.to_model(),
event_filter=json.loads(
base64.b64decode(self.event_filter).decode()
),
action=json.loads(base64.b64decode(self.action).decode()),
description=self.description,
auth_window=self.auth_window,
)
resources = None
if include_resources:
executions = cast(
Page[TriggerExecutionResponse],
get_page_from_list(
items_list=self.executions,
response_model=TriggerExecutionResponse,
include_resources=include_resources,
include_metadata=include_metadata,
),
)
resources = TriggerResponseResources(
event_source=self.event_source.to_model(),
service_account=self.service_account.to_model(),
executions=executions,
)
return TriggerResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
resources=resources,
)
from_request(request)
classmethod
Convert a TriggerRequest to a TriggerSchema.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
request |
TriggerRequest |
The request model to convert. |
required |
Returns:
| Type | Description |
|---|---|
TriggerSchema |
The converted schema. |
Exceptions:
| Type | Description |
|---|---|
ValueError |
If |
Source code in zenml/zen_stores/schemas/trigger_schemas.py
@classmethod
def from_request(cls, request: "TriggerRequest") -> "TriggerSchema":
"""Convert a `TriggerRequest` to a `TriggerSchema`.
Args:
request: The request model to convert.
Returns:
The converted schema.
Raises:
ValueError: If `auth_window` is not set.
"""
if request.auth_window is None:
raise ValueError("auth_window must be set")
return cls(
name=request.name,
workspace_id=request.workspace,
user_id=request.user,
action=base64.b64encode(
json.dumps(request.action, default=pydantic_encoder).encode(
"utf-8"
),
),
action_flavor=request.action_flavor,
action_subtype=request.action_subtype,
event_source_id=request.event_source_id,
service_account_id=request.service_account_id,
auth_window=request.auth_window,
event_filter=base64.b64encode(
json.dumps(
request.event_filter, default=pydantic_encoder
).encode("utf-8")
),
description=request.description,
is_active=True, # Makes no sense for it to be created inactive
)
to_model(self, include_metadata=False, include_resources=False, **kwargs)
Converts the schema to a model.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Flag deciding whether to include the output model(s) metadata fields in the response. |
False |
include_resources |
bool |
Flag deciding whether to include the output model(s) metadata fields in the response. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
Returns:
| Type | Description |
|---|---|
TriggerResponse |
The converted model. |
Source code in zenml/zen_stores/schemas/trigger_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> "TriggerResponse":
"""Converts the schema to a model.
Args:
include_metadata: Flag deciding whether to include the output model(s)
metadata fields in the response.
include_resources: Flag deciding whether to include the output model(s)
metadata fields in the response.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The converted model.
"""
from zenml.models import TriggerExecutionResponse
body = TriggerResponseBody(
user=self.user.to_model() if self.user else None,
created=self.created,
updated=self.updated,
action_flavor=self.action_flavor,
action_subtype=self.action_subtype,
event_source_flavor=self.event_source.flavor,
is_active=self.is_active,
)
metadata = None
if include_metadata:
metadata = TriggerResponseMetadata(
workspace=self.workspace.to_model(),
event_filter=json.loads(
base64.b64decode(self.event_filter).decode()
),
action=json.loads(base64.b64decode(self.action).decode()),
description=self.description,
auth_window=self.auth_window,
)
resources = None
if include_resources:
executions = cast(
Page[TriggerExecutionResponse],
get_page_from_list(
items_list=self.executions,
response_model=TriggerExecutionResponse,
include_resources=include_resources,
include_metadata=include_metadata,
),
)
resources = TriggerResponseResources(
event_source=self.event_source.to_model(),
service_account=self.service_account.to_model(),
executions=executions,
)
return TriggerResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
resources=resources,
)
update(self, trigger_update)
Updates a trigger schema with a trigger update model.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
trigger_update |
TriggerUpdate |
|
required |
Returns:
| Type | Description |
|---|---|
TriggerSchema |
The updated TriggerSchema. |
Source code in zenml/zen_stores/schemas/trigger_schemas.py
def update(self, trigger_update: "TriggerUpdate") -> "TriggerSchema":
"""Updates a trigger schema with a trigger update model.
Args:
trigger_update: `TriggerUpdate` to update the trigger with.
Returns:
The updated TriggerSchema.
"""
for field, value in trigger_update.dict(
exclude_unset=True,
exclude_none=True,
).items():
if field == "event_filter":
self.event_filter = base64.b64encode(
json.dumps(
trigger_update.event_filter, default=pydantic_encoder
).encode("utf-8")
)
elif field == "action":
self.action = base64.b64encode(
json.dumps(
trigger_update.action, default=pydantic_encoder
).encode("utf-8")
)
else:
setattr(self, field, value)
self.updated = datetime.utcnow()
return self
user_schemas
SQLModel implementation of user tables.
UserSchema (NamedSchema)
pydantic-model
SQL Model for users.
Source code in zenml/zen_stores/schemas/user_schemas.py
class UserSchema(NamedSchema, table=True):
"""SQL Model for users."""
__tablename__ = "user"
__table_args__ = (UniqueConstraint("name", "is_service_account"),)
is_service_account: bool = Field(default=False)
full_name: str
description: Optional[str] = Field(sa_column=Column(TEXT, nullable=True))
email: Optional[str] = Field(nullable=True)
active: bool
password: Optional[str] = Field(nullable=True)
activation_token: Optional[str] = Field(nullable=True)
hub_token: Optional[str] = Field(nullable=True)
email_opted_in: Optional[bool] = Field(nullable=True)
external_user_id: Optional[UUID] = Field(nullable=True)
stacks: List["StackSchema"] = Relationship(back_populates="user")
components: List["StackComponentSchema"] = Relationship(
back_populates="user",
)
flavors: List["FlavorSchema"] = Relationship(back_populates="user")
event_sources: List["EventSourceSchema"] = Relationship(
back_populates="user"
)
pipelines: List["PipelineSchema"] = Relationship(back_populates="user")
schedules: List["ScheduleSchema"] = Relationship(
back_populates="user",
)
runs: List["PipelineRunSchema"] = Relationship(back_populates="user")
step_runs: List["StepRunSchema"] = Relationship(back_populates="user")
builds: List["PipelineBuildSchema"] = Relationship(back_populates="user")
artifact_versions: List["ArtifactVersionSchema"] = Relationship(
back_populates="user"
)
run_metadata: List["RunMetadataSchema"] = Relationship(
back_populates="user"
)
secrets: List["SecretSchema"] = Relationship(
back_populates="user",
sa_relationship_kwargs={"cascade": "delete"},
)
triggers: List["TriggerSchema"] = Relationship(
back_populates="user",
sa_relationship_kwargs={
"cascade": "delete",
"primaryjoin": "UserSchema.id==TriggerSchema.user_id",
},
)
auth_triggers: List["TriggerSchema"] = Relationship(
back_populates="service_account",
sa_relationship_kwargs={
"cascade": "delete",
"primaryjoin": "UserSchema.id==TriggerSchema.service_account_id",
},
)
deployments: List["PipelineDeploymentSchema"] = Relationship(
back_populates="user",
)
code_repositories: List["CodeRepositorySchema"] = Relationship(
back_populates="user",
)
service_connectors: List["ServiceConnectorSchema"] = Relationship(
back_populates="user",
)
models: List["ModelSchema"] = Relationship(
back_populates="user",
)
model_versions: List["ModelVersionSchema"] = Relationship(
back_populates="user",
)
model_versions_artifacts_links: List["ModelVersionArtifactSchema"] = (
Relationship(back_populates="user")
)
model_versions_pipeline_runs_links: List[
"ModelVersionPipelineRunSchema"
] = Relationship(back_populates="user")
auth_devices: List["OAuthDeviceSchema"] = Relationship(
back_populates="user",
sa_relationship_kwargs={"cascade": "delete"},
)
api_keys: List["APIKeySchema"] = Relationship(
back_populates="service_account",
sa_relationship_kwargs={"cascade": "delete"},
)
@classmethod
def from_user_request(cls, model: UserRequest) -> "UserSchema":
"""Create a `UserSchema` from a `UserRequest`.
Args:
model: The `UserRequest` from which to create the schema.
Returns:
The created `UserSchema`.
"""
return cls(
name=model.name,
full_name=model.full_name,
active=model.active,
password=model.create_hashed_password(),
activation_token=model.create_hashed_activation_token(),
external_user_id=model.external_user_id,
email_opted_in=model.email_opted_in,
email=model.email,
is_service_account=False,
)
@classmethod
def from_service_account_request(
cls, model: ServiceAccountRequest
) -> "UserSchema":
"""Create a `UserSchema` from a Service Account request.
Args:
model: The `ServiceAccountRequest` from which to create the
schema.
Returns:
The created `UserSchema`.
"""
return cls(
name=model.name,
description=model.description or "",
active=model.active,
is_service_account=True,
email_opted_in=False,
full_name="",
)
def update_user(self, user_update: UserUpdate) -> "UserSchema":
"""Update a `UserSchema` from a `UserUpdate`.
Args:
user_update: The `UserUpdate` from which to update the schema.
Returns:
The updated `UserSchema`.
"""
for field, value in user_update.dict(exclude_unset=True).items():
if field == "password":
setattr(self, field, user_update.create_hashed_password())
elif field == "activation_token":
setattr(
self, field, user_update.create_hashed_activation_token()
)
else:
setattr(self, field, value)
self.updated = datetime.utcnow()
return self
def update_service_account(
self, service_account_update: ServiceAccountUpdate
) -> "UserSchema":
"""Update a `UserSchema` from a `ServiceAccountUpdate`.
Args:
service_account_update: The `ServiceAccountUpdate` from which
to update the schema.
Returns:
The updated `UserSchema`.
"""
for field, value in service_account_update.dict(
exclude_none=True
).items():
setattr(self, field, value)
self.updated = datetime.utcnow()
return self
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
include_private: bool = False,
**kwargs: Any,
) -> UserResponse:
"""Convert a `UserSchema` to a `UserResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
include_private: Whether to include the user private information
this is to limit the amount of data one can get
about other users
Returns:
The converted `UserResponse`.
"""
metadata = None
if include_metadata:
metadata = UserResponseMetadata(
email=self.email if include_private else None,
hub_token=self.hub_token if include_private else None,
external_user_id=self.external_user_id,
)
return UserResponse(
id=self.id,
name=self.name,
body=UserResponseBody(
active=self.active,
full_name=self.full_name,
email_opted_in=self.email_opted_in,
is_service_account=self.is_service_account,
created=self.created,
updated=self.updated,
),
metadata=metadata,
)
def to_service_account_model(
self, include_metadata: bool = False, include_resources: bool = False
) -> ServiceAccountResponse:
"""Convert a `UserSchema` to a `ServiceAccountResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
Returns:
The converted `ServiceAccountResponse`.
"""
metadata = None
if include_metadata:
metadata = ServiceAccountResponseMetadata(
description=self.description or "",
)
body = ServiceAccountResponseBody(
created=self.created,
updated=self.updated,
active=self.active,
)
return ServiceAccountResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
)
from_service_account_request(model)
classmethod
Create a UserSchema from a Service Account request.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model |
ServiceAccountRequest |
The |
required |
Returns:
| Type | Description |
|---|---|
UserSchema |
The created |
Source code in zenml/zen_stores/schemas/user_schemas.py
@classmethod
def from_service_account_request(
cls, model: ServiceAccountRequest
) -> "UserSchema":
"""Create a `UserSchema` from a Service Account request.
Args:
model: The `ServiceAccountRequest` from which to create the
schema.
Returns:
The created `UserSchema`.
"""
return cls(
name=model.name,
description=model.description or "",
active=model.active,
is_service_account=True,
email_opted_in=False,
full_name="",
)
from_user_request(model)
classmethod
Create a UserSchema from a UserRequest.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model |
UserRequest |
The |
required |
Returns:
| Type | Description |
|---|---|
UserSchema |
The created |
Source code in zenml/zen_stores/schemas/user_schemas.py
@classmethod
def from_user_request(cls, model: UserRequest) -> "UserSchema":
"""Create a `UserSchema` from a `UserRequest`.
Args:
model: The `UserRequest` from which to create the schema.
Returns:
The created `UserSchema`.
"""
return cls(
name=model.name,
full_name=model.full_name,
active=model.active,
password=model.create_hashed_password(),
activation_token=model.create_hashed_activation_token(),
external_user_id=model.external_user_id,
email_opted_in=model.email_opted_in,
email=model.email,
is_service_account=False,
)
to_model(self, include_metadata=False, include_resources=False, include_private=False, **kwargs)
Convert a UserSchema to a UserResponse.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
include_private |
bool |
Whether to include the user private information this is to limit the amount of data one can get about other users |
False |
Returns:
| Type | Description |
|---|---|
UserResponse |
The converted |
Source code in zenml/zen_stores/schemas/user_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
include_private: bool = False,
**kwargs: Any,
) -> UserResponse:
"""Convert a `UserSchema` to a `UserResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
include_private: Whether to include the user private information
this is to limit the amount of data one can get
about other users
Returns:
The converted `UserResponse`.
"""
metadata = None
if include_metadata:
metadata = UserResponseMetadata(
email=self.email if include_private else None,
hub_token=self.hub_token if include_private else None,
external_user_id=self.external_user_id,
)
return UserResponse(
id=self.id,
name=self.name,
body=UserResponseBody(
active=self.active,
full_name=self.full_name,
email_opted_in=self.email_opted_in,
is_service_account=self.is_service_account,
created=self.created,
updated=self.updated,
),
metadata=metadata,
)
to_service_account_model(self, include_metadata=False, include_resources=False)
Convert a UserSchema to a ServiceAccountResponse.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
Returns:
| Type | Description |
|---|---|
ServiceAccountResponse |
The converted |
Source code in zenml/zen_stores/schemas/user_schemas.py
def to_service_account_model(
self, include_metadata: bool = False, include_resources: bool = False
) -> ServiceAccountResponse:
"""Convert a `UserSchema` to a `ServiceAccountResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
Returns:
The converted `ServiceAccountResponse`.
"""
metadata = None
if include_metadata:
metadata = ServiceAccountResponseMetadata(
description=self.description or "",
)
body = ServiceAccountResponseBody(
created=self.created,
updated=self.updated,
active=self.active,
)
return ServiceAccountResponse(
id=self.id,
name=self.name,
body=body,
metadata=metadata,
)
update_service_account(self, service_account_update)
Update a UserSchema from a ServiceAccountUpdate.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account_update |
ServiceAccountUpdate |
The |
required |
Returns:
| Type | Description |
|---|---|
UserSchema |
The updated |
Source code in zenml/zen_stores/schemas/user_schemas.py
def update_service_account(
self, service_account_update: ServiceAccountUpdate
) -> "UserSchema":
"""Update a `UserSchema` from a `ServiceAccountUpdate`.
Args:
service_account_update: The `ServiceAccountUpdate` from which
to update the schema.
Returns:
The updated `UserSchema`.
"""
for field, value in service_account_update.dict(
exclude_none=True
).items():
setattr(self, field, value)
self.updated = datetime.utcnow()
return self
update_user(self, user_update)
Update a UserSchema from a UserUpdate.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
user_update |
UserUpdate |
The |
required |
Returns:
| Type | Description |
|---|---|
UserSchema |
The updated |
Source code in zenml/zen_stores/schemas/user_schemas.py
def update_user(self, user_update: UserUpdate) -> "UserSchema":
"""Update a `UserSchema` from a `UserUpdate`.
Args:
user_update: The `UserUpdate` from which to update the schema.
Returns:
The updated `UserSchema`.
"""
for field, value in user_update.dict(exclude_unset=True).items():
if field == "password":
setattr(self, field, user_update.create_hashed_password())
elif field == "activation_token":
setattr(
self, field, user_update.create_hashed_activation_token()
)
else:
setattr(self, field, value)
self.updated = datetime.utcnow()
return self
utils
Utils for schemas.
Page[BaseResponse] (Page)
pydantic-model
Config
Pydantic configuration class.
Source code in zenml/zen_stores/schemas/utils.py
class Config:
"""Pydantic configuration class."""
# This is needed to allow the REST API server to unpack SecretStr
# values correctly before sending them to the client.
json_encoders = {
SecretStr: lambda v: v.get_secret_value() if v else None
}
__json_encoder__(obj)
special
staticmethod
partial(func, args, *keywords) - new function with partial application of the given arguments and keywords.
get_page_from_list(items_list, response_model, size=5, page=1, include_resources=False, include_metadata=False)
Converts list of schemas into page of response models.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
items_list |
List[~S] |
List of schemas |
required |
response_model |
Type[zenml.models.v2.base.base.BaseResponse] |
Response model |
required |
size |
int |
Page size |
5 |
page |
int |
Page number |
1 |
include_metadata |
bool |
Whether metadata should be included in response models |
False |
include_resources |
bool |
Whether resources should be included in response models |
False |
Returns:
| Type | Description |
|---|---|
Page[BaseResponse] |
A page of list items. |
Source code in zenml/zen_stores/schemas/utils.py
def get_page_from_list(
items_list: List[S],
response_model: Type[BaseResponse], # type: ignore[type-arg]
size: int = 5,
page: int = 1,
include_resources: bool = False,
include_metadata: bool = False,
) -> Page[BaseResponse]: # type: ignore[type-arg]
"""Converts list of schemas into page of response models.
Args:
items_list: List of schemas
response_model: Response model
size: Page size
page: Page number
include_metadata: Whether metadata should be included in response models
include_resources: Whether resources should be included in response models
Returns:
A page of list items.
"""
total = len(items_list)
if total == 0:
total_pages = 1
else:
total_pages = math.ceil(total / size)
start = (page - 1) * size
end = start + size
page_items = [
item.to_model(
include_metadata=include_metadata,
include_resources=include_resources,
)
for item in items_list[start:end]
]
return Page[response_model]( # type: ignore[valid-type]
index=page,
max_size=size,
total_pages=total_pages,
total=total,
items=page_items,
)
workspace_schemas
SQL Model Implementations for Workspaces.
WorkspaceSchema (NamedSchema)
pydantic-model
SQL Model for workspaces.
Source code in zenml/zen_stores/schemas/workspace_schemas.py
class WorkspaceSchema(NamedSchema, table=True):
"""SQL Model for workspaces."""
__tablename__ = "workspace"
description: str
stacks: List["StackSchema"] = Relationship(
back_populates="workspace",
sa_relationship_kwargs={"cascade": "delete"},
)
components: List["StackComponentSchema"] = Relationship(
back_populates="workspace",
sa_relationship_kwargs={"cascade": "delete"},
)
flavors: List["FlavorSchema"] = Relationship(
back_populates="workspace",
sa_relationship_kwargs={"cascade": "delete"},
)
pipelines: List["PipelineSchema"] = Relationship(
back_populates="workspace",
sa_relationship_kwargs={"cascade": "delete"},
)
schedules: List["ScheduleSchema"] = Relationship(
back_populates="workspace",
sa_relationship_kwargs={"cascade": "delete"},
)
runs: List["PipelineRunSchema"] = Relationship(
back_populates="workspace",
sa_relationship_kwargs={"cascade": "delete"},
)
step_runs: List["StepRunSchema"] = Relationship(
back_populates="workspace",
sa_relationship_kwargs={"cascade": "delete"},
)
builds: List["PipelineBuildSchema"] = Relationship(
back_populates="workspace",
sa_relationship_kwargs={"cascade": "delete"},
)
artifact_versions: List["ArtifactVersionSchema"] = Relationship(
back_populates="workspace",
sa_relationship_kwargs={"cascade": "delete"},
)
run_metadata: List["RunMetadataSchema"] = Relationship(
back_populates="workspace",
sa_relationship_kwargs={"cascade": "delete"},
)
secrets: List["SecretSchema"] = Relationship(
back_populates="workspace",
sa_relationship_kwargs={"cascade": "delete"},
)
triggers: List["TriggerSchema"] = Relationship(
back_populates="workspace",
sa_relationship_kwargs={"cascade": "delete"},
)
event_sources: List["EventSourceSchema"] = Relationship(
back_populates="workspace",
sa_relationship_kwargs={"cascade": "delete"},
)
deployments: List["PipelineDeploymentSchema"] = Relationship(
back_populates="workspace",
sa_relationship_kwargs={"cascade": "delete"},
)
code_repositories: List["CodeRepositorySchema"] = Relationship(
back_populates="workspace",
sa_relationship_kwargs={"cascade": "delete"},
)
service_connectors: List["ServiceConnectorSchema"] = Relationship(
back_populates="workspace",
sa_relationship_kwargs={"cascade": "delete"},
)
models: List["ModelSchema"] = Relationship(
back_populates="workspace",
sa_relationship_kwargs={"cascade": "delete"},
)
model_versions: List["ModelVersionSchema"] = Relationship(
back_populates="workspace",
sa_relationship_kwargs={"cascade": "delete"},
)
model_versions_artifacts_links: List["ModelVersionArtifactSchema"] = (
Relationship(
back_populates="workspace",
sa_relationship_kwargs={"cascade": "delete"},
)
)
model_versions_pipeline_runs_links: List[
"ModelVersionPipelineRunSchema"
] = Relationship(
back_populates="workspace",
sa_relationship_kwargs={"cascade": "delete"},
)
@classmethod
def from_request(cls, workspace: WorkspaceRequest) -> "WorkspaceSchema":
"""Create a `WorkspaceSchema` from a `WorkspaceResponse`.
Args:
workspace: The `WorkspaceResponse` from which to create the schema.
Returns:
The created `WorkspaceSchema`.
"""
return cls(name=workspace.name, description=workspace.description)
def update(self, workspace_update: WorkspaceUpdate) -> "WorkspaceSchema":
"""Update a `WorkspaceSchema` from a `WorkspaceUpdate`.
Args:
workspace_update: The `WorkspaceUpdate` from which to update the
schema.
Returns:
The updated `WorkspaceSchema`.
"""
for field, value in workspace_update.dict(exclude_unset=True).items():
setattr(self, field, value)
self.updated = datetime.utcnow()
return self
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> WorkspaceResponse:
"""Convert a `WorkspaceSchema` to a `WorkspaceResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The converted `WorkspaceResponseModel`.
"""
metadata = None
if include_metadata:
metadata = WorkspaceResponseMetadata(
description=self.description,
)
return WorkspaceResponse(
id=self.id,
name=self.name,
body=WorkspaceResponseBody(
created=self.created,
updated=self.updated,
),
metadata=metadata,
)
from_request(workspace)
classmethod
Create a WorkspaceSchema from a WorkspaceResponse.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
workspace |
WorkspaceRequest |
The |
required |
Returns:
| Type | Description |
|---|---|
WorkspaceSchema |
The created |
Source code in zenml/zen_stores/schemas/workspace_schemas.py
@classmethod
def from_request(cls, workspace: WorkspaceRequest) -> "WorkspaceSchema":
"""Create a `WorkspaceSchema` from a `WorkspaceResponse`.
Args:
workspace: The `WorkspaceResponse` from which to create the schema.
Returns:
The created `WorkspaceSchema`.
"""
return cls(name=workspace.name, description=workspace.description)
to_model(self, include_metadata=False, include_resources=False, **kwargs)
Convert a WorkspaceSchema to a WorkspaceResponse.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
include_metadata |
bool |
Whether the metadata will be filled. |
False |
include_resources |
bool |
Whether the resources will be filled. |
False |
**kwargs |
Any |
Keyword arguments to allow schema specific logic |
{} |
Returns:
| Type | Description |
|---|---|
WorkspaceResponse |
The converted |
Source code in zenml/zen_stores/schemas/workspace_schemas.py
def to_model(
self,
include_metadata: bool = False,
include_resources: bool = False,
**kwargs: Any,
) -> WorkspaceResponse:
"""Convert a `WorkspaceSchema` to a `WorkspaceResponse`.
Args:
include_metadata: Whether the metadata will be filled.
include_resources: Whether the resources will be filled.
**kwargs: Keyword arguments to allow schema specific logic
Returns:
The converted `WorkspaceResponseModel`.
"""
metadata = None
if include_metadata:
metadata = WorkspaceResponseMetadata(
description=self.description,
)
return WorkspaceResponse(
id=self.id,
name=self.name,
body=WorkspaceResponseBody(
created=self.created,
updated=self.updated,
),
metadata=metadata,
)
update(self, workspace_update)
Update a WorkspaceSchema from a WorkspaceUpdate.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
workspace_update |
WorkspaceUpdate |
The |
required |
Returns:
| Type | Description |
|---|---|
WorkspaceSchema |
The updated |
Source code in zenml/zen_stores/schemas/workspace_schemas.py
def update(self, workspace_update: WorkspaceUpdate) -> "WorkspaceSchema":
"""Update a `WorkspaceSchema` from a `WorkspaceUpdate`.
Args:
workspace_update: The `WorkspaceUpdate` from which to update the
schema.
Returns:
The updated `WorkspaceSchema`.
"""
for field, value in workspace_update.dict(exclude_unset=True).items():
setattr(self, field, value)
self.updated = datetime.utcnow()
return self
secrets_stores
special
Centralized secrets management.
aws_secrets_store
AWS Secrets Store implementation.
AWSSecretsStore (ServiceConnectorSecretsStore)
pydantic-model
Secrets store implementation that uses the AWS Secrets Manager API.
This secrets store implementation uses the AWS Secrets Manager API to store secrets. It allows a single AWS Secrets Manager region "instance" to be shared with other ZenML deployments as well as other third party users and applications.
Here are some implementation highlights:
-
the name/ID of an AWS secret is derived from the ZenML secret UUID and a
zenmlprefix in the formzenml/{zenml_secret_uuid}. This clearly identifies a secret as being managed by ZenML in the AWS console. -
the Secrets Store also uses AWS secret tags to store additional metadata associated with a ZenML secret. The
zenmltag in particular is used to identify and group all secrets that belong to the same ZenML deployment. -
all secret key-values configured in a ZenML secret are stored as a single JSON string value in the AWS secret value.
Source code in zenml/zen_stores/secrets_stores/aws_secrets_store.py
class AWSSecretsStore(ServiceConnectorSecretsStore):
"""Secrets store implementation that uses the AWS Secrets Manager API.
This secrets store implementation uses the AWS Secrets Manager API to
store secrets. It allows a single AWS Secrets Manager region "instance" to
be shared with other ZenML deployments as well as other third party users
and applications.
Here are some implementation highlights:
* the name/ID of an AWS secret is derived from the ZenML secret UUID and a
`zenml` prefix in the form `zenml/{zenml_secret_uuid}`. This clearly
identifies a secret as being managed by ZenML in the AWS console.
* the Secrets Store also uses AWS secret tags to store additional
metadata associated with a ZenML secret. The `zenml` tag in particular is
used to identify and group all secrets that belong to the same ZenML
deployment.
* all secret key-values configured in a ZenML secret are stored as a single
JSON string value in the AWS secret value.
"""
config: AWSSecretsStoreConfiguration
TYPE: ClassVar[SecretsStoreType] = SecretsStoreType.AWS
CONFIG_TYPE: ClassVar[Type[ServiceConnectorSecretsStoreConfiguration]] = (
AWSSecretsStoreConfiguration
)
SERVICE_CONNECTOR_TYPE: ClassVar[str] = AWS_CONNECTOR_TYPE
SERVICE_CONNECTOR_RESOURCE_TYPE: ClassVar[str] = AWS_RESOURCE_TYPE
# ====================================
# Secrets Store interface implementation
# ====================================
# --------------------------------
# Initialization and configuration
# --------------------------------
def _initialize_client_from_connector(self, client: Any) -> Any:
"""Initialize the AWS Secrets Manager client from the service connector client.
Args:
client: The authenticated client object returned by the service
connector.
Returns:
The AWS Secrets Manager client.
"""
assert isinstance(client, boto3.Session)
return client.client(
"secretsmanager",
region_name=self.config.region,
)
# ------
# Secrets
# ------
@staticmethod
def _get_aws_secret_id(
secret_id: UUID,
) -> str:
"""Get the AWS secret ID corresponding to a ZenML secret ID.
The convention used for AWS secret names is to use the ZenML
secret UUID prefixed with `zenml` as the AWS secret name,
i.e. `zenml/<secret_uuid>`.
Args:
secret_id: The ZenML secret ID.
Returns:
The AWS secret name.
"""
return f"{AWS_ZENML_SECRET_NAME_PREFIX}/{str(secret_id)}"
@staticmethod
def _get_aws_secret_tags(
metadata: Dict[str, str],
) -> List[Dict[str, str]]:
"""Convert ZenML secret metadata to AWS secret tags.
Args:
metadata: The ZenML secret metadata.
Returns:
The AWS secret tags.
"""
aws_tags: List[Dict[str, str]] = []
for k, v in metadata.items():
aws_tags.append(
{
"Key": k,
"Value": str(v),
}
)
return aws_tags
def store_secret_values(
self,
secret_id: UUID,
secret_values: Dict[str, str],
) -> None:
"""Store secret values for a new secret.
Args:
secret_id: ID of the secret.
secret_values: Values for the secret.
Raises:
RuntimeError: If the AWS Secrets Manager API returns an unexpected
error.
"""
aws_secret_id = self._get_aws_secret_id(secret_id)
secret_value = json.dumps(secret_values)
# Convert the ZenML secret metadata to AWS tags
metadata = self._get_secret_metadata(secret_id=secret_id)
tags = self._get_aws_secret_tags(metadata)
try:
self.client.create_secret(
Name=aws_secret_id,
SecretString=secret_value,
Tags=tags,
)
except ClientError as e:
raise RuntimeError(f"Error creating secret: {e}")
logger.debug(f"Created AWS secret: {aws_secret_id}")
def get_secret_values(self, secret_id: UUID) -> Dict[str, str]:
"""Get the secret values for an existing secret.
Args:
secret_id: ID of the secret.
Returns:
The secret values.
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
RuntimeError: If the AWS Secrets Manager API returns an unexpected
error.
"""
aws_secret_id = self._get_aws_secret_id(secret_id)
try:
get_secret_value_response = self.client.get_secret_value(
SecretId=aws_secret_id
)
# We need a separate AWS API call to get the AWS secret tags which
# contain the ZenML secret metadata, since the get_secret_ value API
# does not return them.
describe_secret_response = self.client.describe_secret(
SecretId=aws_secret_id
)
except ClientError as e:
if e.response["Error"]["Code"] == "ResourceNotFoundException" or (
e.response["Error"]["Code"] == "InvalidRequestException"
and "marked for deletion" in e.response["Error"]["Message"]
):
raise KeyError(
f"Can't find the secret values for secret ID '{secret_id}' "
f"in the secrets store back-end: {str(e)}"
) from e
raise RuntimeError(
f"Error fetching secret with ID {secret_id} {e}"
)
# Convert the AWS secret tags to a metadata dictionary.
metadata: Dict[str, str] = {
tag["Key"]: tag["Value"]
for tag in describe_secret_response["Tags"]
}
# The _verify_secret_metadata method raises a KeyError if the
# secret is not valid or does not belong to this server. Here we
# simply pass the exception up the stack, as if the secret was not found
# in the first place.
self._verify_secret_metadata(
secret_id=secret_id,
metadata=metadata,
)
values = get_secret_value_response["SecretString"]
logger.debug(f"Fetched AWS secret: {aws_secret_id}")
secret_values = json.loads(values)
if not isinstance(secret_values, dict):
raise RuntimeError(
f"AWS secret values for secret ID {aws_secret_id} could not be "
"decoded: expected a dictionary."
)
return secret_values
def update_secret_values(
self,
secret_id: UUID,
secret_values: Dict[str, str],
) -> None:
"""Updates secret values for an existing secret.
Args:
secret_id: The ID of the secret to be updated.
secret_values: The new secret values.
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
RuntimeError: If the AWS Secrets Manager API returns an unexpected
error.
"""
aws_secret_id = self._get_aws_secret_id(secret_id)
secret_value = json.dumps(secret_values)
# Convert the ZenML secret metadata to AWS tags
metadata = self._get_secret_metadata(secret_id)
tags = self._get_aws_secret_tags(metadata)
try:
# One call to update the secret values
self.client.put_secret_value(
SecretId=aws_secret_id,
SecretString=secret_value,
)
# Another call to update the tags
self.client.tag_resource(
SecretId=aws_secret_id,
Tags=tags,
)
except ClientError as e:
if e.response["Error"]["Code"] == "ResourceNotFoundException":
raise KeyError(f"Secret with ID {secret_id} not found")
raise RuntimeError(f"Error updating secret: {e}")
logger.debug(f"Updated AWS secret: {aws_secret_id}")
def delete_secret_values(self, secret_id: UUID) -> None:
"""Deletes secret values for an existing secret.
Args:
secret_id: The ID of the secret.
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
RuntimeError: If the AWS Secrets Manager API returns an unexpected
error.
"""
aws_secret_id = self._get_aws_secret_id(secret_id)
try:
self.client.delete_secret(
SecretId=aws_secret_id,
# We set this to force immediate deletion of the AWS secret
# instead of waiting for the recovery window to expire.
ForceDeleteWithoutRecovery=True,
)
except ClientError as e:
if e.response["Error"]["Code"] == "ResourceNotFoundException":
raise KeyError(f"Secret with ID {secret_id} not found")
if (
e.response["Error"]["Code"] == "InvalidRequestException"
and "marked for deletion" in e.response["Error"]["Message"]
):
raise KeyError(f"Secret with ID {secret_id} not found")
raise RuntimeError(
f"Error deleting secret with ID {secret_id}: {e}"
)
logger.debug(f"Deleted AWS secret: {aws_secret_id}")
CONFIG_TYPE (ServiceConnectorSecretsStoreConfiguration)
pydantic-model
AWS secrets store configuration.
Attributes:
| Name | Type | Description |
|---|---|---|
type |
SecretsStoreType |
The type of the store. |
Source code in zenml/zen_stores/secrets_stores/aws_secrets_store.py
class AWSSecretsStoreConfiguration(ServiceConnectorSecretsStoreConfiguration):
"""AWS secrets store configuration.
Attributes:
type: The type of the store.
"""
type: SecretsStoreType = SecretsStoreType.AWS
@property
def region(self) -> str:
"""The AWS region to use.
Returns:
The AWS region to use.
Raises:
ValueError: If the region is not configured.
"""
region = self.auth_config.get("region")
if region:
return str(region)
raise ValueError("AWS `region` must be specified in the auth_config.")
@root_validator(pre=True)
def populate_config(cls, values: Dict[str, Any]) -> Dict[str, Any]:
"""Populate the connector configuration from legacy attributes.
Args:
values: Dict representing user-specified runtime settings.
Returns:
Validated settings.
"""
# Search for legacy attributes and populate the connector configuration
# from them, if they exist.
if values.get("region_name"):
if not values.get("aws_access_key_id") or not values.get(
"aws_secret_access_key"
):
logger.warning(
"The `region_name` AWS secrets store attribute is deprecated "
"and will be removed in a future version of ZenML. Please use "
"the `auth_method` and `auth_config` attributes instead. "
"Using an implicit authentication method for AWS Secrets."
)
values["auth_method"] = AWSAuthenticationMethods.IMPLICIT
values["auth_config"] = dict(
region=values.get("region_name"),
)
else:
logger.warning(
"The `aws_access_key_id`, `aws_secret_access_key` and "
"`region_name` AWS secrets store attributes are deprecated and "
"will be removed in a future version of ZenML. Please use the "
"`auth_method` and `auth_config` attributes instead."
)
values["auth_method"] = AWSAuthenticationMethods.SECRET_KEY
values["auth_config"] = dict(
aws_access_key_id=values.get("aws_access_key_id"),
aws_secret_access_key=values.get("aws_secret_access_key"),
region=values.get("region_name"),
)
return values
class Config:
"""Pydantic configuration class."""
# Allow extra attributes set in the class.
extra = "allow"
region: str
property
readonly
The AWS region to use.
Returns:
| Type | Description |
|---|---|
str |
The AWS region to use. |
Exceptions:
| Type | Description |
|---|---|
ValueError |
If the region is not configured. |
Config
Pydantic configuration class.
Source code in zenml/zen_stores/secrets_stores/aws_secrets_store.py
class Config:
"""Pydantic configuration class."""
# Allow extra attributes set in the class.
extra = "allow"
populate_config(values)
classmethod
Populate the connector configuration from legacy attributes.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
values |
Dict[str, Any] |
Dict representing user-specified runtime settings. |
required |
Returns:
| Type | Description |
|---|---|
Dict[str, Any] |
Validated settings. |
Source code in zenml/zen_stores/secrets_stores/aws_secrets_store.py
@root_validator(pre=True)
def populate_config(cls, values: Dict[str, Any]) -> Dict[str, Any]:
"""Populate the connector configuration from legacy attributes.
Args:
values: Dict representing user-specified runtime settings.
Returns:
Validated settings.
"""
# Search for legacy attributes and populate the connector configuration
# from them, if they exist.
if values.get("region_name"):
if not values.get("aws_access_key_id") or not values.get(
"aws_secret_access_key"
):
logger.warning(
"The `region_name` AWS secrets store attribute is deprecated "
"and will be removed in a future version of ZenML. Please use "
"the `auth_method` and `auth_config` attributes instead. "
"Using an implicit authentication method for AWS Secrets."
)
values["auth_method"] = AWSAuthenticationMethods.IMPLICIT
values["auth_config"] = dict(
region=values.get("region_name"),
)
else:
logger.warning(
"The `aws_access_key_id`, `aws_secret_access_key` and "
"`region_name` AWS secrets store attributes are deprecated and "
"will be removed in a future version of ZenML. Please use the "
"`auth_method` and `auth_config` attributes instead."
)
values["auth_method"] = AWSAuthenticationMethods.SECRET_KEY
values["auth_config"] = dict(
aws_access_key_id=values.get("aws_access_key_id"),
aws_secret_access_key=values.get("aws_secret_access_key"),
region=values.get("region_name"),
)
return values
delete_secret_values(self, secret_id)
Deletes secret values for an existing secret.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
The ID of the secret. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if no secret values for the given ID are stored in the secrets store. |
RuntimeError |
If the AWS Secrets Manager API returns an unexpected error. |
Source code in zenml/zen_stores/secrets_stores/aws_secrets_store.py
def delete_secret_values(self, secret_id: UUID) -> None:
"""Deletes secret values for an existing secret.
Args:
secret_id: The ID of the secret.
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
RuntimeError: If the AWS Secrets Manager API returns an unexpected
error.
"""
aws_secret_id = self._get_aws_secret_id(secret_id)
try:
self.client.delete_secret(
SecretId=aws_secret_id,
# We set this to force immediate deletion of the AWS secret
# instead of waiting for the recovery window to expire.
ForceDeleteWithoutRecovery=True,
)
except ClientError as e:
if e.response["Error"]["Code"] == "ResourceNotFoundException":
raise KeyError(f"Secret with ID {secret_id} not found")
if (
e.response["Error"]["Code"] == "InvalidRequestException"
and "marked for deletion" in e.response["Error"]["Message"]
):
raise KeyError(f"Secret with ID {secret_id} not found")
raise RuntimeError(
f"Error deleting secret with ID {secret_id}: {e}"
)
logger.debug(f"Deleted AWS secret: {aws_secret_id}")
get_secret_values(self, secret_id)
Get the secret values for an existing secret.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
ID of the secret. |
required |
Returns:
| Type | Description |
|---|---|
Dict[str, str] |
The secret values. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if no secret values for the given ID are stored in the secrets store. |
RuntimeError |
If the AWS Secrets Manager API returns an unexpected error. |
Source code in zenml/zen_stores/secrets_stores/aws_secrets_store.py
def get_secret_values(self, secret_id: UUID) -> Dict[str, str]:
"""Get the secret values for an existing secret.
Args:
secret_id: ID of the secret.
Returns:
The secret values.
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
RuntimeError: If the AWS Secrets Manager API returns an unexpected
error.
"""
aws_secret_id = self._get_aws_secret_id(secret_id)
try:
get_secret_value_response = self.client.get_secret_value(
SecretId=aws_secret_id
)
# We need a separate AWS API call to get the AWS secret tags which
# contain the ZenML secret metadata, since the get_secret_ value API
# does not return them.
describe_secret_response = self.client.describe_secret(
SecretId=aws_secret_id
)
except ClientError as e:
if e.response["Error"]["Code"] == "ResourceNotFoundException" or (
e.response["Error"]["Code"] == "InvalidRequestException"
and "marked for deletion" in e.response["Error"]["Message"]
):
raise KeyError(
f"Can't find the secret values for secret ID '{secret_id}' "
f"in the secrets store back-end: {str(e)}"
) from e
raise RuntimeError(
f"Error fetching secret with ID {secret_id} {e}"
)
# Convert the AWS secret tags to a metadata dictionary.
metadata: Dict[str, str] = {
tag["Key"]: tag["Value"]
for tag in describe_secret_response["Tags"]
}
# The _verify_secret_metadata method raises a KeyError if the
# secret is not valid or does not belong to this server. Here we
# simply pass the exception up the stack, as if the secret was not found
# in the first place.
self._verify_secret_metadata(
secret_id=secret_id,
metadata=metadata,
)
values = get_secret_value_response["SecretString"]
logger.debug(f"Fetched AWS secret: {aws_secret_id}")
secret_values = json.loads(values)
if not isinstance(secret_values, dict):
raise RuntimeError(
f"AWS secret values for secret ID {aws_secret_id} could not be "
"decoded: expected a dictionary."
)
return secret_values
store_secret_values(self, secret_id, secret_values)
Store secret values for a new secret.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
ID of the secret. |
required |
secret_values |
Dict[str, str] |
Values for the secret. |
required |
Exceptions:
| Type | Description |
|---|---|
RuntimeError |
If the AWS Secrets Manager API returns an unexpected error. |
Source code in zenml/zen_stores/secrets_stores/aws_secrets_store.py
def store_secret_values(
self,
secret_id: UUID,
secret_values: Dict[str, str],
) -> None:
"""Store secret values for a new secret.
Args:
secret_id: ID of the secret.
secret_values: Values for the secret.
Raises:
RuntimeError: If the AWS Secrets Manager API returns an unexpected
error.
"""
aws_secret_id = self._get_aws_secret_id(secret_id)
secret_value = json.dumps(secret_values)
# Convert the ZenML secret metadata to AWS tags
metadata = self._get_secret_metadata(secret_id=secret_id)
tags = self._get_aws_secret_tags(metadata)
try:
self.client.create_secret(
Name=aws_secret_id,
SecretString=secret_value,
Tags=tags,
)
except ClientError as e:
raise RuntimeError(f"Error creating secret: {e}")
logger.debug(f"Created AWS secret: {aws_secret_id}")
update_secret_values(self, secret_id, secret_values)
Updates secret values for an existing secret.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
The ID of the secret to be updated. |
required |
secret_values |
Dict[str, str] |
The new secret values. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if no secret values for the given ID are stored in the secrets store. |
RuntimeError |
If the AWS Secrets Manager API returns an unexpected error. |
Source code in zenml/zen_stores/secrets_stores/aws_secrets_store.py
def update_secret_values(
self,
secret_id: UUID,
secret_values: Dict[str, str],
) -> None:
"""Updates secret values for an existing secret.
Args:
secret_id: The ID of the secret to be updated.
secret_values: The new secret values.
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
RuntimeError: If the AWS Secrets Manager API returns an unexpected
error.
"""
aws_secret_id = self._get_aws_secret_id(secret_id)
secret_value = json.dumps(secret_values)
# Convert the ZenML secret metadata to AWS tags
metadata = self._get_secret_metadata(secret_id)
tags = self._get_aws_secret_tags(metadata)
try:
# One call to update the secret values
self.client.put_secret_value(
SecretId=aws_secret_id,
SecretString=secret_value,
)
# Another call to update the tags
self.client.tag_resource(
SecretId=aws_secret_id,
Tags=tags,
)
except ClientError as e:
if e.response["Error"]["Code"] == "ResourceNotFoundException":
raise KeyError(f"Secret with ID {secret_id} not found")
raise RuntimeError(f"Error updating secret: {e}")
logger.debug(f"Updated AWS secret: {aws_secret_id}")
AWSSecretsStoreConfiguration (ServiceConnectorSecretsStoreConfiguration)
pydantic-model
AWS secrets store configuration.
Attributes:
| Name | Type | Description |
|---|---|---|
type |
SecretsStoreType |
The type of the store. |
Source code in zenml/zen_stores/secrets_stores/aws_secrets_store.py
class AWSSecretsStoreConfiguration(ServiceConnectorSecretsStoreConfiguration):
"""AWS secrets store configuration.
Attributes:
type: The type of the store.
"""
type: SecretsStoreType = SecretsStoreType.AWS
@property
def region(self) -> str:
"""The AWS region to use.
Returns:
The AWS region to use.
Raises:
ValueError: If the region is not configured.
"""
region = self.auth_config.get("region")
if region:
return str(region)
raise ValueError("AWS `region` must be specified in the auth_config.")
@root_validator(pre=True)
def populate_config(cls, values: Dict[str, Any]) -> Dict[str, Any]:
"""Populate the connector configuration from legacy attributes.
Args:
values: Dict representing user-specified runtime settings.
Returns:
Validated settings.
"""
# Search for legacy attributes and populate the connector configuration
# from them, if they exist.
if values.get("region_name"):
if not values.get("aws_access_key_id") or not values.get(
"aws_secret_access_key"
):
logger.warning(
"The `region_name` AWS secrets store attribute is deprecated "
"and will be removed in a future version of ZenML. Please use "
"the `auth_method` and `auth_config` attributes instead. "
"Using an implicit authentication method for AWS Secrets."
)
values["auth_method"] = AWSAuthenticationMethods.IMPLICIT
values["auth_config"] = dict(
region=values.get("region_name"),
)
else:
logger.warning(
"The `aws_access_key_id`, `aws_secret_access_key` and "
"`region_name` AWS secrets store attributes are deprecated and "
"will be removed in a future version of ZenML. Please use the "
"`auth_method` and `auth_config` attributes instead."
)
values["auth_method"] = AWSAuthenticationMethods.SECRET_KEY
values["auth_config"] = dict(
aws_access_key_id=values.get("aws_access_key_id"),
aws_secret_access_key=values.get("aws_secret_access_key"),
region=values.get("region_name"),
)
return values
class Config:
"""Pydantic configuration class."""
# Allow extra attributes set in the class.
extra = "allow"
region: str
property
readonly
The AWS region to use.
Returns:
| Type | Description |
|---|---|
str |
The AWS region to use. |
Exceptions:
| Type | Description |
|---|---|
ValueError |
If the region is not configured. |
Config
Pydantic configuration class.
Source code in zenml/zen_stores/secrets_stores/aws_secrets_store.py
class Config:
"""Pydantic configuration class."""
# Allow extra attributes set in the class.
extra = "allow"
populate_config(values)
classmethod
Populate the connector configuration from legacy attributes.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
values |
Dict[str, Any] |
Dict representing user-specified runtime settings. |
required |
Returns:
| Type | Description |
|---|---|
Dict[str, Any] |
Validated settings. |
Source code in zenml/zen_stores/secrets_stores/aws_secrets_store.py
@root_validator(pre=True)
def populate_config(cls, values: Dict[str, Any]) -> Dict[str, Any]:
"""Populate the connector configuration from legacy attributes.
Args:
values: Dict representing user-specified runtime settings.
Returns:
Validated settings.
"""
# Search for legacy attributes and populate the connector configuration
# from them, if they exist.
if values.get("region_name"):
if not values.get("aws_access_key_id") or not values.get(
"aws_secret_access_key"
):
logger.warning(
"The `region_name` AWS secrets store attribute is deprecated "
"and will be removed in a future version of ZenML. Please use "
"the `auth_method` and `auth_config` attributes instead. "
"Using an implicit authentication method for AWS Secrets."
)
values["auth_method"] = AWSAuthenticationMethods.IMPLICIT
values["auth_config"] = dict(
region=values.get("region_name"),
)
else:
logger.warning(
"The `aws_access_key_id`, `aws_secret_access_key` and "
"`region_name` AWS secrets store attributes are deprecated and "
"will be removed in a future version of ZenML. Please use the "
"`auth_method` and `auth_config` attributes instead."
)
values["auth_method"] = AWSAuthenticationMethods.SECRET_KEY
values["auth_config"] = dict(
aws_access_key_id=values.get("aws_access_key_id"),
aws_secret_access_key=values.get("aws_secret_access_key"),
region=values.get("region_name"),
)
return values
azure_secrets_store
Azure Secrets Store implementation.
AzureSecretsStore (ServiceConnectorSecretsStore)
pydantic-model
Secrets store implementation that uses the Azure Key Vault API.
This secrets store implementation uses the Azure Key Vault API to store secrets. It allows a single Azure Key Vault to be shared with other ZenML deployments as well as other third party users and applications.
Here are some implementation highlights:
-
the name/ID of an Azure secret is derived from the ZenML secret UUID and a
zenmlprefix in the formzenml-{zenml_secret_uuid}. This clearly identifies a secret as being managed by ZenML in the Azure console. -
the Secrets Store also uses Azure Key Vault secret tags to store metadata associated with a ZenML secret. The
zenmltag in particular is used to identify and group all secrets that belong to the same ZenML deployment. -
all secret key-values configured in a ZenML secret are stored as a single JSON string value in the Azure Key Vault secret value.
Source code in zenml/zen_stores/secrets_stores/azure_secrets_store.py
class AzureSecretsStore(ServiceConnectorSecretsStore):
"""Secrets store implementation that uses the Azure Key Vault API.
This secrets store implementation uses the Azure Key Vault API to
store secrets. It allows a single Azure Key Vault to be shared with other
ZenML deployments as well as other third party users and applications.
Here are some implementation highlights:
* the name/ID of an Azure secret is derived from the ZenML secret UUID and a
`zenml` prefix in the form `zenml-{zenml_secret_uuid}`. This clearly
identifies a secret as being managed by ZenML in the Azure console.
* the Secrets Store also uses Azure Key Vault secret tags to store metadata
associated with a ZenML secret. The `zenml` tag in particular is used to
identify and group all secrets that belong to the same ZenML deployment.
* all secret key-values configured in a ZenML secret are stored as a single
JSON string value in the Azure Key Vault secret value.
"""
config: AzureSecretsStoreConfiguration
TYPE: ClassVar[SecretsStoreType] = SecretsStoreType.AZURE
CONFIG_TYPE: ClassVar[Type[ServiceConnectorSecretsStoreConfiguration]] = (
AzureSecretsStoreConfiguration
)
SERVICE_CONNECTOR_TYPE: ClassVar[str] = AZURE_CONNECTOR_TYPE
SERVICE_CONNECTOR_RESOURCE_TYPE: ClassVar[str] = AZURE_RESOURCE_TYPE
@property
def client(self) -> SecretClient:
"""Initialize and return the Azure Key Vault client.
Returns:
The Azure Key Vault client.
"""
return cast(SecretClient, super().client)
# ====================================
# Secrets Store interface implementation
# ====================================
# --------------------------------
# Initialization and configuration
# --------------------------------
def _initialize_client_from_connector(self, client: Any) -> Any:
"""Initialize the Azure Key Vault client from the service connector client.
Args:
client: The authenticated client object returned by the service
connector.
Returns:
The Azure Key Vault client.
"""
assert isinstance(client, TokenCredential)
azure_logger = logging.getLogger("azure")
# Suppress the INFO logging level of the Azure SDK if the
# ZenML logging level is WARNING or lower.
if logger.level <= logging.WARNING:
azure_logger.setLevel(logging.WARNING)
else:
azure_logger.setLevel(logging.INFO)
vault_url = f"https://{self.config.key_vault_name}.vault.azure.net"
return SecretClient(vault_url=vault_url, credential=client)
# ------
# Secrets
# ------
@staticmethod
def _get_azure_secret_id(
secret_id: UUID,
) -> str:
"""Get the Azure secret ID corresponding to a ZenML secret ID.
The convention used for Azure secret names is to use the ZenML
secret UUID prefixed with `zenml` as the Azure secret name,
i.e. `zenml-<secret_uuid>`.
Args:
secret_id: The ZenML secret ID.
Returns:
The Azure secret name.
"""
return f"{AZURE_ZENML_SECRET_NAME_PREFIX}-{str(secret_id)}"
def store_secret_values(
self,
secret_id: UUID,
secret_values: Dict[str, str],
) -> None:
"""Store secret values for a new secret.
Args:
secret_id: ID of the secret.
secret_values: Values for the secret.
Raises:
RuntimeError: if the Azure Key Vault API returns an unexpected
error.
"""
azure_secret_id = self._get_azure_secret_id(secret_id)
secret_value = json.dumps(secret_values)
# Use the ZenML secret metadata as Azure tags
metadata = self._get_secret_metadata(secret_id=secret_id)
try:
self.client.set_secret(
azure_secret_id,
secret_value,
tags=metadata,
content_type="application/json",
)
except HttpResponseError as e:
raise RuntimeError(f"Error creating secret: {e}")
logger.debug(f"Created Azure secret: {azure_secret_id}")
def get_secret_values(self, secret_id: UUID) -> Dict[str, str]:
"""Get the secret values for an existing secret.
Args:
secret_id: ID of the secret.
Returns:
The secret values.
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
RuntimeError: if the Azure Key Vault API returns an unexpected
error.
"""
azure_secret_id = self._get_azure_secret_id(secret_id)
try:
azure_secret = self.client.get_secret(
azure_secret_id,
)
except ResourceNotFoundError as e:
raise KeyError(
f"Can't find the secret values for secret ID '{secret_id}' "
f"in the secrets store back-end: {str(e)}"
) from e
except HttpResponseError as e:
raise RuntimeError(
f"Error fetching secret with ID {secret_id} {e}"
)
# The _verify_secret_metadata method raises a KeyError if the
# secret is not valid or does not belong to this server. Here we
# simply pass the exception up the stack, as if the secret was not found
# in the first place.
assert azure_secret.properties.tags is not None
self._verify_secret_metadata(
secret_id=secret_id,
metadata=azure_secret.properties.tags,
)
values = json.loads(azure_secret.value) if azure_secret.value else {}
if not isinstance(values, dict):
raise RuntimeError(
f"Azure Key Vault secret values for secret {azure_secret_id} "
"could not be retrieved: invalid type for values"
)
logger.debug(f"Retrieved Azure secret: {azure_secret_id}")
return values
def update_secret_values(
self,
secret_id: UUID,
secret_values: Dict[str, str],
) -> None:
"""Updates secret values for an existing secret.
Args:
secret_id: The ID of the secret to be updated.
secret_values: The new secret values.
Raises:
RuntimeError: if the Azure Key Vault API returns an unexpected
error.
"""
azure_secret_id = self._get_azure_secret_id(secret_id)
secret_value = json.dumps(secret_values)
# Convert the ZenML secret metadata to Azure tags
metadata = self._get_secret_metadata(secret_id=secret_id)
try:
self.client.set_secret(
azure_secret_id,
secret_value,
tags=metadata,
content_type="application/json",
)
except HttpResponseError as e:
raise RuntimeError(f"Error updating secret {secret_id}: {e}")
logger.debug(f"Updated Azure secret: {azure_secret_id}")
def delete_secret_values(self, secret_id: UUID) -> None:
"""Deletes secret values for an existing secret.
Args:
secret_id: The ID of the secret.
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
RuntimeError: if the Azure Key Vault API returns an unexpected
error.
"""
azure_secret_id = self._get_azure_secret_id(secret_id)
try:
self.client.begin_delete_secret(
azure_secret_id,
).wait()
except ResourceNotFoundError:
raise KeyError(f"Secret with ID {secret_id} not found")
except HttpResponseError as e:
raise RuntimeError(
f"Error deleting secret with ID {secret_id}: {e}"
)
logger.debug(f"Deleted Azure secret: {azure_secret_id}")
client: azure.keyvault.secrets.SecretClient
property
readonly
Initialize and return the Azure Key Vault client.
Returns:
| Type | Description |
|---|---|
azure.keyvault.secrets.SecretClient |
The Azure Key Vault client. |
CONFIG_TYPE (ServiceConnectorSecretsStoreConfiguration)
pydantic-model
Azure secrets store configuration.
Attributes:
| Name | Type | Description |
|---|---|---|
type |
SecretsStoreType |
The type of the store. |
key_vault_name |
str |
Name of the Azure Key Vault that this secrets store will use to store secrets. |
Source code in zenml/zen_stores/secrets_stores/azure_secrets_store.py
class AzureSecretsStoreConfiguration(
ServiceConnectorSecretsStoreConfiguration
):
"""Azure secrets store configuration.
Attributes:
type: The type of the store.
key_vault_name: Name of the Azure Key Vault that this secrets store
will use to store secrets.
"""
type: SecretsStoreType = SecretsStoreType.AZURE
key_vault_name: str
@root_validator(pre=True)
def populate_config(cls, values: Dict[str, Any]) -> Dict[str, Any]:
"""Populate the connector configuration from legacy attributes.
Args:
values: Dict representing user-specified runtime settings.
Returns:
Validated settings.
"""
# Search for legacy attributes and populate the connector configuration
# from them, if they exist.
if (
values.get("azure_client_id")
and values.get("azure_client_secret")
and values.get("azure_tenant_id")
):
logger.warning(
"The `azure_client_id`, `azure_client_secret` and "
"`azure_tenant_id` attributes are deprecated and will be "
"removed in a future version or ZenML. Please use the "
"`auth_method` and `auth_config` attributes instead."
)
values["auth_method"] = (
AzureAuthenticationMethods.SERVICE_PRINCIPAL
)
values["auth_config"] = dict(
client_id=values.get("azure_client_id"),
client_secret=values.get("azure_client_secret"),
tenant_id=values.get("azure_tenant_id"),
)
return values
class Config:
"""Pydantic configuration class."""
# Forbid extra attributes set in the class.
extra = "allow"
Config
Pydantic configuration class.
Source code in zenml/zen_stores/secrets_stores/azure_secrets_store.py
class Config:
"""Pydantic configuration class."""
# Forbid extra attributes set in the class.
extra = "allow"
populate_config(values)
classmethod
Populate the connector configuration from legacy attributes.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
values |
Dict[str, Any] |
Dict representing user-specified runtime settings. |
required |
Returns:
| Type | Description |
|---|---|
Dict[str, Any] |
Validated settings. |
Source code in zenml/zen_stores/secrets_stores/azure_secrets_store.py
@root_validator(pre=True)
def populate_config(cls, values: Dict[str, Any]) -> Dict[str, Any]:
"""Populate the connector configuration from legacy attributes.
Args:
values: Dict representing user-specified runtime settings.
Returns:
Validated settings.
"""
# Search for legacy attributes and populate the connector configuration
# from them, if they exist.
if (
values.get("azure_client_id")
and values.get("azure_client_secret")
and values.get("azure_tenant_id")
):
logger.warning(
"The `azure_client_id`, `azure_client_secret` and "
"`azure_tenant_id` attributes are deprecated and will be "
"removed in a future version or ZenML. Please use the "
"`auth_method` and `auth_config` attributes instead."
)
values["auth_method"] = (
AzureAuthenticationMethods.SERVICE_PRINCIPAL
)
values["auth_config"] = dict(
client_id=values.get("azure_client_id"),
client_secret=values.get("azure_client_secret"),
tenant_id=values.get("azure_tenant_id"),
)
return values
delete_secret_values(self, secret_id)
Deletes secret values for an existing secret.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
The ID of the secret. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if no secret values for the given ID are stored in the secrets store. |
RuntimeError |
if the Azure Key Vault API returns an unexpected error. |
Source code in zenml/zen_stores/secrets_stores/azure_secrets_store.py
def delete_secret_values(self, secret_id: UUID) -> None:
"""Deletes secret values for an existing secret.
Args:
secret_id: The ID of the secret.
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
RuntimeError: if the Azure Key Vault API returns an unexpected
error.
"""
azure_secret_id = self._get_azure_secret_id(secret_id)
try:
self.client.begin_delete_secret(
azure_secret_id,
).wait()
except ResourceNotFoundError:
raise KeyError(f"Secret with ID {secret_id} not found")
except HttpResponseError as e:
raise RuntimeError(
f"Error deleting secret with ID {secret_id}: {e}"
)
logger.debug(f"Deleted Azure secret: {azure_secret_id}")
get_secret_values(self, secret_id)
Get the secret values for an existing secret.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
ID of the secret. |
required |
Returns:
| Type | Description |
|---|---|
Dict[str, str] |
The secret values. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if no secret values for the given ID are stored in the secrets store. |
RuntimeError |
if the Azure Key Vault API returns an unexpected error. |
Source code in zenml/zen_stores/secrets_stores/azure_secrets_store.py
def get_secret_values(self, secret_id: UUID) -> Dict[str, str]:
"""Get the secret values for an existing secret.
Args:
secret_id: ID of the secret.
Returns:
The secret values.
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
RuntimeError: if the Azure Key Vault API returns an unexpected
error.
"""
azure_secret_id = self._get_azure_secret_id(secret_id)
try:
azure_secret = self.client.get_secret(
azure_secret_id,
)
except ResourceNotFoundError as e:
raise KeyError(
f"Can't find the secret values for secret ID '{secret_id}' "
f"in the secrets store back-end: {str(e)}"
) from e
except HttpResponseError as e:
raise RuntimeError(
f"Error fetching secret with ID {secret_id} {e}"
)
# The _verify_secret_metadata method raises a KeyError if the
# secret is not valid or does not belong to this server. Here we
# simply pass the exception up the stack, as if the secret was not found
# in the first place.
assert azure_secret.properties.tags is not None
self._verify_secret_metadata(
secret_id=secret_id,
metadata=azure_secret.properties.tags,
)
values = json.loads(azure_secret.value) if azure_secret.value else {}
if not isinstance(values, dict):
raise RuntimeError(
f"Azure Key Vault secret values for secret {azure_secret_id} "
"could not be retrieved: invalid type for values"
)
logger.debug(f"Retrieved Azure secret: {azure_secret_id}")
return values
store_secret_values(self, secret_id, secret_values)
Store secret values for a new secret.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
ID of the secret. |
required |
secret_values |
Dict[str, str] |
Values for the secret. |
required |
Exceptions:
| Type | Description |
|---|---|
RuntimeError |
if the Azure Key Vault API returns an unexpected error. |
Source code in zenml/zen_stores/secrets_stores/azure_secrets_store.py
def store_secret_values(
self,
secret_id: UUID,
secret_values: Dict[str, str],
) -> None:
"""Store secret values for a new secret.
Args:
secret_id: ID of the secret.
secret_values: Values for the secret.
Raises:
RuntimeError: if the Azure Key Vault API returns an unexpected
error.
"""
azure_secret_id = self._get_azure_secret_id(secret_id)
secret_value = json.dumps(secret_values)
# Use the ZenML secret metadata as Azure tags
metadata = self._get_secret_metadata(secret_id=secret_id)
try:
self.client.set_secret(
azure_secret_id,
secret_value,
tags=metadata,
content_type="application/json",
)
except HttpResponseError as e:
raise RuntimeError(f"Error creating secret: {e}")
logger.debug(f"Created Azure secret: {azure_secret_id}")
update_secret_values(self, secret_id, secret_values)
Updates secret values for an existing secret.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
The ID of the secret to be updated. |
required |
secret_values |
Dict[str, str] |
The new secret values. |
required |
Exceptions:
| Type | Description |
|---|---|
RuntimeError |
if the Azure Key Vault API returns an unexpected error. |
Source code in zenml/zen_stores/secrets_stores/azure_secrets_store.py
def update_secret_values(
self,
secret_id: UUID,
secret_values: Dict[str, str],
) -> None:
"""Updates secret values for an existing secret.
Args:
secret_id: The ID of the secret to be updated.
secret_values: The new secret values.
Raises:
RuntimeError: if the Azure Key Vault API returns an unexpected
error.
"""
azure_secret_id = self._get_azure_secret_id(secret_id)
secret_value = json.dumps(secret_values)
# Convert the ZenML secret metadata to Azure tags
metadata = self._get_secret_metadata(secret_id=secret_id)
try:
self.client.set_secret(
azure_secret_id,
secret_value,
tags=metadata,
content_type="application/json",
)
except HttpResponseError as e:
raise RuntimeError(f"Error updating secret {secret_id}: {e}")
logger.debug(f"Updated Azure secret: {azure_secret_id}")
AzureSecretsStoreConfiguration (ServiceConnectorSecretsStoreConfiguration)
pydantic-model
Azure secrets store configuration.
Attributes:
| Name | Type | Description |
|---|---|---|
type |
SecretsStoreType |
The type of the store. |
key_vault_name |
str |
Name of the Azure Key Vault that this secrets store will use to store secrets. |
Source code in zenml/zen_stores/secrets_stores/azure_secrets_store.py
class AzureSecretsStoreConfiguration(
ServiceConnectorSecretsStoreConfiguration
):
"""Azure secrets store configuration.
Attributes:
type: The type of the store.
key_vault_name: Name of the Azure Key Vault that this secrets store
will use to store secrets.
"""
type: SecretsStoreType = SecretsStoreType.AZURE
key_vault_name: str
@root_validator(pre=True)
def populate_config(cls, values: Dict[str, Any]) -> Dict[str, Any]:
"""Populate the connector configuration from legacy attributes.
Args:
values: Dict representing user-specified runtime settings.
Returns:
Validated settings.
"""
# Search for legacy attributes and populate the connector configuration
# from them, if they exist.
if (
values.get("azure_client_id")
and values.get("azure_client_secret")
and values.get("azure_tenant_id")
):
logger.warning(
"The `azure_client_id`, `azure_client_secret` and "
"`azure_tenant_id` attributes are deprecated and will be "
"removed in a future version or ZenML. Please use the "
"`auth_method` and `auth_config` attributes instead."
)
values["auth_method"] = (
AzureAuthenticationMethods.SERVICE_PRINCIPAL
)
values["auth_config"] = dict(
client_id=values.get("azure_client_id"),
client_secret=values.get("azure_client_secret"),
tenant_id=values.get("azure_tenant_id"),
)
return values
class Config:
"""Pydantic configuration class."""
# Forbid extra attributes set in the class.
extra = "allow"
Config
Pydantic configuration class.
Source code in zenml/zen_stores/secrets_stores/azure_secrets_store.py
class Config:
"""Pydantic configuration class."""
# Forbid extra attributes set in the class.
extra = "allow"
populate_config(values)
classmethod
Populate the connector configuration from legacy attributes.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
values |
Dict[str, Any] |
Dict representing user-specified runtime settings. |
required |
Returns:
| Type | Description |
|---|---|
Dict[str, Any] |
Validated settings. |
Source code in zenml/zen_stores/secrets_stores/azure_secrets_store.py
@root_validator(pre=True)
def populate_config(cls, values: Dict[str, Any]) -> Dict[str, Any]:
"""Populate the connector configuration from legacy attributes.
Args:
values: Dict representing user-specified runtime settings.
Returns:
Validated settings.
"""
# Search for legacy attributes and populate the connector configuration
# from them, if they exist.
if (
values.get("azure_client_id")
and values.get("azure_client_secret")
and values.get("azure_tenant_id")
):
logger.warning(
"The `azure_client_id`, `azure_client_secret` and "
"`azure_tenant_id` attributes are deprecated and will be "
"removed in a future version or ZenML. Please use the "
"`auth_method` and `auth_config` attributes instead."
)
values["auth_method"] = (
AzureAuthenticationMethods.SERVICE_PRINCIPAL
)
values["auth_config"] = dict(
client_id=values.get("azure_client_id"),
client_secret=values.get("azure_client_secret"),
tenant_id=values.get("azure_tenant_id"),
)
return values
base_secrets_store
Base Secrets Store implementation.
BaseSecretsStore (BaseModel, SecretsStoreInterface, ABC)
pydantic-model
Base class for accessing and persisting ZenML secret values.
Attributes:
| Name | Type | Description |
|---|---|---|
config |
The configuration of the secret store. |
|
_zen_store |
The ZenML store that owns this secrets store. |
Source code in zenml/zen_stores/secrets_stores/base_secrets_store.py
class BaseSecretsStore(BaseModel, SecretsStoreInterface, ABC):
"""Base class for accessing and persisting ZenML secret values.
Attributes:
config: The configuration of the secret store.
_zen_store: The ZenML store that owns this secrets store.
"""
config: SecretsStoreConfiguration
_zen_store: Optional["BaseZenStore"] = None
TYPE: ClassVar[SecretsStoreType]
CONFIG_TYPE: ClassVar[Type[SecretsStoreConfiguration]]
# ---------------------------------
# Initialization and configuration
# ---------------------------------
def __init__(
self,
zen_store: "BaseZenStore",
**kwargs: Any,
) -> None:
"""Create and initialize a secrets store.
Args:
zen_store: The ZenML store that owns this secrets store.
**kwargs: Additional keyword arguments to pass to the Pydantic
constructor.
Raises:
RuntimeError: If the store cannot be initialized.
"""
super().__init__(**kwargs)
self._zen_store = zen_store
try:
self._initialize()
except Exception as e:
raise RuntimeError(
f"Error initializing {self.type.value} secrets store: {str(e)}"
) from e
@staticmethod
def _load_custom_store_class(
store_config: SecretsStoreConfiguration,
) -> Type["BaseSecretsStore"]:
"""Loads the custom secrets store class from the given config.
Args:
store_config: The configuration of the secrets store.
Returns:
The secrets store class corresponding to the configured custom
secrets store.
Raises:
ValueError: If the configured class path cannot be imported or is
not a subclass of `BaseSecretsStore`.
"""
# Ensured through Pydantic root validation
assert store_config.class_path is not None
# Import the class dynamically
try:
store_class = source_utils.load_and_validate_class(
store_config.class_path, expected_class=BaseSecretsStore
)
except (ImportError, AttributeError) as e:
raise ValueError(
f"Could not import class `{store_config.class_path}`: {str(e)}"
) from e
return store_class
@staticmethod
def get_store_class(
store_config: SecretsStoreConfiguration,
) -> Type["BaseSecretsStore"]:
"""Returns the class of the given secrets store type.
Args:
store_config: The configuration of the secrets store.
Returns:
The class corresponding to the configured secrets store or None if
the type is unknown.
Raises:
TypeError: If the secrets store type is unsupported.
"""
if store_config.type == SecretsStoreType.SQL:
from zenml.zen_stores.secrets_stores.sql_secrets_store import (
SqlSecretsStore,
)
return SqlSecretsStore
if store_config.type == SecretsStoreType.AWS:
from zenml.zen_stores.secrets_stores.aws_secrets_store import (
AWSSecretsStore,
)
return AWSSecretsStore
elif store_config.type == SecretsStoreType.GCP:
from zenml.zen_stores.secrets_stores.gcp_secrets_store import (
GCPSecretsStore,
)
return GCPSecretsStore
elif store_config.type == SecretsStoreType.AZURE:
from zenml.zen_stores.secrets_stores.azure_secrets_store import (
AzureSecretsStore,
)
return AzureSecretsStore
elif store_config.type == SecretsStoreType.HASHICORP:
from zenml.zen_stores.secrets_stores.hashicorp_secrets_store import (
HashiCorpVaultSecretsStore,
)
return HashiCorpVaultSecretsStore
elif store_config.type != SecretsStoreType.CUSTOM:
raise TypeError(
f"No store implementation found for secrets store type "
f"`{store_config.type.value}`."
)
return BaseSecretsStore._load_custom_store_class(store_config)
@staticmethod
def create_store(
config: SecretsStoreConfiguration,
**kwargs: Any,
) -> "BaseSecretsStore":
"""Create and initialize a secrets store from a secrets store configuration.
Args:
config: The secrets store configuration to use.
**kwargs: Additional keyword arguments to pass to the store class
Returns:
The initialized secrets store.
"""
logger.debug(
f"Creating secrets store with type '{config.type.value}'..."
)
store_class = BaseSecretsStore.get_store_class(config)
store = store_class(
config=config,
**kwargs,
)
return store
@property
def type(self) -> SecretsStoreType:
"""The type of the secrets store.
Returns:
The type of the secrets store.
"""
return self.TYPE
@property
def zen_store(self) -> "BaseZenStore":
"""The ZenML store that owns this secrets store.
Returns:
The ZenML store that owns this secrets store.
Raises:
ValueError: If the store is not initialized.
"""
if not self._zen_store:
raise ValueError("Store not initialized")
return self._zen_store
# --------------------------------------------------------
# Helpers for Secrets Store back-ends that use tags/labels
# --------------------------------------------------------
def _get_secret_metadata(
self,
secret_id: Optional[UUID] = None,
) -> Dict[str, str]:
"""Get a dictionary with metadata that can be used as tags/labels.
This utility method can be used with Secrets Managers that can
associate metadata (e.g. tags, labels) with a secret. The metadata can
be configured alongside each secret.
NOTE: the ZENML_SECRET_LABEL is always included in the metadata to
distinguish ZenML secrets from other secrets that might be stored in
the same backend, as well as to distinguish between different ZenML
deployments using the same backend. Its value is set to the ZenML
deployment ID.
Args:
secret_id: Optional secret ID to include in the metadata.
Returns:
Dictionary with secret metadata information.
"""
# Always include the main ZenML label to distinguish ZenML secrets
# from other secrets that might be stored in the same backend and
# to distinguish between different ZenML deployments using the same
# backend.
metadata: Dict[str, str] = {
ZENML_SECRET_LABEL: str(self.zen_store.get_store_info().id)
}
# Include the secret ID if provided.
if secret_id is not None:
metadata[ZENML_SECRET_ID_LABEL] = str(secret_id)
return metadata
def _verify_secret_metadata(
self,
secret_id: UUID,
metadata: Dict[str, str],
) -> None:
"""Verify that the given metadata corresponds to a valid ZenML secret.
Args:
secret_id: The ID of the secret.
metadata: ZenML secret metadata collected from the backend secret
(e.g. from secret tags/labels).
Raises:
KeyError: If the secret does not have the required metadata or if it
is not managed by this ZenML instance.
"""
# Double-check that the secret is managed by this ZenML instance.
if metadata.get(ZENML_SECRET_LABEL) != str(
self.zen_store.get_store_info().id
):
raise KeyError("Secret is not managed by this ZenML instance")
# Recover the ZenML secret fields from the input secret metadata.
try:
stored_secret_id = UUID(metadata[ZENML_SECRET_ID_LABEL])
except KeyError as e:
raise KeyError(
f"Secret could not be retrieved: missing required metadata: {e}"
)
if secret_id != stored_secret_id:
raise KeyError(
f"Secret could not be retrieved: secret ID mismatch: "
f"expected {secret_id}, got {stored_secret_id}"
)
class Config:
"""Pydantic configuration class."""
# Validate attributes when assigning them. We need to set this in order
# to have a mix of mutable and immutable attributes
validate_assignment = True
# Ignore extra attributes from configs of previous ZenML versions
extra = "ignore"
# all attributes with leading underscore are private and therefore
# are mutable and not included in serialization
underscore_attrs_are_private = True
type: SecretsStoreType
property
readonly
The type of the secrets store.
Returns:
| Type | Description |
|---|---|
SecretsStoreType |
The type of the secrets store. |
zen_store: BaseZenStore
property
readonly
The ZenML store that owns this secrets store.
Returns:
| Type | Description |
|---|---|
BaseZenStore |
The ZenML store that owns this secrets store. |
Exceptions:
| Type | Description |
|---|---|
ValueError |
If the store is not initialized. |
Config
Pydantic configuration class.
Source code in zenml/zen_stores/secrets_stores/base_secrets_store.py
class Config:
"""Pydantic configuration class."""
# Validate attributes when assigning them. We need to set this in order
# to have a mix of mutable and immutable attributes
validate_assignment = True
# Ignore extra attributes from configs of previous ZenML versions
extra = "ignore"
# all attributes with leading underscore are private and therefore
# are mutable and not included in serialization
underscore_attrs_are_private = True
__init__(self, zen_store, **kwargs)
special
Create and initialize a secrets store.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
zen_store |
BaseZenStore |
The ZenML store that owns this secrets store. |
required |
**kwargs |
Any |
Additional keyword arguments to pass to the Pydantic constructor. |
{} |
Exceptions:
| Type | Description |
|---|---|
RuntimeError |
If the store cannot be initialized. |
Source code in zenml/zen_stores/secrets_stores/base_secrets_store.py
def __init__(
self,
zen_store: "BaseZenStore",
**kwargs: Any,
) -> None:
"""Create and initialize a secrets store.
Args:
zen_store: The ZenML store that owns this secrets store.
**kwargs: Additional keyword arguments to pass to the Pydantic
constructor.
Raises:
RuntimeError: If the store cannot be initialized.
"""
super().__init__(**kwargs)
self._zen_store = zen_store
try:
self._initialize()
except Exception as e:
raise RuntimeError(
f"Error initializing {self.type.value} secrets store: {str(e)}"
) from e
create_store(config, **kwargs)
staticmethod
Create and initialize a secrets store from a secrets store configuration.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
config |
SecretsStoreConfiguration |
The secrets store configuration to use. |
required |
**kwargs |
Any |
Additional keyword arguments to pass to the store class |
{} |
Returns:
| Type | Description |
|---|---|
BaseSecretsStore |
The initialized secrets store. |
Source code in zenml/zen_stores/secrets_stores/base_secrets_store.py
@staticmethod
def create_store(
config: SecretsStoreConfiguration,
**kwargs: Any,
) -> "BaseSecretsStore":
"""Create and initialize a secrets store from a secrets store configuration.
Args:
config: The secrets store configuration to use.
**kwargs: Additional keyword arguments to pass to the store class
Returns:
The initialized secrets store.
"""
logger.debug(
f"Creating secrets store with type '{config.type.value}'..."
)
store_class = BaseSecretsStore.get_store_class(config)
store = store_class(
config=config,
**kwargs,
)
return store
get_store_class(store_config)
staticmethod
Returns the class of the given secrets store type.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
store_config |
SecretsStoreConfiguration |
The configuration of the secrets store. |
required |
Returns:
| Type | Description |
|---|---|
Type[BaseSecretsStore] |
The class corresponding to the configured secrets store or None if the type is unknown. |
Exceptions:
| Type | Description |
|---|---|
TypeError |
If the secrets store type is unsupported. |
Source code in zenml/zen_stores/secrets_stores/base_secrets_store.py
@staticmethod
def get_store_class(
store_config: SecretsStoreConfiguration,
) -> Type["BaseSecretsStore"]:
"""Returns the class of the given secrets store type.
Args:
store_config: The configuration of the secrets store.
Returns:
The class corresponding to the configured secrets store or None if
the type is unknown.
Raises:
TypeError: If the secrets store type is unsupported.
"""
if store_config.type == SecretsStoreType.SQL:
from zenml.zen_stores.secrets_stores.sql_secrets_store import (
SqlSecretsStore,
)
return SqlSecretsStore
if store_config.type == SecretsStoreType.AWS:
from zenml.zen_stores.secrets_stores.aws_secrets_store import (
AWSSecretsStore,
)
return AWSSecretsStore
elif store_config.type == SecretsStoreType.GCP:
from zenml.zen_stores.secrets_stores.gcp_secrets_store import (
GCPSecretsStore,
)
return GCPSecretsStore
elif store_config.type == SecretsStoreType.AZURE:
from zenml.zen_stores.secrets_stores.azure_secrets_store import (
AzureSecretsStore,
)
return AzureSecretsStore
elif store_config.type == SecretsStoreType.HASHICORP:
from zenml.zen_stores.secrets_stores.hashicorp_secrets_store import (
HashiCorpVaultSecretsStore,
)
return HashiCorpVaultSecretsStore
elif store_config.type != SecretsStoreType.CUSTOM:
raise TypeError(
f"No store implementation found for secrets store type "
f"`{store_config.type.value}`."
)
return BaseSecretsStore._load_custom_store_class(store_config)
gcp_secrets_store
Implementation of the GCP Secrets Store.
GCPSecretsStore (ServiceConnectorSecretsStore)
pydantic-model
Secrets store implementation that uses the GCP Secrets Manager API.
Source code in zenml/zen_stores/secrets_stores/gcp_secrets_store.py
class GCPSecretsStore(ServiceConnectorSecretsStore):
"""Secrets store implementation that uses the GCP Secrets Manager API."""
config: GCPSecretsStoreConfiguration
TYPE: ClassVar[SecretsStoreType] = SecretsStoreType.GCP
CONFIG_TYPE: ClassVar[Type[ServiceConnectorSecretsStoreConfiguration]] = (
GCPSecretsStoreConfiguration
)
SERVICE_CONNECTOR_TYPE: ClassVar[str] = GCP_CONNECTOR_TYPE
SERVICE_CONNECTOR_RESOURCE_TYPE: ClassVar[str] = GCP_RESOURCE_TYPE
_client: Optional[SecretManagerServiceClient] = None
@property
def client(self) -> SecretManagerServiceClient:
"""Initialize and return the GCP Secrets Manager client.
Returns:
The GCP Secrets Manager client instance.
"""
return cast(SecretManagerServiceClient, super().client)
# ====================================
# Secrets Store interface implementation
# ====================================
# --------------------------------
# Initialization and configuration
# --------------------------------
def _initialize_client_from_connector(self, client: Any) -> Any:
"""Initialize the GCP Secrets Manager client from the service connector client.
Args:
client: The authenticated client object returned by the service
connector.
Returns:
The GCP Secrets Manager client.
"""
return SecretManagerServiceClient(credentials=client)
# ------
# Secrets
# ------
@property
def parent_name(self) -> str:
"""Construct the GCP parent path to the secret manager.
Returns:
The parent path to the secret manager
"""
return f"projects/{self.config.project_id}"
def _get_gcp_secret_name(
self,
secret_id: UUID,
) -> str:
"""Get the GCP secret name for the given secret.
The convention used for GCP secret names is to use the ZenML
secret UUID prefixed with `zenml` as the AWS secret name,
i.e. `zenml/<secret_uuid>`.
Args:
secret_id: The ZenML secret ID.
Returns:
The GCP secret name.
"""
return f"{GCP_ZENML_SECRET_NAME_PREFIX}-{str(secret_id)}"
def store_secret_values(
self,
secret_id: UUID,
secret_values: Dict[str, str],
) -> None:
"""Store secret values for a new secret.
Args:
secret_id: ID of the secret.
secret_values: Values for the secret.
Raises:
RuntimeError: if the GCP Secrets Manager API returns an unexpected
error.
"""
secret_value = json.dumps(secret_values)
labels = self._get_secret_metadata(secret_id=secret_id)
try:
gcp_secret = self.client.create_secret(
request={
"parent": self.parent_name,
"secret_id": self._get_gcp_secret_name(secret_id),
"secret": {
"replication": {"automatic": {}},
"labels": labels,
},
}
)
logger.debug(f"Created empty GCP parent secret: {gcp_secret.name}")
self.client.add_secret_version(
request={
"parent": gcp_secret.name,
"payload": {"data": secret_value.encode()},
}
)
logger.debug(f"Added value to GCP secret {gcp_secret.name}")
except Exception as e:
raise RuntimeError(f"Failed to create secret.: {str(e)}") from e
logger.debug(f"Created GCP secret {gcp_secret.name}")
def get_secret_values(self, secret_id: UUID) -> Dict[str, str]:
"""Get the secret values for an existing secret.
Args:
secret_id: ID of the secret.
Returns:
The secret values.
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
RuntimeError: if the GCP Secrets Manager API returns an unexpected
error.
"""
gcp_secret_name = self.client.secret_path(
self.config.project_id,
self._get_gcp_secret_name(secret_id=secret_id),
)
try:
secret = self.client.get_secret(name=gcp_secret_name)
secret_version_values = self.client.access_secret_version(
name=f"{gcp_secret_name}/versions/latest"
)
except google_exceptions.NotFound as e:
raise KeyError(
f"Can't find the secret values for secret ID '{secret_id}' "
f"in the secrets store back-end: {str(e)}"
) from e
except Exception as e:
raise RuntimeError(
f"Error fetching secret with ID {secret_id} {e}"
)
# The GCP secret labels do not really behave like a dictionary: when
# a key is not found, it does not raise a KeyError, but instead
# returns an empty string. That's why we make this conversion.
metadata = dict(secret.labels)
# The _verify_secret_metadata method raises a KeyError if the
# secret is not valid or does not belong to this server. Here we
# simply pass the exception up the stack, as if the secret was not found
# in the first place.
self._verify_secret_metadata(
secret_id=secret_id,
metadata=metadata,
)
secret_values = json.loads(
secret_version_values.payload.data.decode("UTF-8")
)
if not isinstance(secret_values, dict):
raise RuntimeError(
f"Google secret values for secret ID {gcp_secret_name} could "
"not be decoded: expected a dictionary."
)
logger.debug(f"Fetched GCP secret: {gcp_secret_name}")
return secret_values
def update_secret_values(
self,
secret_id: UUID,
secret_values: Dict[str, str],
) -> None:
"""Updates secret values for an existing secret.
Args:
secret_id: The ID of the secret to be updated.
secret_values: The new secret values.
Raises:
RuntimeError: if the GCP Secrets Manager API returns an unexpected
error.
"""
gcp_secret_name = self.client.secret_path(
self.config.project_id,
self._get_gcp_secret_name(secret_id=secret_id),
)
# Convert the ZenML secret metadata to GCP labels
metadata = self._get_secret_metadata(secret_id)
try:
# Update the secret metadata
update_secret = {
"name": gcp_secret_name,
"labels": metadata,
}
update_mask = {"paths": ["labels"]}
gcp_updated_secret = self.client.update_secret(
request={
"secret": update_secret,
"update_mask": update_mask,
}
)
# Add a new secret version
secret_value = json.dumps(secret_values)
self.client.add_secret_version(
request={
"parent": gcp_updated_secret.name,
"payload": {"data": secret_value.encode()},
}
)
except Exception as e:
raise RuntimeError(f"Error updating secret: {e}") from e
logger.debug(f"Updated GCP secret: {gcp_secret_name}")
def delete_secret_values(self, secret_id: UUID) -> None:
"""Deletes secret values for an existing secret.
Args:
secret_id: The ID of the secret.
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
RuntimeError: if the GCP Secrets Manager API returns an unexpected
error.
"""
gcp_secret_name = self.client.secret_path(
self.config.project_id,
self._get_gcp_secret_name(secret_id=secret_id),
)
try:
self.client.delete_secret(request={"name": gcp_secret_name})
except google_exceptions.NotFound:
raise KeyError(f"Secret with ID {secret_id} not found")
except Exception as e:
raise RuntimeError(f"Failed to delete secret: {str(e)}") from e
logger.debug(f"Deleted GCP secret: {gcp_secret_name}")
client: google.cloud.secretmanager.SecretManagerServiceClient
property
readonly
Initialize and return the GCP Secrets Manager client.
Returns:
| Type | Description |
|---|---|
google.cloud.secretmanager.SecretManagerServiceClient |
The GCP Secrets Manager client instance. |
parent_name: str
property
readonly
Construct the GCP parent path to the secret manager.
Returns:
| Type | Description |
|---|---|
str |
The parent path to the secret manager |
CONFIG_TYPE (ServiceConnectorSecretsStoreConfiguration)
pydantic-model
GCP secrets store configuration.
Attributes:
| Name | Type | Description |
|---|---|---|
type |
SecretsStoreType |
The type of the store. |
Source code in zenml/zen_stores/secrets_stores/gcp_secrets_store.py
class GCPSecretsStoreConfiguration(ServiceConnectorSecretsStoreConfiguration):
"""GCP secrets store configuration.
Attributes:
type: The type of the store.
"""
type: SecretsStoreType = SecretsStoreType.GCP
@property
def project_id(self) -> str:
"""Get the GCP project ID.
Returns:
The GCP project ID.
Raises:
ValueError: If the project ID is not set.
"""
project_id = self.auth_config.get("project_id")
if project_id:
return str(project_id)
raise ValueError("GCP `project_id` must be specified in auth_config.")
@root_validator(pre=True)
def populate_config(cls, values: Dict[str, Any]) -> Dict[str, Any]:
"""Populate the connector configuration from legacy attributes.
Args:
values: Dict representing user-specified runtime settings.
Returns:
Validated settings.
"""
# Search for legacy attributes and populate the connector configuration
# from them, if they exist.
if values.get("project_id"):
if not os.environ.get("GOOGLE_APPLICATION_CREDENTIALS"):
logger.warning(
"The `project_id` GCP secrets store attribute is "
"deprecated and will be removed in a future version of ZenML. "
"Please use the `auth_method` and `auth_config` attributes "
"instead. Using an implicit GCP authentication to access "
"the GCP Secrets Manager API."
)
values["auth_method"] = GCPAuthenticationMethods.IMPLICIT
values["auth_config"] = dict(
project_id=values.get("project_id"),
)
else:
logger.warning(
"The `project_id` GCP secrets store attribute and the "
"`GOOGLE_APPLICATION_CREDENTIALS` environment variable are "
"deprecated and will be removed in a future version of ZenML. "
"Please use the `auth_method` and `auth_config` attributes "
"instead."
)
values["auth_method"] = (
GCPAuthenticationMethods.SERVICE_ACCOUNT
)
values["auth_config"] = dict(
project_id=values.get("project_id"),
)
# Load the service account credentials from the file
with open(os.environ["GOOGLE_APPLICATION_CREDENTIALS"]) as f:
values["auth_config"]["service_account_json"] = f.read()
return values
class Config:
"""Pydantic configuration class."""
# Forbid extra attributes set in the class.
extra = "allow"
project_id: str
property
readonly
Get the GCP project ID.
Returns:
| Type | Description |
|---|---|
str |
The GCP project ID. |
Exceptions:
| Type | Description |
|---|---|
ValueError |
If the project ID is not set. |
Config
Pydantic configuration class.
Source code in zenml/zen_stores/secrets_stores/gcp_secrets_store.py
class Config:
"""Pydantic configuration class."""
# Forbid extra attributes set in the class.
extra = "allow"
populate_config(values)
classmethod
Populate the connector configuration from legacy attributes.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
values |
Dict[str, Any] |
Dict representing user-specified runtime settings. |
required |
Returns:
| Type | Description |
|---|---|
Dict[str, Any] |
Validated settings. |
Source code in zenml/zen_stores/secrets_stores/gcp_secrets_store.py
@root_validator(pre=True)
def populate_config(cls, values: Dict[str, Any]) -> Dict[str, Any]:
"""Populate the connector configuration from legacy attributes.
Args:
values: Dict representing user-specified runtime settings.
Returns:
Validated settings.
"""
# Search for legacy attributes and populate the connector configuration
# from them, if they exist.
if values.get("project_id"):
if not os.environ.get("GOOGLE_APPLICATION_CREDENTIALS"):
logger.warning(
"The `project_id` GCP secrets store attribute is "
"deprecated and will be removed in a future version of ZenML. "
"Please use the `auth_method` and `auth_config` attributes "
"instead. Using an implicit GCP authentication to access "
"the GCP Secrets Manager API."
)
values["auth_method"] = GCPAuthenticationMethods.IMPLICIT
values["auth_config"] = dict(
project_id=values.get("project_id"),
)
else:
logger.warning(
"The `project_id` GCP secrets store attribute and the "
"`GOOGLE_APPLICATION_CREDENTIALS` environment variable are "
"deprecated and will be removed in a future version of ZenML. "
"Please use the `auth_method` and `auth_config` attributes "
"instead."
)
values["auth_method"] = (
GCPAuthenticationMethods.SERVICE_ACCOUNT
)
values["auth_config"] = dict(
project_id=values.get("project_id"),
)
# Load the service account credentials from the file
with open(os.environ["GOOGLE_APPLICATION_CREDENTIALS"]) as f:
values["auth_config"]["service_account_json"] = f.read()
return values
delete_secret_values(self, secret_id)
Deletes secret values for an existing secret.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
The ID of the secret. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if no secret values for the given ID are stored in the secrets store. |
RuntimeError |
if the GCP Secrets Manager API returns an unexpected error. |
Source code in zenml/zen_stores/secrets_stores/gcp_secrets_store.py
def delete_secret_values(self, secret_id: UUID) -> None:
"""Deletes secret values for an existing secret.
Args:
secret_id: The ID of the secret.
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
RuntimeError: if the GCP Secrets Manager API returns an unexpected
error.
"""
gcp_secret_name = self.client.secret_path(
self.config.project_id,
self._get_gcp_secret_name(secret_id=secret_id),
)
try:
self.client.delete_secret(request={"name": gcp_secret_name})
except google_exceptions.NotFound:
raise KeyError(f"Secret with ID {secret_id} not found")
except Exception as e:
raise RuntimeError(f"Failed to delete secret: {str(e)}") from e
logger.debug(f"Deleted GCP secret: {gcp_secret_name}")
get_secret_values(self, secret_id)
Get the secret values for an existing secret.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
ID of the secret. |
required |
Returns:
| Type | Description |
|---|---|
Dict[str, str] |
The secret values. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if no secret values for the given ID are stored in the secrets store. |
RuntimeError |
if the GCP Secrets Manager API returns an unexpected error. |
Source code in zenml/zen_stores/secrets_stores/gcp_secrets_store.py
def get_secret_values(self, secret_id: UUID) -> Dict[str, str]:
"""Get the secret values for an existing secret.
Args:
secret_id: ID of the secret.
Returns:
The secret values.
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
RuntimeError: if the GCP Secrets Manager API returns an unexpected
error.
"""
gcp_secret_name = self.client.secret_path(
self.config.project_id,
self._get_gcp_secret_name(secret_id=secret_id),
)
try:
secret = self.client.get_secret(name=gcp_secret_name)
secret_version_values = self.client.access_secret_version(
name=f"{gcp_secret_name}/versions/latest"
)
except google_exceptions.NotFound as e:
raise KeyError(
f"Can't find the secret values for secret ID '{secret_id}' "
f"in the secrets store back-end: {str(e)}"
) from e
except Exception as e:
raise RuntimeError(
f"Error fetching secret with ID {secret_id} {e}"
)
# The GCP secret labels do not really behave like a dictionary: when
# a key is not found, it does not raise a KeyError, but instead
# returns an empty string. That's why we make this conversion.
metadata = dict(secret.labels)
# The _verify_secret_metadata method raises a KeyError if the
# secret is not valid or does not belong to this server. Here we
# simply pass the exception up the stack, as if the secret was not found
# in the first place.
self._verify_secret_metadata(
secret_id=secret_id,
metadata=metadata,
)
secret_values = json.loads(
secret_version_values.payload.data.decode("UTF-8")
)
if not isinstance(secret_values, dict):
raise RuntimeError(
f"Google secret values for secret ID {gcp_secret_name} could "
"not be decoded: expected a dictionary."
)
logger.debug(f"Fetched GCP secret: {gcp_secret_name}")
return secret_values
store_secret_values(self, secret_id, secret_values)
Store secret values for a new secret.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
ID of the secret. |
required |
secret_values |
Dict[str, str] |
Values for the secret. |
required |
Exceptions:
| Type | Description |
|---|---|
RuntimeError |
if the GCP Secrets Manager API returns an unexpected error. |
Source code in zenml/zen_stores/secrets_stores/gcp_secrets_store.py
def store_secret_values(
self,
secret_id: UUID,
secret_values: Dict[str, str],
) -> None:
"""Store secret values for a new secret.
Args:
secret_id: ID of the secret.
secret_values: Values for the secret.
Raises:
RuntimeError: if the GCP Secrets Manager API returns an unexpected
error.
"""
secret_value = json.dumps(secret_values)
labels = self._get_secret_metadata(secret_id=secret_id)
try:
gcp_secret = self.client.create_secret(
request={
"parent": self.parent_name,
"secret_id": self._get_gcp_secret_name(secret_id),
"secret": {
"replication": {"automatic": {}},
"labels": labels,
},
}
)
logger.debug(f"Created empty GCP parent secret: {gcp_secret.name}")
self.client.add_secret_version(
request={
"parent": gcp_secret.name,
"payload": {"data": secret_value.encode()},
}
)
logger.debug(f"Added value to GCP secret {gcp_secret.name}")
except Exception as e:
raise RuntimeError(f"Failed to create secret.: {str(e)}") from e
logger.debug(f"Created GCP secret {gcp_secret.name}")
update_secret_values(self, secret_id, secret_values)
Updates secret values for an existing secret.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
The ID of the secret to be updated. |
required |
secret_values |
Dict[str, str] |
The new secret values. |
required |
Exceptions:
| Type | Description |
|---|---|
RuntimeError |
if the GCP Secrets Manager API returns an unexpected error. |
Source code in zenml/zen_stores/secrets_stores/gcp_secrets_store.py
def update_secret_values(
self,
secret_id: UUID,
secret_values: Dict[str, str],
) -> None:
"""Updates secret values for an existing secret.
Args:
secret_id: The ID of the secret to be updated.
secret_values: The new secret values.
Raises:
RuntimeError: if the GCP Secrets Manager API returns an unexpected
error.
"""
gcp_secret_name = self.client.secret_path(
self.config.project_id,
self._get_gcp_secret_name(secret_id=secret_id),
)
# Convert the ZenML secret metadata to GCP labels
metadata = self._get_secret_metadata(secret_id)
try:
# Update the secret metadata
update_secret = {
"name": gcp_secret_name,
"labels": metadata,
}
update_mask = {"paths": ["labels"]}
gcp_updated_secret = self.client.update_secret(
request={
"secret": update_secret,
"update_mask": update_mask,
}
)
# Add a new secret version
secret_value = json.dumps(secret_values)
self.client.add_secret_version(
request={
"parent": gcp_updated_secret.name,
"payload": {"data": secret_value.encode()},
}
)
except Exception as e:
raise RuntimeError(f"Error updating secret: {e}") from e
logger.debug(f"Updated GCP secret: {gcp_secret_name}")
GCPSecretsStoreConfiguration (ServiceConnectorSecretsStoreConfiguration)
pydantic-model
GCP secrets store configuration.
Attributes:
| Name | Type | Description |
|---|---|---|
type |
SecretsStoreType |
The type of the store. |
Source code in zenml/zen_stores/secrets_stores/gcp_secrets_store.py
class GCPSecretsStoreConfiguration(ServiceConnectorSecretsStoreConfiguration):
"""GCP secrets store configuration.
Attributes:
type: The type of the store.
"""
type: SecretsStoreType = SecretsStoreType.GCP
@property
def project_id(self) -> str:
"""Get the GCP project ID.
Returns:
The GCP project ID.
Raises:
ValueError: If the project ID is not set.
"""
project_id = self.auth_config.get("project_id")
if project_id:
return str(project_id)
raise ValueError("GCP `project_id` must be specified in auth_config.")
@root_validator(pre=True)
def populate_config(cls, values: Dict[str, Any]) -> Dict[str, Any]:
"""Populate the connector configuration from legacy attributes.
Args:
values: Dict representing user-specified runtime settings.
Returns:
Validated settings.
"""
# Search for legacy attributes and populate the connector configuration
# from them, if they exist.
if values.get("project_id"):
if not os.environ.get("GOOGLE_APPLICATION_CREDENTIALS"):
logger.warning(
"The `project_id` GCP secrets store attribute is "
"deprecated and will be removed in a future version of ZenML. "
"Please use the `auth_method` and `auth_config` attributes "
"instead. Using an implicit GCP authentication to access "
"the GCP Secrets Manager API."
)
values["auth_method"] = GCPAuthenticationMethods.IMPLICIT
values["auth_config"] = dict(
project_id=values.get("project_id"),
)
else:
logger.warning(
"The `project_id` GCP secrets store attribute and the "
"`GOOGLE_APPLICATION_CREDENTIALS` environment variable are "
"deprecated and will be removed in a future version of ZenML. "
"Please use the `auth_method` and `auth_config` attributes "
"instead."
)
values["auth_method"] = (
GCPAuthenticationMethods.SERVICE_ACCOUNT
)
values["auth_config"] = dict(
project_id=values.get("project_id"),
)
# Load the service account credentials from the file
with open(os.environ["GOOGLE_APPLICATION_CREDENTIALS"]) as f:
values["auth_config"]["service_account_json"] = f.read()
return values
class Config:
"""Pydantic configuration class."""
# Forbid extra attributes set in the class.
extra = "allow"
project_id: str
property
readonly
Get the GCP project ID.
Returns:
| Type | Description |
|---|---|
str |
The GCP project ID. |
Exceptions:
| Type | Description |
|---|---|
ValueError |
If the project ID is not set. |
Config
Pydantic configuration class.
Source code in zenml/zen_stores/secrets_stores/gcp_secrets_store.py
class Config:
"""Pydantic configuration class."""
# Forbid extra attributes set in the class.
extra = "allow"
populate_config(values)
classmethod
Populate the connector configuration from legacy attributes.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
values |
Dict[str, Any] |
Dict representing user-specified runtime settings. |
required |
Returns:
| Type | Description |
|---|---|
Dict[str, Any] |
Validated settings. |
Source code in zenml/zen_stores/secrets_stores/gcp_secrets_store.py
@root_validator(pre=True)
def populate_config(cls, values: Dict[str, Any]) -> Dict[str, Any]:
"""Populate the connector configuration from legacy attributes.
Args:
values: Dict representing user-specified runtime settings.
Returns:
Validated settings.
"""
# Search for legacy attributes and populate the connector configuration
# from them, if they exist.
if values.get("project_id"):
if not os.environ.get("GOOGLE_APPLICATION_CREDENTIALS"):
logger.warning(
"The `project_id` GCP secrets store attribute is "
"deprecated and will be removed in a future version of ZenML. "
"Please use the `auth_method` and `auth_config` attributes "
"instead. Using an implicit GCP authentication to access "
"the GCP Secrets Manager API."
)
values["auth_method"] = GCPAuthenticationMethods.IMPLICIT
values["auth_config"] = dict(
project_id=values.get("project_id"),
)
else:
logger.warning(
"The `project_id` GCP secrets store attribute and the "
"`GOOGLE_APPLICATION_CREDENTIALS` environment variable are "
"deprecated and will be removed in a future version of ZenML. "
"Please use the `auth_method` and `auth_config` attributes "
"instead."
)
values["auth_method"] = (
GCPAuthenticationMethods.SERVICE_ACCOUNT
)
values["auth_config"] = dict(
project_id=values.get("project_id"),
)
# Load the service account credentials from the file
with open(os.environ["GOOGLE_APPLICATION_CREDENTIALS"]) as f:
values["auth_config"]["service_account_json"] = f.read()
return values
hashicorp_secrets_store
HashiCorp Vault Secrets Store implementation.
HashiCorpVaultSecretsStore (BaseSecretsStore)
pydantic-model
Secrets store implementation that uses the HashiCorp Vault API.
This secrets store implementation uses the HashiCorp Vault API to store secrets. It allows a single HashiCorp Vault server to be shared with other ZenML deployments as well as other third party users and applications.
Here are some implementation highlights:
-
the name/ID of an HashiCorp Vault secret is derived from the ZenML secret UUID and a
zenmlprefix in the formzenml/{zenml_secret_uuid}. This clearly identifies a secret as being managed by ZenML in the HashiCorp Vault server. -
given that HashiCorp Vault secrets do not support attaching arbitrary metadata in the form of label or tags, we store the entire ZenML secret metadata alongside the secret values in the HashiCorp Vault secret value.
Attributes:
| Name | Type | Description |
|---|---|---|
config |
The configuration of the HashiCorp Vault secrets store. |
|
TYPE |
The type of the store. |
|
CONFIG_TYPE |
The type of the store configuration. |
Source code in zenml/zen_stores/secrets_stores/hashicorp_secrets_store.py
class HashiCorpVaultSecretsStore(BaseSecretsStore):
"""Secrets store implementation that uses the HashiCorp Vault API.
This secrets store implementation uses the HashiCorp Vault API to
store secrets. It allows a single HashiCorp Vault server to be shared with
other ZenML deployments as well as other third party users and applications.
Here are some implementation highlights:
* the name/ID of an HashiCorp Vault secret is derived from the ZenML secret
UUID and a `zenml` prefix in the form `zenml/{zenml_secret_uuid}`. This
clearly identifies a secret as being managed by ZenML in the HashiCorp Vault
server.
* given that HashiCorp Vault secrets do not support attaching arbitrary
metadata in the form of label or tags, we store the entire ZenML secret
metadata alongside the secret values in the HashiCorp Vault secret value.
Attributes:
config: The configuration of the HashiCorp Vault secrets store.
TYPE: The type of the store.
CONFIG_TYPE: The type of the store configuration.
"""
config: HashiCorpVaultSecretsStoreConfiguration
TYPE: ClassVar[SecretsStoreType] = SecretsStoreType.HASHICORP
CONFIG_TYPE: ClassVar[Type[SecretsStoreConfiguration]] = (
HashiCorpVaultSecretsStoreConfiguration
)
_client: Optional[hvac.Client] = None
@property
def client(self) -> hvac.Client:
"""Initialize and return the HashiCorp Vault client.
Returns:
The HashiCorp Vault client.
"""
if self._client is None:
# Initialize the HashiCorp Vault client with the
# credentials from the configuration.
self._client = hvac.Client(
url=self.config.vault_addr,
token=self.config.vault_token.get_secret_value()
if self.config.vault_token
else None,
namespace=self.config.vault_namespace,
)
self._client.secrets.kv.v2.configure(
max_versions=self.config.max_versions,
)
if self.config.mount_point:
self._client.secrets.kv.v2.configure(
mount_point=self.config.mount_point,
)
return self._client
# ====================================
# Secrets Store interface implementation
# ====================================
# --------------------------------
# Initialization and configuration
# --------------------------------
def _initialize(self) -> None:
"""Initialize the HashiCorp Vault secrets store."""
logger.debug("Initializing HashiCorpVaultSecretsStore")
# Initialize the HashiCorp Vault client early, just to catch any
# configuration or authentication errors early, before the Secrets
# Store is used.
_ = self.client
# ------
# Secrets
# ------
@staticmethod
def _get_vault_secret_id(
secret_id: UUID,
) -> str:
"""Get the HashiCorp Vault secret ID corresponding to a ZenML secret ID.
The convention used for HashiCorp Vault secret names is to use the ZenML
secret UUID prefixed with `zenml` as the HashiCorp Vault secret name,
i.e. `zenml/<secret_uuid>`.
Args:
secret_id: The ZenML secret ID.
Returns:
The HashiCorp Vault secret name.
"""
return f"{HVAC_ZENML_SECRET_NAME_PREFIX}/{str(secret_id)}"
def store_secret_values(
self,
secret_id: UUID,
secret_values: Dict[str, str],
) -> None:
"""Store secret values for a new secret.
Args:
secret_id: ID of the secret.
secret_values: Values for the secret.
Raises:
RuntimeError: If the HashiCorp Vault API returns an unexpected
error.
"""
vault_secret_id = self._get_vault_secret_id(secret_id)
metadata = self._get_secret_metadata(secret_id=secret_id)
try:
self.client.secrets.kv.v2.create_or_update_secret(
path=vault_secret_id,
# Store the ZenML secret metadata alongside the secret values
secret={
ZENML_VAULT_SECRET_VALUES_KEY: secret_values,
ZENML_VAULT_SECRET_METADATA_KEY: metadata,
},
# Do not allow overwriting an existing secret
cas=0,
)
except VaultError as e:
raise RuntimeError(f"Error creating secret: {e}")
logger.debug(f"Created HashiCorp Vault secret: {vault_secret_id}")
def get_secret_values(self, secret_id: UUID) -> Dict[str, str]:
"""Get the secret values for an existing secret.
Args:
secret_id: ID of the secret.
Returns:
The secret values.
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
RuntimeError: If the HashiCorp Vault API returns an unexpected
error.
"""
vault_secret_id = self._get_vault_secret_id(secret_id)
try:
vault_secret = (
self.client.secrets.kv.v2.read_secret(
path=vault_secret_id,
)
.get("data", {})
.get("data", {})
)
except InvalidPath as e:
raise KeyError(
f"Can't find the secret values for secret ID '{secret_id}' "
f"in the secrets store back-end: {str(e)}"
) from e
except VaultError as e:
raise RuntimeError(
f"Error fetching secret with ID {secret_id} {e}"
)
try:
metadata = vault_secret[ZENML_VAULT_SECRET_METADATA_KEY]
values = vault_secret[ZENML_VAULT_SECRET_VALUES_KEY]
except (KeyError, ValueError) as e:
raise KeyError(
f"Secret could not be retrieved: missing required metadata: {e}"
)
if not isinstance(values, dict) or not isinstance(metadata, dict):
raise RuntimeError(
f"HashiCorp Vault secret values for secret {vault_secret_id} "
"could not be retrieved: invalid type for metadata or values"
)
# The _verify_secret_metadata method raises a KeyError if the
# secret is not valid or does not belong to this server. Here we
# simply pass the exception up the stack, as if the secret was not found
# in the first place.
self._verify_secret_metadata(
secret_id=secret_id,
metadata=metadata,
)
logger.debug(f"Fetched HashiCorp Vault secret: {vault_secret_id}")
return values
def update_secret_values(
self,
secret_id: UUID,
secret_values: Dict[str, str],
) -> None:
"""Updates secret values for an existing secret.
Args:
secret_id: The ID of the secret to be updated.
secret_values: The new secret values.
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
RuntimeError: If the HashiCorp Vault API returns an unexpected
error.
"""
vault_secret_id = self._get_vault_secret_id(secret_id)
# Convert the ZenML secret metadata to HashiCorp Vault tags
metadata = self._get_secret_metadata(secret_id=secret_id)
try:
self.client.secrets.kv.v2.create_or_update_secret(
path=vault_secret_id,
# Store the ZenML secret metadata alongside the secret values
secret={
ZENML_VAULT_SECRET_VALUES_KEY: secret_values,
ZENML_VAULT_SECRET_METADATA_KEY: metadata,
},
)
except InvalidPath:
raise KeyError(f"Secret with ID {secret_id} does not exist.")
except VaultError as e:
raise RuntimeError(f"Error updating secret {secret_id}: {e}")
logger.debug(f"Updated HashiCorp Vault secret: {vault_secret_id}")
def delete_secret_values(self, secret_id: UUID) -> None:
"""Deletes secret values for an existing secret.
Args:
secret_id: The ID of the secret.
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
RuntimeError: If the HashiCorp Vault API returns an unexpected
error.
"""
vault_secret_id = self._get_vault_secret_id(secret_id)
try:
self.client.secrets.kv.v2.delete_metadata_and_all_versions(
path=vault_secret_id,
)
except InvalidPath:
raise KeyError(f"Secret with ID {secret_id} does not exist.")
except VaultError as e:
raise RuntimeError(
f"Error deleting secret with ID {secret_id}: {e}"
)
logger.debug(f"Deleted HashiCorp Vault secret: {vault_secret_id}")
client: hvac.Client
property
readonly
Initialize and return the HashiCorp Vault client.
Returns:
| Type | Description |
|---|---|
hvac.Client |
The HashiCorp Vault client. |
CONFIG_TYPE (SecretsStoreConfiguration)
pydantic-model
HashiCorp Vault secrets store configuration.
Attributes:
| Name | Type | Description |
|---|---|---|
type |
SecretsStoreType |
The type of the store. |
vault_addr |
str |
The url of the Vault server. If not set, the value will be loaded from the VAULT_ADDR environment variable, if configured. |
vault_token |
Optional[pydantic.types.SecretStr] |
The token used to authenticate with the Vault server. If not set, the token will be loaded from the VAULT_TOKEN environment variable or from the ~/.vault-token file, if configured. |
vault_namespace |
Optional[str] |
The Vault Enterprise namespace. |
mount_point |
Optional[str] |
The mount point to use for all secrets. |
max_versions |
int |
The maximum number of secret versions to keep. |
Source code in zenml/zen_stores/secrets_stores/hashicorp_secrets_store.py
class HashiCorpVaultSecretsStoreConfiguration(SecretsStoreConfiguration):
"""HashiCorp Vault secrets store configuration.
Attributes:
type: The type of the store.
vault_addr: The url of the Vault server. If not set, the value will be
loaded from the VAULT_ADDR environment variable, if configured.
vault_token: The token used to authenticate with the Vault server. If
not set, the token will be loaded from the VAULT_TOKEN environment
variable or from the ~/.vault-token file, if configured.
vault_namespace: The Vault Enterprise namespace.
mount_point: The mount point to use for all secrets.
max_versions: The maximum number of secret versions to keep.
"""
type: SecretsStoreType = SecretsStoreType.HASHICORP
vault_addr: str
vault_token: Optional[SecretStr] = None
vault_namespace: Optional[str] = None
mount_point: Optional[str] = None
max_versions: int = 1
class Config:
"""Pydantic configuration class."""
# Forbid extra attributes set in the class.
extra = "forbid"
Config
Pydantic configuration class.
Source code in zenml/zen_stores/secrets_stores/hashicorp_secrets_store.py
class Config:
"""Pydantic configuration class."""
# Forbid extra attributes set in the class.
extra = "forbid"
delete_secret_values(self, secret_id)
Deletes secret values for an existing secret.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
The ID of the secret. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if no secret values for the given ID are stored in the secrets store. |
RuntimeError |
If the HashiCorp Vault API returns an unexpected error. |
Source code in zenml/zen_stores/secrets_stores/hashicorp_secrets_store.py
def delete_secret_values(self, secret_id: UUID) -> None:
"""Deletes secret values for an existing secret.
Args:
secret_id: The ID of the secret.
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
RuntimeError: If the HashiCorp Vault API returns an unexpected
error.
"""
vault_secret_id = self._get_vault_secret_id(secret_id)
try:
self.client.secrets.kv.v2.delete_metadata_and_all_versions(
path=vault_secret_id,
)
except InvalidPath:
raise KeyError(f"Secret with ID {secret_id} does not exist.")
except VaultError as e:
raise RuntimeError(
f"Error deleting secret with ID {secret_id}: {e}"
)
logger.debug(f"Deleted HashiCorp Vault secret: {vault_secret_id}")
get_secret_values(self, secret_id)
Get the secret values for an existing secret.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
ID of the secret. |
required |
Returns:
| Type | Description |
|---|---|
Dict[str, str] |
The secret values. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if no secret values for the given ID are stored in the secrets store. |
RuntimeError |
If the HashiCorp Vault API returns an unexpected error. |
Source code in zenml/zen_stores/secrets_stores/hashicorp_secrets_store.py
def get_secret_values(self, secret_id: UUID) -> Dict[str, str]:
"""Get the secret values for an existing secret.
Args:
secret_id: ID of the secret.
Returns:
The secret values.
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
RuntimeError: If the HashiCorp Vault API returns an unexpected
error.
"""
vault_secret_id = self._get_vault_secret_id(secret_id)
try:
vault_secret = (
self.client.secrets.kv.v2.read_secret(
path=vault_secret_id,
)
.get("data", {})
.get("data", {})
)
except InvalidPath as e:
raise KeyError(
f"Can't find the secret values for secret ID '{secret_id}' "
f"in the secrets store back-end: {str(e)}"
) from e
except VaultError as e:
raise RuntimeError(
f"Error fetching secret with ID {secret_id} {e}"
)
try:
metadata = vault_secret[ZENML_VAULT_SECRET_METADATA_KEY]
values = vault_secret[ZENML_VAULT_SECRET_VALUES_KEY]
except (KeyError, ValueError) as e:
raise KeyError(
f"Secret could not be retrieved: missing required metadata: {e}"
)
if not isinstance(values, dict) or not isinstance(metadata, dict):
raise RuntimeError(
f"HashiCorp Vault secret values for secret {vault_secret_id} "
"could not be retrieved: invalid type for metadata or values"
)
# The _verify_secret_metadata method raises a KeyError if the
# secret is not valid or does not belong to this server. Here we
# simply pass the exception up the stack, as if the secret was not found
# in the first place.
self._verify_secret_metadata(
secret_id=secret_id,
metadata=metadata,
)
logger.debug(f"Fetched HashiCorp Vault secret: {vault_secret_id}")
return values
store_secret_values(self, secret_id, secret_values)
Store secret values for a new secret.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
ID of the secret. |
required |
secret_values |
Dict[str, str] |
Values for the secret. |
required |
Exceptions:
| Type | Description |
|---|---|
RuntimeError |
If the HashiCorp Vault API returns an unexpected error. |
Source code in zenml/zen_stores/secrets_stores/hashicorp_secrets_store.py
def store_secret_values(
self,
secret_id: UUID,
secret_values: Dict[str, str],
) -> None:
"""Store secret values for a new secret.
Args:
secret_id: ID of the secret.
secret_values: Values for the secret.
Raises:
RuntimeError: If the HashiCorp Vault API returns an unexpected
error.
"""
vault_secret_id = self._get_vault_secret_id(secret_id)
metadata = self._get_secret_metadata(secret_id=secret_id)
try:
self.client.secrets.kv.v2.create_or_update_secret(
path=vault_secret_id,
# Store the ZenML secret metadata alongside the secret values
secret={
ZENML_VAULT_SECRET_VALUES_KEY: secret_values,
ZENML_VAULT_SECRET_METADATA_KEY: metadata,
},
# Do not allow overwriting an existing secret
cas=0,
)
except VaultError as e:
raise RuntimeError(f"Error creating secret: {e}")
logger.debug(f"Created HashiCorp Vault secret: {vault_secret_id}")
update_secret_values(self, secret_id, secret_values)
Updates secret values for an existing secret.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
The ID of the secret to be updated. |
required |
secret_values |
Dict[str, str] |
The new secret values. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if no secret values for the given ID are stored in the secrets store. |
RuntimeError |
If the HashiCorp Vault API returns an unexpected error. |
Source code in zenml/zen_stores/secrets_stores/hashicorp_secrets_store.py
def update_secret_values(
self,
secret_id: UUID,
secret_values: Dict[str, str],
) -> None:
"""Updates secret values for an existing secret.
Args:
secret_id: The ID of the secret to be updated.
secret_values: The new secret values.
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
RuntimeError: If the HashiCorp Vault API returns an unexpected
error.
"""
vault_secret_id = self._get_vault_secret_id(secret_id)
# Convert the ZenML secret metadata to HashiCorp Vault tags
metadata = self._get_secret_metadata(secret_id=secret_id)
try:
self.client.secrets.kv.v2.create_or_update_secret(
path=vault_secret_id,
# Store the ZenML secret metadata alongside the secret values
secret={
ZENML_VAULT_SECRET_VALUES_KEY: secret_values,
ZENML_VAULT_SECRET_METADATA_KEY: metadata,
},
)
except InvalidPath:
raise KeyError(f"Secret with ID {secret_id} does not exist.")
except VaultError as e:
raise RuntimeError(f"Error updating secret {secret_id}: {e}")
logger.debug(f"Updated HashiCorp Vault secret: {vault_secret_id}")
HashiCorpVaultSecretsStoreConfiguration (SecretsStoreConfiguration)
pydantic-model
HashiCorp Vault secrets store configuration.
Attributes:
| Name | Type | Description |
|---|---|---|
type |
SecretsStoreType |
The type of the store. |
vault_addr |
str |
The url of the Vault server. If not set, the value will be loaded from the VAULT_ADDR environment variable, if configured. |
vault_token |
Optional[pydantic.types.SecretStr] |
The token used to authenticate with the Vault server. If not set, the token will be loaded from the VAULT_TOKEN environment variable or from the ~/.vault-token file, if configured. |
vault_namespace |
Optional[str] |
The Vault Enterprise namespace. |
mount_point |
Optional[str] |
The mount point to use for all secrets. |
max_versions |
int |
The maximum number of secret versions to keep. |
Source code in zenml/zen_stores/secrets_stores/hashicorp_secrets_store.py
class HashiCorpVaultSecretsStoreConfiguration(SecretsStoreConfiguration):
"""HashiCorp Vault secrets store configuration.
Attributes:
type: The type of the store.
vault_addr: The url of the Vault server. If not set, the value will be
loaded from the VAULT_ADDR environment variable, if configured.
vault_token: The token used to authenticate with the Vault server. If
not set, the token will be loaded from the VAULT_TOKEN environment
variable or from the ~/.vault-token file, if configured.
vault_namespace: The Vault Enterprise namespace.
mount_point: The mount point to use for all secrets.
max_versions: The maximum number of secret versions to keep.
"""
type: SecretsStoreType = SecretsStoreType.HASHICORP
vault_addr: str
vault_token: Optional[SecretStr] = None
vault_namespace: Optional[str] = None
mount_point: Optional[str] = None
max_versions: int = 1
class Config:
"""Pydantic configuration class."""
# Forbid extra attributes set in the class.
extra = "forbid"
Config
Pydantic configuration class.
Source code in zenml/zen_stores/secrets_stores/hashicorp_secrets_store.py
class Config:
"""Pydantic configuration class."""
# Forbid extra attributes set in the class.
extra = "forbid"
secrets_store_interface
ZenML secrets store interface.
SecretsStoreInterface (ABC)
ZenML secrets store interface.
All ZenML secrets stores must implement the methods in this interface.
Source code in zenml/zen_stores/secrets_stores/secrets_store_interface.py
class SecretsStoreInterface(ABC):
"""ZenML secrets store interface.
All ZenML secrets stores must implement the methods in this interface.
"""
# ---------------------------------
# Initialization and configuration
# ---------------------------------
@abstractmethod
def _initialize(self) -> None:
"""Initialize the secrets store.
This method is called immediately after the secrets store is created.
It should be used to set up the backend (database, connection etc.).
"""
# ---------
# Secrets
# ---------
@abstractmethod
def store_secret_values(
self,
secret_id: UUID,
secret_values: Dict[str, str],
) -> None:
"""Store secret values for a new secret.
Args:
secret_id: ID of the secret.
secret_values: Values for the secret.
"""
@abstractmethod
def get_secret_values(self, secret_id: UUID) -> Dict[str, str]:
"""Get the secret values for an existing secret.
Args:
secret_id: ID of the secret.
Returns:
The secret values.
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
"""
@abstractmethod
def update_secret_values(
self,
secret_id: UUID,
secret_values: Dict[str, str],
) -> None:
"""Updates secret values for an existing secret.
Args:
secret_id: The ID of the secret to be updated.
secret_values: The new secret values.
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
"""
@abstractmethod
def delete_secret_values(self, secret_id: UUID) -> None:
"""Deletes secret values for an existing secret.
Args:
secret_id: The ID of the secret.
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
"""
delete_secret_values(self, secret_id)
Deletes secret values for an existing secret.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
The ID of the secret. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if no secret values for the given ID are stored in the secrets store. |
Source code in zenml/zen_stores/secrets_stores/secrets_store_interface.py
@abstractmethod
def delete_secret_values(self, secret_id: UUID) -> None:
"""Deletes secret values for an existing secret.
Args:
secret_id: The ID of the secret.
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
"""
get_secret_values(self, secret_id)
Get the secret values for an existing secret.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
ID of the secret. |
required |
Returns:
| Type | Description |
|---|---|
Dict[str, str] |
The secret values. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if no secret values for the given ID are stored in the secrets store. |
Source code in zenml/zen_stores/secrets_stores/secrets_store_interface.py
@abstractmethod
def get_secret_values(self, secret_id: UUID) -> Dict[str, str]:
"""Get the secret values for an existing secret.
Args:
secret_id: ID of the secret.
Returns:
The secret values.
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
"""
store_secret_values(self, secret_id, secret_values)
Store secret values for a new secret.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
ID of the secret. |
required |
secret_values |
Dict[str, str] |
Values for the secret. |
required |
Source code in zenml/zen_stores/secrets_stores/secrets_store_interface.py
@abstractmethod
def store_secret_values(
self,
secret_id: UUID,
secret_values: Dict[str, str],
) -> None:
"""Store secret values for a new secret.
Args:
secret_id: ID of the secret.
secret_values: Values for the secret.
"""
update_secret_values(self, secret_id, secret_values)
Updates secret values for an existing secret.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
The ID of the secret to be updated. |
required |
secret_values |
Dict[str, str] |
The new secret values. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if no secret values for the given ID are stored in the secrets store. |
Source code in zenml/zen_stores/secrets_stores/secrets_store_interface.py
@abstractmethod
def update_secret_values(
self,
secret_id: UUID,
secret_values: Dict[str, str],
) -> None:
"""Updates secret values for an existing secret.
Args:
secret_id: The ID of the secret to be updated.
secret_values: The new secret values.
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
"""
service_connector_secrets_store
Base secrets store class used for all secrets stores that use a service connector.
ServiceConnectorSecretsStore (BaseSecretsStore)
pydantic-model
Base secrets store class for service connector-based secrets stores.
All secrets store implementations that use a Service Connector to authenticate and connect to the secrets store back-end should inherit from this class and:
- implement the
_initialize_client_from_connectormethod - use a configuration class that inherits from
ServiceConnectorSecretsStoreConfiguration - set the
SERVICE_CONNECTOR_TYPEto the service connector type used to connect to the secrets store back-end - set the
SERVICE_CONNECTOR_RESOURCE_TYPEto the resource type used to connect to the secrets store back-end
Source code in zenml/zen_stores/secrets_stores/service_connector_secrets_store.py
class ServiceConnectorSecretsStore(BaseSecretsStore):
"""Base secrets store class for service connector-based secrets stores.
All secrets store implementations that use a Service Connector to
authenticate and connect to the secrets store back-end should inherit from
this class and:
* implement the `_initialize_client_from_connector` method
* use a configuration class that inherits from
`ServiceConnectorSecretsStoreConfiguration`
* set the `SERVICE_CONNECTOR_TYPE` to the service connector type used
to connect to the secrets store back-end
* set the `SERVICE_CONNECTOR_RESOURCE_TYPE` to the resource type used
to connect to the secrets store back-end
"""
config: ServiceConnectorSecretsStoreConfiguration
CONFIG_TYPE: ClassVar[Type[ServiceConnectorSecretsStoreConfiguration]]
SERVICE_CONNECTOR_TYPE: ClassVar[str]
SERVICE_CONNECTOR_RESOURCE_TYPE: ClassVar[str]
_connector: Optional[ServiceConnector] = None
_client: Optional[Any] = None
_lock: Optional[Lock] = None
def _initialize(self) -> None:
"""Initialize the secrets store."""
self._lock = Lock()
# Initialize the client early, just to catch any configuration or
# authentication errors early, before the Secrets Store is used.
_ = self.client
def _get_client(self) -> Any:
"""Initialize and return the secrets store API client.
Returns:
The secrets store API client object.
"""
if self._connector is not None:
# If the client connector expires, we'll try to get a new one.
if self._connector.has_expired():
self._connector = None
self._client = None
if self._connector is None:
# Initialize a base service connector with the credentials from
# the configuration.
request = ServiceConnectorRequest(
name="secrets-store",
connector_type=self.SERVICE_CONNECTOR_TYPE,
resource_types=[self.SERVICE_CONNECTOR_RESOURCE_TYPE],
user=uuid4(), # Use a fake user ID
workspace=uuid4(), # Use a fake workspace ID
auth_method=self.config.auth_method,
configuration=self.config.auth_config,
)
base_connector = service_connector_registry.instantiate_connector(
model=request
)
# Set the `allow_implicit_auth_methods` flag to `True` to allow
# implicit authentication methods to be used even when not globally
# enabled via the `ZENML_ENABLE_IMPLICIT_AUTH_METHODS` environment
# variable.
base_connector.allow_implicit_auth_methods = True
self._connector = base_connector.get_connector_client()
if self._client is None:
# Use the connector to get a client object.
client = self._connector.connect(
# Don't verify again because we already did that when we
# initialized the connector.
verify=False
)
self._client = self._initialize_client_from_connector(client)
return self._client
@property
def lock(self) -> Lock:
"""Get the lock used to treat the client initialization as a critical section.
Returns:
The lock instance.
"""
assert self._lock is not None
return self._lock
@property
def client(self) -> Any:
"""Get the secrets store API client.
Returns:
The secrets store API client instance.
"""
# Multiple API calls can be made to this secrets store in the context
# of different threads. We want to make sure that we only initialize
# the client once, and then reuse it. We have to use a lock to treat
# this method as a critical section.
with self.lock:
return self._get_client()
@abstractmethod
def _initialize_client_from_connector(self, client: Any) -> Any:
"""Initialize the client from the service connector.
Args:
client: The authenticated client object returned by the service
connector.
Returns:
The initialized client instance.
"""
client: Any
property
readonly
Get the secrets store API client.
Returns:
| Type | Description |
|---|---|
Any |
The secrets store API client instance. |
lock: <built-in function allocate_lock>
property
readonly
Get the lock used to treat the client initialization as a critical section.
Returns:
| Type | Description |
|---|---|
<built-in function allocate_lock> |
The lock instance. |
ServiceConnectorSecretsStoreConfiguration (SecretsStoreConfiguration)
pydantic-model
Base configuration for secrets stores that use a service connector.
Attributes:
| Name | Type | Description |
|---|---|---|
auth_method |
str |
The service connector authentication method to use. |
auth_config |
Dict[str, Any] |
The service connector authentication configuration. |
Source code in zenml/zen_stores/secrets_stores/service_connector_secrets_store.py
class ServiceConnectorSecretsStoreConfiguration(SecretsStoreConfiguration):
"""Base configuration for secrets stores that use a service connector.
Attributes:
auth_method: The service connector authentication method to use.
auth_config: The service connector authentication configuration.
"""
auth_method: str
auth_config: Dict[str, Any] = Field(default_factory=dict)
@root_validator(pre=True)
def validate_auth_config(cls, values: Dict[str, Any]) -> Dict[str, Any]:
"""Convert the authentication configuration if given in JSON format.
Args:
values: The configuration values.
Returns:
The validated configuration values.
Raises:
ValueError: If the authentication configuration is not a valid
JSON object.
"""
if isinstance(values.get("auth_config"), str):
try:
values["auth_config"] = json.loads(values["auth_config"])
except json.JSONDecodeError as e:
raise ValueError(
f"The authentication configuration is not a valid JSON "
f"object: {e}"
)
return values
validate_auth_config(values)
classmethod
Convert the authentication configuration if given in JSON format.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
values |
Dict[str, Any] |
The configuration values. |
required |
Returns:
| Type | Description |
|---|---|
Dict[str, Any] |
The validated configuration values. |
Exceptions:
| Type | Description |
|---|---|
ValueError |
If the authentication configuration is not a valid JSON object. |
Source code in zenml/zen_stores/secrets_stores/service_connector_secrets_store.py
@root_validator(pre=True)
def validate_auth_config(cls, values: Dict[str, Any]) -> Dict[str, Any]:
"""Convert the authentication configuration if given in JSON format.
Args:
values: The configuration values.
Returns:
The validated configuration values.
Raises:
ValueError: If the authentication configuration is not a valid
JSON object.
"""
if isinstance(values.get("auth_config"), str):
try:
values["auth_config"] = json.loads(values["auth_config"])
except json.JSONDecodeError as e:
raise ValueError(
f"The authentication configuration is not a valid JSON "
f"object: {e}"
)
return values
sql_secrets_store
SQL Secrets Store implementation.
SqlSecretsStore (BaseSecretsStore)
pydantic-model
Secrets store implementation that uses the SQL ZenML store as a backend.
This secrets store piggybacks on the SQL ZenML store. It uses the same database and configuration as the SQL ZenML store.
Attributes:
| Name | Type | Description |
|---|---|---|
config |
The configuration of the SQL secrets store. |
|
TYPE |
The type of the store. |
|
CONFIG_TYPE |
The type of the store configuration. |
Source code in zenml/zen_stores/secrets_stores/sql_secrets_store.py
class SqlSecretsStore(BaseSecretsStore):
"""Secrets store implementation that uses the SQL ZenML store as a backend.
This secrets store piggybacks on the SQL ZenML store. It uses the same
database and configuration as the SQL ZenML store.
Attributes:
config: The configuration of the SQL secrets store.
TYPE: The type of the store.
CONFIG_TYPE: The type of the store configuration.
"""
config: SqlSecretsStoreConfiguration
TYPE: ClassVar[SecretsStoreType] = SecretsStoreType.SQL
CONFIG_TYPE: ClassVar[Type[SecretsStoreConfiguration]] = (
SqlSecretsStoreConfiguration
)
_encryption_engine: Optional[AesGcmEngine] = None
def __init__(
self,
zen_store: "BaseZenStore",
**kwargs: Any,
) -> None:
"""Create and initialize the SQL secrets store.
Args:
zen_store: The ZenML store that owns this SQL secrets store.
**kwargs: Additional keyword arguments to pass to the Pydantic
constructor.
Raises:
IllegalOperationError: If the ZenML store to which this secrets
store belongs is not a SQL ZenML store.
"""
from zenml.zen_stores.sql_zen_store import SqlZenStore
if not isinstance(zen_store, SqlZenStore):
raise IllegalOperationError(
"The SQL secrets store can only be used with the SQL ZenML "
"store."
)
super().__init__(zen_store, **kwargs)
@property
def engine(self) -> Engine:
"""The SQLAlchemy engine.
Returns:
The SQLAlchemy engine.
"""
return self.zen_store.engine
@property
def zen_store(self) -> "SqlZenStore":
"""The ZenML store that this SQL secrets store is using as a back-end.
Returns:
The ZenML store that this SQL secrets store is using as a back-end.
Raises:
ValueError: If the store is not initialized.
"""
from zenml.zen_stores.sql_zen_store import SqlZenStore
if not self._zen_store:
raise ValueError("Store not initialized")
assert isinstance(self._zen_store, SqlZenStore)
return self._zen_store
# ====================================
# Secrets Store interface implementation
# ====================================
# --------------------------------
# Initialization and configuration
# --------------------------------
def _initialize(self) -> None:
"""Initialize the secrets SQL store."""
logger.debug("Initializing SqlSecretsStore")
# Initialize the encryption engine
if self.config.encryption_key:
self._encryption_engine = AesGcmEngine()
self._encryption_engine._update_key(self.config.encryption_key)
# Nothing else to do here, the SQL ZenML store back-end is already
# initialized
# ------
# Secrets
# ------
def store_secret_values(
self,
secret_id: UUID,
secret_values: Dict[str, str],
) -> None:
"""Store secret values for a new secret.
The secret is already created in the database by the SQL Zen store, this
method only stores the secret values.
Args:
secret_id: ID of the secret.
secret_values: Values for the secret.
Raises:
KeyError: if a secret for the given ID is not found.
"""
with Session(self.engine) as session:
secret_in_db = session.exec(
select(SecretSchema).where(SecretSchema.id == secret_id)
).first()
if secret_in_db is None:
raise KeyError(f"Secret with ID {secret_id} not found.")
secret_in_db.set_secret_values(
secret_values=secret_values,
encryption_engine=self._encryption_engine,
)
session.add(secret_in_db)
session.commit()
def get_secret_values(self, secret_id: UUID) -> Dict[str, str]:
"""Get the secret values for an existing secret.
Args:
secret_id: ID of the secret.
Returns:
The secret values.
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
"""
with Session(self.engine) as session:
secret_in_db = session.exec(
select(SecretSchema).where(SecretSchema.id == secret_id)
).first()
if secret_in_db is None:
raise KeyError(f"Secret with ID {secret_id} not found.")
try:
return secret_in_db.get_secret_values(
encryption_engine=self._encryption_engine,
)
except SecretDecodeError:
raise KeyError(
f"Secret values for secret {secret_id} could not be "
f"decoded. This can happen if encryption has "
f"been enabled/disabled or if the encryption key has been "
"reconfigured without proper secrets migration."
)
def update_secret_values(
self,
secret_id: UUID,
secret_values: Dict[str, str],
) -> None:
"""Updates secret values for an existing secret.
Args:
secret_id: The ID of the secret to be updated.
secret_values: The new secret values.
"""
self.store_secret_values(secret_id, secret_values)
def delete_secret_values(self, secret_id: UUID) -> None:
"""Deletes secret values for an existing secret.
Args:
secret_id: The ID of the secret.
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
"""
with Session(self.engine) as session:
try:
secret_in_db = session.exec(
select(SecretSchema).where(SecretSchema.id == secret_id)
).one()
secret_in_db.values = None
session.commit()
except NoResultFound:
raise KeyError(f"Secret with ID {secret_id} not found.")
engine: Engine
property
readonly
The SQLAlchemy engine.
Returns:
| Type | Description |
|---|---|
Engine |
The SQLAlchemy engine. |
zen_store: SqlZenStore
property
readonly
The ZenML store that this SQL secrets store is using as a back-end.
Returns:
| Type | Description |
|---|---|
SqlZenStore |
The ZenML store that this SQL secrets store is using as a back-end. |
Exceptions:
| Type | Description |
|---|---|
ValueError |
If the store is not initialized. |
CONFIG_TYPE (SecretsStoreConfiguration)
pydantic-model
SQL secrets store configuration.
Attributes:
| Name | Type | Description |
|---|---|---|
type |
SecretsStoreType |
The type of the store. |
encryption_key |
Optional[str] |
The encryption key to use for the SQL secrets store. If not set, the passwords will not be encrypted in the database. |
Source code in zenml/zen_stores/secrets_stores/sql_secrets_store.py
class SqlSecretsStoreConfiguration(SecretsStoreConfiguration):
"""SQL secrets store configuration.
Attributes:
type: The type of the store.
encryption_key: The encryption key to use for the SQL secrets store.
If not set, the passwords will not be encrypted in the database.
"""
type: SecretsStoreType = SecretsStoreType.SQL
encryption_key: Optional[str] = None
class Config:
"""Pydantic configuration class."""
# Don't validate attributes when assigning them. This is necessary
# because the certificate attributes can be expanded to the contents
# of the certificate files.
validate_assignment = False
# Forbid extra attributes set in the class.
extra = "forbid"
Config
Pydantic configuration class.
Source code in zenml/zen_stores/secrets_stores/sql_secrets_store.py
class Config:
"""Pydantic configuration class."""
# Don't validate attributes when assigning them. This is necessary
# because the certificate attributes can be expanded to the contents
# of the certificate files.
validate_assignment = False
# Forbid extra attributes set in the class.
extra = "forbid"
__init__(self, zen_store, **kwargs)
special
Create and initialize the SQL secrets store.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
zen_store |
BaseZenStore |
The ZenML store that owns this SQL secrets store. |
required |
**kwargs |
Any |
Additional keyword arguments to pass to the Pydantic constructor. |
{} |
Exceptions:
| Type | Description |
|---|---|
IllegalOperationError |
If the ZenML store to which this secrets store belongs is not a SQL ZenML store. |
Source code in zenml/zen_stores/secrets_stores/sql_secrets_store.py
def __init__(
self,
zen_store: "BaseZenStore",
**kwargs: Any,
) -> None:
"""Create and initialize the SQL secrets store.
Args:
zen_store: The ZenML store that owns this SQL secrets store.
**kwargs: Additional keyword arguments to pass to the Pydantic
constructor.
Raises:
IllegalOperationError: If the ZenML store to which this secrets
store belongs is not a SQL ZenML store.
"""
from zenml.zen_stores.sql_zen_store import SqlZenStore
if not isinstance(zen_store, SqlZenStore):
raise IllegalOperationError(
"The SQL secrets store can only be used with the SQL ZenML "
"store."
)
super().__init__(zen_store, **kwargs)
delete_secret_values(self, secret_id)
Deletes secret values for an existing secret.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
The ID of the secret. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if no secret values for the given ID are stored in the secrets store. |
Source code in zenml/zen_stores/secrets_stores/sql_secrets_store.py
def delete_secret_values(self, secret_id: UUID) -> None:
"""Deletes secret values for an existing secret.
Args:
secret_id: The ID of the secret.
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
"""
with Session(self.engine) as session:
try:
secret_in_db = session.exec(
select(SecretSchema).where(SecretSchema.id == secret_id)
).one()
secret_in_db.values = None
session.commit()
except NoResultFound:
raise KeyError(f"Secret with ID {secret_id} not found.")
get_secret_values(self, secret_id)
Get the secret values for an existing secret.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
ID of the secret. |
required |
Returns:
| Type | Description |
|---|---|
Dict[str, str] |
The secret values. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if no secret values for the given ID are stored in the secrets store. |
Source code in zenml/zen_stores/secrets_stores/sql_secrets_store.py
def get_secret_values(self, secret_id: UUID) -> Dict[str, str]:
"""Get the secret values for an existing secret.
Args:
secret_id: ID of the secret.
Returns:
The secret values.
Raises:
KeyError: if no secret values for the given ID are stored in the
secrets store.
"""
with Session(self.engine) as session:
secret_in_db = session.exec(
select(SecretSchema).where(SecretSchema.id == secret_id)
).first()
if secret_in_db is None:
raise KeyError(f"Secret with ID {secret_id} not found.")
try:
return secret_in_db.get_secret_values(
encryption_engine=self._encryption_engine,
)
except SecretDecodeError:
raise KeyError(
f"Secret values for secret {secret_id} could not be "
f"decoded. This can happen if encryption has "
f"been enabled/disabled or if the encryption key has been "
"reconfigured without proper secrets migration."
)
store_secret_values(self, secret_id, secret_values)
Store secret values for a new secret.
The secret is already created in the database by the SQL Zen store, this method only stores the secret values.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
ID of the secret. |
required |
secret_values |
Dict[str, str] |
Values for the secret. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if a secret for the given ID is not found. |
Source code in zenml/zen_stores/secrets_stores/sql_secrets_store.py
def store_secret_values(
self,
secret_id: UUID,
secret_values: Dict[str, str],
) -> None:
"""Store secret values for a new secret.
The secret is already created in the database by the SQL Zen store, this
method only stores the secret values.
Args:
secret_id: ID of the secret.
secret_values: Values for the secret.
Raises:
KeyError: if a secret for the given ID is not found.
"""
with Session(self.engine) as session:
secret_in_db = session.exec(
select(SecretSchema).where(SecretSchema.id == secret_id)
).first()
if secret_in_db is None:
raise KeyError(f"Secret with ID {secret_id} not found.")
secret_in_db.set_secret_values(
secret_values=secret_values,
encryption_engine=self._encryption_engine,
)
session.add(secret_in_db)
session.commit()
update_secret_values(self, secret_id, secret_values)
Updates secret values for an existing secret.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
The ID of the secret to be updated. |
required |
secret_values |
Dict[str, str] |
The new secret values. |
required |
Source code in zenml/zen_stores/secrets_stores/sql_secrets_store.py
def update_secret_values(
self,
secret_id: UUID,
secret_values: Dict[str, str],
) -> None:
"""Updates secret values for an existing secret.
Args:
secret_id: The ID of the secret to be updated.
secret_values: The new secret values.
"""
self.store_secret_values(secret_id, secret_values)
SqlSecretsStoreConfiguration (SecretsStoreConfiguration)
pydantic-model
SQL secrets store configuration.
Attributes:
| Name | Type | Description |
|---|---|---|
type |
SecretsStoreType |
The type of the store. |
encryption_key |
Optional[str] |
The encryption key to use for the SQL secrets store. If not set, the passwords will not be encrypted in the database. |
Source code in zenml/zen_stores/secrets_stores/sql_secrets_store.py
class SqlSecretsStoreConfiguration(SecretsStoreConfiguration):
"""SQL secrets store configuration.
Attributes:
type: The type of the store.
encryption_key: The encryption key to use for the SQL secrets store.
If not set, the passwords will not be encrypted in the database.
"""
type: SecretsStoreType = SecretsStoreType.SQL
encryption_key: Optional[str] = None
class Config:
"""Pydantic configuration class."""
# Don't validate attributes when assigning them. This is necessary
# because the certificate attributes can be expanded to the contents
# of the certificate files.
validate_assignment = False
# Forbid extra attributes set in the class.
extra = "forbid"
Config
Pydantic configuration class.
Source code in zenml/zen_stores/secrets_stores/sql_secrets_store.py
class Config:
"""Pydantic configuration class."""
# Don't validate attributes when assigning them. This is necessary
# because the certificate attributes can be expanded to the contents
# of the certificate files.
validate_assignment = False
# Forbid extra attributes set in the class.
extra = "forbid"
sql_zen_store
SQL Zen Store implementation.
SQLDatabaseDriver (StrEnum)
SQL database drivers supported by the SQL ZenML store.
Source code in zenml/zen_stores/sql_zen_store.py
class SQLDatabaseDriver(StrEnum):
"""SQL database drivers supported by the SQL ZenML store."""
MYSQL = "mysql"
SQLITE = "sqlite"
SqlZenStore (BaseZenStore)
pydantic-model
Store Implementation that uses SQL database backend.
Attributes:
| Name | Type | Description |
|---|---|---|
config |
SqlZenStoreConfiguration |
The configuration of the SQL ZenML store. |
skip_migrations |
bool |
Whether to skip migrations when initializing the store. |
TYPE |
ClassVar[zenml.enums.StoreType] |
The type of the store. |
CONFIG_TYPE |
ClassVar[Type[zenml.config.store_config.StoreConfiguration]] |
The type of the store configuration. |
_engine |
Optional[sqlalchemy.engine.base.Engine] |
The SQLAlchemy engine. |
Source code in zenml/zen_stores/sql_zen_store.py
class SqlZenStore(BaseZenStore):
"""Store Implementation that uses SQL database backend.
Attributes:
config: The configuration of the SQL ZenML store.
skip_migrations: Whether to skip migrations when initializing the store.
TYPE: The type of the store.
CONFIG_TYPE: The type of the store configuration.
_engine: The SQLAlchemy engine.
"""
config: SqlZenStoreConfiguration
skip_migrations: bool = False
TYPE: ClassVar[StoreType] = StoreType.SQL
CONFIG_TYPE: ClassVar[Type[StoreConfiguration]] = SqlZenStoreConfiguration
_engine: Optional[Engine] = None
_migration_utils: Optional[MigrationUtils] = None
_alembic: Optional[Alembic] = None
_secrets_store: Optional[BaseSecretsStore] = None
_backup_secrets_store: Optional[BaseSecretsStore] = None
@property
def secrets_store(self) -> "BaseSecretsStore":
"""The secrets store associated with this store.
Returns:
The secrets store associated with this store.
Raises:
SecretsStoreNotConfiguredError: If no secrets store is configured.
"""
if self._secrets_store is None:
raise SecretsStoreNotConfiguredError(
"No secrets store is configured. Please configure a secrets "
"store to create and manage ZenML secrets."
)
return self._secrets_store
@property
def backup_secrets_store(self) -> Optional["BaseSecretsStore"]:
"""The backup secrets store associated with this store.
Returns:
The backup secrets store associated with this store.
"""
return self._backup_secrets_store
@property
def engine(self) -> Engine:
"""The SQLAlchemy engine.
Returns:
The SQLAlchemy engine.
Raises:
ValueError: If the store is not initialized.
"""
if not self._engine:
raise ValueError("Store not initialized")
return self._engine
@property
def migration_utils(self) -> MigrationUtils:
"""The migration utils.
Returns:
The migration utils.
Raises:
ValueError: If the store is not initialized.
"""
if not self._migration_utils:
raise ValueError("Store not initialized")
return self._migration_utils
@property
def alembic(self) -> Alembic:
"""The Alembic wrapper.
Returns:
The Alembic wrapper.
Raises:
ValueError: If the store is not initialized.
"""
if not self._alembic:
raise ValueError("Store not initialized")
return self._alembic
@classmethod
def filter_and_paginate(
cls,
session: Session,
query: Union[Select[Any], SelectOfScalar[Any]],
table: Type[AnySchema],
filter_model: BaseFilter,
custom_schema_to_model_conversion: Optional[
Callable[..., AnyResponse]
] = None,
custom_fetch: Optional[
Callable[
[
Session,
Union[Select[Any], SelectOfScalar[Any]],
BaseFilter,
],
List[Any],
]
] = None,
hydrate: bool = False,
) -> Page[AnyResponse]:
"""Given a query, return a Page instance with a list of filtered Models.
Args:
session: The SQLModel Session
query: The query to execute
table: The table to select from
filter_model: The filter to use, including pagination and sorting
custom_schema_to_model_conversion: Callable to convert the schema
into a model. This is used if the Model contains additional
data that is not explicitly stored as a field or relationship
on the model.
custom_fetch: Custom callable to use to fetch items from the
database for a given query. This is used if the items fetched
from the database need to be processed differently (e.g. to
perform additional filtering). The callable should take a
`Session`, a `Select` query and a `BaseFilterModel` filter as
arguments and return a `List` of items.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The Domain Model representation of the DB resource
Raises:
ValueError: if the filtered page number is out of bounds.
RuntimeError: if the schema does not have a `to_model` method.
"""
query = filter_model.apply_filter(query=query, table=table)
# Get the total amount of items in the database for a given query
custom_fetch_result: Optional[List[Any]] = None
if custom_fetch:
custom_fetch_result = custom_fetch(session, query, filter_model)
total = len(custom_fetch_result)
else:
total = session.scalar(
select([func.count("*")]).select_from(
query.options(noload("*")).subquery()
)
)
# Sorting
column, operand = filter_model.sorting_params
if operand == SorterOps.DESCENDING:
query = query.order_by(desc(getattr(table, column)))
else:
query = query.order_by(asc(getattr(table, column)))
# Get the total amount of pages in the database for a given query
if total == 0:
total_pages = 1
else:
total_pages = math.ceil(total / filter_model.size)
if filter_model.page > total_pages:
raise ValueError(
f"Invalid page {filter_model.page}. The requested page size is "
f"{filter_model.size} and there are a total of {total} items "
f"for this query. The maximum page value therefore is "
f"{total_pages}."
)
# Get a page of the actual data
item_schemas: List[AnySchema]
if custom_fetch:
assert custom_fetch_result is not None
item_schemas = custom_fetch_result
# select the items in the current page
item_schemas = item_schemas[
filter_model.offset : filter_model.offset + filter_model.size
]
else:
item_schemas = (
session.exec(
query.limit(filter_model.size).offset(filter_model.offset)
)
.unique()
.all()
)
# Convert this page of items from schemas to models.
items: List[AnyResponse] = []
for schema in item_schemas:
# If a custom conversion function is provided, use it.
if custom_schema_to_model_conversion:
items.append(custom_schema_to_model_conversion(schema))
continue
# Otherwise, try to use the `to_model` method of the schema.
to_model = getattr(schema, "to_model", None)
if callable(to_model):
items.append(to_model(include_metadata=hydrate))
continue
# If neither of the above work, raise an error.
raise RuntimeError(
f"Cannot convert schema `{schema.__class__.__name__}` to model "
"since it does not have a `to_model` method."
)
return Page[Any](
total=total,
total_pages=total_pages,
items=items,
index=filter_model.page,
max_size=filter_model.size,
)
# ====================================
# ZenML Store interface implementation
# ====================================
# --------------------------------
# Initialization and configuration
# --------------------------------
def _initialize(self) -> None:
"""Initialize the SQL store."""
logger.debug("Initializing SqlZenStore at %s", self.config.url)
url, connect_args, engine_args = self.config.get_sqlalchemy_config()
self._engine = create_engine(
url=url, connect_args=connect_args, **engine_args
)
self._migration_utils = MigrationUtils(
url=url,
connect_args=connect_args,
engine_args=engine_args,
)
# SQLite: As long as the parent directory exists, SQLAlchemy will
# automatically create the database.
if (
self.config.driver == SQLDatabaseDriver.SQLITE
and self.config.database
and not fileio.exists(self.config.database)
):
fileio.makedirs(os.path.dirname(self.config.database))
# MySQL: We might need to create the database manually.
# To do so, we create a new engine that connects to the `mysql` database
# and then create the desired database.
# See https://stackoverflow.com/a/8977109
if (
self.config.driver == SQLDatabaseDriver.MYSQL
and self.config.database
):
if not self.migration_utils.database_exists():
self.migration_utils.create_database()
self._alembic = Alembic(self.engine)
if (
not self.skip_migrations
and ENV_ZENML_DISABLE_DATABASE_MIGRATION not in os.environ
):
self.migrate_database()
secrets_store_config = self.config.secrets_store
# Initialize the secrets store
if (
secrets_store_config
and secrets_store_config.type != SecretsStoreType.NONE
):
secrets_store_class = BaseSecretsStore.get_store_class(
secrets_store_config
)
self._secrets_store = secrets_store_class(
zen_store=self,
config=secrets_store_config,
)
# Update the config with the actual secrets store config
# to reflect the default values in the saved configuration
self.config.secrets_store = self._secrets_store.config
backup_secrets_store_config = self.config.backup_secrets_store
# Initialize the backup secrets store, if configured
if (
backup_secrets_store_config
and backup_secrets_store_config.type != SecretsStoreType.NONE
):
secrets_store_class = BaseSecretsStore.get_store_class(
backup_secrets_store_config
)
self._backup_secrets_store = secrets_store_class(
zen_store=self,
config=backup_secrets_store_config,
)
# Update the config with the actual secrets store config
# to reflect the default values in the saved configuration
self.config.backup_secrets_store = (
self._backup_secrets_store.config
)
def _initialize_database(self) -> None:
"""Initialize the database on first use."""
self._get_or_create_default_workspace()
config = ServerConfiguration.get_server_config()
# If the auth scheme is external, don't create the default user
if config.auth_scheme != AuthScheme.EXTERNAL:
self._get_or_create_default_user()
def _get_db_backup_file_path(self) -> str:
"""Get the path to the database backup file.
Returns:
The path to the configured database backup file.
"""
if self.config.driver == SQLDatabaseDriver.SQLITE:
return os.path.join(
self.config.backup_directory,
# Add the -backup suffix to the database filename
ZENML_SQLITE_DB_FILENAME[:-3] + "-backup.db",
)
# For a MySQL database, we need to dump the database to a JSON
# file
return os.path.join(
self.config.backup_directory,
f"{self.engine.url.database}-backup.json",
)
def backup_database(
self,
strategy: Optional[DatabaseBackupStrategy] = None,
location: Optional[str] = None,
overwrite: bool = False,
) -> Tuple[str, Any]:
"""Backup the database.
Args:
strategy: Custom backup strategy to use. If not set, the backup
strategy from the store configuration will be used.
location: Custom target location to backup the database to. If not
set, the configured backup location will be used. Depending on
the backup strategy, this can be a file path or a database name.
overwrite: Whether to overwrite an existing backup if it exists.
If set to False, the existing backup will be reused.
Returns:
The location where the database was backed up to and an accompanying
user-friendly message that describes the backup location, or None
if no backup was created (i.e. because the backup already exists).
Raises:
ValueError: If the backup database name is not set when the backup
database is requested or if the backup strategy is invalid.
"""
strategy = strategy or self.config.backup_strategy
if (
strategy == DatabaseBackupStrategy.DUMP_FILE
or self.config.driver == SQLDatabaseDriver.SQLITE
):
dump_file = location or self._get_db_backup_file_path()
if not overwrite and os.path.isfile(dump_file):
logger.warning(
f"A previous backup file already exists at '{dump_file}'. "
"Reusing the existing backup."
)
else:
self.migration_utils.backup_database_to_file(
dump_file=dump_file
)
return f"the '{dump_file}' backup file", dump_file
elif strategy == DatabaseBackupStrategy.DATABASE:
backup_db_name = location or self.config.backup_database
if not backup_db_name:
raise ValueError(
"The backup database name must be set in the store "
"configuration to use the backup database strategy."
)
if not overwrite and self.migration_utils.database_exists(
backup_db_name
):
logger.warning(
"A previous backup database already exists at "
f"'{backup_db_name}'. Reusing the existing backup."
)
else:
self.migration_utils.backup_database_to_db(
backup_db_name=backup_db_name
)
return f"the '{backup_db_name}' backup database", backup_db_name
elif strategy == DatabaseBackupStrategy.IN_MEMORY:
return (
"memory",
self.migration_utils.backup_database_to_memory(),
)
else:
raise ValueError(f"Invalid backup strategy: {strategy}.")
def restore_database(
self,
strategy: Optional[DatabaseBackupStrategy] = None,
location: Optional[Any] = None,
cleanup: bool = False,
) -> None:
"""Restore the database.
Args:
strategy: Custom backup strategy to use. If not set, the backup
strategy from the store configuration will be used.
location: Custom target location to restore the database from. If
not set, the configured backup location will be used. Depending
on the backup strategy, this can be a file path, a database
name or an in-memory database representation.
cleanup: Whether to cleanup the backup after restoring the database.
Raises:
ValueError: If the backup database name is not set when the backup
database is requested or if the backup strategy is invalid.
"""
strategy = strategy or self.config.backup_strategy
if (
strategy == DatabaseBackupStrategy.DUMP_FILE
or self.config.driver == SQLDatabaseDriver.SQLITE
):
dump_file = location or self._get_db_backup_file_path()
self.migration_utils.restore_database_from_file(
dump_file=dump_file
)
elif strategy == DatabaseBackupStrategy.DATABASE:
backup_db_name = location or self.config.backup_database
if not backup_db_name:
raise ValueError(
"The backup database name must be set in the store "
"configuration to use the backup database strategy."
)
self.migration_utils.restore_database_from_db(
backup_db_name=backup_db_name
)
elif strategy == DatabaseBackupStrategy.IN_MEMORY:
if location is None or not isinstance(location, list):
raise ValueError(
"The in-memory database representation must be provided "
"to restore the database from an in-memory backup."
)
self.migration_utils.restore_database_from_memory(db_dump=location)
else:
raise ValueError(f"Invalid backup strategy: {strategy}.")
if cleanup:
self.cleanup_database_backup()
def cleanup_database_backup(
self,
strategy: Optional[DatabaseBackupStrategy] = None,
location: Optional[Any] = None,
) -> None:
"""Delete the database backup.
Args:
strategy: Custom backup strategy to use. If not set, the backup
strategy from the store configuration will be used.
location: Custom target location to delete the database backup
from. If not set, the configured backup location will be used.
Depending on the backup strategy, this can be a file path or a
database name.
Raises:
ValueError: If the backup database name is not set when the backup
database is requested.
"""
strategy = strategy or self.config.backup_strategy
if (
strategy == DatabaseBackupStrategy.DUMP_FILE
or self.config.driver == SQLDatabaseDriver.SQLITE
):
dump_file = location or self._get_db_backup_file_path()
if dump_file is not None and os.path.isfile(dump_file):
try:
os.remove(dump_file)
except OSError:
logger.warning(
f"Failed to cleanup database dump file "
f"{dump_file}."
)
else:
logger.info(
f"Successfully cleaned up database dump file "
f"{dump_file}."
)
elif strategy == DatabaseBackupStrategy.DATABASE:
backup_db_name = location or self.config.backup_database
if not backup_db_name:
raise ValueError(
"The backup database name must be set in the store "
"configuration to use the backup database strategy."
)
if self.migration_utils.database_exists(backup_db_name):
# Drop the backup database
self.migration_utils.drop_database(
database=backup_db_name,
)
logger.info(
f"Successfully cleaned up backup database "
f"{backup_db_name}."
)
def migrate_database(self) -> None:
"""Migrate the database to the head as defined by the python package.
Raises:
RuntimeError: If the database exists and is not empty but has never
been migrated with alembic before.
"""
alembic_logger = logging.getLogger("alembic")
# remove all existing handlers
while len(alembic_logger.handlers):
alembic_logger.removeHandler(alembic_logger.handlers[0])
logging_level = get_logging_level()
# suppress alembic info logging if the zenml logging level is not debug
if logging_level == LoggingLevels.DEBUG:
alembic_logger.setLevel(logging.DEBUG)
else:
alembic_logger.setLevel(logging.WARNING)
alembic_logger.addHandler(get_console_handler())
# We need to account for 3 distinct cases here:
# 1. the database is completely empty (not initialized)
# 2. the database is not empty and has been migrated with alembic before
# 3. the database is not empty, but has never been migrated with alembic
# before (i.e. was created with SQLModel back when alembic wasn't
# used). We don't support this direct upgrade case anymore.
current_revisions = self.alembic.current_revisions()
head_revisions = self.alembic.head_revisions()
if len(current_revisions) >= 1:
# Case 2: the database has been migrated with alembic before. Just
# upgrade to the latest revision.
if len(current_revisions) > 1:
logger.warning(
"The ZenML database has more than one migration head "
"revision. This is not expected and might indicate a "
"database migration problem. Please raise an issue on "
"GitHub if you encounter this."
)
logger.debug("Current revisions: %s", current_revisions)
logger.debug("Head revisions: %s", head_revisions)
# If the current revision and head revision don't match, a database
# migration that changes the database structure or contents may
# actually be performed, in which case we enable the backup
# functionality. We only enable the backup functionality if the
# database will actually be changed, to avoid the overhead for
# unnecessary backups.
backup_enabled = (
self.config.backup_strategy != DatabaseBackupStrategy.DISABLED
and set(current_revisions) != set(head_revisions)
)
backup_location: Optional[Any] = None
backup_location_msg: Optional[str] = None
if backup_enabled:
try:
logger.info("Backing up the database before migration.")
(
backup_location_msg,
backup_location,
) = self.backup_database(overwrite=True)
except Exception as e:
raise RuntimeError(
f"Failed to backup the database: {str(e)}. "
"Please check the logs for more details."
"If you would like to disable the database backup "
"functionality, set the `backup_strategy` attribute "
"of the store configuration to `disabled`."
) from e
else:
if backup_location is not None:
logger.info(
"Database successfully backed up to "
f"{backup_location_msg}. If something goes wrong "
"with the upgrade, ZenML will attempt to restore "
"the database from this backup automatically."
)
try:
self.alembic.upgrade()
except Exception as e:
if backup_enabled and backup_location:
logger.exception(
"Failed to migrate the database. Attempting to restore "
f"the database from {backup_location_msg}."
)
try:
self.restore_database(location=backup_location)
except Exception:
logger.exception(
"Failed to restore the database from "
f"{backup_location_msg}. Please "
"check the logs for more details. You might need "
"to restore the database manually."
)
else:
raise RuntimeError(
"The database migration failed, but the database "
"was successfully restored from the backup. "
"You can safely retry the upgrade or revert to "
"the previous version of ZenML. Please check the "
"logs for more details."
) from e
raise RuntimeError(
f"The database migration failed: {str(e)}"
) from e
else:
# We always remove the backup after a successful upgrade,
# not just to avoid cluttering the disk, but also to avoid
# reusing an outdated database from the backup in case of
# future upgrade failures.
try:
self.cleanup_database_backup()
except Exception:
logger.exception("Failed to cleanup the database backup.")
elif self.alembic.db_is_empty():
# Case 1: the database is empty. We can just create the
# tables from scratch with from SQLModel. After tables are
# created we put an alembic revision to latest and populate
# identity table with needed info.
logger.info("Creating database tables")
with self.engine.begin() as conn:
conn.run_callable(
SQLModel.metadata.create_all # type: ignore[arg-type]
)
with Session(self.engine) as session:
session.add(
IdentitySchema(
id=str(GlobalConfiguration().user_id).replace("-", "")
)
)
session.commit()
self.alembic.stamp("head")
else:
# Case 3: the database is not empty, but has never been
# migrated with alembic before. We don't support this direct
# upgrade case anymore. The user needs to run a two-step
# upgrade.
raise RuntimeError(
"The ZenML database has never been migrated with alembic "
"before. This can happen if you are performing a direct "
"upgrade from a really old version of ZenML. This direct "
"upgrade path is not supported anymore. Please upgrade "
"your ZenML installation first to 0.54.0 or an earlier "
"version and then to the latest version."
)
# If an alembic migration took place, all non-custom flavors are purged
# and the FlavorRegistry recreates all in-built and integration
# flavors in the db.
revisions_afterwards = self.alembic.current_revisions()
if current_revisions != revisions_afterwards:
self._sync_flavors()
def _sync_flavors(self) -> None:
"""Purge all in-built and integration flavors from the DB and sync."""
FlavorRegistry().register_flavors(store=self)
def get_store_info(self) -> ServerModel:
"""Get information about the store.
Returns:
Information about the store.
"""
model = super().get_store_info()
sql_url = make_url(self.config.url)
model.database_type = ServerDatabaseType(sql_url.drivername)
# Fetch the deployment ID from the database and use it to replace
# the one fetched from the global configuration
model.id = self.get_deployment_id()
return model
def get_deployment_id(self) -> UUID:
"""Get the ID of the deployment.
Returns:
The ID of the deployment.
Raises:
KeyError: If the deployment ID could not be loaded from the
database.
"""
# Fetch the deployment ID from the database
with Session(self.engine) as session:
identity = session.exec(select(IdentitySchema)).first()
if identity is None:
raise KeyError(
"The deployment ID could not be loaded from the database."
)
return identity.id
# ------------------------- API Keys -------------------------
def _get_api_key(
self,
service_account_id: UUID,
api_key_name_or_id: Union[str, UUID],
session: Session,
) -> APIKeySchema:
"""Helper method to fetch an API key by name or ID.
Args:
service_account_id: The ID of the service account for which to
fetch the API key.
api_key_name_or_id: The name or ID of the API key to get.
session: The database session to use for the query.
Returns:
The requested API key.
Raises:
KeyError: if the name or ID does not identify an API key that is
configured for the given service account.
"""
# Fetch the service account, to make sure it exists
service_account = self._get_account_schema(
service_account_id, session=session, service_account=True
)
if uuid_utils.is_valid_uuid(api_key_name_or_id):
filter_params = APIKeySchema.id == api_key_name_or_id
else:
filter_params = APIKeySchema.name == api_key_name_or_id
api_key = session.exec(
select(APIKeySchema)
.where(filter_params)
.where(APIKeySchema.service_account_id == service_account.id)
).first()
if api_key is None:
raise KeyError(
f"An API key with ID or name '{api_key_name_or_id}' is not "
f"configured for service account with ID "
f"'{service_account_id}'."
)
return api_key
def create_api_key(
self, service_account_id: UUID, api_key: APIKeyRequest
) -> APIKeyResponse:
"""Create a new API key for a service account.
Args:
service_account_id: The ID of the service account for which to
create the API key.
api_key: The API key to create.
Returns:
The created API key.
Raises:
EntityExistsError: If an API key with the same name is already
configured for the same service account.
"""
with Session(self.engine) as session:
# Fetch the service account
service_account = self._get_account_schema(
service_account_id, session=session, service_account=True
)
# Check if a key with the same name already exists for the same
# service account
try:
self._get_api_key(
service_account_id=service_account.id,
api_key_name_or_id=api_key.name,
session=session,
)
raise EntityExistsError(
f"Unable to register API key with name '{api_key.name}': "
"Found an existing API key with the same name configured "
f"for the same '{service_account.name}' service account."
)
except KeyError:
pass
new_api_key, key_value = APIKeySchema.from_request(
service_account_id=service_account.id,
request=api_key,
)
session.add(new_api_key)
session.commit()
api_key_model = new_api_key.to_model(include_metadata=True)
api_key_model.set_key(key_value)
return api_key_model
def get_api_key(
self,
service_account_id: UUID,
api_key_name_or_id: Union[str, UUID],
hydrate: bool = True,
) -> APIKeyResponse:
"""Get an API key for a service account.
Args:
service_account_id: The ID of the service account for which to fetch
the API key.
api_key_name_or_id: The name or ID of the API key to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The API key with the given ID.
"""
with Session(self.engine) as session:
api_key = self._get_api_key(
service_account_id=service_account_id,
api_key_name_or_id=api_key_name_or_id,
session=session,
)
return api_key.to_model(include_metadata=hydrate)
def get_internal_api_key(
self, api_key_id: UUID, hydrate: bool = True
) -> APIKeyInternalResponse:
"""Get internal details for an API key by its unique ID.
Args:
api_key_id: The ID of the API key to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The internal details for the API key with the given ID.
Raises:
KeyError: if the API key doesn't exist.
"""
with Session(self.engine) as session:
api_key = session.exec(
select(APIKeySchema).where(APIKeySchema.id == api_key_id)
).first()
if api_key is None:
raise KeyError(f"API key with ID {api_key_id} not found.")
return api_key.to_internal_model(hydrate=hydrate)
def list_api_keys(
self,
service_account_id: UUID,
filter_model: APIKeyFilter,
hydrate: bool = False,
) -> Page[APIKeyResponse]:
"""List all API keys for a service account matching the given filter criteria.
Args:
service_account_id: The ID of the service account for which to list
the API keys.
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all API keys matching the filter criteria.
"""
with Session(self.engine) as session:
# Fetch the service account
service_account = self._get_account_schema(
service_account_id, session=session, service_account=True
)
filter_model.set_service_account(service_account.id)
query = select(APIKeySchema)
return self.filter_and_paginate(
session=session,
query=query,
table=APIKeySchema,
filter_model=filter_model,
hydrate=hydrate,
)
def update_api_key(
self,
service_account_id: UUID,
api_key_name_or_id: Union[str, UUID],
api_key_update: APIKeyUpdate,
) -> APIKeyResponse:
"""Update an API key for a service account.
Args:
service_account_id: The ID of the service account for which to update
the API key.
api_key_name_or_id: The name or ID of the API key to update.
api_key_update: The update request on the API key.
Returns:
The updated API key.
Raises:
EntityExistsError: if the API key update would result in a name
conflict with an existing API key for the same service account.
"""
with Session(self.engine) as session:
api_key = self._get_api_key(
service_account_id=service_account_id,
api_key_name_or_id=api_key_name_or_id,
session=session,
)
if api_key_update.name and api_key.name != api_key_update.name:
# Check if a key with the new name already exists for the same
# service account
try:
self._get_api_key(
service_account_id=service_account_id,
api_key_name_or_id=api_key_update.name,
session=session,
)
raise EntityExistsError(
f"Unable to update API key with name "
f"'{api_key_update.name}': Found an existing API key "
"with the same name configured for the same "
f"'{api_key.service_account.name}' service account."
)
except KeyError:
pass
api_key.update(update=api_key_update)
session.add(api_key)
session.commit()
# Refresh the Model that was just created
session.refresh(api_key)
return api_key.to_model(include_metadata=True)
def update_internal_api_key(
self, api_key_id: UUID, api_key_update: APIKeyInternalUpdate
) -> APIKeyResponse:
"""Update an API key with internal details.
Args:
api_key_id: The ID of the API key.
api_key_update: The update request on the API key.
Returns:
The updated API key.
Raises:
KeyError: if the API key doesn't exist.
"""
with Session(self.engine) as session:
api_key = session.exec(
select(APIKeySchema).where(APIKeySchema.id == api_key_id)
).first()
if not api_key:
raise KeyError(f"API key with ID {api_key_id} not found.")
api_key.internal_update(update=api_key_update)
session.add(api_key)
session.commit()
# Refresh the Model that was just created
session.refresh(api_key)
return api_key.to_model(include_metadata=True)
def rotate_api_key(
self,
service_account_id: UUID,
api_key_name_or_id: Union[str, UUID],
rotate_request: APIKeyRotateRequest,
) -> APIKeyResponse:
"""Rotate an API key for a service account.
Args:
service_account_id: The ID of the service account for which to
rotate the API key.
api_key_name_or_id: The name or ID of the API key to rotate.
rotate_request: The rotate request on the API key.
Returns:
The updated API key.
"""
with Session(self.engine) as session:
api_key = self._get_api_key(
service_account_id=service_account_id,
api_key_name_or_id=api_key_name_or_id,
session=session,
)
_, new_key = api_key.rotate(rotate_request)
session.add(api_key)
session.commit()
# Refresh the Model that was just created
session.refresh(api_key)
api_key_model = api_key.to_model()
api_key_model.set_key(new_key)
return api_key_model
def delete_api_key(
self,
service_account_id: UUID,
api_key_name_or_id: Union[str, UUID],
) -> None:
"""Delete an API key for a service account.
Args:
service_account_id: The ID of the service account for which to
delete the API key.
api_key_name_or_id: The name or ID of the API key to delete.
"""
with Session(self.engine) as session:
api_key = self._get_api_key(
service_account_id=service_account_id,
api_key_name_or_id=api_key_name_or_id,
session=session,
)
session.delete(api_key)
session.commit()
# -------------------- Artifacts --------------------
def create_artifact(self, artifact: ArtifactRequest) -> ArtifactResponse:
"""Creates a new artifact.
Args:
artifact: The artifact to create.
Returns:
The newly created artifact.
Raises:
EntityExistsError: If an artifact with the same name already exists.
"""
with Session(self.engine) as session:
# Check if an artifact with the given name already exists
existing_artifact = session.exec(
select(ArtifactSchema).where(
ArtifactSchema.name == artifact.name
)
).first()
if existing_artifact is not None:
raise EntityExistsError(
f"Unable to create artifact with name '{artifact.name}': "
"An artifact with the same name already exists."
)
# Create the artifact.
artifact_schema = ArtifactSchema.from_request(artifact)
# Save tags of the artifact.
if artifact.tags:
self._attach_tags_to_resource(
tag_names=artifact.tags,
resource_id=artifact_schema.id,
resource_type=TaggableResourceTypes.ARTIFACT,
)
session.add(artifact_schema)
session.commit()
return artifact_schema.to_model(include_metadata=True)
def get_artifact(
self, artifact_id: UUID, hydrate: bool = True
) -> ArtifactResponse:
"""Gets an artifact.
Args:
artifact_id: The ID of the artifact to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The artifact.
Raises:
KeyError: if the artifact doesn't exist.
"""
with Session(self.engine) as session:
artifact = session.exec(
select(ArtifactSchema).where(ArtifactSchema.id == artifact_id)
).first()
if artifact is None:
raise KeyError(
f"Unable to get artifact with ID {artifact_id}: No "
"artifact with this ID found."
)
return artifact.to_model(include_metadata=hydrate)
def list_artifacts(
self, filter_model: ArtifactFilter, hydrate: bool = False
) -> Page[ArtifactResponse]:
"""List all artifacts matching the given filter criteria.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all artifacts matching the filter criteria.
"""
with Session(self.engine) as session:
query = select(ArtifactSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=ArtifactSchema,
filter_model=filter_model,
hydrate=hydrate,
)
def update_artifact(
self, artifact_id: UUID, artifact_update: ArtifactUpdate
) -> ArtifactResponse:
"""Updates an artifact.
Args:
artifact_id: The ID of the artifact to update.
artifact_update: The update to be applied to the artifact.
Returns:
The updated artifact.
Raises:
KeyError: if the artifact doesn't exist.
"""
with Session(self.engine) as session:
existing_artifact = session.exec(
select(ArtifactSchema).where(ArtifactSchema.id == artifact_id)
).first()
if not existing_artifact:
raise KeyError(f"Artifact with ID {artifact_id} not found.")
# Handle tag updates.
if artifact_update.add_tags:
self._attach_tags_to_resource(
tag_names=artifact_update.add_tags,
resource_id=existing_artifact.id,
resource_type=TaggableResourceTypes.ARTIFACT,
)
if artifact_update.remove_tags:
self._detach_tags_from_resource(
tag_names=artifact_update.remove_tags,
resource_id=existing_artifact.id,
resource_type=TaggableResourceTypes.ARTIFACT,
)
# Update the schema itself.
existing_artifact.update(artifact_update=artifact_update)
session.add(existing_artifact)
session.commit()
session.refresh(existing_artifact)
return existing_artifact.to_model(include_metadata=True)
def delete_artifact(self, artifact_id: UUID) -> None:
"""Deletes an artifact.
Args:
artifact_id: The ID of the artifact to delete.
Raises:
KeyError: if the artifact doesn't exist.
"""
with Session(self.engine) as session:
existing_artifact = session.exec(
select(ArtifactSchema).where(ArtifactSchema.id == artifact_id)
).first()
if not existing_artifact:
raise KeyError(f"Artifact with ID {artifact_id} not found.")
session.delete(existing_artifact)
session.commit()
# -------------------- Artifact Versions --------------------
def create_artifact_version(
self, artifact_version: ArtifactVersionRequest
) -> ArtifactVersionResponse:
"""Creates an artifact version.
Args:
artifact_version: The artifact version to create.
Returns:
The created artifact version.
Raises:
EntityExistsError: if an artifact with the same name and version
already exists.
"""
with Session(self.engine) as session:
# Check if an artifact with the given name and version exists
def _check(tolerance: int = 0) -> None:
query = session.exec(
select(ArtifactVersionSchema)
.where(
ArtifactVersionSchema.artifact_id
== artifact_version.artifact_id
)
.where(
ArtifactVersionSchema.version
== artifact_version.version
)
)
existing_artifact = query.fetchmany(tolerance + 1)
if (
existing_artifact is not None
and len(existing_artifact) > tolerance
):
raise EntityExistsError(
f"Unable to create artifact with name "
f"'{existing_artifact[0].artifact.name}' and version "
f"'{artifact_version.version}': An artifact with the same "
"name and version already exists."
)
_check()
# Create the artifact version.
artifact_version_schema = ArtifactVersionSchema.from_request(
artifact_version
)
session.add(artifact_version_schema)
# Save visualizations of the artifact.
if artifact_version.visualizations:
for vis in artifact_version.visualizations:
vis_schema = ArtifactVisualizationSchema.from_model(
artifact_visualization_request=vis,
artifact_version_id=artifact_version_schema.id,
)
session.add(vis_schema)
# Save tags of the artifact.
if artifact_version.tags:
self._attach_tags_to_resource(
tag_names=artifact_version.tags,
resource_id=artifact_version_schema.id,
resource_type=TaggableResourceTypes.ARTIFACT_VERSION,
)
try:
_check(1)
session.commit()
except EntityExistsError as e:
session.rollback()
raise e
return artifact_version_schema.to_model(include_metadata=True)
def get_artifact_version(
self, artifact_version_id: UUID, hydrate: bool = True
) -> ArtifactVersionResponse:
"""Gets an artifact version.
Args:
artifact_version_id: The ID of the artifact version to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The artifact version.
Raises:
KeyError: if the artifact version doesn't exist.
"""
with Session(self.engine) as session:
artifact_version = session.exec(
select(ArtifactVersionSchema).where(
ArtifactVersionSchema.id == artifact_version_id
)
).first()
if artifact_version is None:
raise KeyError(
f"Unable to get artifact version with ID "
f"{artifact_version_id}: No artifact version with this ID "
f"found."
)
return artifact_version.to_model(include_metadata=hydrate)
def list_artifact_versions(
self,
artifact_version_filter_model: ArtifactVersionFilter,
hydrate: bool = False,
) -> Page[ArtifactVersionResponse]:
"""List all artifact versions matching the given filter criteria.
Args:
artifact_version_filter_model: All filter parameters including
pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all artifact versions matching the filter criteria.
"""
with Session(self.engine) as session:
query = select(ArtifactVersionSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=ArtifactVersionSchema,
filter_model=artifact_version_filter_model,
hydrate=hydrate,
)
def update_artifact_version(
self,
artifact_version_id: UUID,
artifact_version_update: ArtifactVersionUpdate,
) -> ArtifactVersionResponse:
"""Updates an artifact version.
Args:
artifact_version_id: The ID of the artifact version to update.
artifact_version_update: The update to be applied to the artifact
version.
Returns:
The updated artifact version.
Raises:
KeyError: if the artifact version doesn't exist.
"""
with Session(self.engine) as session:
existing_artifact_version = session.exec(
select(ArtifactVersionSchema).where(
ArtifactVersionSchema.id == artifact_version_id
)
).first()
if not existing_artifact_version:
raise KeyError(
f"Artifact version with ID {artifact_version_id} not found."
)
# Handle tag updates.
if artifact_version_update.add_tags:
self._attach_tags_to_resource(
tag_names=artifact_version_update.add_tags,
resource_id=existing_artifact_version.id,
resource_type=TaggableResourceTypes.ARTIFACT_VERSION,
)
if artifact_version_update.remove_tags:
self._detach_tags_from_resource(
tag_names=artifact_version_update.remove_tags,
resource_id=existing_artifact_version.id,
resource_type=TaggableResourceTypes.ARTIFACT_VERSION,
)
# Update the schema itself.
existing_artifact_version.update(
artifact_version_update=artifact_version_update
)
session.add(existing_artifact_version)
session.commit()
session.refresh(existing_artifact_version)
return existing_artifact_version.to_model(include_metadata=True)
def delete_artifact_version(self, artifact_version_id: UUID) -> None:
"""Deletes an artifact version.
Args:
artifact_version_id: The ID of the artifact version to delete.
Raises:
KeyError: if the artifact version doesn't exist.
"""
with Session(self.engine) as session:
artifact_version = session.exec(
select(ArtifactVersionSchema).where(
ArtifactVersionSchema.id == artifact_version_id
)
).first()
if artifact_version is None:
raise KeyError(
f"Unable to delete artifact version with ID "
f"{artifact_version_id}: No artifact version with this ID "
"found."
)
session.delete(artifact_version)
session.commit()
def prune_artifact_versions(
self,
only_versions: bool = True,
) -> None:
"""Prunes unused artifact versions and their artifacts.
Args:
only_versions: Only delete artifact versions, keeping artifacts
"""
with Session(self.engine) as session:
unused_artifact_versions = [
a[0]
for a in session.execute(
select(ArtifactVersionSchema.id).where(
and_(
col(ArtifactVersionSchema.id).notin_(
select(StepRunOutputArtifactSchema.artifact_id)
),
col(ArtifactVersionSchema.id).notin_(
select(StepRunInputArtifactSchema.artifact_id)
),
)
)
).fetchall()
]
session.execute(
delete(ArtifactVersionSchema).where(
col(ArtifactVersionSchema.id).in_(
unused_artifact_versions
),
)
)
if not only_versions:
unused_artifacts = [
a[0]
for a in session.execute(
select(ArtifactSchema.id).where(
col(ArtifactSchema.id).notin_(
select(ArtifactVersionSchema.artifact_id)
)
)
).fetchall()
]
session.execute(
delete(ArtifactSchema).where(
col(ArtifactSchema.id).in_(unused_artifacts)
)
)
session.commit()
# ------------------------ Artifact Visualizations ------------------------
def get_artifact_visualization(
self, artifact_visualization_id: UUID, hydrate: bool = True
) -> ArtifactVisualizationResponse:
"""Gets an artifact visualization.
Args:
artifact_visualization_id: The ID of the artifact visualization to
get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The artifact visualization.
Raises:
KeyError: if the code reference doesn't exist.
"""
with Session(self.engine) as session:
artifact_visualization = session.exec(
select(ArtifactVisualizationSchema).where(
ArtifactVisualizationSchema.id == artifact_visualization_id
)
).first()
if artifact_visualization is None:
raise KeyError(
f"Unable to get artifact visualization with ID "
f"{artifact_visualization_id}: "
f"No artifact visualization with this ID found."
)
return artifact_visualization.to_model(include_metadata=hydrate)
# ------------------------ Code References ------------------------
def get_code_reference(
self, code_reference_id: UUID, hydrate: bool = True
) -> CodeReferenceResponse:
"""Gets a code reference.
Args:
code_reference_id: The ID of the code reference to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The code reference.
Raises:
KeyError: if the code reference doesn't exist.
"""
with Session(self.engine) as session:
code_reference = session.exec(
select(CodeReferenceSchema).where(
CodeRepositorySchema.id == code_reference_id
)
).first()
if code_reference is None:
raise KeyError(
f"Unable to get code reference with ID "
f"{code_reference_id}: "
f"No code reference with this ID found."
)
return code_reference.to_model(include_metadata=hydrate)
# --------------------------- Code Repositories ---------------------------
@track_decorator(AnalyticsEvent.REGISTERED_CODE_REPOSITORY)
def create_code_repository(
self, code_repository: CodeRepositoryRequest
) -> CodeRepositoryResponse:
"""Creates a new code repository.
Args:
code_repository: Code repository to be created.
Returns:
The newly created code repository.
Raises:
EntityExistsError: If a code repository with the given name already
exists.
"""
with Session(self.engine) as session:
existing_repo = session.exec(
select(CodeRepositorySchema)
.where(CodeRepositorySchema.name == code_repository.name)
.where(
CodeRepositorySchema.workspace_id
== code_repository.workspace
)
).first()
if existing_repo is not None:
raise EntityExistsError(
f"Unable to create code repository in workspace "
f"'{code_repository.workspace}': A code repository with "
"this name already exists."
)
new_repo = CodeRepositorySchema.from_request(code_repository)
session.add(new_repo)
session.commit()
session.refresh(new_repo)
return new_repo.to_model(include_metadata=True)
def get_code_repository(
self, code_repository_id: UUID, hydrate: bool = True
) -> CodeRepositoryResponse:
"""Gets a specific code repository.
Args:
code_repository_id: The ID of the code repository to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested code repository, if it was found.
Raises:
KeyError: If no code repository with the given ID exists.
"""
with Session(self.engine) as session:
repo = session.exec(
select(CodeRepositorySchema).where(
CodeRepositorySchema.id == code_repository_id
)
).first()
if repo is None:
raise KeyError(
f"Unable to get code repository with ID "
f"'{code_repository_id}': No code repository with this "
"ID found."
)
return repo.to_model(include_metadata=hydrate)
def list_code_repositories(
self,
filter_model: CodeRepositoryFilter,
hydrate: bool = False,
) -> Page[CodeRepositoryResponse]:
"""List all code repositories.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all code repositories.
"""
with Session(self.engine) as session:
query = select(CodeRepositorySchema)
return self.filter_and_paginate(
session=session,
query=query,
table=CodeRepositorySchema,
filter_model=filter_model,
hydrate=hydrate,
)
def update_code_repository(
self, code_repository_id: UUID, update: CodeRepositoryUpdate
) -> CodeRepositoryResponse:
"""Updates an existing code repository.
Args:
code_repository_id: The ID of the code repository to update.
update: The update to be applied to the code repository.
Returns:
The updated code repository.
Raises:
KeyError: If no code repository with the given name exists.
"""
with Session(self.engine) as session:
existing_repo = session.exec(
select(CodeRepositorySchema).where(
CodeRepositorySchema.id == code_repository_id
)
).first()
if existing_repo is None:
raise KeyError(
f"Unable to update code repository with ID "
f"{code_repository_id}: No code repository with this ID "
"found."
)
existing_repo.update(update)
session.add(existing_repo)
session.commit()
return existing_repo.to_model(include_metadata=True)
def delete_code_repository(self, code_repository_id: UUID) -> None:
"""Deletes a code repository.
Args:
code_repository_id: The ID of the code repository to delete.
Raises:
KeyError: If no code repository with the given ID exists.
"""
with Session(self.engine) as session:
existing_repo = session.exec(
select(CodeRepositorySchema).where(
CodeRepositorySchema.id == code_repository_id
)
).first()
if existing_repo is None:
raise KeyError(
f"Unable to delete code repository with ID "
f"{code_repository_id}: No code repository with this ID "
"found."
)
session.delete(existing_repo)
session.commit()
# ----------------------------- Components -----------------------------
@track_decorator(AnalyticsEvent.REGISTERED_STACK_COMPONENT)
def create_stack_component(
self,
component: ComponentRequest,
) -> ComponentResponse:
"""Create a stack component.
Args:
component: The stack component to create.
Returns:
The created stack component.
Raises:
KeyError: if the stack component references a non-existent
connector.
"""
with Session(self.engine) as session:
self._fail_if_component_with_name_type_exists(
name=component.name,
component_type=component.type,
workspace_id=component.workspace,
session=session,
)
service_connector: Optional[ServiceConnectorSchema] = None
if component.connector:
service_connector = session.exec(
select(ServiceConnectorSchema).where(
ServiceConnectorSchema.id == component.connector
)
).first()
if service_connector is None:
raise KeyError(
f"Service connector with ID {component.connector} not "
"found."
)
# Create the component
new_component = StackComponentSchema(
name=component.name,
workspace_id=component.workspace,
user_id=component.user,
component_spec_path=component.component_spec_path,
type=component.type,
flavor=component.flavor,
configuration=base64.b64encode(
json.dumps(component.configuration).encode("utf-8")
),
labels=base64.b64encode(
json.dumps(component.labels).encode("utf-8")
),
connector=service_connector,
connector_resource_id=component.connector_resource_id,
)
session.add(new_component)
session.commit()
session.refresh(new_component)
return new_component.to_model(include_metadata=True)
def get_stack_component(
self, component_id: UUID, hydrate: bool = True
) -> ComponentResponse:
"""Get a stack component by ID.
Args:
component_id: The ID of the stack component to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The stack component.
Raises:
KeyError: if the stack component doesn't exist.
"""
with Session(self.engine) as session:
stack_component = session.exec(
select(StackComponentSchema).where(
StackComponentSchema.id == component_id
)
).first()
if stack_component is None:
raise KeyError(
f"Stack component with ID {component_id} not found."
)
return stack_component.to_model(include_metadata=hydrate)
def list_stack_components(
self,
component_filter_model: ComponentFilter,
hydrate: bool = False,
) -> Page[ComponentResponse]:
"""List all stack components matching the given filter criteria.
Args:
component_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all stack components matching the filter criteria.
"""
with Session(self.engine) as session:
query = select(StackComponentSchema)
paged_components: Page[ComponentResponse] = (
self.filter_and_paginate(
session=session,
query=query,
table=StackComponentSchema,
filter_model=component_filter_model,
hydrate=hydrate,
)
)
return paged_components
def update_stack_component(
self, component_id: UUID, component_update: ComponentUpdate
) -> ComponentResponse:
"""Update an existing stack component.
Args:
component_id: The ID of the stack component to update.
component_update: The update to be applied to the stack component.
Returns:
The updated stack component.
Raises:
KeyError: if the stack component doesn't exist.
IllegalOperationError: if the stack component is a default stack
component.
"""
with Session(self.engine) as session:
existing_component = session.exec(
select(StackComponentSchema).where(
StackComponentSchema.id == component_id
)
).first()
if existing_component is None:
raise KeyError(
f"Unable to update component with id "
f"'{component_id}': Found no"
f"existing component with this id."
)
if (
existing_component.name == DEFAULT_STACK_AND_COMPONENT_NAME
and existing_component.type
in [
StackComponentType.ORCHESTRATOR,
StackComponentType.ARTIFACT_STORE,
]
):
raise IllegalOperationError(
f"The default {existing_component.type} cannot be modified."
)
# In case of a renaming update, make sure no component of the same
# type already exists with that name
if component_update.name:
if existing_component.name != component_update.name:
self._fail_if_component_with_name_type_exists(
name=component_update.name,
component_type=existing_component.type,
workspace_id=existing_component.workspace_id,
session=session,
)
existing_component.update(component_update=component_update)
if component_update.connector:
service_connector = session.exec(
select(ServiceConnectorSchema).where(
ServiceConnectorSchema.id == component_update.connector
)
).first()
if service_connector is None:
raise KeyError(
"Service connector with ID "
f"{component_update.connector} not found."
)
existing_component.connector = service_connector
existing_component.connector_resource_id = (
component_update.connector_resource_id
)
else:
existing_component.connector = None
existing_component.connector_resource_id = None
session.add(existing_component)
session.commit()
return existing_component.to_model(include_metadata=True)
def delete_stack_component(self, component_id: UUID) -> None:
"""Delete a stack component.
Args:
component_id: The id of the stack component to delete.
Raises:
KeyError: if the stack component doesn't exist.
IllegalOperationError: if the stack component is part of one or
more stacks, or if it's a default stack component.
"""
with Session(self.engine) as session:
try:
stack_component = session.exec(
select(StackComponentSchema).where(
StackComponentSchema.id == component_id
)
).one()
if stack_component is None:
raise KeyError(f"Stack with ID {component_id} not found.")
if (
stack_component.name == DEFAULT_STACK_AND_COMPONENT_NAME
and stack_component.type
in [
StackComponentType.ORCHESTRATOR,
StackComponentType.ARTIFACT_STORE,
]
):
raise IllegalOperationError(
f"The default {stack_component.type} cannot be deleted."
)
if len(stack_component.stacks) > 0:
raise IllegalOperationError(
f"Stack Component `{stack_component.name}` of type "
f"`{stack_component.type} cannot be "
f"deleted as it is part of "
f"{len(stack_component.stacks)} stacks. "
f"Before deleting this stack "
f"component, make sure to remove it "
f"from all stacks."
)
else:
session.delete(stack_component)
except NoResultFound as error:
raise KeyError from error
session.commit()
def count_stack_components(
self, filter_model: Optional[ComponentFilter] = None
) -> int:
"""Count all components.
Args:
filter_model: The filter model to use for counting components.
Returns:
The number of components.
"""
return self._count_entity(
schema=StackComponentSchema, filter_model=filter_model
)
@staticmethod
def _fail_if_component_with_name_type_exists(
name: str,
component_type: StackComponentType,
workspace_id: UUID,
session: Session,
) -> None:
"""Raise an exception if a component with same name/type exists.
Args:
name: The name of the component
component_type: The type of the component
workspace_id: The ID of the workspace
session: The Session
Raises:
StackComponentExistsError: If a component with the given name and
type already exists.
"""
# Check if component with the same domain key (name, type, workspace)
# already exists
existing_domain_component = session.exec(
select(StackComponentSchema)
.where(StackComponentSchema.name == name)
.where(StackComponentSchema.workspace_id == workspace_id)
.where(StackComponentSchema.type == component_type)
).first()
if existing_domain_component is not None:
raise StackComponentExistsError(
f"Unable to register '{component_type}' component "
f"with name '{name}': Found an existing "
f"component with the same name and type in the same "
f" workspace '{existing_domain_component.workspace.name}'."
)
# -------------------------- Devices -------------------------
def create_authorized_device(
self, device: OAuthDeviceInternalRequest
) -> OAuthDeviceInternalResponse:
"""Creates a new OAuth 2.0 authorized device.
Args:
device: The device to be created.
Returns:
The newly created device.
Raises:
EntityExistsError: If a device for the same client ID already
exists.
"""
with Session(self.engine) as session:
existing_device = session.exec(
select(OAuthDeviceSchema).where(
OAuthDeviceSchema.client_id == device.client_id
)
).first()
if existing_device is not None:
raise EntityExistsError(
f"Unable to create device with client ID "
f"'{device.client_id}': A device with this client ID "
"already exists."
)
(
new_device,
user_code,
device_code,
) = OAuthDeviceSchema.from_request(device)
session.add(new_device)
session.commit()
session.refresh(new_device)
device_model = new_device.to_internal_model(hydrate=True)
# Replace the hashed user code with the original user code
device_model.user_code = user_code
# Replace the hashed device code with the original device code
device_model.device_code = device_code
return device_model
def get_authorized_device(
self, device_id: UUID, hydrate: bool = True
) -> OAuthDeviceResponse:
"""Gets a specific OAuth 2.0 authorized device.
Args:
device_id: The ID of the device to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested device, if it was found.
Raises:
KeyError: If no device with the given ID exists.
"""
with Session(self.engine) as session:
device = session.exec(
select(OAuthDeviceSchema).where(
OAuthDeviceSchema.id == device_id
)
).first()
if device is None:
raise KeyError(
f"Unable to get device with ID {device_id}: No device with "
"this ID found."
)
return device.to_model(include_metadata=hydrate)
def get_internal_authorized_device(
self,
device_id: Optional[UUID] = None,
client_id: Optional[UUID] = None,
hydrate: bool = True,
) -> OAuthDeviceInternalResponse:
"""Gets a specific OAuth 2.0 authorized device for internal use.
Args:
client_id: The client ID of the device to get.
device_id: The ID of the device to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested device, if it was found.
Raises:
KeyError: If no device with the given client ID exists.
ValueError: If neither device ID nor client ID are provided.
"""
with Session(self.engine) as session:
if device_id is not None:
device = session.exec(
select(OAuthDeviceSchema).where(
OAuthDeviceSchema.id == device_id
)
).first()
elif client_id is not None:
device = session.exec(
select(OAuthDeviceSchema).where(
OAuthDeviceSchema.client_id == client_id
)
).first()
else:
raise ValueError(
"Either device ID or client ID must be provided."
)
if device is None:
raise KeyError(
f"Unable to get device with client ID {client_id}: No "
"device with this client ID found."
)
return device.to_internal_model(hydrate=hydrate)
def list_authorized_devices(
self,
filter_model: OAuthDeviceFilter,
hydrate: bool = False,
) -> Page[OAuthDeviceResponse]:
"""List all OAuth 2.0 authorized devices for a user.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all matching OAuth 2.0 authorized devices.
"""
with Session(self.engine) as session:
query = select(OAuthDeviceSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=OAuthDeviceSchema,
filter_model=filter_model,
hydrate=hydrate,
)
def update_authorized_device(
self, device_id: UUID, update: OAuthDeviceUpdate
) -> OAuthDeviceResponse:
"""Updates an existing OAuth 2.0 authorized device for internal use.
Args:
device_id: The ID of the device to update.
update: The update to be applied to the device.
Returns:
The updated OAuth 2.0 authorized device.
Raises:
KeyError: If no device with the given ID exists.
"""
with Session(self.engine) as session:
existing_device = session.exec(
select(OAuthDeviceSchema).where(
OAuthDeviceSchema.id == device_id
)
).first()
if existing_device is None:
raise KeyError(
f"Unable to update device with ID {device_id}: No "
"device with this ID found."
)
existing_device.update(update)
session.add(existing_device)
session.commit()
return existing_device.to_model(include_metadata=True)
def update_internal_authorized_device(
self, device_id: UUID, update: OAuthDeviceInternalUpdate
) -> OAuthDeviceInternalResponse:
"""Updates an existing OAuth 2.0 authorized device.
Args:
device_id: The ID of the device to update.
update: The update to be applied to the device.
Returns:
The updated OAuth 2.0 authorized device.
Raises:
KeyError: If no device with the given ID exists.
"""
with Session(self.engine) as session:
existing_device = session.exec(
select(OAuthDeviceSchema).where(
OAuthDeviceSchema.id == device_id
)
).first()
if existing_device is None:
raise KeyError(
f"Unable to update device with ID {device_id}: No device "
"with this ID found."
)
(
_,
user_code,
device_code,
) = existing_device.internal_update(update)
session.add(existing_device)
session.commit()
device_model = existing_device.to_internal_model(hydrate=True)
if user_code:
# Replace the hashed user code with the original user code
device_model.user_code = user_code
if device_code:
# Replace the hashed device code with the original device code
device_model.device_code = device_code
return device_model
def delete_authorized_device(self, device_id: UUID) -> None:
"""Deletes an OAuth 2.0 authorized device.
Args:
device_id: The ID of the device to delete.
Raises:
KeyError: If no device with the given ID exists.
"""
with Session(self.engine) as session:
existing_device = session.exec(
select(OAuthDeviceSchema).where(
OAuthDeviceSchema.id == device_id
)
).first()
if existing_device is None:
raise KeyError(
f"Unable to delete device with ID {device_id}: No device "
"with this ID found."
)
session.delete(existing_device)
session.commit()
def delete_expired_authorized_devices(self) -> None:
"""Deletes all expired OAuth 2.0 authorized devices."""
with Session(self.engine) as session:
expired_devices = session.exec(
select(OAuthDeviceSchema).where(OAuthDeviceSchema.user is None)
).all()
for device in expired_devices:
# Delete devices that have expired
if (
device.expires is not None
and device.expires < datetime.now()
and device.user_id is None
):
session.delete(device)
session.commit()
# ----------------------------- Flavors -----------------------------
@track_decorator(AnalyticsEvent.CREATED_FLAVOR)
def create_flavor(self, flavor: FlavorRequest) -> FlavorResponse:
"""Creates a new stack component flavor.
Args:
flavor: The stack component flavor to create.
Returns:
The newly created flavor.
Raises:
EntityExistsError: If a flavor with the same name and type
is already owned by this user in this workspace.
ValueError: In case the config_schema string exceeds the max length.
"""
with Session(self.engine) as session:
# Check if flavor with the same domain key (name, type, workspace,
# owner) already exists
existing_flavor = session.exec(
select(FlavorSchema)
.where(FlavorSchema.name == flavor.name)
.where(FlavorSchema.type == flavor.type)
.where(FlavorSchema.workspace_id == flavor.workspace)
.where(FlavorSchema.user_id == flavor.user)
).first()
if existing_flavor is not None:
raise EntityExistsError(
f"Unable to register '{flavor.type.value}' flavor "
f"with name '{flavor.name}': Found an existing "
f"flavor with the same name and type in the same "
f"'{flavor.workspace}' workspace owned by the same "
f"'{flavor.user}' user."
)
config_schema = json.dumps(flavor.config_schema)
if len(config_schema) > TEXT_FIELD_MAX_LENGTH:
raise ValueError(
"Json representation of configuration schema"
"exceeds max length."
)
else:
new_flavor = FlavorSchema(
name=flavor.name,
type=flavor.type,
source=flavor.source,
config_schema=config_schema,
integration=flavor.integration,
connector_type=flavor.connector_type,
connector_resource_type=flavor.connector_resource_type,
connector_resource_id_attr=flavor.connector_resource_id_attr,
workspace_id=flavor.workspace,
user_id=flavor.user,
logo_url=flavor.logo_url,
docs_url=flavor.docs_url,
sdk_docs_url=flavor.sdk_docs_url,
is_custom=flavor.is_custom,
)
session.add(new_flavor)
session.commit()
return new_flavor.to_model(include_metadata=True)
def get_flavor(
self, flavor_id: UUID, hydrate: bool = True
) -> FlavorResponse:
"""Get a flavor by ID.
Args:
flavor_id: The ID of the flavor to fetch.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The stack component flavor.
Raises:
KeyError: if the stack component flavor doesn't exist.
"""
with Session(self.engine) as session:
flavor_in_db = session.exec(
select(FlavorSchema).where(FlavorSchema.id == flavor_id)
).first()
if flavor_in_db is None:
raise KeyError(f"Flavor with ID {flavor_id} not found.")
return flavor_in_db.to_model(include_metadata=hydrate)
def list_flavors(
self,
flavor_filter_model: FlavorFilter,
hydrate: bool = False,
) -> Page[FlavorResponse]:
"""List all stack component flavors matching the given filter criteria.
Args:
flavor_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
List of all the stack component flavors matching the given criteria.
"""
with Session(self.engine) as session:
query = select(FlavorSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=FlavorSchema,
filter_model=flavor_filter_model,
hydrate=hydrate,
)
def update_flavor(
self, flavor_id: UUID, flavor_update: FlavorUpdate
) -> FlavorResponse:
"""Updates an existing user.
Args:
flavor_id: The id of the flavor to update.
flavor_update: The update to be applied to the flavor.
Returns:
The updated flavor.
Raises:
KeyError: If no flavor with the given id exists.
"""
with Session(self.engine) as session:
existing_flavor = session.exec(
select(FlavorSchema).where(FlavorSchema.id == flavor_id)
).first()
if not existing_flavor:
raise KeyError(f"Flavor with ID {flavor_id} not found.")
existing_flavor.update(flavor_update=flavor_update)
session.add(existing_flavor)
session.commit()
# Refresh the Model that was just created
session.refresh(existing_flavor)
return existing_flavor.to_model(include_metadata=True)
def delete_flavor(self, flavor_id: UUID) -> None:
"""Delete a flavor.
Args:
flavor_id: The id of the flavor to delete.
Raises:
KeyError: if the flavor doesn't exist.
IllegalOperationError: if the flavor is used by a stack component.
"""
with Session(self.engine) as session:
try:
flavor_in_db = session.exec(
select(FlavorSchema).where(FlavorSchema.id == flavor_id)
).one()
if flavor_in_db is None:
raise KeyError(f"Flavor with ID {flavor_id} not found.")
components_of_flavor = session.exec(
select(StackComponentSchema).where(
StackComponentSchema.flavor == flavor_in_db.name
)
).all()
if len(components_of_flavor) > 0:
raise IllegalOperationError(
f"Stack Component `{flavor_in_db.name}` of type "
f"`{flavor_in_db.type} cannot be "
f"deleted as it is used by "
f"{len(components_of_flavor)} "
f"components. Before deleting this "
f"flavor, make sure to delete all "
f"associated components."
)
else:
session.delete(flavor_in_db)
session.commit()
except NoResultFound as error:
raise KeyError from error
# ------------------------ Logs ------------------------
def get_logs(self, logs_id: UUID, hydrate: bool = True) -> LogsResponse:
"""Gets logs with the given ID.
Args:
logs_id: The ID of the logs to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The logs.
Raises:
KeyError: if the logs doesn't exist.
"""
with Session(self.engine) as session:
logs = session.exec(
select(LogsSchema).where(LogsSchema.id == logs_id)
).first()
if logs is None:
raise KeyError(
f"Unable to get logs with ID "
f"{logs_id}: "
f"No logs with this ID found."
)
return logs.to_model(include_metadata=hydrate)
# ----------------------------- Pipelines -----------------------------
@track_decorator(AnalyticsEvent.CREATE_PIPELINE)
def create_pipeline(
self,
pipeline: PipelineRequest,
) -> PipelineResponse:
"""Creates a new pipeline in a workspace.
Args:
pipeline: The pipeline to create.
Returns:
The newly created pipeline.
Raises:
EntityExistsError: If an identical pipeline already exists.
"""
with Session(self.engine) as session:
# Check if pipeline with the given name already exists
existing_pipeline = session.exec(
select(PipelineSchema)
.where(PipelineSchema.name == pipeline.name)
.where(PipelineSchema.version_hash == pipeline.version_hash)
.where(PipelineSchema.workspace_id == pipeline.workspace)
).first()
if existing_pipeline is not None:
raise EntityExistsError(
f"Unable to create pipeline in workspace "
f"'{pipeline.workspace}': A pipeline with this name and "
f"version already exists."
)
# Create the pipeline
new_pipeline = PipelineSchema.from_request(pipeline)
session.add(new_pipeline)
session.commit()
session.refresh(new_pipeline)
return new_pipeline.to_model(include_metadata=True)
def get_pipeline(
self, pipeline_id: UUID, hydrate: bool = True
) -> PipelineResponse:
"""Get a pipeline with a given ID.
Args:
pipeline_id: ID of the pipeline.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The pipeline.
Raises:
KeyError: if the pipeline does not exist.
"""
with Session(self.engine) as session:
# Check if pipeline with the given ID exists
pipeline = session.exec(
select(PipelineSchema).where(PipelineSchema.id == pipeline_id)
).first()
if pipeline is None:
raise KeyError(
f"Unable to get pipeline with ID '{pipeline_id}': "
"No pipeline with this ID found."
)
return pipeline.to_model(include_metadata=hydrate)
def list_pipeline_namespaces(
self,
filter_model: PipelineNamespaceFilter,
hydrate: bool = False,
) -> Page[PipelineNamespaceResponse]:
"""List all pipeline namespaces matching the given filter criteria.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all pipeline namespaces matching the filter criteria.
"""
def _custom_conversion(
row: Tuple[str, UUID, str],
) -> PipelineNamespaceResponse:
name, latest_run_id, latest_run_status = row
body = PipelineNamespaceResponseBody(
latest_run_id=latest_run_id,
latest_run_status=latest_run_status,
)
return PipelineNamespaceResponse(name=name, body=body)
def _custom_fetch(
session: Session,
query: Union[Select[Any], SelectOfScalar[Any]],
filter: BaseFilter,
) -> List[Any]:
return session.exec(query).unique().all()
with Session(self.engine) as session:
max_date_subquery = (
select( # type: ignore[call-overload]
PipelineSchema.name,
func.max(PipelineRunSchema.created).label("max_created"),
)
.outerjoin(
PipelineRunSchema,
PipelineSchema.id == PipelineRunSchema.pipeline_id,
)
.group_by(PipelineSchema.name)
.subquery()
)
query = (
select(
max_date_subquery.c.name,
PipelineRunSchema.id,
PipelineRunSchema.status,
)
.outerjoin(
PipelineSchema,
PipelineSchema.name == max_date_subquery.c.name,
)
.outerjoin(
PipelineRunSchema,
PipelineRunSchema.created
== max_date_subquery.c.max_created,
)
)
return self.filter_and_paginate(
session=session,
query=query,
table=PipelineSchema,
filter_model=filter_model,
hydrate=hydrate,
custom_fetch=_custom_fetch,
custom_schema_to_model_conversion=_custom_conversion,
)
def list_pipelines(
self,
pipeline_filter_model: PipelineFilter,
hydrate: bool = False,
) -> Page[PipelineResponse]:
"""List all pipelines matching the given filter criteria.
Args:
pipeline_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all pipelines matching the filter criteria.
"""
with Session(self.engine) as session:
query = select(PipelineSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=PipelineSchema,
filter_model=pipeline_filter_model,
hydrate=hydrate,
)
def count_pipelines(self, filter_model: Optional[PipelineFilter]) -> int:
"""Count all pipelines.
Args:
filter_model: The filter model to use for counting pipelines.
Returns:
The number of pipelines.
"""
return self._count_entity(
schema=PipelineSchema, filter_model=filter_model
)
def update_pipeline(
self,
pipeline_id: UUID,
pipeline_update: PipelineUpdate,
) -> PipelineResponse:
"""Updates a pipeline.
Args:
pipeline_id: The ID of the pipeline to be updated.
pipeline_update: The update to be applied.
Returns:
The updated pipeline.
Raises:
KeyError: if the pipeline doesn't exist.
"""
with Session(self.engine) as session:
# Check if pipeline with the given ID exists
existing_pipeline = session.exec(
select(PipelineSchema).where(PipelineSchema.id == pipeline_id)
).first()
if existing_pipeline is None:
raise KeyError(
f"Unable to update pipeline with ID {pipeline_id}: "
f"No pipeline with this ID found."
)
# Update the pipeline
existing_pipeline.update(pipeline_update)
session.add(existing_pipeline)
session.commit()
return existing_pipeline.to_model(include_metadata=True)
def delete_pipeline(self, pipeline_id: UUID) -> None:
"""Deletes a pipeline.
Args:
pipeline_id: The ID of the pipeline to delete.
Raises:
KeyError: if the pipeline doesn't exist.
"""
with Session(self.engine) as session:
# Check if pipeline with the given ID exists
pipeline = session.exec(
select(PipelineSchema).where(PipelineSchema.id == pipeline_id)
).first()
if pipeline is None:
raise KeyError(
f"Unable to delete pipeline with ID {pipeline_id}: "
f"No pipeline with this ID found."
)
session.delete(pipeline)
session.commit()
# --------------------------- Pipeline Builds ---------------------------
def create_build(
self,
build: PipelineBuildRequest,
) -> PipelineBuildResponse:
"""Creates a new build in a workspace.
Args:
build: The build to create.
Returns:
The newly created build.
"""
with Session(self.engine) as session:
# Create the build
new_build = PipelineBuildSchema.from_request(build)
session.add(new_build)
session.commit()
session.refresh(new_build)
return new_build.to_model(include_metadata=True)
def get_build(
self, build_id: UUID, hydrate: bool = True
) -> PipelineBuildResponse:
"""Get a build with a given ID.
Args:
build_id: ID of the build.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The build.
Raises:
KeyError: If the build does not exist.
"""
with Session(self.engine) as session:
# Check if build with the given ID exists
build = session.exec(
select(PipelineBuildSchema).where(
PipelineBuildSchema.id == build_id
)
).first()
if build is None:
raise KeyError(
f"Unable to get build with ID '{build_id}': "
"No build with this ID found."
)
return build.to_model(include_metadata=hydrate)
def list_builds(
self,
build_filter_model: PipelineBuildFilter,
hydrate: bool = False,
) -> Page[PipelineBuildResponse]:
"""List all builds matching the given filter criteria.
Args:
build_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all builds matching the filter criteria.
"""
with Session(self.engine) as session:
query = select(PipelineBuildSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=PipelineBuildSchema,
filter_model=build_filter_model,
hydrate=hydrate,
)
def delete_build(self, build_id: UUID) -> None:
"""Deletes a build.
Args:
build_id: The ID of the build to delete.
Raises:
KeyError: if the build doesn't exist.
"""
with Session(self.engine) as session:
# Check if build with the given ID exists
build = session.exec(
select(PipelineBuildSchema).where(
PipelineBuildSchema.id == build_id
)
).first()
if build is None:
raise KeyError(
f"Unable to delete build with ID {build_id}: "
f"No build with this ID found."
)
session.delete(build)
session.commit()
# -------------------------- Pipeline Deployments --------------------------
def create_deployment(
self,
deployment: PipelineDeploymentRequest,
) -> PipelineDeploymentResponse:
"""Creates a new deployment in a workspace.
Args:
deployment: The deployment to create.
Returns:
The newly created deployment.
"""
with Session(self.engine) as session:
code_reference_id = self._create_or_reuse_code_reference(
session=session,
workspace_id=deployment.workspace,
code_reference=deployment.code_reference,
)
new_deployment = PipelineDeploymentSchema.from_request(
deployment, code_reference_id=code_reference_id
)
session.add(new_deployment)
session.commit()
session.refresh(new_deployment)
return new_deployment.to_model(include_metadata=True)
def get_deployment(
self, deployment_id: UUID, hydrate: bool = True
) -> PipelineDeploymentResponse:
"""Get a deployment with a given ID.
Args:
deployment_id: ID of the deployment.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The deployment.
Raises:
KeyError: If the deployment does not exist.
"""
with Session(self.engine) as session:
# Check if deployment with the given ID exists
deployment = session.exec(
select(PipelineDeploymentSchema).where(
PipelineDeploymentSchema.id == deployment_id
)
).first()
if deployment is None:
raise KeyError(
f"Unable to get deployment with ID '{deployment_id}': "
"No deployment with this ID found."
)
return deployment.to_model(include_metadata=hydrate)
def list_deployments(
self,
deployment_filter_model: PipelineDeploymentFilter,
hydrate: bool = False,
) -> Page[PipelineDeploymentResponse]:
"""List all deployments matching the given filter criteria.
Args:
deployment_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all deployments matching the filter criteria.
"""
with Session(self.engine) as session:
query = select(PipelineDeploymentSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=PipelineDeploymentSchema,
filter_model=deployment_filter_model,
hydrate=hydrate,
)
def delete_deployment(self, deployment_id: UUID) -> None:
"""Deletes a deployment.
Args:
deployment_id: The ID of the deployment to delete.
Raises:
KeyError: If the deployment doesn't exist.
"""
with Session(self.engine) as session:
# Check if build with the given ID exists
deployment = session.exec(
select(PipelineDeploymentSchema).where(
PipelineDeploymentSchema.id == deployment_id
)
).first()
if deployment is None:
raise KeyError(
f"Unable to delete deployment with ID {deployment_id}: "
f"No deployment with this ID found."
)
session.delete(deployment)
session.commit()
# -------------------- Event Sources --------------------
def _fail_if_event_source_with_name_exists(
self, event_source: EventSourceRequest, session: Session
) -> None:
"""Raise an exception if a stack with same name exists.
Args:
event_source: The event_source to create.
session: The Session
Returns:
None
Raises:
EventSourceExistsError: In case the event source already exists
"""
existing_domain_event_source = session.exec(
select(EventSourceSchema)
.where(EventSourceSchema.name == event_source.name)
.where(EventSourceSchema.workspace_id == event_source.workspace)
).first()
if existing_domain_event_source is not None:
workspace = self._get_workspace_schema(
workspace_name_or_id=event_source.workspace, session=session
)
raise EventSourceExistsError(
f"Unable to register event source with name "
f"'{event_source.name}': Found an existing event source with "
f"the same name in the active workspace, '{workspace.name}'."
)
return None
def create_event_source(
self, event_source: EventSourceRequest
) -> EventSourceResponse:
"""Create an event_source.
Args:
event_source: The event_source to create.
Returns:
The created event_source.
"""
with Session(self.engine) as session:
self._fail_if_event_source_with_name_exists(
event_source=event_source,
session=session,
)
new_event_source = EventSourceSchema.from_request(event_source)
session.add(new_event_source)
session.commit()
session.refresh(new_event_source)
return new_event_source.to_model(
include_metadata=True, include_resources=True
)
def _get_event_source(
self,
event_source_id: UUID,
session: Session,
) -> EventSourceSchema:
"""Get an event_source by ID.
Args:
event_source_id: The ID of the event_source to get.
session: The DB session.
Returns:
The event_source schema.
"""
return self._get_schema_by_name_or_id(
object_name_or_id=event_source_id,
schema_class=EventSourceSchema,
schema_name="event_source",
session=session,
)
def get_event_source(
self,
event_source_id: UUID,
hydrate: bool = True,
) -> EventSourceResponse:
"""Get an event_source by ID.
Args:
event_source_id: The ID of the event_source to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The event_source.
"""
with Session(self.engine) as session:
return self._get_event_source(
event_source_id=event_source_id, session=session
).to_model(include_metadata=hydrate, include_resources=True)
def list_event_sources(
self,
event_source_filter_model: EventSourceFilter,
hydrate: bool = False,
) -> Page[EventSourceResponse]:
"""List all event_sources matching the given filter criteria.
Args:
event_source_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all event_sources matching the filter criteria.
"""
with Session(self.engine) as session:
query = select(EventSourceSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=EventSourceSchema,
filter_model=event_source_filter_model,
hydrate=hydrate,
)
def update_event_source(
self,
event_source_id: UUID,
event_source_update: EventSourceUpdate,
) -> EventSourceResponse:
"""Update an existing event_source.
Args:
event_source_id: The ID of the event_source to update.
event_source_update: The update to be applied to the event_source.
Returns:
The updated event_source.
"""
with Session(self.engine) as session:
event_source = self._get_event_source(
session=session, event_source_id=event_source_id
)
event_source.update(update=event_source_update)
session.add(event_source)
session.commit()
# Refresh the event_source that was just created
session.refresh(event_source)
return event_source.to_model(
include_metadata=True, include_resources=True
)
def delete_event_source(self, event_source_id: UUID) -> None:
"""Delete an event_source.
Args:
event_source_id: The ID of the event_source to delete.
Raises:
KeyError: if the event_source doesn't exist.
"""
with Session(self.engine) as session:
event_source = self._get_event_source(
event_source_id=event_source_id, session=session
)
if event_source is None:
raise KeyError(
f"Unable to delete event_source with ID `{event_source_id}`: "
f"No event_source with this ID found."
)
session.delete(event_source)
session.commit()
# TODO: catch and throw proper error if it can't be deleted due to
# not-null constraints on triggers
# ----------------------------- Pipeline runs -----------------------------
def create_run(
self, pipeline_run: PipelineRunRequest
) -> PipelineRunResponse:
"""Creates a pipeline run.
Args:
pipeline_run: The pipeline run to create.
Returns:
The created pipeline run.
Raises:
EntityExistsError: If a run with the same name already exists.
"""
with Session(self.engine) as session:
# Check if pipeline run with same name already exists.
existing_domain_run = session.exec(
select(PipelineRunSchema).where(
PipelineRunSchema.name == pipeline_run.name
)
).first()
if existing_domain_run is not None:
raise EntityExistsError(
f"Unable to create pipeline run: A pipeline run with name "
f"'{pipeline_run.name}' already exists."
)
# Create the pipeline run
new_run = PipelineRunSchema.from_request(pipeline_run)
session.add(new_run)
session.commit()
return new_run.to_model(include_metadata=True)
def get_run(
self, run_name_or_id: Union[str, UUID], hydrate: bool = True
) -> PipelineRunResponse:
"""Gets a pipeline run.
Args:
run_name_or_id: The name or ID of the pipeline run to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The pipeline run.
"""
with Session(self.engine) as session:
return self._get_run_schema(
run_name_or_id, session=session
).to_model(include_metadata=hydrate)
def _replace_placeholder_run(
self, pipeline_run: PipelineRunRequest
) -> PipelineRunResponse:
"""Replace a placeholder run with the requested pipeline run.
Args:
pipeline_run: Pipeline run request.
Raises:
KeyError: If no placeholder run exists.
Returns:
The run model.
"""
with Session(self.engine) as session:
run_schema = session.exec(
select(PipelineRunSchema)
# The following line locks the row in the DB, so anyone else
# calling `SELECT ... FOR UPDATE` will wait until the first
# transaction to do so finishes. After the first transaction
# finishes, the subsequent queries will not be able to find a
# placeholder run anymore, as we already updated the
# orchestrator_run_id.
# Note: This only locks a single row if the where clause of
# the query is indexed (we have a unique index due to the
# unique constraint on those columns). Otherwise this will lock
# multiple rows or even the complete table which we want to
# avoid.
.with_for_update()
.where(
PipelineRunSchema.deployment_id == pipeline_run.deployment
)
.where(
PipelineRunSchema.orchestrator_run_id.is_(None) # type: ignore[union-attr]
)
).first()
if not run_schema:
raise KeyError("No placeholder run found.")
run_schema.update_placeholder(pipeline_run)
session.add(run_schema)
session.commit()
return run_schema.to_model(include_metadata=True)
def _get_run_by_orchestrator_run_id(
self, orchestrator_run_id: str, deployment_id: UUID
) -> PipelineRunResponse:
"""Get a pipeline run based on deployment and orchestrator run ID.
Args:
orchestrator_run_id: The orchestrator run ID.
deployment_id: The deployment ID.
Raises:
KeyError: If no run exists for the deployment and orchestrator run
ID.
Returns:
The pipeline run.
"""
with Session(self.engine) as session:
run_schema = session.exec(
select(PipelineRunSchema)
.where(PipelineRunSchema.deployment_id == deployment_id)
.where(
PipelineRunSchema.orchestrator_run_id
== orchestrator_run_id
)
).first()
if not run_schema:
raise KeyError(
f"Unable to get run for orchestrator run ID "
f"{orchestrator_run_id} and deployment ID {deployment_id}."
)
return run_schema.to_model(include_metadata=True)
def get_or_create_run(
self, pipeline_run: PipelineRunRequest
) -> Tuple[PipelineRunResponse, bool]:
"""Gets or creates a pipeline run.
If a run with the same ID or name already exists, it is returned.
Otherwise, a new run is created.
Args:
pipeline_run: The pipeline run to get or create.
# noqa: DAR401
Raises:
ValueError: If the request does not contain an orchestrator run ID.
EntityExistsError: If a run with the same name already exists.
RuntimeError: If the run fetching failed unexpectedly.
Returns:
The pipeline run, and a boolean indicating whether the run was
created or not.
"""
if not pipeline_run.orchestrator_run_id:
raise ValueError(
"Unable to get or create run for request with missing "
"orchestrator run ID."
)
try:
return (
self._replace_placeholder_run(pipeline_run=pipeline_run),
True,
)
except KeyError:
# We were not able to find/replace a placeholder run. This could be
# due to one of the following three reasons:
# (1) There never was a placeholder run for the deployment. This is
# the case if the user ran the pipeline on a schedule.
# (2) There was a placeholder run, but a previous pipeline run
# already used it. This is the case if users rerun a pipeline
# run e.g. from the orchestrator UI, as they will use the same
# deployment_id with a new orchestrator_run_id.
# (3) A step of the same pipeline run already replaced the
# placeholder run.
pass
try:
# We now try to create a new run. The following will happen in the
# three cases described above:
# (1) The behavior depends on whether we're the first step of the
# pipeline run that's trying to create the run. If yes, the
# `self.create_run(...)` will succeed. If no, a run with the
# same deployment_id and orchestrator_run_id already exists and
# the `self.create_run(...)` call will fail due to the unique
# constraint on those columns.
# (2) Same as (1).
# (3) A step of the same pipeline run replaced the placeholder
# run, which now contains the deployment_id and
# orchestrator_run_id of the run that we're trying to create.
# -> The `self.create_run(...) call will fail due to the unique
# constraint on those columns.
return self.create_run(pipeline_run), True
except (EntityExistsError, IntegrityError) as create_error:
# Creating the run failed with an
# - IntegrityError: This happens when we violated a unique
# constraint, which in turn means a run with the same
# deployment_id and orchestrator_run_id exists. We now fetch and
# return that run.
# - EntityExistsError: This happens when a run with the same name
# already exists. This could be either a different run (in which
# case we want to fail) or a run created by a step of the same
# pipeline run (in which case we want to return it).
# Note: The IntegrityError might also be raised when other unique
# constraints get violated. The only other such constraint is the
# primary key constraint on the run ID, which means we randomly
# generated an existing UUID. In this case the call below will fail,
# but the chance of that happening is so low we don't handle it.
try:
return (
self._get_run_by_orchestrator_run_id(
orchestrator_run_id=pipeline_run.orchestrator_run_id,
deployment_id=pipeline_run.deployment,
),
False,
)
except KeyError:
if isinstance(create_error, EntityExistsError):
# There was a run with the same name which does not share
# the deployment_id and orchestrator_run_id -> We fail with
# the error that run names must be unique.
raise create_error from None
# This should never happen as the run creation failed with an
# IntegrityError which means a run with the deployment_id and
# orchestrator_run_id exists.
raise RuntimeError(
f"Failed to get or create run: {create_error}"
)
def list_runs(
self,
runs_filter_model: PipelineRunFilter,
hydrate: bool = False,
) -> Page[PipelineRunResponse]:
"""List all pipeline runs matching the given filter criteria.
Args:
runs_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all pipeline runs matching the filter criteria.
"""
with Session(self.engine) as session:
query = select(PipelineRunSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=PipelineRunSchema,
filter_model=runs_filter_model,
hydrate=hydrate,
)
def update_run(
self, run_id: UUID, run_update: PipelineRunUpdate
) -> PipelineRunResponse:
"""Updates a pipeline run.
Args:
run_id: The ID of the pipeline run to update.
run_update: The update to be applied to the pipeline run.
Returns:
The updated pipeline run.
Raises:
KeyError: if the pipeline run doesn't exist.
"""
with Session(self.engine) as session:
# Check if pipeline run with the given ID exists
existing_run = session.exec(
select(PipelineRunSchema).where(PipelineRunSchema.id == run_id)
).first()
if existing_run is None:
raise KeyError(
f"Unable to update pipeline run with ID {run_id}: "
f"No pipeline run with this ID found."
)
# Update the pipeline run
existing_run.update(run_update=run_update)
session.add(existing_run)
session.commit()
session.refresh(existing_run)
return existing_run.to_model(include_metadata=True)
def delete_run(self, run_id: UUID) -> None:
"""Deletes a pipeline run.
Args:
run_id: The ID of the pipeline run to delete.
Raises:
KeyError: if the pipeline run doesn't exist.
"""
with Session(self.engine) as session:
# Check if pipeline run with the given ID exists
existing_run = session.exec(
select(PipelineRunSchema).where(PipelineRunSchema.id == run_id)
).first()
if existing_run is None:
raise KeyError(
f"Unable to delete pipeline run with ID {run_id}: "
f"No pipeline run with this ID found."
)
# Delete the pipeline run
session.delete(existing_run)
session.commit()
def count_runs(self, filter_model: Optional[PipelineRunFilter]) -> int:
"""Count all pipeline runs.
Args:
filter_model: The filter model to filter the runs.
Returns:
The number of pipeline runs.
"""
return self._count_entity(
schema=PipelineRunSchema, filter_model=filter_model
)
# ----------------------------- Run Metadata -----------------------------
def create_run_metadata(
self, run_metadata: RunMetadataRequest
) -> List[RunMetadataResponse]:
"""Creates run metadata.
Args:
run_metadata: The run metadata to create.
Returns:
The created run metadata.
"""
return_value: List[RunMetadataResponse] = []
with Session(self.engine) as session:
for key, value in run_metadata.values.items():
type_ = run_metadata.types[key]
run_metadata_schema = RunMetadataSchema(
workspace_id=run_metadata.workspace,
user_id=run_metadata.user,
resource_id=run_metadata.resource_id,
resource_type=run_metadata.resource_type.value,
stack_component_id=run_metadata.stack_component_id,
key=key,
value=json.dumps(value),
type=type_,
)
session.add(run_metadata_schema)
session.commit()
return_value.append(
run_metadata_schema.to_model(include_metadata=True)
)
return return_value
def get_run_metadata(
self, run_metadata_id: UUID, hydrate: bool = True
) -> RunMetadataResponse:
"""Gets run metadata with the given ID.
Args:
run_metadata_id: The ID of the run metadata to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The run metadata.
Raises:
KeyError: if the run metadata doesn't exist.
"""
with Session(self.engine) as session:
run_metadata = session.exec(
select(RunMetadataSchema).where(
RunMetadataSchema.id == run_metadata_id
)
).first()
if run_metadata is None:
raise KeyError(
f"Unable to get run metadata with ID "
f"{run_metadata_id}: "
f"No run metadata with this ID found."
)
return run_metadata.to_model(include_metadata=hydrate)
def list_run_metadata(
self,
run_metadata_filter_model: RunMetadataFilter,
hydrate: bool = False,
) -> Page[RunMetadataResponse]:
"""List run metadata.
Args:
run_metadata_filter_model: All filter parameters including
pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The run metadata.
"""
with Session(self.engine) as session:
query = select(RunMetadataSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=RunMetadataSchema,
filter_model=run_metadata_filter_model,
hydrate=hydrate,
)
# ----------------------------- Schedules -----------------------------
def create_schedule(self, schedule: ScheduleRequest) -> ScheduleResponse:
"""Creates a new schedule.
Args:
schedule: The schedule to create.
Returns:
The newly created schedule.
"""
with Session(self.engine) as session:
new_schedule = ScheduleSchema.from_request(schedule)
session.add(new_schedule)
session.commit()
return new_schedule.to_model(include_metadata=True)
def get_schedule(
self, schedule_id: UUID, hydrate: bool = True
) -> ScheduleResponse:
"""Get a schedule with a given ID.
Args:
schedule_id: ID of the schedule.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The schedule.
Raises:
KeyError: if the schedule does not exist.
"""
with Session(self.engine) as session:
# Check if schedule with the given ID exists
schedule = session.exec(
select(ScheduleSchema).where(ScheduleSchema.id == schedule_id)
).first()
if schedule is None:
raise KeyError(
f"Unable to get schedule with ID '{schedule_id}': "
"No schedule with this ID found."
)
return schedule.to_model(include_metadata=hydrate)
def list_schedules(
self,
schedule_filter_model: ScheduleFilter,
hydrate: bool = False,
) -> Page[ScheduleResponse]:
"""List all schedules in the workspace.
Args:
schedule_filter_model: All filter parameters including pagination
params
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of schedules.
"""
with Session(self.engine) as session:
query = select(ScheduleSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=ScheduleSchema,
filter_model=schedule_filter_model,
hydrate=hydrate,
)
def update_schedule(
self,
schedule_id: UUID,
schedule_update: ScheduleUpdate,
) -> ScheduleResponse:
"""Updates a schedule.
Args:
schedule_id: The ID of the schedule to be updated.
schedule_update: The update to be applied.
Returns:
The updated schedule.
Raises:
KeyError: if the schedule doesn't exist.
"""
with Session(self.engine) as session:
# Check if schedule with the given ID exists
existing_schedule = session.exec(
select(ScheduleSchema).where(ScheduleSchema.id == schedule_id)
).first()
if existing_schedule is None:
raise KeyError(
f"Unable to update schedule with ID {schedule_id}: "
f"No schedule with this ID found."
)
# Update the schedule
existing_schedule = existing_schedule.update(schedule_update)
session.add(existing_schedule)
session.commit()
return existing_schedule.to_model(include_metadata=True)
def delete_schedule(self, schedule_id: UUID) -> None:
"""Deletes a schedule.
Args:
schedule_id: The ID of the schedule to delete.
Raises:
KeyError: if the schedule doesn't exist.
"""
with Session(self.engine) as session:
# Check if schedule with the given ID exists
schedule = session.exec(
select(ScheduleSchema).where(ScheduleSchema.id == schedule_id)
).first()
if schedule is None:
raise KeyError(
f"Unable to delete schedule with ID {schedule_id}: "
f"No schedule with this ID found."
)
# Delete the schedule
session.delete(schedule)
session.commit()
# ------------------------- Secrets -------------------------
def _check_sql_secret_scope(
self,
session: Session,
secret_name: str,
scope: SecretScope,
workspace: UUID,
user: UUID,
exclude_secret_id: Optional[UUID] = None,
) -> Tuple[bool, str]:
"""Checks if a secret with the given name already exists in the given scope.
This method enforces the following scope rules:
- only one workspace-scoped secret with the given name can exist
in the target workspace.
- only one user-scoped secret with the given name can exist in the
target workspace for the target user.
Args:
session: The SQLAlchemy session.
secret_name: The name of the secret.
scope: The scope of the secret.
workspace: The ID of the workspace to which the secret belongs.
user: The ID of the user to which the secret belongs.
exclude_secret_id: The ID of a secret to exclude from the check
(used e.g. during an update to exclude the existing secret).
Returns:
True if a secret with the given name already exists in the given
scope, False otherwise, and an error message.
"""
scope_filter = (
select(SecretSchema)
.where(SecretSchema.name == secret_name)
.where(SecretSchema.scope == scope.value)
)
if scope in [SecretScope.WORKSPACE, SecretScope.USER]:
scope_filter = scope_filter.where(
SecretSchema.workspace_id == workspace
)
if scope == SecretScope.USER:
scope_filter = scope_filter.where(SecretSchema.user_id == user)
if exclude_secret_id is not None:
scope_filter = scope_filter.where(
SecretSchema.id != exclude_secret_id
)
existing_secret = session.exec(scope_filter).first()
if existing_secret is not None:
existing_secret_model = existing_secret.to_model(
include_metadata=True
)
msg = (
f"Found an existing {scope.value} scoped secret with the "
f"same '{secret_name}' name"
)
if scope in [SecretScope.WORKSPACE, SecretScope.USER]:
msg += (
f" in the same '{existing_secret_model.workspace.name}' "
f"workspace"
)
if scope == SecretScope.USER:
assert existing_secret_model.user
msg += (
f" for the same '{existing_secret_model.user.name}' user"
)
return True, msg
return False, ""
def _set_secret_values(
self, secret_id: UUID, values: Dict[str, str], backup: bool = True
) -> None:
"""Sets the values of a secret in the configured secrets store.
Args:
secret_id: The ID of the secret to set the values of.
values: The values to set.
backup: Whether to back up the values in the backup secrets store,
if configured.
# noqa: DAR401
"""
def do_backup() -> bool:
"""Backs up the values of a secret in the configured backup secrets store.
Returns:
True if the backup succeeded, False otherwise.
"""
if not backup or not self.backup_secrets_store:
return False
logger.info(
f"Storing secret {secret_id} in the backup secrets store. "
)
try:
self._backup_secret_values(secret_id=secret_id, values=values)
except Exception:
logger.exception(
f"Failed to store secret values for secret with ID "
f"{secret_id} in the backup secrets store. "
)
return False
return True
try:
self.secrets_store.store_secret_values(
secret_id=secret_id, secret_values=values
)
except Exception:
logger.exception(
f"Failed to store secret values for secret with ID "
f"{secret_id} in the primary secrets store. "
)
if not do_backup():
raise
else:
do_backup()
def _backup_secret_values(
self, secret_id: UUID, values: Dict[str, str]
) -> None:
"""Backs up the values of a secret in the configured backup secrets store.
Args:
secret_id: The ID of the secret the values of which to backup.
values: The values to back up.
"""
if self.backup_secrets_store:
# We attempt either an update or a create operation depending on
# whether the secret values are already stored in the backup secrets
# store. This is to account for any inconsistencies in the backup
# secrets store without impairing the backup functionality.
try:
self.backup_secrets_store.get_secret_values(
secret_id=secret_id,
)
except KeyError:
self.backup_secrets_store.store_secret_values(
secret_id=secret_id, secret_values=values
)
else:
self.backup_secrets_store.update_secret_values(
secret_id=secret_id, secret_values=values
)
def _get_secret_values(
self, secret_id: UUID, use_backup: bool = True
) -> Dict[str, str]:
"""Gets the values of a secret from the configured secrets store.
Args:
secret_id: The ID of the secret to get the values of.
use_backup: Whether to use the backup secrets store if the primary
secrets store fails to retrieve the values and if a backup
secrets store is configured.
Returns:
The values of the secret.
# noqa: DAR401
"""
try:
return self.secrets_store.get_secret_values(
secret_id=secret_id,
)
except Exception as e:
if use_backup and self.backup_secrets_store:
logger.exception(
f"Failed to get secret values for secret with ID "
f"{secret_id} from the primary secrets store. "
f"Trying to get them from the backup secrets store. "
)
try:
backup_values = self._get_backup_secret_values(
secret_id=secret_id
)
if isinstance(e, KeyError):
# Attempt to automatically restore the values in the
# primary secrets store if the backup secrets store
# succeeds in retrieving them and if the values are
# missing in the primary secrets store.
try:
self.secrets_store.store_secret_values(
secret_id=secret_id,
secret_values=backup_values,
)
except Exception:
logger.exception(
f"Failed to restore secret values for secret "
f"with ID {secret_id} in the primary secrets "
"store. "
)
return backup_values
except Exception:
logger.exception(
f"Failed to get secret values for secret with ID "
f"{secret_id} from the backup secrets store. "
)
raise
def _get_backup_secret_values(self, secret_id: UUID) -> Dict[str, str]:
"""Gets the backup values of a secret from the configured backup secrets store.
Args:
secret_id: The ID of the secret to get the values of.
Returns:
The backup values of the secret.
Raises:
KeyError: If no backup secrets store is configured.
"""
if self.backup_secrets_store:
return self.backup_secrets_store.get_secret_values(
secret_id=secret_id,
)
raise KeyError(
f"Unable to get backup secret values for secret with ID "
f"{secret_id}: No backup secrets store is configured."
)
def _update_secret_values(
self,
secret_id: UUID,
values: Dict[str, Optional[str]],
overwrite: bool = False,
backup: bool = True,
) -> Dict[str, str]:
"""Updates the values of a secret in the configured secrets store.
This method will update the existing values with the new values
and drop `None` values.
Args:
secret_id: The ID of the secret to set the values of.
values: The updated values to set.
overwrite: Whether to overwrite the existing values with the new
values. If set to False, the new values will be merged with the
existing values.
backup: Whether to back up the updated values in the backup secrets
store, if configured.
Returns:
The updated values.
# noqa: DAR401
"""
try:
existing_values = self._get_secret_values(
secret_id=secret_id, use_backup=backup
)
except KeyError:
logger.error(
f"Unable to update secret values for secret with ID "
f"{secret_id}: No secret with this ID found in the secrets "
f"store back-end. Creating a new secret instead."
)
# If no secret values are yet stored in the secrets store,
# we simply treat this as a create operation. This is to account
# for cases in which secrets are manually deleted in the secrets
# store backend or when the secrets store backend is reconfigured to
# a different account, provider, region etc. without migrating
# the actual existing secrets themselves.
new_values: Dict[str, str] = {
k: v for k, v in values.items() if v is not None
}
self._set_secret_values(
secret_id=secret_id, values=new_values, backup=backup
)
return new_values
if overwrite:
existing_values = {
k: v for k, v in values.items() if v is not None
}
else:
for k, v in values.items():
if v is not None:
existing_values[k] = v
# Drop values removed in the update
if v is None and k in existing_values:
del existing_values[k]
def do_backup() -> bool:
"""Backs up the values of a secret in the configured backup secrets store.
Returns:
True if the backup succeeded, False otherwise.
"""
if not backup or not self.backup_secrets_store:
return False
logger.info(
f"Storing secret {secret_id} in the backup secrets store. "
)
try:
self._backup_secret_values(
secret_id=secret_id, values=existing_values
)
except Exception:
logger.exception(
f"Failed to store secret values for secret with ID "
f"{secret_id} in the backup secrets store. "
)
return False
return True
try:
self.secrets_store.update_secret_values(
secret_id=secret_id, secret_values=existing_values
)
except Exception:
logger.exception(
f"Failed to update secret values for secret with ID "
f"{secret_id} in the primary secrets store. "
)
if not do_backup():
raise
else:
do_backup()
return existing_values
def _delete_secret_values(
self,
secret_id: UUID,
delete_backup: bool = True,
) -> None:
"""Deletes the values of a secret in the configured secrets store.
Args:
secret_id: The ID of the secret for which to delete the values.
delete_backup: Whether to delete the backup values of the secret
from the backup secrets store, if configured.
# noqa: DAR401
"""
def do_delete_backup() -> bool:
"""Deletes the backup values of a secret in the configured backup secrets store.
Returns:
True if the backup deletion succeeded, False otherwise.
"""
if not delete_backup or not self.backup_secrets_store:
return False
logger.info(
f"Deleting secret {secret_id} from the backup secrets store."
)
try:
self._delete_backup_secret_values(secret_id=secret_id)
except KeyError:
# If the secret doesn't exist in the backup secrets store, we
# consider this a success.
return True
except Exception:
logger.exception(
f"Failed to delete secret values for secret with ID "
f"{secret_id} from the backup secrets store. "
)
return False
return True
try:
self.secrets_store.delete_secret_values(secret_id=secret_id)
except KeyError:
# If the secret doesn't exist in the primary secrets store, we
# consider this a success.
do_delete_backup()
except Exception:
logger.exception(
f"Failed to delete secret values for secret with ID "
f"{secret_id} from the primary secrets store. "
)
if not do_delete_backup():
raise
else:
do_delete_backup()
def _delete_backup_secret_values(
self,
secret_id: UUID,
) -> None:
"""Deletes the backup values of a secret in the configured backup secrets store.
Args:
secret_id: The ID of the secret for which to delete the backup values.
"""
if self.backup_secrets_store:
self.backup_secrets_store.delete_secret_values(secret_id=secret_id)
@track_decorator(AnalyticsEvent.CREATED_SECRET)
def create_secret(self, secret: SecretRequest) -> SecretResponse:
"""Creates a new secret.
The new secret is also validated against the scoping rules enforced in
the secrets store:
- only one workspace-scoped secret with the given name can exist
in the target workspace.
- only one user-scoped secret with the given name can exist in the
target workspace for the target user.
Args:
secret: The secret to create.
Returns:
The newly created secret.
Raises:
EntityExistsError: If a secret with the same name already exists in
the same scope.
"""
with Session(self.engine) as session:
# Check if a secret with the same name already exists in the same
# scope.
secret_exists, msg = self._check_sql_secret_scope(
session=session,
secret_name=secret.name,
scope=secret.scope,
workspace=secret.workspace,
user=secret.user,
)
if secret_exists:
raise EntityExistsError(msg)
new_secret = SecretSchema.from_request(
secret,
)
session.add(new_secret)
session.commit()
secret_model = new_secret.to_model(include_metadata=True)
try:
# Set the secret values in the configured secrets store
self._set_secret_values(
secret_id=new_secret.id, values=secret.secret_values
)
except:
# If setting the secret values fails, delete the secret from the
# database.
with Session(self.engine) as session:
session.delete(new_secret)
session.commit()
raise
secret_model.set_secrets(secret.secret_values)
return secret_model
def get_secret(
self, secret_id: UUID, hydrate: bool = True
) -> SecretResponse:
"""Get a secret by ID.
Args:
secret_id: The ID of the secret to fetch.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The secret.
Raises:
KeyError: if the secret doesn't exist.
"""
with Session(self.engine) as session:
secret_in_db = session.exec(
select(SecretSchema).where(SecretSchema.id == secret_id)
).first()
if secret_in_db is None:
raise KeyError(f"Secret with ID {secret_id} not found.")
secret_model = secret_in_db.to_model(include_metadata=hydrate)
secret_model.set_secrets(self._get_secret_values(secret_id=secret_id))
return secret_model
def list_secrets(
self, secret_filter_model: SecretFilter, hydrate: bool = False
) -> Page[SecretResponse]:
"""List all secrets matching the given filter criteria.
Note that returned secrets do not include any secret values. To fetch
the secret values, use `get_secret`.
Args:
secret_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all secrets matching the filter criteria, with pagination
information and sorted according to the filter criteria. The
returned secrets do not include any secret values, only metadata. To
fetch the secret values, use `get_secret` individually with each
secret.
"""
with Session(self.engine) as session:
query = select(SecretSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=SecretSchema,
filter_model=secret_filter_model,
hydrate=hydrate,
)
def update_secret(
self, secret_id: UUID, secret_update: SecretUpdate
) -> SecretResponse:
"""Updates a secret.
Secret values that are specified as `None` in the update that are
present in the existing secret are removed from the existing secret.
Values that are present in both secrets are overwritten. All other
values in both the existing secret and the update are kept (merged).
If the update includes a change of name or scope, the scoping rules
enforced in the secrets store are used to validate the update:
- only one workspace-scoped secret with the given name can exist
in the target workspace.
- only one user-scoped secret with the given name can exist in the
target workspace for the target user.
Args:
secret_id: The ID of the secret to be updated.
secret_update: The update to be applied.
Returns:
The updated secret.
Raises:
KeyError: if the secret doesn't exist.
EntityExistsError: If a secret with the same name already exists in
the same scope.
"""
with Session(self.engine) as session:
existing_secret = session.exec(
select(SecretSchema).where(SecretSchema.id == secret_id)
).first()
if not existing_secret:
raise KeyError(f"Secret with ID {secret_id} not found.")
# A change in name or scope requires a check of the scoping rules.
if (
secret_update.name is not None
and existing_secret.name != secret_update.name
or secret_update.scope is not None
and existing_secret.scope != secret_update.scope
):
secret_exists, msg = self._check_sql_secret_scope(
session=session,
secret_name=secret_update.name or existing_secret.name,
scope=secret_update.scope
or SecretScope(existing_secret.scope),
workspace=existing_secret.workspace.id,
user=existing_secret.user.id,
exclude_secret_id=secret_id,
)
if secret_exists:
raise EntityExistsError(msg)
existing_secret.update(
secret_update=secret_update,
)
session.add(existing_secret)
session.commit()
# Refresh the Model that was just created
session.refresh(existing_secret)
secret_model = existing_secret.to_model(include_metadata=True)
if secret_update.values is not None:
# Update the secret values in the configured secrets store
updated_values = self._update_secret_values(
secret_id=secret_id,
values=secret_update.get_secret_values_update(),
)
secret_model.set_secrets(updated_values)
else:
secret_model.set_secrets(self._get_secret_values(secret_id))
return secret_model
def delete_secret(self, secret_id: UUID) -> None:
"""Delete a secret.
Args:
secret_id: The id of the secret to delete.
Raises:
KeyError: if the secret doesn't exist.
"""
# Delete the secret values in the configured secrets store
try:
self._delete_secret_values(secret_id=secret_id)
except KeyError:
# If the secret values don't exist in the secrets store, we don't
# need to raise an error.
pass
with Session(self.engine) as session:
try:
secret_in_db = session.exec(
select(SecretSchema).where(SecretSchema.id == secret_id)
).one()
session.delete(secret_in_db)
session.commit()
except NoResultFound:
raise KeyError(f"Secret with ID {secret_id} not found.")
def backup_secrets(
self, ignore_errors: bool = True, delete_secrets: bool = False
) -> None:
"""Backs up all secrets to the configured backup secrets store.
Args:
ignore_errors: Whether to ignore individual errors during the backup
process and attempt to backup all secrets.
delete_secrets: Whether to delete the secrets that have been
successfully backed up from the primary secrets store. Setting
this flag effectively moves all secrets from the primary secrets
store to the backup secrets store.
# noqa: DAR401
Raises:
BackupSecretsStoreNotConfiguredError: if no backup secrets store is
configured.
"""
if not self.backup_secrets_store:
raise BackupSecretsStoreNotConfiguredError(
"Unable to backup secrets: No backup secrets store is "
"configured."
)
with Session(self.engine) as session:
secrets_in_db = session.exec(select(SecretSchema)).all()
for secret in secrets_in_db:
try:
values = self._get_secret_values(
secret_id=secret.id, use_backup=False
)
except Exception:
logger.exception(
f"Failed to get secret values for secret with ID "
f"{secret.id}."
)
if ignore_errors:
continue
raise
try:
self._backup_secret_values(secret_id=secret.id, values=values)
except Exception:
logger.exception(
f"Failed to backup secret with ID {secret.id}. "
)
if ignore_errors:
continue
raise
if delete_secrets:
try:
self._delete_secret_values(
secret_id=secret.id, delete_backup=False
)
except Exception:
logger.exception(
f"Failed to delete secret with ID {secret.id} from the "
f"primary secrets store after backing it up to the "
f"backup secrets store."
)
if ignore_errors:
continue
raise
def restore_secrets(
self, ignore_errors: bool = False, delete_secrets: bool = False
) -> None:
"""Restore all secrets from the configured backup secrets store.
Args:
ignore_errors: Whether to ignore individual errors during the
restore process and attempt to restore all secrets.
delete_secrets: Whether to delete the secrets that have been
successfully restored from the backup secrets store. Setting
this flag effectively moves all secrets from the backup secrets
store to the primary secrets store.
# noqa: DAR401
Raises:
BackupSecretsStoreNotConfiguredError: if no backup secrets store is
configured.
"""
if not self.backup_secrets_store:
raise BackupSecretsStoreNotConfiguredError(
"Unable to restore secrets: No backup secrets store is "
"configured."
)
with Session(self.engine) as session:
secrets_in_db = session.exec(select(SecretSchema)).all()
for secret in secrets_in_db:
try:
values = self._get_backup_secret_values(secret_id=secret.id)
except Exception:
logger.exception(
f"Failed to get backup secret values for secret with ID "
f"{secret.id}."
)
if ignore_errors:
continue
raise
try:
self._update_secret_values(
secret_id=secret.id,
values=cast(Dict[str, Optional[str]], values),
overwrite=True,
backup=False,
)
except Exception:
logger.exception(
f"Failed to restore secret with ID {secret.id}. "
)
if ignore_errors:
continue
raise
if delete_secrets:
try:
self._delete_backup_secret_values(secret_id=secret.id)
except Exception:
logger.exception(
f"Failed to delete backup secret with ID {secret.id} "
f"from the backup secrets store after restoring it to "
f"the primary secrets store."
)
if ignore_errors:
continue
raise
# ------------------------- Service Accounts -------------------------
@track_decorator(AnalyticsEvent.CREATED_SERVICE_ACCOUNT)
def create_service_account(
self, service_account: ServiceAccountRequest
) -> ServiceAccountResponse:
"""Creates a new service account.
Args:
service_account: Service account to be created.
Returns:
The newly created service account.
Raises:
EntityExistsError: If a user or service account with the given name
already exists.
"""
with Session(self.engine) as session:
# Check if a service account with the given name already
# exists
err_msg = (
f"Unable to create service account with name "
f"'{service_account.name}': Found existing service "
"account with this name."
)
try:
self._get_account_schema(
service_account.name, session=session, service_account=True
)
raise EntityExistsError(err_msg)
except KeyError:
pass
# Create the service account
new_account = UserSchema.from_service_account_request(
service_account
)
session.add(new_account)
# on commit an IntegrityError may arise we let it bubble up
session.commit()
return new_account.to_service_account_model(include_metadata=True)
def get_service_account(
self,
service_account_name_or_id: Union[str, UUID],
hydrate: bool = True,
) -> ServiceAccountResponse:
"""Gets a specific service account.
Raises a KeyError in case a service account with that id does not exist.
Args:
service_account_name_or_id: The name or ID of the service account to
get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested service account, if it was found.
"""
with Session(self.engine) as session:
account = self._get_account_schema(
service_account_name_or_id,
session=session,
service_account=True,
)
return account.to_service_account_model(include_metadata=hydrate)
def list_service_accounts(
self,
filter_model: ServiceAccountFilter,
hydrate: bool = False,
) -> Page[ServiceAccountResponse]:
"""List all service accounts.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of filtered service accounts.
"""
with Session(self.engine) as session:
query = select(UserSchema)
paged_service_accounts: Page[ServiceAccountResponse] = (
self.filter_and_paginate(
session=session,
query=query,
table=UserSchema,
filter_model=filter_model,
custom_schema_to_model_conversion=lambda user: user.to_service_account_model(
include_metadata=hydrate
),
hydrate=hydrate,
)
)
return paged_service_accounts
def update_service_account(
self,
service_account_name_or_id: Union[str, UUID],
service_account_update: ServiceAccountUpdate,
) -> ServiceAccountResponse:
"""Updates an existing service account.
Args:
service_account_name_or_id: The name or the ID of the service
account to update.
service_account_update: The update to be applied to the service
account.
Returns:
The updated service account.
Raises:
EntityExistsError: If a user or service account with the given name
already exists.
"""
with Session(self.engine) as session:
existing_service_account = self._get_account_schema(
service_account_name_or_id,
session=session,
service_account=True,
)
if (
service_account_update.name is not None
and service_account_update.name
!= existing_service_account.name
):
try:
self._get_account_schema(
service_account_update.name,
session=session,
service_account=True,
)
raise EntityExistsError(
f"Unable to update service account with name "
f"'{service_account_update.name}': Found an existing "
"service account with this name."
)
except KeyError:
pass
existing_service_account.update_service_account(
service_account_update=service_account_update
)
session.add(existing_service_account)
session.commit()
# Refresh the Model that was just created
session.refresh(existing_service_account)
return existing_service_account.to_service_account_model(
include_metadata=True
)
def delete_service_account(
self,
service_account_name_or_id: Union[str, UUID],
) -> None:
"""Delete a service account.
Args:
service_account_name_or_id: The name or the ID of the service
account to delete.
Raises:
IllegalOperationError: if the service account has already been used
to create other resources.
"""
with Session(self.engine) as session:
service_account = self._get_account_schema(
service_account_name_or_id,
session=session,
service_account=True,
)
# Check if the service account has any resources associated with it
# and raise an error if it does.
if self._account_owns_resources(service_account, session=session):
raise IllegalOperationError(
"The service account has already been used to create "
"other resources that it now owns and therefore cannot be "
"deleted. Please delete all resources owned by the service "
"account or consider deactivating it instead."
)
session.delete(service_account)
session.commit()
# --------------------------- Service Connectors ---------------------------
@track_decorator(AnalyticsEvent.CREATED_SERVICE_CONNECTOR)
def create_service_connector(
self, service_connector: ServiceConnectorRequest
) -> ServiceConnectorResponse:
"""Creates a new service connector.
Args:
service_connector: Service connector to be created.
Returns:
The newly created service connector.
Raises:
Exception: If anything goes wrong during the creation of the
service connector.
"""
# If the connector type is locally available, we validate the request
# against the connector type schema before storing it in the database
if service_connector_registry.is_registered(service_connector.type):
connector_type = (
service_connector_registry.get_service_connector_type(
service_connector.type
)
)
service_connector.validate_and_configure_resources(
connector_type=connector_type,
resource_types=service_connector.resource_types,
resource_id=service_connector.resource_id,
configuration=service_connector.configuration,
secrets=service_connector.secrets,
)
with Session(self.engine) as session:
self._fail_if_service_connector_with_name_exists(
name=service_connector.name,
workspace_id=service_connector.workspace,
session=session,
)
# Create the secret
secret_id = self._create_connector_secret(
connector_name=service_connector.name,
user=service_connector.user,
workspace=service_connector.workspace,
secrets=service_connector.secrets,
)
try:
# Create the service connector
new_service_connector = ServiceConnectorSchema.from_request(
service_connector,
secret_id=secret_id,
)
session.add(new_service_connector)
session.commit()
session.refresh(new_service_connector)
except Exception:
# Delete the secret if it was created
if secret_id:
try:
self.delete_secret(secret_id)
except Exception:
# Ignore any errors that occur while deleting the
# secret
pass
raise
connector = new_service_connector.to_model(include_metadata=True)
self._populate_connector_type(connector)
return connector
def get_service_connector(
self, service_connector_id: UUID, hydrate: bool = True
) -> ServiceConnectorResponse:
"""Gets a specific service connector.
Args:
service_connector_id: The ID of the service connector to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested service connector, if it was found.
Raises:
KeyError: If no service connector with the given ID exists.
"""
with Session(self.engine) as session:
service_connector = session.exec(
select(ServiceConnectorSchema).where(
ServiceConnectorSchema.id == service_connector_id
)
).first()
if service_connector is None:
raise KeyError(
f"Service connector with ID {service_connector_id} not "
"found."
)
connector = service_connector.to_model(include_metadata=hydrate)
self._populate_connector_type(connector)
return connector
def list_service_connectors(
self,
filter_model: ServiceConnectorFilter,
hydrate: bool = False,
) -> Page[ServiceConnectorResponse]:
"""List all service connectors.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all service connectors.
"""
def fetch_connectors(
session: Session,
query: Union[
Select[ServiceConnectorSchema],
SelectOfScalar[ServiceConnectorSchema],
],
filter_model: BaseFilter,
) -> List[ServiceConnectorSchema]:
"""Custom fetch function for connector filtering and pagination.
Applies resource type and label filters to the query.
Args:
session: The database session.
query: The query to filter.
filter_model: The filter model.
Returns:
The filtered and paginated results.
"""
assert isinstance(filter_model, ServiceConnectorFilter)
items = self._list_filtered_service_connectors(
session=session, query=query, filter_model=filter_model
)
return items
with Session(self.engine) as session:
query = select(ServiceConnectorSchema)
paged_connectors: Page[ServiceConnectorResponse] = (
self.filter_and_paginate(
session=session,
query=query,
table=ServiceConnectorSchema,
filter_model=filter_model,
custom_fetch=fetch_connectors,
hydrate=hydrate,
)
)
self._populate_connector_type(*paged_connectors.items)
return paged_connectors
def update_service_connector(
self, service_connector_id: UUID, update: ServiceConnectorUpdate
) -> ServiceConnectorResponse:
"""Updates an existing service connector.
The update model contains the fields to be updated. If a field value is
set to None in the model, the field is not updated, but there are
special rules concerning some fields:
* the `configuration` and `secrets` fields together represent a full
valid configuration update, not just a partial update. If either is
set (i.e. not None) in the update, their values are merged together and
will replace the existing configuration and secrets values.
* the `resource_id` field value is also a full replacement value: if set
to `None`, the resource ID is removed from the service connector.
* the `expiration_seconds` field value is also a full replacement value:
if set to `None`, the expiration is removed from the service connector.
* the `secret_id` field value in the update is ignored, given that
secrets are managed internally by the ZenML store.
* the `labels` field is also a full labels update: if set (i.e. not
`None`), all existing labels are removed and replaced by the new labels
in the update.
Args:
service_connector_id: The ID of the service connector to update.
update: The update to be applied to the service connector.
Returns:
The updated service connector.
Raises:
KeyError: If no service connector with the given ID exists.
IllegalOperationError: If the service connector is referenced by
one or more stack components and the update would change the
connector type, resource type or resource ID.
"""
with Session(self.engine) as session:
existing_connector = session.exec(
select(ServiceConnectorSchema).where(
ServiceConnectorSchema.id == service_connector_id
)
).first()
if existing_connector is None:
raise KeyError(
f"Unable to update service connector with ID "
f"'{service_connector_id}': Found no existing service "
"connector with this ID."
)
# In case of a renaming update, make sure no service connector uses
# that name already
if update.name and existing_connector.name != update.name:
self._fail_if_service_connector_with_name_exists(
name=update.name,
workspace_id=existing_connector.workspace_id,
session=session,
)
existing_connector_model = existing_connector.to_model(
include_metadata=True
)
if len(existing_connector.components):
# If the service connector is already used in one or more
# stack components, the update is no longer allowed to change
# the service connector's authentication method, connector type,
# resource type, or resource ID
if (
update.connector_type
and update.type != existing_connector_model.connector_type
):
raise IllegalOperationError(
"The service type of a service connector that is "
"already actively used in one or more stack components "
"cannot be changed."
)
if (
update.auth_method
and update.auth_method
!= existing_connector_model.auth_method
):
raise IllegalOperationError(
"The authentication method of a service connector that "
"is already actively used in one or more stack "
"components cannot be changed."
)
if (
update.resource_types
and update.resource_types
!= existing_connector_model.resource_types
):
raise IllegalOperationError(
"The resource type of a service connector that is "
"already actively used in one or more stack components "
"cannot be changed."
)
# The resource ID field cannot be used as a partial update: if
# set to None, the existing resource ID is also removed
if update.resource_id != existing_connector_model.resource_id:
raise IllegalOperationError(
"The resource ID of a service connector that is "
"already actively used in one or more stack components "
"cannot be changed."
)
# If the connector type is locally available, we validate the update
# against the connector type schema before storing it in the
# database
if service_connector_registry.is_registered(
existing_connector.connector_type
):
connector_type = (
service_connector_registry.get_service_connector_type(
existing_connector.connector_type
)
)
# We need the auth method to be set to be able to validate the
# configuration
update.auth_method = (
update.auth_method or existing_connector_model.auth_method
)
# Validate the configuration update. If the configuration or
# secrets fields are set, together they are merged into a
# full configuration that is validated against the connector
# type schema and replaces the existing configuration and
# secrets values
update.validate_and_configure_resources(
connector_type=connector_type,
resource_types=update.resource_types,
resource_id=update.resource_id,
configuration=update.configuration,
secrets=update.secrets,
)
# Update secret
secret_id = self._update_connector_secret(
existing_connector=existing_connector_model,
updated_connector=update,
)
existing_connector.update(
connector_update=update, secret_id=secret_id
)
session.add(existing_connector)
session.commit()
connector = existing_connector.to_model(include_metadata=True)
self._populate_connector_type(connector)
return connector
def delete_service_connector(self, service_connector_id: UUID) -> None:
"""Deletes a service connector.
Args:
service_connector_id: The ID of the service connector to delete.
Raises:
KeyError: If no service connector with the given ID exists.
IllegalOperationError: If the service connector is still referenced
by one or more stack components.
"""
with Session(self.engine) as session:
try:
service_connector = session.exec(
select(ServiceConnectorSchema).where(
ServiceConnectorSchema.id == service_connector_id
)
).one()
if service_connector is None:
raise KeyError(
f"Service connector with ID {service_connector_id} not "
"found."
)
if len(service_connector.components) > 0:
raise IllegalOperationError(
f"Service connector with ID {service_connector_id} "
f"cannot be deleted as it is still referenced by "
f"{len(service_connector.components)} "
"stack components. Before deleting this service "
"connector, make sure to remove it from all stack "
"components."
)
else:
session.delete(service_connector)
if service_connector.secret_id:
try:
self.delete_secret(service_connector.secret_id)
except KeyError:
# If the secret doesn't exist anymore, we can ignore
# this error
pass
except NoResultFound as error:
raise KeyError from error
session.commit()
@staticmethod
def _fail_if_service_connector_with_name_exists(
name: str,
workspace_id: UUID,
session: Session,
) -> None:
"""Raise an exception if a service connector with same name exists.
Args:
name: The name of the service connector
workspace_id: The ID of the workspace
session: The Session
Raises:
EntityExistsError: If a service connector with the given name
already exists.
"""
# Check if service connector with the same domain key (name, workspace)
# already exists
existing_domain_connector = session.exec(
select(ServiceConnectorSchema)
.where(ServiceConnectorSchema.name == name)
.where(ServiceConnectorSchema.workspace_id == workspace_id)
).first()
if existing_domain_connector is not None:
raise EntityExistsError(
f"Unable to register service connector with name '{name}': "
"Found an existing service connector with the same name in the "
f"same workspace '{existing_domain_connector.workspace.name}'."
)
def _create_connector_secret(
self,
connector_name: str,
user: UUID,
workspace: UUID,
secrets: Optional[Dict[str, Optional[SecretStr]]],
) -> Optional[UUID]:
"""Creates a new secret to store the service connector secret credentials.
Args:
connector_name: The name of the service connector for which to
create a secret.
user: The ID of the user who owns the service connector.
workspace: The ID of the workspace in which the service connector
is registered.
secrets: The secret credentials to store.
Returns:
The ID of the newly created secret or None, if the service connector
does not contain any secret credentials.
"""
if not secrets:
return None
# Generate a unique name for the secret
# Replace all non-alphanumeric characters with a dash because
# the secret name must be a valid DNS subdomain name in some
# secrets stores
connector_name = re.sub(r"[^a-zA-Z0-9-]", "-", connector_name)
# Generate unique names using a random suffix until we find a name
# that is not already in use
while True:
secret_name = f"connector-{connector_name}-{random_str(4)}".lower()
existing_secrets = self.list_secrets(
SecretFilter(
name=secret_name,
)
)
if not existing_secrets.size:
try:
return self.create_secret(
SecretRequest(
name=secret_name,
user=user,
workspace=workspace,
scope=SecretScope.WORKSPACE,
values=secrets,
)
).id
except KeyError:
# The secret already exists, try again
continue
@staticmethod
def _populate_connector_type(
*service_connectors: ServiceConnectorResponse,
) -> None:
"""Populates the connector type of the given service connectors.
If the connector type is not locally available, the connector type
field is left as is.
Args:
service_connectors: The service connectors to populate.
"""
for service_connector in service_connectors:
if not service_connector_registry.is_registered(
service_connector.type
):
continue
service_connector.set_connector_type(
service_connector_registry.get_service_connector_type(
service_connector.type
)
)
@staticmethod
def _list_filtered_service_connectors(
session: Session,
query: Union[
Select[ServiceConnectorSchema],
SelectOfScalar[ServiceConnectorSchema],
],
filter_model: ServiceConnectorFilter,
) -> List[ServiceConnectorSchema]:
"""Refine a service connector query.
Applies resource type and label filters to the query.
Args:
session: The database session.
query: The query to filter.
filter_model: The filter model.
Returns:
The filtered list of service connectors.
"""
items: List[ServiceConnectorSchema] = (
session.exec(query).unique().all()
)
# filter out items that don't match the resource type
if filter_model.resource_type:
items = [
item
for item in items
if filter_model.resource_type in item.resource_types_list
]
# filter out items that don't match the labels
if filter_model.labels:
items = [
item for item in items if item.has_labels(filter_model.labels)
]
return items
def _update_connector_secret(
self,
existing_connector: ServiceConnectorResponse,
updated_connector: ServiceConnectorUpdate,
) -> Optional[UUID]:
"""Updates the secret for a service connector.
If the secrets field in the service connector update is set (i.e. not
None), the existing secret, if any, is replaced. If the secrets field is
set to an empty dict, the existing secret is deleted.
Args:
existing_connector: Existing service connector for which to update a
secret.
updated_connector: Updated service connector.
Returns:
The ID of the updated secret or None, if the new service connector
does not contain any secret credentials.
"""
if updated_connector.secrets is None:
# If the connector update does not contain a secrets update, keep
# the existing secret (if any)
return existing_connector.secret_id
# Delete the existing secret (if any), to be replaced by the new secret
if existing_connector.secret_id:
try:
self.delete_secret(existing_connector.secret_id)
except KeyError:
# Ignore if the secret no longer exists
pass
# If the new service connector does not contain any secret credentials,
# return None
if not updated_connector.secrets:
return None
assert existing_connector.user is not None
# A secret does not exist yet, create a new one
return self._create_connector_secret(
connector_name=updated_connector.name or existing_connector.name,
user=existing_connector.user.id,
workspace=existing_connector.workspace.id,
secrets=updated_connector.secrets,
)
def verify_service_connector_config(
self,
service_connector: ServiceConnectorRequest,
list_resources: bool = True,
) -> ServiceConnectorResourcesModel:
"""Verifies if a service connector configuration has access to resources.
Args:
service_connector: The service connector configuration to verify.
list_resources: If True, the list of all resources accessible
through the service connector is returned.
Returns:
The list of resources that the service connector configuration has
access to.
"""
connector_instance = service_connector_registry.instantiate_connector(
model=service_connector
)
return connector_instance.verify(list_resources=list_resources)
def verify_service_connector(
self,
service_connector_id: UUID,
resource_type: Optional[str] = None,
resource_id: Optional[str] = None,
list_resources: bool = True,
) -> ServiceConnectorResourcesModel:
"""Verifies if a service connector instance has access to one or more resources.
Args:
service_connector_id: The ID of the service connector to verify.
resource_type: The type of resource to verify access to.
resource_id: The ID of the resource to verify access to.
list_resources: If True, the list of all resources accessible
through the service connector and matching the supplied resource
type and ID are returned.
Returns:
The list of resources that the service connector has access to,
scoped to the supplied resource type and ID, if provided.
"""
connector = self.get_service_connector(service_connector_id)
connector_instance = service_connector_registry.instantiate_connector(
model=connector
)
return connector_instance.verify(
resource_type=resource_type,
resource_id=resource_id,
list_resources=list_resources,
)
def get_service_connector_client(
self,
service_connector_id: UUID,
resource_type: Optional[str] = None,
resource_id: Optional[str] = None,
) -> ServiceConnectorResponse:
"""Get a service connector client for a service connector and given resource.
Args:
service_connector_id: The ID of the base service connector to use.
resource_type: The type of resource to get a client for.
resource_id: The ID of the resource to get a client for.
Returns:
A service connector client that can be used to access the given
resource.
"""
connector = self.get_service_connector(service_connector_id)
connector_instance = service_connector_registry.instantiate_connector(
model=connector
)
# Fetch the connector client
connector_client = connector_instance.get_connector_client(
resource_type=resource_type,
resource_id=resource_id,
)
# Return the model for the connector client
connector = connector_client.to_response_model(
user=connector.user,
workspace=connector.workspace,
description=connector.description,
labels=connector.labels,
)
self._populate_connector_type(connector)
return connector
def list_service_connector_resources(
self,
workspace_name_or_id: Union[str, UUID],
connector_type: Optional[str] = None,
resource_type: Optional[str] = None,
resource_id: Optional[str] = None,
filter_model: Optional[ServiceConnectorFilter] = None,
) -> List[ServiceConnectorResourcesModel]:
"""List resources that can be accessed by service connectors.
Args:
workspace_name_or_id: The name or ID of the workspace to scope to.
connector_type: The type of service connector to scope to.
resource_type: The type of resource to scope to.
resource_id: The ID of the resource to scope to.
filter_model: Optional filter model to use when fetching service
connectors.
Returns:
The matching list of resources that available service
connectors have access to.
"""
workspace = self.get_workspace(workspace_name_or_id)
if not filter_model:
filter_model = ServiceConnectorFilter(
connector_type=connector_type,
resource_type=resource_type,
workspace_id=workspace.id,
)
service_connectors = self.list_service_connectors(
filter_model=filter_model
).items
resource_list: List[ServiceConnectorResourcesModel] = []
for connector in service_connectors:
if not service_connector_registry.is_registered(connector.type):
# For connectors that we can instantiate, i.e. those that have a
# connector type available locally, we return complete
# information about the resources that they have access to.
#
# For those that are not locally available, we only return
# rudimentary information extracted from the connector model
# without actively trying to discover the resources that they
# have access to.
if resource_id and connector.resource_id != resource_id:
# If an explicit resource ID is required, the connector
# has to be configured with it.
continue
resources = (
ServiceConnectorResourcesModel.from_connector_model(
connector,
resource_type=resource_type,
)
)
for r in resources.resources:
if not r.resource_ids:
r.error = (
f"The service '{connector.type}' connector type is "
"not available."
)
else:
try:
connector_instance = (
service_connector_registry.instantiate_connector(
model=connector
)
)
resources = connector_instance.verify(
resource_type=resource_type,
resource_id=resource_id,
list_resources=True,
)
except (ValueError, AuthorizationException) as e:
error = (
f'Failed to fetch {resource_type or "available"} '
f"resources from service connector {connector.name}/"
f"{connector.id}: {e}"
)
# Log an exception if debug logging is enabled
if logger.isEnabledFor(logging.DEBUG):
logger.exception(error)
else:
logger.error(error)
continue
resource_list.append(resources)
return resource_list
def list_service_connector_types(
self,
connector_type: Optional[str] = None,
resource_type: Optional[str] = None,
auth_method: Optional[str] = None,
) -> List[ServiceConnectorTypeModel]:
"""Get a list of service connector types.
Args:
connector_type: Filter by connector type.
resource_type: Filter by resource type.
auth_method: Filter by authentication method.
Returns:
List of service connector types.
"""
return service_connector_registry.list_service_connector_types(
connector_type=connector_type,
resource_type=resource_type,
auth_method=auth_method,
)
def get_service_connector_type(
self,
connector_type: str,
) -> ServiceConnectorTypeModel:
"""Returns the requested service connector type.
Args:
connector_type: the service connector type identifier.
Returns:
The requested service connector type.
"""
return service_connector_registry.get_service_connector_type(
connector_type
)
# ----------------------------- Stacks -----------------------------
@track_decorator(AnalyticsEvent.REGISTERED_STACK)
def create_stack(self, stack: StackRequest) -> StackResponse:
"""Register a new stack.
Args:
stack: The stack to register.
Returns:
The registered stack.
"""
with Session(self.engine) as session:
self._fail_if_stack_with_name_exists(stack=stack, session=session)
# Get the Schemas of all components mentioned
component_ids = (
[
component_id
for list_of_component_ids in stack.components.values()
for component_id in list_of_component_ids
]
if stack.components is not None
else []
)
filters = [
(StackComponentSchema.id == component_id)
for component_id in component_ids
]
defined_components = session.exec(
select(StackComponentSchema).where(or_(*filters))
).all()
new_stack_schema = StackSchema(
workspace_id=stack.workspace,
user_id=stack.user,
stack_spec_path=stack.stack_spec_path,
name=stack.name,
description=stack.description,
components=defined_components,
)
session.add(new_stack_schema)
session.commit()
session.refresh(new_stack_schema)
return new_stack_schema.to_model(include_metadata=True)
def get_stack(self, stack_id: UUID, hydrate: bool = True) -> StackResponse:
"""Get a stack by its unique ID.
Args:
stack_id: The ID of the stack to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The stack with the given ID.
Raises:
KeyError: if the stack doesn't exist.
"""
with Session(self.engine) as session:
stack = session.exec(
select(StackSchema).where(StackSchema.id == stack_id)
).first()
if stack is None:
raise KeyError(f"Stack with ID {stack_id} not found.")
return stack.to_model(include_metadata=hydrate)
def list_stacks(
self,
stack_filter_model: StackFilter,
hydrate: bool = False,
) -> Page[StackResponse]:
"""List all stacks matching the given filter criteria.
Args:
stack_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all stacks matching the filter criteria.
"""
with Session(self.engine) as session:
query = select(StackSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=StackSchema,
filter_model=stack_filter_model,
hydrate=hydrate,
)
@track_decorator(AnalyticsEvent.UPDATED_STACK)
def update_stack(
self, stack_id: UUID, stack_update: StackUpdate
) -> StackResponse:
"""Update a stack.
Args:
stack_id: The ID of the stack update.
stack_update: The update request on the stack.
Returns:
The updated stack.
Raises:
KeyError: if the stack doesn't exist.
IllegalOperationError: if the stack is a default stack.
"""
with Session(self.engine) as session:
# Check if stack with the domain key (name, workspace, owner)
# already exists
existing_stack = session.exec(
select(StackSchema).where(StackSchema.id == stack_id)
).first()
if existing_stack is None:
raise KeyError(
f"Unable to update stack with id '{stack_id}': Found no"
f"existing stack with this id."
)
if existing_stack.name == DEFAULT_STACK_AND_COMPONENT_NAME:
raise IllegalOperationError(
"The default stack cannot be modified."
)
# In case of a renaming update, make sure no stack already exists
# with that name
if stack_update.name:
if existing_stack.name != stack_update.name:
self._fail_if_stack_with_name_exists(
stack=stack_update,
session=session,
)
components = []
if stack_update.components:
filters = [
(StackComponentSchema.id == component_id)
for list_of_component_ids in stack_update.components.values()
for component_id in list_of_component_ids
]
components = session.exec(
select(StackComponentSchema).where(or_(*filters))
).all()
existing_stack.update(
stack_update=stack_update,
components=components,
)
session.add(existing_stack)
session.commit()
session.refresh(existing_stack)
return existing_stack.to_model(include_metadata=True)
def delete_stack(self, stack_id: UUID) -> None:
"""Delete a stack.
Args:
stack_id: The ID of the stack to delete.
Raises:
KeyError: if the stack doesn't exist.
IllegalOperationError: if the stack is a default stack.
"""
with Session(self.engine) as session:
try:
stack = session.exec(
select(StackSchema).where(StackSchema.id == stack_id)
).one()
if stack is None:
raise KeyError(f"Stack with ID {stack_id} not found.")
if stack.name == DEFAULT_STACK_AND_COMPONENT_NAME:
raise IllegalOperationError(
"The default stack cannot be deleted."
)
session.delete(stack)
except NoResultFound as error:
raise KeyError from error
session.commit()
def count_stacks(self, filter_model: Optional[StackFilter]) -> int:
"""Count all stacks.
Args:
filter_model: The filter model to filter the stacks.
Returns:
The number of stacks.
"""
return self._count_entity(
schema=StackSchema, filter_model=filter_model
)
def _fail_if_stack_with_name_exists(
self,
stack: StackRequest,
session: Session,
) -> None:
"""Raise an exception if a stack with same name exists.
Args:
stack: The Stack
session: The Session
Returns:
None
Raises:
StackExistsError: If a stack with the given name already exists.
"""
existing_domain_stack = session.exec(
select(StackSchema)
.where(StackSchema.name == stack.name)
.where(StackSchema.workspace_id == stack.workspace)
).first()
if existing_domain_stack is not None:
workspace = self._get_workspace_schema(
workspace_name_or_id=stack.workspace, session=session
)
raise StackExistsError(
f"Unable to register stack with name "
f"'{stack.name}': Found an existing stack with the same "
f"name in the active workspace, '{workspace.name}'."
)
return None
def _create_default_stack(
self,
workspace_id: UUID,
) -> StackResponse:
"""Create the default stack components and stack.
The default stack contains a local orchestrator and a local artifact
store.
Args:
workspace_id: ID of the workspace to which the stack
belongs.
Returns:
The model of the created default stack.
"""
with analytics_disabler():
workspace = self.get_workspace(workspace_name_or_id=workspace_id)
logger.info(
f"Creating default stack in workspace {workspace.name}..."
)
orchestrator = self.create_stack_component(
component=InternalComponentRequest(
# Passing `None` for the user here means the orchestrator
# is owned by the server, which for RBAC indicates that
# everyone can read it
user=None,
workspace=workspace.id,
name=DEFAULT_STACK_AND_COMPONENT_NAME,
type=StackComponentType.ORCHESTRATOR,
flavor="local",
configuration={},
),
)
artifact_store = self.create_stack_component(
component=InternalComponentRequest(
# Passing `None` for the user here means the stack is owned
# by the server, which for RBAC indicates that everyone can
# read it
user=None,
workspace=workspace.id,
name=DEFAULT_STACK_AND_COMPONENT_NAME,
type=StackComponentType.ARTIFACT_STORE,
flavor="local",
configuration={},
),
)
components = {
c.type: [c.id] for c in [orchestrator, artifact_store]
}
stack = InternalStackRequest(
# Passing `None` for the user here means the stack is owned by
# the server, which for RBAC indicates that everyone can read it
user=None,
name=DEFAULT_STACK_AND_COMPONENT_NAME,
components=components,
workspace=workspace.id,
)
return self.create_stack(stack=stack)
def _get_or_create_default_stack(
self, workspace: WorkspaceResponse
) -> StackResponse:
"""Get or create the default stack if it doesn't exist.
Args:
workspace: The workspace for which to create the default stack.
Returns:
The default stack.
"""
try:
return self._get_default_stack(
workspace_id=workspace.id,
)
except KeyError:
return self._create_default_stack(
workspace_id=workspace.id,
)
# ----------------------------- Step runs -----------------------------
def create_run_step(self, step_run: StepRunRequest) -> StepRunResponse:
"""Creates a step run.
Args:
step_run: The step run to create.
Returns:
The created step run.
Raises:
EntityExistsError: if the step run already exists.
KeyError: if the pipeline run doesn't exist.
"""
with Session(self.engine) as session:
# Check if the pipeline run exists
run = session.exec(
select(PipelineRunSchema).where(
PipelineRunSchema.id == step_run.pipeline_run_id
)
).first()
if run is None:
raise KeyError(
f"Unable to create step '{step_run.name}': No pipeline run "
f"with ID '{step_run.pipeline_run_id}' found."
)
# Check if the step name already exists in the pipeline run
existing_step_run = session.exec(
select(StepRunSchema)
.where(StepRunSchema.name == step_run.name)
.where(
StepRunSchema.pipeline_run_id == step_run.pipeline_run_id
)
).first()
if existing_step_run is not None:
raise EntityExistsError(
f"Unable to create step '{step_run.name}': A step with "
f"this name already exists in the pipeline run with ID "
f"'{step_run.pipeline_run_id}'."
)
# Create the step
step_schema = StepRunSchema.from_request(step_run)
session.add(step_schema)
# Add logs entry for the step if exists
if step_run.logs is not None:
log_entry = LogsSchema(
uri=step_run.logs.uri,
step_run_id=step_schema.id,
artifact_store_id=step_run.logs.artifact_store_id,
)
session.add(log_entry)
# Save parent step IDs into the database.
for parent_step_id in step_run.parent_step_ids:
self._set_run_step_parent_step(
child_id=step_schema.id,
parent_id=parent_step_id,
session=session,
)
# Save input artifact IDs into the database.
for input_name, artifact_version_id in step_run.inputs.items():
self._set_run_step_input_artifact(
run_step_id=step_schema.id,
artifact_version_id=artifact_version_id,
name=input_name,
input_type=StepRunInputArtifactType.DEFAULT,
session=session,
)
# Save output artifact IDs into the database.
for output_name, artifact_version_id in step_run.outputs.items():
self._set_run_step_output_artifact(
step_run_id=step_schema.id,
artifact_version_id=artifact_version_id,
name=output_name,
output_type=StepRunOutputArtifactType.DEFAULT,
session=session,
)
if step_run.status != ExecutionStatus.RUNNING:
self._update_pipeline_run_status(
pipeline_run_id=step_run.pipeline_run_id, session=session
)
session.commit()
return step_schema.to_model(include_metadata=True)
def get_run_step(
self, step_run_id: UUID, hydrate: bool = True
) -> StepRunResponse:
"""Get a step run by ID.
Args:
step_run_id: The ID of the step run to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The step run.
Raises:
KeyError: if the step run doesn't exist.
"""
with Session(self.engine) as session:
step_run = session.exec(
select(StepRunSchema).where(StepRunSchema.id == step_run_id)
).first()
if step_run is None:
raise KeyError(
f"Unable to get step run with ID {step_run_id}: No step "
"run with this ID found."
)
return step_run.to_model(include_metadata=hydrate)
def list_run_steps(
self,
step_run_filter_model: StepRunFilter,
hydrate: bool = False,
) -> Page[StepRunResponse]:
"""List all step runs matching the given filter criteria.
Args:
step_run_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all step runs matching the filter criteria.
"""
with Session(self.engine) as session:
query = select(StepRunSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=StepRunSchema,
filter_model=step_run_filter_model,
hydrate=hydrate,
)
def update_run_step(
self,
step_run_id: UUID,
step_run_update: StepRunUpdate,
) -> StepRunResponse:
"""Updates a step run.
Args:
step_run_id: The ID of the step to update.
step_run_update: The update to be applied to the step.
Returns:
The updated step run.
Raises:
KeyError: if the step run doesn't exist.
"""
with Session(self.engine) as session:
# Check if the step exists
existing_step_run = session.exec(
select(StepRunSchema).where(StepRunSchema.id == step_run_id)
).first()
if existing_step_run is None:
raise KeyError(
f"Unable to update step with ID {step_run_id}: "
f"No step with this ID found."
)
# Update the step
existing_step_run.update(step_run_update)
session.add(existing_step_run)
# Update the output artifacts.
for name, artifact_version_id in step_run_update.outputs.items():
self._set_run_step_output_artifact(
step_run_id=step_run_id,
artifact_version_id=artifact_version_id,
name=name,
output_type=StepRunOutputArtifactType.DEFAULT,
session=session,
)
# Update saved artifacts
for (
artifact_name,
artifact_version_id,
) in step_run_update.saved_artifact_versions.items():
self._set_run_step_output_artifact(
step_run_id=step_run_id,
artifact_version_id=artifact_version_id,
name=artifact_name,
output_type=StepRunOutputArtifactType.MANUAL,
session=session,
)
# Update loaded artifacts.
for (
artifact_name,
artifact_version_id,
) in step_run_update.loaded_artifact_versions.items():
self._set_run_step_input_artifact(
run_step_id=step_run_id,
artifact_version_id=artifact_version_id,
name=artifact_name,
input_type=StepRunInputArtifactType.MANUAL,
session=session,
)
self._update_pipeline_run_status(
pipeline_run_id=existing_step_run.pipeline_run_id,
session=session,
)
session.commit()
session.refresh(existing_step_run)
return existing_step_run.to_model(include_metadata=True)
@staticmethod
def _set_run_step_parent_step(
child_id: UUID, parent_id: UUID, session: Session
) -> None:
"""Sets the parent step run for a step run.
Args:
child_id: The ID of the child step run to set the parent for.
parent_id: The ID of the parent step run to set a child for.
session: The database session to use.
Raises:
KeyError: if the child step run or parent step run doesn't exist.
"""
# Check if the child step exists.
child_step_run = session.exec(
select(StepRunSchema).where(StepRunSchema.id == child_id)
).first()
if child_step_run is None:
raise KeyError(
f"Unable to set parent step for step with ID "
f"{child_id}: No step with this ID found."
)
# Check if the parent step exists.
parent_step_run = session.exec(
select(StepRunSchema).where(StepRunSchema.id == parent_id)
).first()
if parent_step_run is None:
raise KeyError(
f"Unable to set parent step for step with ID "
f"{child_id}: No parent step with ID {parent_id} "
"found."
)
# Check if the parent step is already set.
assignment = session.exec(
select(StepRunParentsSchema)
.where(StepRunParentsSchema.child_id == child_id)
.where(StepRunParentsSchema.parent_id == parent_id)
).first()
if assignment is not None:
return
# Save the parent step assignment in the database.
assignment = StepRunParentsSchema(
child_id=child_id, parent_id=parent_id
)
session.add(assignment)
@staticmethod
def _set_run_step_input_artifact(
run_step_id: UUID,
artifact_version_id: UUID,
name: str,
input_type: StepRunInputArtifactType,
session: Session,
) -> None:
"""Sets an artifact as an input of a step run.
Args:
run_step_id: The ID of the step run.
artifact_version_id: The ID of the artifact.
name: The name of the input in the step run.
input_type: In which way the artifact was loaded in the step.
session: The database session to use.
Raises:
KeyError: if the step run or artifact doesn't exist.
"""
# Check if the step exists.
step_run = session.exec(
select(StepRunSchema).where(StepRunSchema.id == run_step_id)
).first()
if step_run is None:
raise KeyError(
f"Unable to set input artifact: No step run with ID "
f"'{run_step_id}' found."
)
# Check if the artifact exists.
artifact = session.exec(
select(ArtifactVersionSchema).where(
ArtifactVersionSchema.id == artifact_version_id
)
).first()
if artifact is None:
raise KeyError(
f"Unable to set input artifact: No artifact with ID "
f"'{artifact_version_id}' found."
)
# Check if the input is already set.
assignment = session.exec(
select(StepRunInputArtifactSchema)
.where(StepRunInputArtifactSchema.step_id == run_step_id)
.where(
StepRunInputArtifactSchema.artifact_id == artifact_version_id
)
.where(StepRunInputArtifactSchema.name == name)
).first()
if assignment is not None:
return
# Save the input assignment in the database.
assignment = StepRunInputArtifactSchema(
step_id=run_step_id,
artifact_id=artifact_version_id,
name=name,
type=input_type,
)
session.add(assignment)
@staticmethod
def _set_run_step_output_artifact(
step_run_id: UUID,
artifact_version_id: UUID,
name: str,
output_type: StepRunOutputArtifactType,
session: Session,
) -> None:
"""Sets an artifact as an output of a step run.
Args:
step_run_id: The ID of the step run.
artifact_version_id: The ID of the artifact version.
name: The name of the output in the step run.
output_type: In which way the artifact was saved by the step.
session: The database session to use.
Raises:
KeyError: if the step run or artifact doesn't exist.
"""
# Check if the step exists.
step_run = session.exec(
select(StepRunSchema).where(StepRunSchema.id == step_run_id)
).first()
if step_run is None:
raise KeyError(
f"Unable to set output artifact: No step run with ID "
f"'{step_run_id}' found."
)
# Check if the artifact exists.
artifact = session.exec(
select(ArtifactVersionSchema).where(
ArtifactVersionSchema.id == artifact_version_id
)
).first()
if artifact is None:
raise KeyError(
f"Unable to set output artifact: No artifact with ID "
f"'{artifact_version_id}' found."
)
# Check if the output is already set.
assignment = session.exec(
select(StepRunOutputArtifactSchema)
.where(StepRunOutputArtifactSchema.step_id == step_run_id)
.where(
StepRunOutputArtifactSchema.artifact_id == artifact_version_id
)
).first()
if assignment is not None:
return
# Save the output assignment in the database.
assignment = StepRunOutputArtifactSchema(
step_id=step_run_id,
artifact_id=artifact_version_id,
name=name,
type=output_type,
)
session.add(assignment)
def _update_pipeline_run_status(
self,
pipeline_run_id: UUID,
session: Session,
) -> None:
"""Updates the status of a pipeline run.
Args:
pipeline_run_id: The ID of the pipeline run to update.
session: The database session to use.
"""
from zenml.orchestrators.publish_utils import get_pipeline_run_status
pipeline_run = session.exec(
select(PipelineRunSchema).where(
PipelineRunSchema.id == pipeline_run_id
)
).one()
step_runs = session.exec(
select(StepRunSchema).where(
StepRunSchema.pipeline_run_id == pipeline_run_id
)
).all()
# Deployment always exists for pipeline runs of newer versions
assert pipeline_run.deployment
num_steps = len(pipeline_run.deployment.to_model().step_configurations)
new_status = get_pipeline_run_status(
step_statuses=[step_run.status for step_run in step_runs],
num_steps=num_steps,
)
if new_status != pipeline_run.status:
run_update = PipelineRunUpdate(status=new_status)
if new_status in {
ExecutionStatus.COMPLETED,
ExecutionStatus.FAILED,
}:
run_update.end_time = datetime.utcnow()
if pipeline_run.start_time and isinstance(
pipeline_run.start_time, datetime
):
duration_time = (
run_update.end_time - pipeline_run.start_time
)
duration_seconds = duration_time.total_seconds()
start_time_str = pipeline_run.start_time.strftime(
"%Y-%m-%dT%H:%M:%S.%fZ"
)
else:
start_time_str = None
duration_seconds = None
stack = pipeline_run.deployment.stack
assert stack
stack_metadata = {
str(component.type): component.flavor
for component in stack.components
}
with track_handler(
AnalyticsEvent.RUN_PIPELINE_ENDED
) as analytics_handler:
analytics_handler.metadata = {
"pipeline_run_id": pipeline_run_id,
"status": new_status,
"num_steps": num_steps,
"start_time": start_time_str,
"end_time": run_update.end_time.strftime(
"%Y-%m-%dT%H:%M:%S.%fZ"
),
"duration_seconds": duration_seconds,
**stack_metadata,
}
pipeline_run.update(run_update)
session.add(pipeline_run)
# --------------------------- Triggers ---------------------------
@track_decorator(AnalyticsEvent.CREATED_TRIGGER)
def create_trigger(self, trigger: TriggerRequest) -> TriggerResponse:
"""Creates a new trigger.
Args:
trigger: Trigger to be created.
Returns:
The newly created trigger.
"""
with Session(self.engine) as session:
# Verify that the given event_source exists
self._get_event_source(
event_source_id=trigger.event_source_id, session=session
)
# Verify that the given service account exists
self._get_account_schema(
account_name_or_id=trigger.service_account_id,
session=session,
service_account=True,
)
# Verify that the trigger won't validate Unique
self._fail_if_trigger_with_name_exists(
trigger_name=trigger.name,
workspace_id=trigger.workspace,
session=session,
)
new_trigger = TriggerSchema.from_request(trigger)
session.add(new_trigger)
session.commit()
session.refresh(new_trigger)
return new_trigger.to_model(
include_metadata=True, include_resources=True
)
def get_trigger(
self, trigger_id: UUID, hydrate: bool = True
) -> TriggerResponse:
"""Get a trigger by its unique ID.
Args:
trigger_id: The ID of the trigger to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The trigger with the given ID.
Raises:
KeyError: if the trigger doesn't exist.
"""
with Session(self.engine) as session:
trigger = session.exec(
select(TriggerSchema).where(TriggerSchema.id == trigger_id)
).first()
if trigger is None:
raise KeyError(f"Trigger with ID {trigger_id} not found.")
return trigger.to_model(
include_metadata=hydrate, include_resources=hydrate
)
def list_triggers(
self,
trigger_filter_model: TriggerFilter,
hydrate: bool = False,
) -> Page[TriggerResponse]:
"""List all trigger matching the given filter criteria.
Args:
trigger_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all triggers matching the filter criteria.
"""
with Session(self.engine) as session:
query = select(TriggerSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=TriggerSchema,
filter_model=trigger_filter_model,
hydrate=hydrate,
)
@track_decorator(AnalyticsEvent.UPDATED_TRIGGER)
def update_trigger(
self, trigger_id: UUID, trigger_update: TriggerUpdate
) -> TriggerResponse:
"""Update a trigger.
Args:
trigger_id: The ID of the trigger update.
trigger_update: The update request on the trigger.
Returns:
The updated trigger.
Raises:
KeyError: if the trigger doesn't exist.
"""
with Session(self.engine) as session:
# Check if trigger with the domain key (name, workspace, owner)
# already exists
existing_trigger = session.exec(
select(TriggerSchema).where(TriggerSchema.id == trigger_id)
).first()
if existing_trigger is None:
raise KeyError(
f"Unable to update trigger with id '{trigger_id}': Found no"
f"existing trigger with this id."
)
if trigger_update.service_account_id:
# Verify that the given service account exists
self._get_account_schema(
account_name_or_id=trigger_update.service_account_id,
session=session,
service_account=True,
)
# In case of a renaming update, make sure no trigger already exists
# with that name
if trigger_update.name:
if existing_trigger.name != trigger_update.name:
self._fail_if_trigger_with_name_exists(
trigger_name=trigger_update.name,
workspace_id=existing_trigger.workspace.id,
session=session,
)
existing_trigger.update(
trigger_update=trigger_update,
)
session.add(existing_trigger)
session.commit()
session.refresh(existing_trigger)
return existing_trigger.to_model(
include_metadata=True, include_resources=True
)
def delete_trigger(self, trigger_id: UUID) -> None:
"""Delete a trigger.
Args:
trigger_id: The ID of the trigger to delete.
Raises:
KeyError: if the trigger doesn't exist.
"""
with Session(self.engine) as session:
try:
trigger = session.exec(
select(TriggerSchema).where(TriggerSchema.id == trigger_id)
).one()
if trigger is None:
raise KeyError(f"Trigger with ID {trigger_id} not found.")
session.delete(trigger)
except NoResultFound as error:
raise KeyError from error
session.commit()
def _fail_if_trigger_with_name_exists(
self,
trigger_name: str,
workspace_id: UUID,
session: Session,
) -> None:
"""Raise an exception if a trigger with same name exists.
Args:
trigger_name: The Trigger name
workspace_id: The workspace ID
session: The Session
Returns:
None
Raises:
TriggerExistsError: If a trigger with the given name already exists.
"""
existing_domain_trigger = session.exec(
select(TriggerSchema)
.where(TriggerSchema.name == trigger_name)
.where(TriggerSchema.workspace_id == workspace_id)
).first()
if existing_domain_trigger is not None:
workspace = self._get_workspace_schema(
workspace_name_or_id=workspace_id, session=session
)
raise TriggerExistsError(
f"Unable to register trigger with name "
f"'{trigger_name}': Found an existing trigger with the same "
f"name in the active workspace, '{workspace.name}'."
)
return None
# -------------------- Trigger Executions --------------------
def create_trigger_execution(
self, trigger_execution: TriggerExecutionRequest
) -> TriggerExecutionResponse:
"""Create a trigger execution.
Args:
trigger_execution: The trigger execution to create.
Returns:
The created trigger execution.
"""
with Session(self.engine) as session:
# TODO: Verify that the given trigger exists
new_execution = TriggerExecutionSchema.from_request(
trigger_execution
)
session.add(new_execution)
session.commit()
session.refresh(new_execution)
return new_execution.to_model(
include_metadata=True, include_resources=True
)
def get_trigger_execution(
self,
trigger_execution_id: UUID,
hydrate: bool = True,
) -> TriggerExecutionResponse:
"""Get an trigger execution by ID.
Args:
trigger_execution_id: The ID of the trigger execution to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The trigger execution.
Raises:
KeyError: If the trigger execution doesn't exist.
"""
with Session(self.engine) as session:
execution = session.exec(
select(TriggerExecutionSchema).where(
TriggerExecutionSchema.id == trigger_execution_id
)
).first()
if execution is None:
raise KeyError(
f"Trigger execution with ID {trigger_execution_id} not found."
)
return execution.to_model(
include_metadata=hydrate, include_resources=True
)
def list_trigger_executions(
self,
trigger_execution_filter_model: TriggerExecutionFilter,
hydrate: bool = False,
) -> Page[TriggerExecutionResponse]:
"""List all trigger executions matching the given filter criteria.
Args:
trigger_execution_filter_model: All filter parameters including
pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all trigger executions matching the filter criteria.
"""
with Session(self.engine) as session:
query = select(TriggerExecutionSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=TriggerExecutionSchema,
filter_model=trigger_execution_filter_model,
hydrate=hydrate,
)
def delete_trigger_execution(self, trigger_execution_id: UUID) -> None:
"""Delete a trigger execution.
Args:
trigger_execution_id: The ID of the trigger execution to delete.
Raises:
KeyError: If the trigger execution doesn't exist.
"""
with Session(self.engine) as session:
try:
execution = session.exec(
select(TriggerExecutionSchema).where(
TriggerExecutionSchema.id == trigger_execution_id
)
).one()
session.delete(execution)
session.commit()
except NoResultFound:
raise KeyError(
f"Execution with ID {trigger_execution_id} not found."
)
# ----------------------------- Users -----------------------------
@classmethod
@lru_cache(maxsize=1)
def _get_resource_references(
cls,
) -> List[Tuple[Type[SQLModel], str]]:
"""Get a list of all other table columns that reference the user table.
Given that this list doesn't change at runtime, we cache it.
Returns:
A list of all other table columns that reference the user table
as a list of tuples of the form
(<sqlmodel-schema-class>, <attribute-name>).
"""
from zenml.zen_stores import schemas as zenml_schemas
# Get a list of attributes that represent relationships to other
# resources
resource_attrs = [
attr
for attr in UserSchema.__sqlmodel_relationships__.keys()
if not attr.startswith("_")
and attr
not in
# These are not resources owned by the user or are resources that
# are deleted automatically when the user is deleted.
["api_keys", "auth_devices"]
]
# This next part is crucial in preserving scalability: we don't fetch
# the values of the relationship attributes, because this would
# potentially load a huge amount of data into memory through
# lazy-loading. Instead, we use a DB query to count resources
# associated with the user for each individual resource attribute.
# To create this query, we need a list of all tables and their foreign
# keys that point to the user table.
foreign_keys: List[Tuple[Type[SQLModel], str]] = []
for resource_attr in resource_attrs:
# Extract the target schema from the annotation
annotation = UserSchema.__annotations__[resource_attr]
# The annotation must be of the form
# `typing.List[ForwardRef('<schema-class>')]`
# We need to recover the schema class from the ForwardRef
assert annotation._name == "List"
assert annotation.__args__
schema_ref = annotation.__args__[0]
assert isinstance(schema_ref, ForwardRef)
# We pass the zenml_schemas module as the globals dict to
# _evaluate, because this is where the schema classes are
# defined
if sys.version_info < (3, 9):
# For Python versions <3.9, leave out the third parameter to
# _evaluate
target_schema = schema_ref._evaluate(vars(zenml_schemas), {})
else:
target_schema = schema_ref._evaluate(
vars(zenml_schemas), {}, frozenset()
)
assert target_schema is not None
assert issubclass(target_schema, SQLModel)
# Next, we need to identify the foreign key attribute in the
# target table
table = UserSchema.metadata.tables[target_schema.__tablename__]
foreign_key_attr = None
for fk in table.foreign_keys:
if fk.column.table.name != UserSchema.__tablename__:
continue
if fk.column.name != "id":
continue
assert fk.parent is not None
foreign_key_attr = fk.parent.name
break
assert foreign_key_attr is not None
foreign_keys.append((target_schema, foreign_key_attr))
return foreign_keys
def _account_owns_resources(
self, account: UserSchema, session: Session
) -> bool:
"""Check if the account owns any resources.
Args:
account: The account to check.
session: The database session to use for the query.
Returns:
Whether the account owns any resources.
"""
# Get a list of all other table columns that reference the user table
resource_attrs = self._get_resource_references()
for schema, resource_attr in resource_attrs:
# Check if the user owns any resources of this type
count = session.scalar(
select([func.count("*")])
.select_from(schema)
.where(getattr(schema, resource_attr) == account.id)
)
if count > 0:
logger.debug(
f"User {account.name} owns {count} resources of type "
f"{schema.__tablename__}"
)
return True
return False
def create_user(self, user: UserRequest) -> UserResponse:
"""Creates a new user.
Args:
user: User to be created.
Returns:
The newly created user.
Raises:
EntityExistsError: If a user or service account with the given name
already exists.
"""
with Session(self.engine) as session:
# Check if a user account with the given name already exists
err_msg = (
f"Unable to create user with name '{user.name}': "
f"Found an existing user account with this name."
)
try:
self._get_account_schema(
user.name,
session=session,
# Filter out service accounts
service_account=False,
)
raise EntityExistsError(err_msg)
except KeyError:
pass
# Create the user
new_user = UserSchema.from_user_request(user)
session.add(new_user)
# on commit an IntegrityError may arise we let it bubble up
session.commit()
return new_user.to_model(include_metadata=True)
def get_user(
self,
user_name_or_id: Optional[Union[str, UUID]] = None,
include_private: bool = False,
hydrate: bool = True,
) -> UserResponse:
"""Gets a specific user, when no id is specified the active user is returned.
# noqa: DAR401
# noqa: DAR402
Raises a KeyError in case a user with that name or id does not exist.
For backwards-compatibility reasons, this method can also be called
to fetch service accounts by their ID.
Args:
user_name_or_id: The name or ID of the user to get.
include_private: Whether to include private user information
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested user, if it was found.
Raises:
KeyError: If the user does not exist.
"""
if not user_name_or_id:
user_name_or_id = self._default_user_name
with Session(self.engine) as session:
# If a UUID is passed, we also allow fetching service accounts
# with that ID.
service_account: Optional[bool] = False
if uuid_utils.is_valid_uuid(user_name_or_id):
service_account = None
user = self._get_account_schema(
user_name_or_id,
session=session,
service_account=service_account,
)
return user.to_model(
include_private=include_private, include_metadata=hydrate
)
def get_auth_user(
self, user_name_or_id: Union[str, UUID]
) -> UserAuthModel:
"""Gets the auth model to a specific user.
Args:
user_name_or_id: The name or ID of the user to get.
Returns:
The requested user, if it was found.
"""
with Session(self.engine) as session:
user = self._get_account_schema(
user_name_or_id, session=session, service_account=False
)
return UserAuthModel(
id=user.id,
name=user.name,
full_name=user.full_name,
email_opted_in=user.email_opted_in,
active=user.active,
created=user.created,
updated=user.updated,
password=user.password,
activation_token=user.activation_token,
is_service_account=False,
)
def list_users(
self,
user_filter_model: UserFilter,
hydrate: bool = False,
) -> Page[UserResponse]:
"""List all users.
Args:
user_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all users.
"""
with Session(self.engine) as session:
query = select(UserSchema)
paged_user: Page[UserResponse] = self.filter_and_paginate(
session=session,
query=query,
table=UserSchema,
filter_model=user_filter_model,
hydrate=hydrate,
)
return paged_user
def update_user(
self, user_id: UUID, user_update: UserUpdate
) -> UserResponse:
"""Updates an existing user.
Args:
user_id: The id of the user to update.
user_update: The update to be applied to the user.
Returns:
The updated user.
Raises:
IllegalOperationError: If the request tries to update the username
for the default user account.
EntityExistsError: If the request tries to update the username to
a name that is already taken by another user or service account.
"""
with Session(self.engine) as session:
existing_user = self._get_account_schema(
user_id, session=session, service_account=False
)
if (
user_update.name is not None
and user_update.name != existing_user.name
):
if existing_user.name == self._default_user_name:
raise IllegalOperationError(
"The username of the default user account cannot be "
"changed."
)
try:
self._get_account_schema(
user_update.name,
session=session,
service_account=False,
)
raise EntityExistsError(
f"Unable to update user account with name "
f"'{user_update.name}': Found an existing user "
"account with this name."
)
except KeyError:
pass
existing_user.update_user(user_update=user_update)
session.add(existing_user)
session.commit()
# Refresh the Model that was just created
session.refresh(existing_user)
return existing_user.to_model(include_metadata=True)
def delete_user(self, user_name_or_id: Union[str, UUID]) -> None:
"""Deletes a user.
Args:
user_name_or_id: The name or the ID of the user to delete.
Raises:
IllegalOperationError: If the user is the default user account or
if the user already owns resources.
"""
with Session(self.engine) as session:
user = self._get_account_schema(
user_name_or_id, session=session, service_account=False
)
if user.name == self._default_user_name:
raise IllegalOperationError(
"The default user account cannot be deleted."
)
if self._account_owns_resources(user, session=session):
raise IllegalOperationError(
"The user account has already been used to create "
"other resources that it now owns and therefore cannot be "
"deleted. Please delete all resources owned by the user "
"account or consider deactivating it instead."
)
session.delete(user)
session.commit()
@property
def _default_user_name(self) -> str:
"""Get the default user name.
Returns:
The default user name.
"""
return os.getenv(ENV_ZENML_DEFAULT_USER_NAME, DEFAULT_USERNAME)
def _get_or_create_default_user(self) -> UserResponse:
"""Get or create the default user if it doesn't exist.
Returns:
The default user.
"""
default_user_name = self._default_user_name
try:
return self.get_user(default_user_name)
except KeyError:
password = os.getenv(
ENV_ZENML_DEFAULT_USER_PASSWORD, DEFAULT_PASSWORD
)
logger.info(f"Creating default user '{default_user_name}' ...")
return self.create_user(
UserRequest(
name=default_user_name,
active=True,
password=password,
)
)
# ----------------------------- Workspaces -----------------------------
@track_decorator(AnalyticsEvent.CREATED_WORKSPACE)
def create_workspace(
self, workspace: WorkspaceRequest
) -> WorkspaceResponse:
"""Creates a new workspace.
Args:
workspace: The workspace to create.
Returns:
The newly created workspace.
Raises:
EntityExistsError: If a workspace with the given name already exists.
"""
with Session(self.engine) as session:
# Check if workspace with the given name already exists
existing_workspace = session.exec(
select(WorkspaceSchema).where(
WorkspaceSchema.name == workspace.name
)
).first()
if existing_workspace is not None:
raise EntityExistsError(
f"Unable to create workspace {workspace.name}: "
"A workspace with this name already exists."
)
# Create the workspace
new_workspace = WorkspaceSchema.from_request(workspace)
session.add(new_workspace)
session.commit()
# Explicitly refresh the new_workspace schema
session.refresh(new_workspace)
workspace_model = new_workspace.to_model(include_metadata=True)
self._get_or_create_default_stack(workspace=workspace_model)
return workspace_model
def get_workspace(
self, workspace_name_or_id: Union[str, UUID], hydrate: bool = True
) -> WorkspaceResponse:
"""Get an existing workspace by name or ID.
Args:
workspace_name_or_id: Name or ID of the workspace to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested workspace if one was found.
"""
with Session(self.engine) as session:
workspace = self._get_workspace_schema(
workspace_name_or_id, session=session
)
return workspace.to_model(include_metadata=hydrate)
def list_workspaces(
self,
workspace_filter_model: WorkspaceFilter,
hydrate: bool = False,
) -> Page[WorkspaceResponse]:
"""List all workspace matching the given filter criteria.
Args:
workspace_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all workspace matching the filter criteria.
"""
with Session(self.engine) as session:
query = select(WorkspaceSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=WorkspaceSchema,
filter_model=workspace_filter_model,
hydrate=hydrate,
)
def update_workspace(
self, workspace_id: UUID, workspace_update: WorkspaceUpdate
) -> WorkspaceResponse:
"""Update an existing workspace.
Args:
workspace_id: The ID of the workspace to be updated.
workspace_update: The update to be applied to the workspace.
Returns:
The updated workspace.
Raises:
IllegalOperationError: if the workspace is the default workspace.
KeyError: if the workspace does not exist.
"""
with Session(self.engine) as session:
existing_workspace = session.exec(
select(WorkspaceSchema).where(
WorkspaceSchema.id == workspace_id
)
).first()
if existing_workspace is None:
raise KeyError(
f"Unable to update workspace with id "
f"'{workspace_id}': Found no"
f"existing workspaces with this id."
)
if (
existing_workspace.name == self._default_workspace_name
and "name" in workspace_update.__fields_set__
and workspace_update.name != existing_workspace.name
):
raise IllegalOperationError(
"The name of the default workspace cannot be changed."
)
# Update the workspace
existing_workspace.update(workspace_update=workspace_update)
session.add(existing_workspace)
session.commit()
# Refresh the Model that was just created
session.refresh(existing_workspace)
return existing_workspace.to_model(include_metadata=True)
def delete_workspace(self, workspace_name_or_id: Union[str, UUID]) -> None:
"""Deletes a workspace.
Args:
workspace_name_or_id: Name or ID of the workspace to delete.
Raises:
IllegalOperationError: If the workspace is the default workspace.
"""
with Session(self.engine) as session:
# Check if workspace with the given name exists
workspace = self._get_workspace_schema(
workspace_name_or_id, session=session
)
if workspace.name == self._default_workspace_name:
raise IllegalOperationError(
"The default workspace cannot be deleted."
)
session.delete(workspace)
session.commit()
def _get_or_create_default_workspace(self) -> WorkspaceResponse:
"""Get or create the default workspace if it doesn't exist.
Returns:
The default workspace.
"""
default_workspace_name = self._default_workspace_name
try:
return self.get_workspace(default_workspace_name)
except KeyError:
logger.info(
f"Creating default workspace '{default_workspace_name}' ..."
)
return self.create_workspace(
WorkspaceRequest(name=default_workspace_name)
)
# =======================
# Internal helper methods
# =======================
def _count_entity(
self,
schema: Type[BaseSchema],
filter_model: Optional[BaseFilter] = None,
) -> int:
"""Return count of a given entity.
Args:
schema: Schema of the Entity
filter_model: The filter model to filter the entity table.
Returns:
Count of the entity as integer.
"""
with Session(self.engine) as session:
query = select([func.count(schema.id)])
if filter_model:
query = filter_model.apply_filter(query=query, table=schema)
entity_count = session.scalar(query)
return int(entity_count)
def entity_exists(
self, entity_id: UUID, schema_class: Type[AnySchema]
) -> bool:
"""Check whether an entity exists in the database.
Args:
entity_id: The ID of the entity to check.
schema_class: The schema class.
Returns:
If the entity exists.
"""
with Session(self.engine) as session:
schema = session.exec(
select(schema_class.id).where(schema_class.id == entity_id)
).first()
return False if schema is None else True
def get_entity_by_id(
self, entity_id: UUID, schema_class: Type[AnySchema]
) -> Optional[AnyIdentifiedResponse]:
"""Get an entity by ID.
Args:
entity_id: The ID of the entity to get.
schema_class: The schema class.
Raises:
RuntimeError: If the schema to model conversion failed.
Returns:
The entity if it exists, None otherwise
"""
with Session(self.engine) as session:
schema = session.exec(
select(schema_class).where(schema_class.id == entity_id)
).first()
if not schema:
return None
to_model = getattr(schema, "to_model", None)
if callable(to_model):
return cast(AnyIdentifiedResponse, to_model(hydrate=True))
else:
raise RuntimeError("Unable to convert schema to model.")
@staticmethod
def _get_schema_by_name_or_id(
object_name_or_id: Union[str, UUID],
schema_class: Type[AnyNamedSchema],
schema_name: str,
session: Session,
) -> AnyNamedSchema:
"""Query a schema by its 'name' or 'id' field.
Args:
object_name_or_id: The name or ID of the object to query.
schema_class: The schema class to query. E.g., `WorkspaceSchema`.
schema_name: The name of the schema used for error messages.
E.g., "workspace".
session: The database session to use.
Returns:
The schema object.
Raises:
KeyError: if the object couldn't be found.
ValueError: if the schema_name isn't provided.
"""
if object_name_or_id is None:
raise ValueError(
f"Unable to get {schema_name}: No {schema_name} ID or name "
"provided."
)
if uuid_utils.is_valid_uuid(object_name_or_id):
filter_params = schema_class.id == object_name_or_id
error_msg = (
f"Unable to get {schema_name} with name or ID "
f"'{object_name_or_id}': No {schema_name} with this ID found."
)
else:
filter_params = schema_class.name == object_name_or_id
error_msg = (
f"Unable to get {schema_name} with name or ID "
f"'{object_name_or_id}': '{object_name_or_id}' is not a valid "
f" UUID and no {schema_name} with this name exists."
)
schema = session.exec(
select(schema_class).where(filter_params)
).first()
if schema is None:
raise KeyError(error_msg)
return schema
def _get_workspace_schema(
self,
workspace_name_or_id: Union[str, UUID],
session: Session,
) -> WorkspaceSchema:
"""Gets a workspace schema by name or ID.
This is a helper method that is used in various places to find the
workspace associated to some other object.
Args:
workspace_name_or_id: The name or ID of the workspace to get.
session: The database session to use.
Returns:
The workspace schema.
"""
return self._get_schema_by_name_or_id(
object_name_or_id=workspace_name_or_id,
schema_class=WorkspaceSchema,
schema_name="workspace",
session=session,
)
def _get_account_schema(
self,
account_name_or_id: Union[str, UUID],
session: Session,
service_account: Optional[bool] = None,
) -> UserSchema:
"""Gets a user account or a service account schema by name or ID.
This helper method is used to fetch both user accounts and service
accounts by name or ID. It is required because in the DB, user accounts
and service accounts are stored using the same UserSchema to make
it easier to implement resource ownership.
Args:
account_name_or_id: The name or ID of the account to get.
session: The database session to use.
service_account: Whether to get a service account or a user
account. If None, both are considered with a priority for
user accounts if both exist (e.g. with the same name).
Returns:
The account schema.
Raises:
KeyError: If no account with the given name or ID exists.
"""
account_type = ""
query = select(UserSchema)
if uuid_utils.is_valid_uuid(account_name_or_id):
query = query.where(UserSchema.id == account_name_or_id)
else:
query = query.where(UserSchema.name == account_name_or_id)
if service_account is not None:
if service_account is True:
account_type = "service "
elif service_account is False:
account_type = "user "
query = query.where(
UserSchema.is_service_account == service_account # noqa: E712
)
error_msg = (
f"No {account_type}account with the '{account_name_or_id}' name "
"or ID was found"
)
results = session.exec(query).all()
if len(results) == 0:
raise KeyError(error_msg)
if len(results) == 1:
return results[0]
# We could have two results if a service account and a user account
# have the same name. In that case, we return the user account.
for result in results:
if not result.is_service_account:
return result
raise KeyError(error_msg)
def _get_run_schema(
self,
run_name_or_id: Union[str, UUID],
session: Session,
) -> PipelineRunSchema:
"""Gets a run schema by name or ID.
This is a helper method that is used in various places to find a run
by its name or ID.
Args:
run_name_or_id: The name or ID of the run to get.
session: The database session to use.
Returns:
The run schema.
"""
return self._get_schema_by_name_or_id(
object_name_or_id=run_name_or_id,
schema_class=PipelineRunSchema,
schema_name="run",
session=session,
)
def _get_model_schema(
self,
model_name_or_id: Union[str, UUID],
session: Session,
) -> ModelSchema:
"""Gets a model schema by name or ID.
This is a helper method that is used in various places to find a model
by its name or ID.
Args:
model_name_or_id: The name or ID of the model to get.
session: The database session to use.
Returns:
The model schema.
"""
return self._get_schema_by_name_or_id(
object_name_or_id=model_name_or_id,
schema_class=ModelSchema,
schema_name="model",
session=session,
)
def _get_tag_schema(
self,
tag_name_or_id: Union[str, UUID],
session: Session,
) -> TagSchema:
"""Gets a tag schema by name or ID.
This is a helper method that is used in various places to find a tag
by its name or ID.
Args:
tag_name_or_id: The name or ID of the tag to get.
session: The database session to use.
Returns:
The tag schema.
"""
return self._get_schema_by_name_or_id(
object_name_or_id=tag_name_or_id,
schema_class=TagSchema,
schema_name=TagSchema.__tablename__,
session=session,
)
def _get_tag_model_schema(
self,
tag_id: UUID,
resource_id: UUID,
resource_type: TaggableResourceTypes,
session: Session,
) -> TagResourceSchema:
"""Gets a tag model schema by tag and resource.
Args:
tag_id: The ID of the tag to get.
resource_id: The ID of the resource to get.
resource_type: The type of the resource to get.
session: The database session to use.
Returns:
The tag resource schema.
Raises:
KeyError: if entity not found.
"""
with Session(self.engine) as session:
schema = session.exec(
select(TagResourceSchema).where(
TagResourceSchema.tag_id == tag_id,
TagResourceSchema.resource_id == resource_id,
TagResourceSchema.resource_type == resource_type.value,
)
).first()
if schema is None:
raise KeyError(
f"Unable to get {TagResourceSchema.__tablename__} with IDs "
f"`tag_id`='{tag_id}' and `resource_id`='{resource_id}' and "
f"`resource_type`='{resource_type.value}': No "
f"{TagResourceSchema.__tablename__} with these IDs found."
)
return schema
@staticmethod
def _create_or_reuse_code_reference(
session: Session,
workspace_id: UUID,
code_reference: Optional["CodeReferenceRequest"],
) -> Optional[UUID]:
"""Creates or reuses a code reference.
Args:
session: The database session to use.
workspace_id: ID of the workspace in which the code reference
should be.
code_reference: Request of the reference to create.
Returns:
The code reference ID.
"""
if not code_reference:
return None
existing_reference = session.exec(
select(CodeReferenceSchema)
.where(CodeReferenceSchema.workspace_id == workspace_id)
.where(
CodeReferenceSchema.code_repository_id
== code_reference.code_repository
)
.where(CodeReferenceSchema.commit == code_reference.commit)
.where(
CodeReferenceSchema.subdirectory == code_reference.subdirectory
)
).first()
if existing_reference is not None:
return existing_reference.id
new_reference = CodeReferenceSchema.from_request(
code_reference, workspace_id=workspace_id
)
session.add(new_reference)
return new_reference.id
# ----------------------------- Models -----------------------------
@track_decorator(AnalyticsEvent.CREATED_MODEL)
def create_model(self, model: ModelRequest) -> ModelResponse:
"""Creates a new model.
Args:
model: the Model to be created.
Returns:
The newly created model.
Raises:
EntityExistsError: If a workspace with the given name already exists.
"""
with Session(self.engine) as session:
existing_model = session.exec(
select(ModelSchema).where(ModelSchema.name == model.name)
).first()
if existing_model is not None:
raise EntityExistsError(
f"Unable to create model {model.name}: "
"A model with this name already exists."
)
model_schema = ModelSchema.from_request(model)
session.add(model_schema)
if model.tags:
self._attach_tags_to_resource(
tag_names=model.tags,
resource_id=model_schema.id,
resource_type=TaggableResourceTypes.MODEL,
)
session.commit()
return model_schema.to_model(include_metadata=True)
def get_model(
self,
model_name_or_id: Union[str, UUID],
hydrate: bool = True,
) -> ModelResponse:
"""Get an existing model.
Args:
model_name_or_id: name or id of the model to be retrieved.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Raises:
KeyError: specified ID or name not found.
Returns:
The model of interest.
"""
with Session(self.engine) as session:
model = self._get_model_schema(
model_name_or_id=model_name_or_id, session=session
)
if model is None:
raise KeyError(
f"Unable to get model with ID `{model_name_or_id}`: "
f"No model with this ID found."
)
return model.to_model(include_metadata=hydrate)
def list_models(
self,
model_filter_model: ModelFilter,
hydrate: bool = False,
) -> Page[ModelResponse]:
"""Get all models by filter.
Args:
model_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all models.
"""
with Session(self.engine) as session:
query = select(ModelSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=ModelSchema,
filter_model=model_filter_model,
hydrate=hydrate,
)
def delete_model(self, model_name_or_id: Union[str, UUID]) -> None:
"""Deletes a model.
Args:
model_name_or_id: name or id of the model to be deleted.
Raises:
KeyError: specified ID or name not found.
"""
with Session(self.engine) as session:
model = self._get_model_schema(
model_name_or_id=model_name_or_id, session=session
)
if model is None:
raise KeyError(
f"Unable to delete model with ID `{model_name_or_id}`: "
f"No model with this ID found."
)
session.delete(model)
session.commit()
def update_model(
self,
model_id: UUID,
model_update: ModelUpdate,
) -> ModelResponse:
"""Updates an existing model.
Args:
model_id: UUID of the model to be updated.
model_update: the Model to be updated.
Raises:
KeyError: specified ID not found.
Returns:
The updated model.
"""
with Session(self.engine) as session:
existing_model = session.exec(
select(ModelSchema).where(ModelSchema.id == model_id)
).first()
if not existing_model:
raise KeyError(f"Model with ID {model_id} not found.")
if model_update.add_tags:
self._attach_tags_to_resource(
tag_names=model_update.add_tags,
resource_id=existing_model.id,
resource_type=TaggableResourceTypes.MODEL,
)
model_update.add_tags = None
if model_update.remove_tags:
self._detach_tags_from_resource(
tag_names=model_update.remove_tags,
resource_id=existing_model.id,
resource_type=TaggableResourceTypes.MODEL,
)
model_update.remove_tags = None
existing_model.update(model_update=model_update)
session.add(existing_model)
session.commit()
# Refresh the Model that was just created
session.refresh(existing_model)
return existing_model.to_model(include_metadata=True)
# ----------------------------- Model Versions -----------------------------
@track_decorator(AnalyticsEvent.CREATED_MODEL_VERSION)
def create_model_version(
self, model_version: ModelVersionRequest
) -> ModelVersionResponse:
"""Creates a new model version.
Args:
model_version: the Model Version to be created.
Returns:
The newly created model version.
Raises:
ValueError: If `number` is not None during model version creation.
EntityExistsError: If a workspace with the given name already exists.
"""
if model_version.number is not None:
raise ValueError(
"`number` field must be None during model version creation."
)
with Session(self.engine) as session:
model_version_ = model_version.copy()
model = self.get_model(model_version_.model)
def _check(tolerance: int = 0) -> None:
query = session.exec(
select(ModelVersionSchema)
.where(ModelVersionSchema.model_id == model.id)
.where(ModelVersionSchema.name == model_version_.name)
)
existing_model_version = query.fetchmany(tolerance + 1)
if (
existing_model_version is not None
and len(existing_model_version) > tolerance
):
raise EntityExistsError(
f"Unable to create model version {model_version_.name}: "
f"A model version with this name already exists in {model.name} model."
)
_check()
all_versions = session.exec(
select(ModelVersionSchema)
.where(ModelVersionSchema.model_id == model.id)
.order_by(ModelVersionSchema.number.desc()) # type: ignore[attr-defined]
).first()
model_version_.number = (
all_versions.number + 1 if all_versions else 1
)
if model_version_.name is None:
model_version_.name = str(model_version_.number)
model_version_schema = ModelVersionSchema.from_request(
model_version_
)
session.add(model_version_schema)
if model_version_.tags:
self._attach_tags_to_resource(
tag_names=model_version_.tags,
resource_id=model_version_schema.id,
resource_type=TaggableResourceTypes.MODEL_VERSION,
)
try:
_check(1)
session.commit()
except EntityExistsError as e:
session.rollback()
raise e
return model_version_schema.to_model(include_metadata=True)
def get_model_version(
self, model_version_id: UUID, hydrate: bool = True
) -> ModelVersionResponse:
"""Get an existing model version.
Args:
model_version_id: name, id, stage or number of the model version to
be retrieved. If skipped - latest is retrieved.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The model version of interest.
Raises:
KeyError: specified ID or name not found.
"""
with Session(self.engine) as session:
model_version = self._get_schema_by_name_or_id(
object_name_or_id=model_version_id,
schema_class=ModelVersionSchema,
schema_name="model_version",
session=session,
)
if model_version is None:
raise KeyError(
f"Unable to get model version with ID "
f"`{model_version_id}`: No model version with this "
f"ID found."
)
return model_version.to_model(include_metadata=hydrate)
def list_model_versions(
self,
model_version_filter_model: ModelVersionFilter,
model_name_or_id: Optional[Union[str, UUID]] = None,
hydrate: bool = False,
) -> Page[ModelVersionResponse]:
"""Get all model versions by filter.
Args:
model_name_or_id: name or id of the model containing the model
versions.
model_version_filter_model: All filter parameters including
pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all model versions.
"""
with Session(self.engine) as session:
if model_name_or_id:
model = self.get_model(model_name_or_id)
model_version_filter_model.set_scope_model(model.id)
query = select(ModelVersionSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=ModelVersionSchema,
filter_model=model_version_filter_model,
hydrate=hydrate,
)
def delete_model_version(
self,
model_version_id: UUID,
) -> None:
"""Deletes a model version.
Args:
model_version_id: name or id of the model version to be deleted.
Raises:
KeyError: specified ID or name not found.
"""
with Session(self.engine) as session:
query = select(ModelVersionSchema).where(
ModelVersionSchema.id == model_version_id
)
model_version = session.exec(query).first()
if model_version is None:
raise KeyError(
"Unable to delete model version with id "
f"`{model_version_id}`: "
"No model version with this id found."
)
session.delete(model_version)
session.commit()
def update_model_version(
self,
model_version_id: UUID,
model_version_update_model: ModelVersionUpdate,
) -> ModelVersionResponse:
"""Get all model versions by filter.
Args:
model_version_id: The ID of model version to be updated.
model_version_update_model: The model version to be updated.
Returns:
An updated model version.
Raises:
KeyError: If the model version not found
RuntimeError: If there is a model version with target stage,
but `force` flag is off
"""
with Session(self.engine) as session:
existing_model_version = session.exec(
select(ModelVersionSchema)
.where(
ModelVersionSchema.model_id
== model_version_update_model.model
)
.where(ModelVersionSchema.id == model_version_id)
).first()
if not existing_model_version:
raise KeyError(f"Model version {model_version_id} not found.")
stage = None
if (stage_ := model_version_update_model.stage) is not None:
stage = getattr(stage_, "value", stage_)
existing_model_version_in_target_stage = session.exec(
select(ModelVersionSchema)
.where(
ModelVersionSchema.model_id
== model_version_update_model.model
)
.where(ModelVersionSchema.stage == stage)
).first()
if (
existing_model_version_in_target_stage is not None
and existing_model_version_in_target_stage.id
!= existing_model_version.id
):
if not model_version_update_model.force:
raise RuntimeError(
f"Model version {existing_model_version_in_target_stage.name} is "
f"in {stage}, but `force` flag is False."
)
else:
existing_model_version_in_target_stage.update(
target_stage=ModelStages.ARCHIVED.value
)
session.add(existing_model_version_in_target_stage)
logger.info(
f"Model version {existing_model_version_in_target_stage.name} has been set to {ModelStages.ARCHIVED.value}."
)
if model_version_update_model.add_tags:
self._attach_tags_to_resource(
tag_names=model_version_update_model.add_tags,
resource_id=existing_model_version.id,
resource_type=TaggableResourceTypes.MODEL_VERSION,
)
if model_version_update_model.remove_tags:
self._detach_tags_from_resource(
tag_names=model_version_update_model.remove_tags,
resource_id=existing_model_version.id,
resource_type=TaggableResourceTypes.MODEL_VERSION,
)
existing_model_version.update(
target_stage=stage,
target_name=model_version_update_model.name,
target_description=model_version_update_model.description,
)
session.add(existing_model_version)
session.commit()
session.refresh(existing_model_version)
return existing_model_version.to_model(include_metadata=True)
# ------------------------ Model Versions Artifacts ------------------------
def create_model_version_artifact_link(
self, model_version_artifact_link: ModelVersionArtifactRequest
) -> ModelVersionArtifactResponse:
"""Creates a new model version link.
Args:
model_version_artifact_link: the Model Version to Artifact Link
to be created.
Returns:
The newly created model version to artifact link.
"""
with Session(self.engine) as session:
# If the link already exists, return it
existing_model_version_artifact_link = session.exec(
select(ModelVersionArtifactSchema)
.where(
ModelVersionArtifactSchema.model_version_id
== model_version_artifact_link.model_version
)
.where(
ModelVersionArtifactSchema.artifact_version_id
== model_version_artifact_link.artifact_version,
)
).first()
if existing_model_version_artifact_link is not None:
return existing_model_version_artifact_link.to_model()
model_version_artifact_link_schema = (
ModelVersionArtifactSchema.from_request(
model_version_artifact_request=model_version_artifact_link,
)
)
session.add(model_version_artifact_link_schema)
session.commit()
return model_version_artifact_link_schema.to_model(
include_metadata=True
)
def list_model_version_artifact_links(
self,
model_version_artifact_link_filter_model: ModelVersionArtifactFilter,
hydrate: bool = False,
) -> Page[ModelVersionArtifactResponse]:
"""Get all model version to artifact links by filter.
Args:
model_version_artifact_link_filter_model: All filter parameters
including pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all model version to artifact links.
"""
with Session(self.engine) as session:
query = select(ModelVersionArtifactSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=ModelVersionArtifactSchema,
filter_model=model_version_artifact_link_filter_model,
hydrate=hydrate,
)
def delete_model_version_artifact_link(
self,
model_version_id: UUID,
model_version_artifact_link_name_or_id: Union[str, UUID],
) -> None:
"""Deletes a model version to artifact link.
Args:
model_version_id: ID of the model version containing the link.
model_version_artifact_link_name_or_id: name or ID of the model
version to artifact link to be deleted.
Raises:
KeyError: specified ID or name not found.
"""
with Session(self.engine) as session:
model_version = self.get_model_version(model_version_id)
query = select(ModelVersionArtifactSchema).where(
ModelVersionArtifactSchema.model_version_id == model_version.id
)
try:
UUID(str(model_version_artifact_link_name_or_id))
query = query.where(
ModelVersionArtifactSchema.id
== model_version_artifact_link_name_or_id
)
except ValueError:
query = (
query.where(
ModelVersionArtifactSchema.artifact_version_id
== ArtifactVersionSchema.id
)
.where(
ArtifactVersionSchema.artifact_id == ArtifactSchema.id
)
.where(
ArtifactSchema.name
== model_version_artifact_link_name_or_id
)
)
model_version_artifact_link = session.exec(query).first()
if model_version_artifact_link is None:
raise KeyError(
f"Unable to delete model version link with name or ID "
f"`{model_version_artifact_link_name_or_id}`: "
f"No model version link with this name found."
)
session.delete(model_version_artifact_link)
session.commit()
def delete_all_model_version_artifact_links(
self,
model_version_id: UUID,
only_links: bool = True,
) -> None:
"""Deletes all model version to artifact links.
Args:
model_version_id: ID of the model version containing the link.
only_links: Whether to only delete the link to the artifact.
"""
with Session(self.engine) as session:
if not only_links:
artifact_version_ids = session.execute(
select(
ModelVersionArtifactSchema.artifact_version_id
).where(
ModelVersionArtifactSchema.model_version_id
== model_version_id
)
).fetchall()
session.execute(
delete(ArtifactVersionSchema).where(
col(ArtifactVersionSchema.id).in_(
[a[0] for a in artifact_version_ids]
)
),
)
session.execute(
delete(ModelVersionArtifactSchema).where(
ModelVersionArtifactSchema.model_version_id
== model_version_id
)
)
session.commit()
# ---------------------- Model Versions Pipeline Runs ----------------------
def create_model_version_pipeline_run_link(
self,
model_version_pipeline_run_link: ModelVersionPipelineRunRequest,
) -> ModelVersionPipelineRunResponse:
"""Creates a new model version to pipeline run link.
Args:
model_version_pipeline_run_link: the Model Version to Pipeline Run
Link to be created.
Returns:
- If Model Version to Pipeline Run Link already exists - returns
the existing link.
- Otherwise, returns the newly created model version to pipeline
run link.
"""
with Session(self.engine) as session:
# If the link already exists, return it
existing_model_version_pipeline_run_link = session.exec(
select(ModelVersionPipelineRunSchema)
.where(
ModelVersionPipelineRunSchema.model_version_id
== model_version_pipeline_run_link.model_version
)
.where(
ModelVersionPipelineRunSchema.pipeline_run_id
== model_version_pipeline_run_link.pipeline_run,
)
).first()
if existing_model_version_pipeline_run_link is not None:
return existing_model_version_pipeline_run_link.to_model()
# Otherwise, create a new link
model_version_pipeline_run_link_schema = (
ModelVersionPipelineRunSchema.from_request(
model_version_pipeline_run_link
)
)
session.add(model_version_pipeline_run_link_schema)
session.commit()
return model_version_pipeline_run_link_schema.to_model(
include_metadata=True
)
def list_model_version_pipeline_run_links(
self,
model_version_pipeline_run_link_filter_model: ModelVersionPipelineRunFilter,
hydrate: bool = False,
) -> Page[ModelVersionPipelineRunResponse]:
"""Get all model version to pipeline run links by filter.
Args:
model_version_pipeline_run_link_filter_model: All filter parameters
including pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all model version to pipeline run links.
"""
query = select(ModelVersionPipelineRunSchema)
with Session(self.engine) as session:
return self.filter_and_paginate(
session=session,
query=query,
table=ModelVersionPipelineRunSchema,
filter_model=model_version_pipeline_run_link_filter_model,
hydrate=hydrate,
)
def delete_model_version_pipeline_run_link(
self,
model_version_id: UUID,
model_version_pipeline_run_link_name_or_id: Union[str, UUID],
) -> None:
"""Deletes a model version to pipeline run link.
Args:
model_version_id: name or ID of the model version containing the
link.
model_version_pipeline_run_link_name_or_id: name or ID of the model
version to pipeline run link to be deleted.
Raises:
KeyError: specified ID not found.
"""
with Session(self.engine) as session:
model_version = self.get_model_version(
model_version_id=model_version_id
)
query = select(ModelVersionPipelineRunSchema).where(
ModelVersionPipelineRunSchema.model_version_id
== model_version.id
)
try:
UUID(str(model_version_pipeline_run_link_name_or_id))
query = query.where(
ModelVersionPipelineRunSchema.id
== model_version_pipeline_run_link_name_or_id
)
except ValueError:
query = query.where(
ModelVersionPipelineRunSchema.pipeline_run_id
== PipelineRunSchema.id
).where(
PipelineRunSchema.name
== model_version_pipeline_run_link_name_or_id
)
model_version_pipeline_run_link = session.exec(query).first()
if model_version_pipeline_run_link is None:
raise KeyError(
f"Unable to delete model version link with name "
f"`{model_version_pipeline_run_link_name_or_id}`: "
f"No model version link with this name found."
)
session.delete(model_version_pipeline_run_link)
session.commit()
#################
# Tags
#################
def _attach_tags_to_resource(
self,
tag_names: List[str],
resource_id: UUID,
resource_type: TaggableResourceTypes,
) -> None:
"""Creates a tag<>resource link if not present.
Args:
tag_names: The list of names of the tags.
resource_id: The id of the resource.
resource_type: The type of the resource to create link with.
"""
for tag_name in tag_names:
try:
tag = self.get_tag(tag_name)
except KeyError:
tag = self.create_tag(TagRequest(name=tag_name))
try:
self.create_tag_resource(
TagResourceRequest(
tag_id=tag.id,
resource_id=resource_id,
resource_type=resource_type,
)
)
except EntityExistsError:
pass
def _detach_tags_from_resource(
self,
tag_names: List[str],
resource_id: UUID,
resource_type: TaggableResourceTypes,
) -> None:
"""Deletes tag<>resource link if present.
Args:
tag_names: The list of names of the tags.
resource_id: The id of the resource.
resource_type: The type of the resource to create link with.
"""
for tag_name in tag_names:
try:
tag = self.get_tag(tag_name)
self.delete_tag_resource(
tag_id=tag.id,
resource_id=resource_id,
resource_type=resource_type,
)
except KeyError:
pass
@track_decorator(AnalyticsEvent.CREATED_TAG)
def create_tag(self, tag: TagRequest) -> TagResponse:
"""Creates a new tag.
Args:
tag: the tag to be created.
Returns:
The newly created tag.
Raises:
EntityExistsError: If a tag with the given name already exists.
"""
with Session(self.engine) as session:
existing_tag = session.exec(
select(TagSchema).where(TagSchema.name == tag.name)
).first()
if existing_tag is not None:
raise EntityExistsError(
f"Unable to create tag {tag.name}: "
"A tag with this name already exists."
)
tag_schema = TagSchema.from_request(tag)
session.add(tag_schema)
session.commit()
return tag_schema.to_model(include_metadata=True)
def delete_tag(
self,
tag_name_or_id: Union[str, UUID],
) -> None:
"""Deletes a tag.
Args:
tag_name_or_id: name or id of the tag to delete.
Raises:
KeyError: specified ID or name not found.
"""
with Session(self.engine) as session:
tag = self._get_tag_schema(
tag_name_or_id=tag_name_or_id, session=session
)
if tag is None:
raise KeyError(
f"Unable to delete tag with ID `{tag_name_or_id}`: "
f"No tag with this ID found."
)
session.delete(tag)
session.commit()
def get_tag(
self, tag_name_or_id: Union[str, UUID], hydrate: bool = True
) -> TagResponse:
"""Get an existing tag.
Args:
tag_name_or_id: name or id of the tag to be retrieved.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The tag of interest.
Raises:
KeyError: specified ID or name not found.
"""
with Session(self.engine) as session:
tag = self._get_tag_schema(
tag_name_or_id=tag_name_or_id, session=session
)
if tag is None:
raise KeyError(
f"Unable to get tag with ID `{tag_name_or_id}`: "
f"No tag with this ID found."
)
return tag.to_model(include_metadata=hydrate)
def list_tags(
self,
tag_filter_model: TagFilter,
hydrate: bool = False,
) -> Page[TagResponse]:
"""Get all tags by filter.
Args:
tag_filter_model: All filter parameters including pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all tags.
"""
with Session(self.engine) as session:
query = select(TagSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=TagSchema,
filter_model=tag_filter_model,
hydrate=hydrate,
)
def update_tag(
self,
tag_name_or_id: Union[str, UUID],
tag_update_model: TagUpdate,
) -> TagResponse:
"""Update tag.
Args:
tag_name_or_id: name or id of the tag to be updated.
tag_update_model: Tag to use for the update.
Returns:
An updated tag.
Raises:
KeyError: If the tag is not found
"""
with Session(self.engine) as session:
tag = self._get_tag_schema(
tag_name_or_id=tag_name_or_id, session=session
)
if not tag:
raise KeyError(f"Tag with ID `{tag_name_or_id}` not found.")
tag.update(update=tag_update_model)
session.add(tag)
session.commit()
# Refresh the tag that was just created
session.refresh(tag)
return tag.to_model(include_metadata=True)
####################
# Tags <> resources
####################
def create_tag_resource(
self, tag_resource: TagResourceRequest
) -> TagResourceResponse:
"""Creates a new tag resource relationship.
Args:
tag_resource: the tag resource relationship to be created.
Returns:
The newly created tag resource relationship.
Raises:
EntityExistsError: If a tag resource relationship with the given
configuration already exists.
"""
with Session(self.engine) as session:
existing_tag_resource = session.exec(
select(TagResourceSchema).where(
TagResourceSchema.tag_id == tag_resource.tag_id,
TagResourceSchema.resource_id == tag_resource.resource_id,
TagResourceSchema.resource_type
== tag_resource.resource_type.value,
)
).first()
if existing_tag_resource is not None:
raise EntityExistsError(
f"Unable to create a tag "
f"{tag_resource.resource_type.name.lower()} "
f"relationship with IDs "
f"`{tag_resource.tag_id}`|`{tag_resource.resource_id}`. "
"This relationship already exists."
)
tag_resource_schema = TagResourceSchema.from_request(tag_resource)
session.add(tag_resource_schema)
session.commit()
return tag_resource_schema.to_model(include_metadata=True)
def delete_tag_resource(
self,
tag_id: UUID,
resource_id: UUID,
resource_type: TaggableResourceTypes,
) -> None:
"""Deletes a tag resource relationship.
Args:
tag_id: The ID of the tag to delete.
resource_id: The ID of the resource to delete.
resource_type: The type of the resource to delete.
Raises:
KeyError: specified ID not found.
"""
with Session(self.engine) as session:
tag_model = self._get_tag_model_schema(
tag_id=tag_id,
resource_id=resource_id,
resource_type=resource_type,
session=session,
)
if tag_model is None:
raise KeyError(
f"Unable to delete tag<>resource with IDs: "
f"`tag_id`='{tag_id}' and `resource_id`='{resource_id}' "
f"and `resource_type`='{resource_type.value}': No "
"tag<>resource with these IDs found."
)
session.delete(tag_model)
session.commit()
alembic: Alembic
property
readonly
The Alembic wrapper.
Returns:
| Type | Description |
|---|---|
Alembic |
The Alembic wrapper. |
Exceptions:
| Type | Description |
|---|---|
ValueError |
If the store is not initialized. |
backup_secrets_store: Optional[BaseSecretsStore]
property
readonly
The backup secrets store associated with this store.
Returns:
| Type | Description |
|---|---|
Optional[BaseSecretsStore] |
The backup secrets store associated with this store. |
engine: Engine
property
readonly
The SQLAlchemy engine.
Returns:
| Type | Description |
|---|---|
Engine |
The SQLAlchemy engine. |
Exceptions:
| Type | Description |
|---|---|
ValueError |
If the store is not initialized. |
migration_utils: MigrationUtils
property
readonly
The migration utils.
Returns:
| Type | Description |
|---|---|
MigrationUtils |
The migration utils. |
Exceptions:
| Type | Description |
|---|---|
ValueError |
If the store is not initialized. |
secrets_store: BaseSecretsStore
property
readonly
The secrets store associated with this store.
Returns:
| Type | Description |
|---|---|
BaseSecretsStore |
The secrets store associated with this store. |
Exceptions:
| Type | Description |
|---|---|
SecretsStoreNotConfiguredError |
If no secrets store is configured. |
CONFIG_TYPE (StoreConfiguration)
pydantic-model
SQL ZenML store configuration.
Attributes:
| Name | Type | Description |
|---|---|---|
type |
StoreType |
The type of the store. |
secrets_store |
Optional[zenml.config.secrets_store_config.SecretsStoreConfiguration] |
The configuration of the secrets store to use. This defaults to a SQL secrets store that extends the SQL ZenML store. |
backup_secrets_store |
Optional[zenml.config.secrets_store_config.SecretsStoreConfiguration] |
The configuration of a backup secrets store to use in addition to the primary one as an intermediate step during the migration to a new secrets store. |
driver |
Optional[zenml.zen_stores.sql_zen_store.SQLDatabaseDriver] |
The SQL database driver. |
database |
Optional[str] |
database name. If not already present on the server, it will be created automatically on first access. |
username |
Optional[str] |
The database username. |
password |
Optional[str] |
The database password. |
ssl_ca |
Optional[str] |
certificate authority certificate. Required for SSL enabled authentication if the CA certificate is not part of the certificates shipped by the operating system. |
ssl_cert |
Optional[str] |
client certificate. Required for SSL enabled authentication if client certificates are used. |
ssl_key |
Optional[str] |
client certificate private key. Required for SSL enabled if client certificates are used. |
ssl_verify_server_cert |
bool |
set to verify the identity of the server against the provided server certificate. |
pool_size |
int |
The maximum number of connections to keep in the SQLAlchemy pool. |
max_overflow |
int |
The maximum number of connections to allow in the SQLAlchemy pool in addition to the pool_size. |
pool_pre_ping |
bool |
Enable emitting a test statement on the SQL connection at the start of each connection pool checkout, to test that the database connection is still viable. |
Source code in zenml/zen_stores/sql_zen_store.py
class SqlZenStoreConfiguration(StoreConfiguration):
"""SQL ZenML store configuration.
Attributes:
type: The type of the store.
secrets_store: The configuration of the secrets store to use.
This defaults to a SQL secrets store that extends the SQL ZenML
store.
backup_secrets_store: The configuration of a backup secrets store to
use in addition to the primary one as an intermediate step during
the migration to a new secrets store.
driver: The SQL database driver.
database: database name. If not already present on the server, it will
be created automatically on first access.
username: The database username.
password: The database password.
ssl_ca: certificate authority certificate. Required for SSL
enabled authentication if the CA certificate is not part of the
certificates shipped by the operating system.
ssl_cert: client certificate. Required for SSL enabled
authentication if client certificates are used.
ssl_key: client certificate private key. Required for SSL
enabled if client certificates are used.
ssl_verify_server_cert: set to verify the identity of the server
against the provided server certificate.
pool_size: The maximum number of connections to keep in the SQLAlchemy
pool.
max_overflow: The maximum number of connections to allow in the
SQLAlchemy pool in addition to the pool_size.
pool_pre_ping: Enable emitting a test statement on the SQL connection
at the start of each connection pool checkout, to test that the
database connection is still viable.
"""
type: StoreType = StoreType.SQL
secrets_store: Optional[SecretsStoreConfiguration] = None
backup_secrets_store: Optional[SecretsStoreConfiguration] = None
driver: Optional[SQLDatabaseDriver] = None
database: Optional[str] = None
username: Optional[str] = None
password: Optional[str] = None
ssl_ca: Optional[str] = None
ssl_cert: Optional[str] = None
ssl_key: Optional[str] = None
ssl_verify_server_cert: bool = False
pool_size: int = 20
max_overflow: int = 20
pool_pre_ping: bool = True
backup_strategy: DatabaseBackupStrategy = DatabaseBackupStrategy.IN_MEMORY
# database backup directory
backup_directory: str = Field(
default_factory=lambda: os.path.join(
GlobalConfiguration().config_directory,
SQL_STORE_BACKUP_DIRECTORY_NAME,
)
)
backup_database: Optional[str] = None
@validator("secrets_store")
def validate_secrets_store(
cls, secrets_store: Optional[SecretsStoreConfiguration]
) -> SecretsStoreConfiguration:
"""Ensures that the secrets store is initialized with a default SQL secrets store.
Args:
secrets_store: The secrets store config to be validated.
Returns:
The validated secrets store config.
"""
if secrets_store is None:
secrets_store = SqlSecretsStoreConfiguration()
return secrets_store
@root_validator(pre=True)
def _remove_grpc_attributes(cls, values: Dict[str, Any]) -> Dict[str, Any]:
"""Removes old GRPC attributes.
Args:
values: All model attribute values.
Returns:
The model attribute values
"""
grpc_attribute_keys = [
"grpc_metadata_host",
"grpc_metadata_port",
"grpc_metadata_ssl_ca",
"grpc_metadata_ssl_key",
"grpc_metadata_ssl_cert",
]
grpc_values = [values.pop(key, None) for key in grpc_attribute_keys]
if any(grpc_values):
logger.warning(
"The GRPC attributes %s are unused and will be removed soon. "
"Please remove them from SQLZenStore configuration. This will "
"become an error in future versions of ZenML."
)
return values
@root_validator
def _validate_backup_strategy(
cls, values: Dict[str, Any]
) -> Dict[str, Any]:
"""Validate the backup strategy.
Args:
values: All model attribute values.
Returns:
The model attribute values.
Raises:
ValueError: If the backup database name is not set when the backup
database is requested.
"""
backup_strategy = values.get("backup_strategy")
if backup_strategy == DatabaseBackupStrategy.DATABASE and (
not values.get("backup_database")
):
raise ValueError(
"The `backup_database` attribute must also be set if the "
"backup strategy is set to use a backup database."
)
return values
@root_validator
def _validate_url(cls, values: Dict[str, Any]) -> Dict[str, Any]:
"""Validate the SQL URL.
The validator also moves the MySQL username, password and database
parameters from the URL into the other configuration arguments, if they
are present in the URL.
Args:
values: The values to validate.
Returns:
The validated values.
Raises:
ValueError: If the URL is invalid or the SQL driver is not
supported.
"""
url = values.get("url")
if url is None:
return values
# When running inside a container, if the URL uses localhost, the
# target service will not be available. We try to replace localhost
# with one of the special Docker or K3D internal hostnames.
url = replace_localhost_with_internal_hostname(url)
try:
sql_url = make_url(url)
except ArgumentError as e:
raise ValueError(
"Invalid SQL URL `%s`: %s. The URL must be in the format "
"`driver://[[username:password@]hostname:port]/database["
"?<extra-args>]`.",
url,
str(e),
)
if sql_url.drivername not in SQLDatabaseDriver.values():
raise ValueError(
"Invalid SQL driver value `%s`: The driver must be one of: %s.",
url,
", ".join(SQLDatabaseDriver.values()),
)
values["driver"] = SQLDatabaseDriver(sql_url.drivername)
if sql_url.drivername == SQLDatabaseDriver.SQLITE:
if (
sql_url.username
or sql_url.password
or sql_url.query
or sql_url.database is None
):
raise ValueError(
"Invalid SQLite URL `%s`: The URL must be in the "
"format `sqlite:///path/to/database.db`.",
url,
)
if values.get("username") or values.get("password"):
raise ValueError(
"Invalid SQLite configuration: The username and password "
"must not be set",
url,
)
values["database"] = sql_url.database
elif sql_url.drivername == SQLDatabaseDriver.MYSQL:
if sql_url.username:
values["username"] = sql_url.username
sql_url = sql_url._replace(username=None)
if sql_url.password:
values["password"] = sql_url.password
sql_url = sql_url._replace(password=None)
if sql_url.database:
values["database"] = sql_url.database
sql_url = sql_url._replace(database=None)
if sql_url.query:
for k, v in sql_url.query.items():
if k == "ssl_ca":
values["ssl_ca"] = v
elif k == "ssl_cert":
values["ssl_cert"] = v
elif k == "ssl_key":
values["ssl_key"] = v
elif k == "ssl_verify_server_cert":
values["ssl_verify_server_cert"] = v
else:
raise ValueError(
"Invalid MySQL URL query parameter `%s`: The "
"parameter must be one of: ssl_ca, ssl_cert, "
"ssl_key, or ssl_verify_server_cert.",
k,
)
sql_url = sql_url._replace(query={})
database = values.get("database")
if (
not values.get("username")
or not values.get("password")
or not database
):
raise ValueError(
"Invalid MySQL configuration: The username, password and "
"database must be set in the URL or as configuration "
"attributes",
)
regexp = r"^[^\\/?%*:|\"<>.-]{1,64}$"
match = re.match(regexp, database)
if not match:
raise ValueError(
f"The database name does not conform to the required "
f"format "
f"rules ({regexp}): {database}"
)
# Save the certificates in a secure location on disk
secret_folder = Path(
GlobalConfiguration().local_stores_path,
"certificates",
)
for key in ["ssl_key", "ssl_ca", "ssl_cert"]:
content = values.get(key)
if content and not os.path.isfile(content):
fileio.makedirs(str(secret_folder))
file_path = Path(secret_folder, f"{key}.pem")
with open(file_path, "w") as f:
f.write(content)
file_path.chmod(0o600)
values[key] = str(file_path)
values["url"] = str(sql_url)
return values
@staticmethod
def get_local_url(path: str) -> str:
"""Get a local SQL url for a given local path.
Args:
path: The path to the local sqlite file.
Returns:
The local SQL url for the given path.
"""
return f"sqlite:///{path}/{ZENML_SQLITE_DB_FILENAME}"
@classmethod
def supports_url_scheme(cls, url: str) -> bool:
"""Check if a URL scheme is supported by this store.
Args:
url: The URL to check.
Returns:
True if the URL scheme is supported, False otherwise.
"""
return make_url(url).drivername in SQLDatabaseDriver.values()
def expand_certificates(self) -> None:
"""Expands the certificates in the verify_ssl field."""
# Load the certificate values back into the configuration
for key in ["ssl_key", "ssl_ca", "ssl_cert"]:
file_path = getattr(self, key, None)
if file_path and os.path.isfile(file_path):
with open(file_path, "r") as f:
setattr(self, key, f.read())
def get_sqlalchemy_config(
self,
database: Optional[str] = None,
) -> Tuple[URL, Dict[str, Any], Dict[str, Any]]:
"""Get the SQLAlchemy engine configuration for the SQL ZenML store.
Args:
database: Custom database name to use. If not set, the database name
from the configuration will be used.
Returns:
The URL and connection arguments for the SQLAlchemy engine.
Raises:
NotImplementedError: If the SQL driver is not supported.
"""
sql_url = make_url(self.url)
sqlalchemy_connect_args: Dict[str, Any] = {}
engine_args = {}
if sql_url.drivername == SQLDatabaseDriver.SQLITE:
assert self.database is not None
# The following default value is needed for sqlite to avoid the
# Error:
# sqlite3.ProgrammingError: SQLite objects created in a thread can
# only be used in that same thread.
sqlalchemy_connect_args = {"check_same_thread": False}
elif sql_url.drivername == SQLDatabaseDriver.MYSQL:
# all these are guaranteed by our root validator
assert self.database is not None
assert self.username is not None
assert self.password is not None
assert sql_url.host is not None
if not database:
database = self.database
engine_args = {
"pool_size": self.pool_size,
"max_overflow": self.max_overflow,
"pool_pre_ping": self.pool_pre_ping,
}
sql_url = sql_url._replace(
drivername="mysql+pymysql",
username=self.username,
password=self.password,
database=database,
)
sqlalchemy_ssl_args: Dict[str, Any] = {}
# Handle SSL params
for key in ["ssl_key", "ssl_ca", "ssl_cert"]:
ssl_setting = getattr(self, key)
if not ssl_setting:
continue
if not os.path.isfile(ssl_setting):
logger.warning(
f"Database SSL setting `{key}` is not a file. "
)
sqlalchemy_ssl_args[key.lstrip("ssl_")] = ssl_setting
if len(sqlalchemy_ssl_args) > 0:
sqlalchemy_ssl_args["check_hostname"] = (
self.ssl_verify_server_cert
)
sqlalchemy_connect_args["ssl"] = sqlalchemy_ssl_args
else:
raise NotImplementedError(
f"SQL driver `{sql_url.drivername}` is not supported."
)
return sql_url, sqlalchemy_connect_args, engine_args
class Config:
"""Pydantic configuration class."""
# Don't validate attributes when assigning them. This is necessary
# because the certificate attributes can be expanded to the contents
# of the certificate files.
validate_assignment = False
# Forbid extra attributes set in the class.
extra = "forbid"
Config
Pydantic configuration class.
Source code in zenml/zen_stores/sql_zen_store.py
class Config:
"""Pydantic configuration class."""
# Don't validate attributes when assigning them. This is necessary
# because the certificate attributes can be expanded to the contents
# of the certificate files.
validate_assignment = False
# Forbid extra attributes set in the class.
extra = "forbid"
expand_certificates(self)
Expands the certificates in the verify_ssl field.
Source code in zenml/zen_stores/sql_zen_store.py
def expand_certificates(self) -> None:
"""Expands the certificates in the verify_ssl field."""
# Load the certificate values back into the configuration
for key in ["ssl_key", "ssl_ca", "ssl_cert"]:
file_path = getattr(self, key, None)
if file_path and os.path.isfile(file_path):
with open(file_path, "r") as f:
setattr(self, key, f.read())
get_local_url(path)
staticmethod
Get a local SQL url for a given local path.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
path |
str |
The path to the local sqlite file. |
required |
Returns:
| Type | Description |
|---|---|
str |
The local SQL url for the given path. |
Source code in zenml/zen_stores/sql_zen_store.py
@staticmethod
def get_local_url(path: str) -> str:
"""Get a local SQL url for a given local path.
Args:
path: The path to the local sqlite file.
Returns:
The local SQL url for the given path.
"""
return f"sqlite:///{path}/{ZENML_SQLITE_DB_FILENAME}"
get_sqlalchemy_config(self, database=None)
Get the SQLAlchemy engine configuration for the SQL ZenML store.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
database |
Optional[str] |
Custom database name to use. If not set, the database name from the configuration will be used. |
None |
Returns:
| Type | Description |
|---|---|
Tuple[sqlalchemy.engine.url.URL, Dict[str, Any], Dict[str, Any]] |
The URL and connection arguments for the SQLAlchemy engine. |
Exceptions:
| Type | Description |
|---|---|
NotImplementedError |
If the SQL driver is not supported. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_sqlalchemy_config(
self,
database: Optional[str] = None,
) -> Tuple[URL, Dict[str, Any], Dict[str, Any]]:
"""Get the SQLAlchemy engine configuration for the SQL ZenML store.
Args:
database: Custom database name to use. If not set, the database name
from the configuration will be used.
Returns:
The URL and connection arguments for the SQLAlchemy engine.
Raises:
NotImplementedError: If the SQL driver is not supported.
"""
sql_url = make_url(self.url)
sqlalchemy_connect_args: Dict[str, Any] = {}
engine_args = {}
if sql_url.drivername == SQLDatabaseDriver.SQLITE:
assert self.database is not None
# The following default value is needed for sqlite to avoid the
# Error:
# sqlite3.ProgrammingError: SQLite objects created in a thread can
# only be used in that same thread.
sqlalchemy_connect_args = {"check_same_thread": False}
elif sql_url.drivername == SQLDatabaseDriver.MYSQL:
# all these are guaranteed by our root validator
assert self.database is not None
assert self.username is not None
assert self.password is not None
assert sql_url.host is not None
if not database:
database = self.database
engine_args = {
"pool_size": self.pool_size,
"max_overflow": self.max_overflow,
"pool_pre_ping": self.pool_pre_ping,
}
sql_url = sql_url._replace(
drivername="mysql+pymysql",
username=self.username,
password=self.password,
database=database,
)
sqlalchemy_ssl_args: Dict[str, Any] = {}
# Handle SSL params
for key in ["ssl_key", "ssl_ca", "ssl_cert"]:
ssl_setting = getattr(self, key)
if not ssl_setting:
continue
if not os.path.isfile(ssl_setting):
logger.warning(
f"Database SSL setting `{key}` is not a file. "
)
sqlalchemy_ssl_args[key.lstrip("ssl_")] = ssl_setting
if len(sqlalchemy_ssl_args) > 0:
sqlalchemy_ssl_args["check_hostname"] = (
self.ssl_verify_server_cert
)
sqlalchemy_connect_args["ssl"] = sqlalchemy_ssl_args
else:
raise NotImplementedError(
f"SQL driver `{sql_url.drivername}` is not supported."
)
return sql_url, sqlalchemy_connect_args, engine_args
supports_url_scheme(url)
classmethod
Check if a URL scheme is supported by this store.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
url |
str |
The URL to check. |
required |
Returns:
| Type | Description |
|---|---|
bool |
True if the URL scheme is supported, False otherwise. |
Source code in zenml/zen_stores/sql_zen_store.py
@classmethod
def supports_url_scheme(cls, url: str) -> bool:
"""Check if a URL scheme is supported by this store.
Args:
url: The URL to check.
Returns:
True if the URL scheme is supported, False otherwise.
"""
return make_url(url).drivername in SQLDatabaseDriver.values()
validate_secrets_store(secrets_store)
classmethod
Ensures that the secrets store is initialized with a default SQL secrets store.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secrets_store |
Optional[zenml.config.secrets_store_config.SecretsStoreConfiguration] |
The secrets store config to be validated. |
required |
Returns:
| Type | Description |
|---|---|
SecretsStoreConfiguration |
The validated secrets store config. |
Source code in zenml/zen_stores/sql_zen_store.py
@validator("secrets_store")
def validate_secrets_store(
cls, secrets_store: Optional[SecretsStoreConfiguration]
) -> SecretsStoreConfiguration:
"""Ensures that the secrets store is initialized with a default SQL secrets store.
Args:
secrets_store: The secrets store config to be validated.
Returns:
The validated secrets store config.
"""
if secrets_store is None:
secrets_store = SqlSecretsStoreConfiguration()
return secrets_store
backup_database(self, strategy=None, location=None, overwrite=False)
Backup the database.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
strategy |
Optional[zenml.enums.DatabaseBackupStrategy] |
Custom backup strategy to use. If not set, the backup strategy from the store configuration will be used. |
None |
location |
Optional[str] |
Custom target location to backup the database to. If not set, the configured backup location will be used. Depending on the backup strategy, this can be a file path or a database name. |
None |
overwrite |
bool |
Whether to overwrite an existing backup if it exists. If set to False, the existing backup will be reused. |
False |
Returns:
| Type | Description |
|---|---|
Tuple[str, Any] |
The location where the database was backed up to and an accompanying user-friendly message that describes the backup location, or None if no backup was created (i.e. because the backup already exists). |
Exceptions:
| Type | Description |
|---|---|
ValueError |
If the backup database name is not set when the backup database is requested or if the backup strategy is invalid. |
Source code in zenml/zen_stores/sql_zen_store.py
def backup_database(
self,
strategy: Optional[DatabaseBackupStrategy] = None,
location: Optional[str] = None,
overwrite: bool = False,
) -> Tuple[str, Any]:
"""Backup the database.
Args:
strategy: Custom backup strategy to use. If not set, the backup
strategy from the store configuration will be used.
location: Custom target location to backup the database to. If not
set, the configured backup location will be used. Depending on
the backup strategy, this can be a file path or a database name.
overwrite: Whether to overwrite an existing backup if it exists.
If set to False, the existing backup will be reused.
Returns:
The location where the database was backed up to and an accompanying
user-friendly message that describes the backup location, or None
if no backup was created (i.e. because the backup already exists).
Raises:
ValueError: If the backup database name is not set when the backup
database is requested or if the backup strategy is invalid.
"""
strategy = strategy or self.config.backup_strategy
if (
strategy == DatabaseBackupStrategy.DUMP_FILE
or self.config.driver == SQLDatabaseDriver.SQLITE
):
dump_file = location or self._get_db_backup_file_path()
if not overwrite and os.path.isfile(dump_file):
logger.warning(
f"A previous backup file already exists at '{dump_file}'. "
"Reusing the existing backup."
)
else:
self.migration_utils.backup_database_to_file(
dump_file=dump_file
)
return f"the '{dump_file}' backup file", dump_file
elif strategy == DatabaseBackupStrategy.DATABASE:
backup_db_name = location or self.config.backup_database
if not backup_db_name:
raise ValueError(
"The backup database name must be set in the store "
"configuration to use the backup database strategy."
)
if not overwrite and self.migration_utils.database_exists(
backup_db_name
):
logger.warning(
"A previous backup database already exists at "
f"'{backup_db_name}'. Reusing the existing backup."
)
else:
self.migration_utils.backup_database_to_db(
backup_db_name=backup_db_name
)
return f"the '{backup_db_name}' backup database", backup_db_name
elif strategy == DatabaseBackupStrategy.IN_MEMORY:
return (
"memory",
self.migration_utils.backup_database_to_memory(),
)
else:
raise ValueError(f"Invalid backup strategy: {strategy}.")
backup_secrets(self, ignore_errors=True, delete_secrets=False)
Backs up all secrets to the configured backup secrets store.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
ignore_errors |
bool |
Whether to ignore individual errors during the backup process and attempt to backup all secrets. |
True |
delete_secrets |
bool |
Whether to delete the secrets that have been successfully backed up from the primary secrets store. Setting this flag effectively moves all secrets from the primary secrets store to the backup secrets store. |
False |
noqa: DAR401
Exceptions:
| Type | Description |
|---|---|
BackupSecretsStoreNotConfiguredError |
if no backup secrets store is configured. |
Source code in zenml/zen_stores/sql_zen_store.py
def backup_secrets(
self, ignore_errors: bool = True, delete_secrets: bool = False
) -> None:
"""Backs up all secrets to the configured backup secrets store.
Args:
ignore_errors: Whether to ignore individual errors during the backup
process and attempt to backup all secrets.
delete_secrets: Whether to delete the secrets that have been
successfully backed up from the primary secrets store. Setting
this flag effectively moves all secrets from the primary secrets
store to the backup secrets store.
# noqa: DAR401
Raises:
BackupSecretsStoreNotConfiguredError: if no backup secrets store is
configured.
"""
if not self.backup_secrets_store:
raise BackupSecretsStoreNotConfiguredError(
"Unable to backup secrets: No backup secrets store is "
"configured."
)
with Session(self.engine) as session:
secrets_in_db = session.exec(select(SecretSchema)).all()
for secret in secrets_in_db:
try:
values = self._get_secret_values(
secret_id=secret.id, use_backup=False
)
except Exception:
logger.exception(
f"Failed to get secret values for secret with ID "
f"{secret.id}."
)
if ignore_errors:
continue
raise
try:
self._backup_secret_values(secret_id=secret.id, values=values)
except Exception:
logger.exception(
f"Failed to backup secret with ID {secret.id}. "
)
if ignore_errors:
continue
raise
if delete_secrets:
try:
self._delete_secret_values(
secret_id=secret.id, delete_backup=False
)
except Exception:
logger.exception(
f"Failed to delete secret with ID {secret.id} from the "
f"primary secrets store after backing it up to the "
f"backup secrets store."
)
if ignore_errors:
continue
raise
cleanup_database_backup(self, strategy=None, location=None)
Delete the database backup.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
strategy |
Optional[zenml.enums.DatabaseBackupStrategy] |
Custom backup strategy to use. If not set, the backup strategy from the store configuration will be used. |
None |
location |
Optional[Any] |
Custom target location to delete the database backup from. If not set, the configured backup location will be used. Depending on the backup strategy, this can be a file path or a database name. |
None |
Exceptions:
| Type | Description |
|---|---|
ValueError |
If the backup database name is not set when the backup database is requested. |
Source code in zenml/zen_stores/sql_zen_store.py
def cleanup_database_backup(
self,
strategy: Optional[DatabaseBackupStrategy] = None,
location: Optional[Any] = None,
) -> None:
"""Delete the database backup.
Args:
strategy: Custom backup strategy to use. If not set, the backup
strategy from the store configuration will be used.
location: Custom target location to delete the database backup
from. If not set, the configured backup location will be used.
Depending on the backup strategy, this can be a file path or a
database name.
Raises:
ValueError: If the backup database name is not set when the backup
database is requested.
"""
strategy = strategy or self.config.backup_strategy
if (
strategy == DatabaseBackupStrategy.DUMP_FILE
or self.config.driver == SQLDatabaseDriver.SQLITE
):
dump_file = location or self._get_db_backup_file_path()
if dump_file is not None and os.path.isfile(dump_file):
try:
os.remove(dump_file)
except OSError:
logger.warning(
f"Failed to cleanup database dump file "
f"{dump_file}."
)
else:
logger.info(
f"Successfully cleaned up database dump file "
f"{dump_file}."
)
elif strategy == DatabaseBackupStrategy.DATABASE:
backup_db_name = location or self.config.backup_database
if not backup_db_name:
raise ValueError(
"The backup database name must be set in the store "
"configuration to use the backup database strategy."
)
if self.migration_utils.database_exists(backup_db_name):
# Drop the backup database
self.migration_utils.drop_database(
database=backup_db_name,
)
logger.info(
f"Successfully cleaned up backup database "
f"{backup_db_name}."
)
count_pipelines(self, filter_model)
Count all pipelines.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
filter_model |
Optional[zenml.models.v2.core.pipeline.PipelineFilter] |
The filter model to use for counting pipelines. |
required |
Returns:
| Type | Description |
|---|---|
int |
The number of pipelines. |
Source code in zenml/zen_stores/sql_zen_store.py
def count_pipelines(self, filter_model: Optional[PipelineFilter]) -> int:
"""Count all pipelines.
Args:
filter_model: The filter model to use for counting pipelines.
Returns:
The number of pipelines.
"""
return self._count_entity(
schema=PipelineSchema, filter_model=filter_model
)
count_runs(self, filter_model)
Count all pipeline runs.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
filter_model |
Optional[zenml.models.v2.core.pipeline_run.PipelineRunFilter] |
The filter model to filter the runs. |
required |
Returns:
| Type | Description |
|---|---|
int |
The number of pipeline runs. |
Source code in zenml/zen_stores/sql_zen_store.py
def count_runs(self, filter_model: Optional[PipelineRunFilter]) -> int:
"""Count all pipeline runs.
Args:
filter_model: The filter model to filter the runs.
Returns:
The number of pipeline runs.
"""
return self._count_entity(
schema=PipelineRunSchema, filter_model=filter_model
)
count_stack_components(self, filter_model=None)
Count all components.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
filter_model |
Optional[zenml.models.v2.core.component.ComponentFilter] |
The filter model to use for counting components. |
None |
Returns:
| Type | Description |
|---|---|
int |
The number of components. |
Source code in zenml/zen_stores/sql_zen_store.py
def count_stack_components(
self, filter_model: Optional[ComponentFilter] = None
) -> int:
"""Count all components.
Args:
filter_model: The filter model to use for counting components.
Returns:
The number of components.
"""
return self._count_entity(
schema=StackComponentSchema, filter_model=filter_model
)
count_stacks(self, filter_model)
Count all stacks.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
filter_model |
Optional[zenml.models.v2.core.stack.StackFilter] |
The filter model to filter the stacks. |
required |
Returns:
| Type | Description |
|---|---|
int |
The number of stacks. |
Source code in zenml/zen_stores/sql_zen_store.py
def count_stacks(self, filter_model: Optional[StackFilter]) -> int:
"""Count all stacks.
Args:
filter_model: The filter model to filter the stacks.
Returns:
The number of stacks.
"""
return self._count_entity(
schema=StackSchema, filter_model=filter_model
)
create_api_key(self, service_account_id, api_key)
Create a new API key for a service account.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account_id |
UUID |
The ID of the service account for which to create the API key. |
required |
api_key |
APIKeyRequest |
The API key to create. |
required |
Returns:
| Type | Description |
|---|---|
APIKeyResponse |
The created API key. |
Exceptions:
| Type | Description |
|---|---|
EntityExistsError |
If an API key with the same name is already configured for the same service account. |
Source code in zenml/zen_stores/sql_zen_store.py
def create_api_key(
self, service_account_id: UUID, api_key: APIKeyRequest
) -> APIKeyResponse:
"""Create a new API key for a service account.
Args:
service_account_id: The ID of the service account for which to
create the API key.
api_key: The API key to create.
Returns:
The created API key.
Raises:
EntityExistsError: If an API key with the same name is already
configured for the same service account.
"""
with Session(self.engine) as session:
# Fetch the service account
service_account = self._get_account_schema(
service_account_id, session=session, service_account=True
)
# Check if a key with the same name already exists for the same
# service account
try:
self._get_api_key(
service_account_id=service_account.id,
api_key_name_or_id=api_key.name,
session=session,
)
raise EntityExistsError(
f"Unable to register API key with name '{api_key.name}': "
"Found an existing API key with the same name configured "
f"for the same '{service_account.name}' service account."
)
except KeyError:
pass
new_api_key, key_value = APIKeySchema.from_request(
service_account_id=service_account.id,
request=api_key,
)
session.add(new_api_key)
session.commit()
api_key_model = new_api_key.to_model(include_metadata=True)
api_key_model.set_key(key_value)
return api_key_model
create_artifact(self, artifact)
Creates a new artifact.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact |
ArtifactRequest |
The artifact to create. |
required |
Returns:
| Type | Description |
|---|---|
ArtifactResponse |
The newly created artifact. |
Exceptions:
| Type | Description |
|---|---|
EntityExistsError |
If an artifact with the same name already exists. |
Source code in zenml/zen_stores/sql_zen_store.py
def create_artifact(self, artifact: ArtifactRequest) -> ArtifactResponse:
"""Creates a new artifact.
Args:
artifact: The artifact to create.
Returns:
The newly created artifact.
Raises:
EntityExistsError: If an artifact with the same name already exists.
"""
with Session(self.engine) as session:
# Check if an artifact with the given name already exists
existing_artifact = session.exec(
select(ArtifactSchema).where(
ArtifactSchema.name == artifact.name
)
).first()
if existing_artifact is not None:
raise EntityExistsError(
f"Unable to create artifact with name '{artifact.name}': "
"An artifact with the same name already exists."
)
# Create the artifact.
artifact_schema = ArtifactSchema.from_request(artifact)
# Save tags of the artifact.
if artifact.tags:
self._attach_tags_to_resource(
tag_names=artifact.tags,
resource_id=artifact_schema.id,
resource_type=TaggableResourceTypes.ARTIFACT,
)
session.add(artifact_schema)
session.commit()
return artifact_schema.to_model(include_metadata=True)
create_artifact_version(self, artifact_version)
Creates an artifact version.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_version |
ArtifactVersionRequest |
The artifact version to create. |
required |
Returns:
| Type | Description |
|---|---|
ArtifactVersionResponse |
The created artifact version. |
Exceptions:
| Type | Description |
|---|---|
EntityExistsError |
if an artifact with the same name and version already exists. |
Source code in zenml/zen_stores/sql_zen_store.py
def create_artifact_version(
self, artifact_version: ArtifactVersionRequest
) -> ArtifactVersionResponse:
"""Creates an artifact version.
Args:
artifact_version: The artifact version to create.
Returns:
The created artifact version.
Raises:
EntityExistsError: if an artifact with the same name and version
already exists.
"""
with Session(self.engine) as session:
# Check if an artifact with the given name and version exists
def _check(tolerance: int = 0) -> None:
query = session.exec(
select(ArtifactVersionSchema)
.where(
ArtifactVersionSchema.artifact_id
== artifact_version.artifact_id
)
.where(
ArtifactVersionSchema.version
== artifact_version.version
)
)
existing_artifact = query.fetchmany(tolerance + 1)
if (
existing_artifact is not None
and len(existing_artifact) > tolerance
):
raise EntityExistsError(
f"Unable to create artifact with name "
f"'{existing_artifact[0].artifact.name}' and version "
f"'{artifact_version.version}': An artifact with the same "
"name and version already exists."
)
_check()
# Create the artifact version.
artifact_version_schema = ArtifactVersionSchema.from_request(
artifact_version
)
session.add(artifact_version_schema)
# Save visualizations of the artifact.
if artifact_version.visualizations:
for vis in artifact_version.visualizations:
vis_schema = ArtifactVisualizationSchema.from_model(
artifact_visualization_request=vis,
artifact_version_id=artifact_version_schema.id,
)
session.add(vis_schema)
# Save tags of the artifact.
if artifact_version.tags:
self._attach_tags_to_resource(
tag_names=artifact_version.tags,
resource_id=artifact_version_schema.id,
resource_type=TaggableResourceTypes.ARTIFACT_VERSION,
)
try:
_check(1)
session.commit()
except EntityExistsError as e:
session.rollback()
raise e
return artifact_version_schema.to_model(include_metadata=True)
create_authorized_device(self, device)
Creates a new OAuth 2.0 authorized device.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
device |
OAuthDeviceInternalRequest |
The device to be created. |
required |
Returns:
| Type | Description |
|---|---|
OAuthDeviceInternalResponse |
The newly created device. |
Exceptions:
| Type | Description |
|---|---|
EntityExistsError |
If a device for the same client ID already exists. |
Source code in zenml/zen_stores/sql_zen_store.py
def create_authorized_device(
self, device: OAuthDeviceInternalRequest
) -> OAuthDeviceInternalResponse:
"""Creates a new OAuth 2.0 authorized device.
Args:
device: The device to be created.
Returns:
The newly created device.
Raises:
EntityExistsError: If a device for the same client ID already
exists.
"""
with Session(self.engine) as session:
existing_device = session.exec(
select(OAuthDeviceSchema).where(
OAuthDeviceSchema.client_id == device.client_id
)
).first()
if existing_device is not None:
raise EntityExistsError(
f"Unable to create device with client ID "
f"'{device.client_id}': A device with this client ID "
"already exists."
)
(
new_device,
user_code,
device_code,
) = OAuthDeviceSchema.from_request(device)
session.add(new_device)
session.commit()
session.refresh(new_device)
device_model = new_device.to_internal_model(hydrate=True)
# Replace the hashed user code with the original user code
device_model.user_code = user_code
# Replace the hashed device code with the original device code
device_model.device_code = device_code
return device_model
create_build(self, build)
Creates a new build in a workspace.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
build |
PipelineBuildRequest |
The build to create. |
required |
Returns:
| Type | Description |
|---|---|
PipelineBuildResponse |
The newly created build. |
Source code in zenml/zen_stores/sql_zen_store.py
def create_build(
self,
build: PipelineBuildRequest,
) -> PipelineBuildResponse:
"""Creates a new build in a workspace.
Args:
build: The build to create.
Returns:
The newly created build.
"""
with Session(self.engine) as session:
# Create the build
new_build = PipelineBuildSchema.from_request(build)
session.add(new_build)
session.commit()
session.refresh(new_build)
return new_build.to_model(include_metadata=True)
create_code_repository(self, code_repository)
Creates a new code repository.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
code_repository |
CodeRepositoryRequest |
Code repository to be created. |
required |
Returns:
| Type | Description |
|---|---|
CodeRepositoryResponse |
The newly created code repository. |
Exceptions:
| Type | Description |
|---|---|
EntityExistsError |
If a code repository with the given name already exists. |
Source code in zenml/zen_stores/sql_zen_store.py
@track_decorator(AnalyticsEvent.REGISTERED_CODE_REPOSITORY)
def create_code_repository(
self, code_repository: CodeRepositoryRequest
) -> CodeRepositoryResponse:
"""Creates a new code repository.
Args:
code_repository: Code repository to be created.
Returns:
The newly created code repository.
Raises:
EntityExistsError: If a code repository with the given name already
exists.
"""
with Session(self.engine) as session:
existing_repo = session.exec(
select(CodeRepositorySchema)
.where(CodeRepositorySchema.name == code_repository.name)
.where(
CodeRepositorySchema.workspace_id
== code_repository.workspace
)
).first()
if existing_repo is not None:
raise EntityExistsError(
f"Unable to create code repository in workspace "
f"'{code_repository.workspace}': A code repository with "
"this name already exists."
)
new_repo = CodeRepositorySchema.from_request(code_repository)
session.add(new_repo)
session.commit()
session.refresh(new_repo)
return new_repo.to_model(include_metadata=True)
create_deployment(self, deployment)
Creates a new deployment in a workspace.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
deployment |
PipelineDeploymentRequest |
The deployment to create. |
required |
Returns:
| Type | Description |
|---|---|
PipelineDeploymentResponse |
The newly created deployment. |
Source code in zenml/zen_stores/sql_zen_store.py
def create_deployment(
self,
deployment: PipelineDeploymentRequest,
) -> PipelineDeploymentResponse:
"""Creates a new deployment in a workspace.
Args:
deployment: The deployment to create.
Returns:
The newly created deployment.
"""
with Session(self.engine) as session:
code_reference_id = self._create_or_reuse_code_reference(
session=session,
workspace_id=deployment.workspace,
code_reference=deployment.code_reference,
)
new_deployment = PipelineDeploymentSchema.from_request(
deployment, code_reference_id=code_reference_id
)
session.add(new_deployment)
session.commit()
session.refresh(new_deployment)
return new_deployment.to_model(include_metadata=True)
create_event_source(self, event_source)
Create an event_source.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
event_source |
EventSourceRequest |
The event_source to create. |
required |
Returns:
| Type | Description |
|---|---|
EventSourceResponse |
The created event_source. |
Source code in zenml/zen_stores/sql_zen_store.py
def create_event_source(
self, event_source: EventSourceRequest
) -> EventSourceResponse:
"""Create an event_source.
Args:
event_source: The event_source to create.
Returns:
The created event_source.
"""
with Session(self.engine) as session:
self._fail_if_event_source_with_name_exists(
event_source=event_source,
session=session,
)
new_event_source = EventSourceSchema.from_request(event_source)
session.add(new_event_source)
session.commit()
session.refresh(new_event_source)
return new_event_source.to_model(
include_metadata=True, include_resources=True
)
create_flavor(self, flavor)
Creates a new stack component flavor.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
flavor |
FlavorRequest |
The stack component flavor to create. |
required |
Returns:
| Type | Description |
|---|---|
FlavorResponse |
The newly created flavor. |
Exceptions:
| Type | Description |
|---|---|
EntityExistsError |
If a flavor with the same name and type is already owned by this user in this workspace. |
ValueError |
In case the config_schema string exceeds the max length. |
Source code in zenml/zen_stores/sql_zen_store.py
@track_decorator(AnalyticsEvent.CREATED_FLAVOR)
def create_flavor(self, flavor: FlavorRequest) -> FlavorResponse:
"""Creates a new stack component flavor.
Args:
flavor: The stack component flavor to create.
Returns:
The newly created flavor.
Raises:
EntityExistsError: If a flavor with the same name and type
is already owned by this user in this workspace.
ValueError: In case the config_schema string exceeds the max length.
"""
with Session(self.engine) as session:
# Check if flavor with the same domain key (name, type, workspace,
# owner) already exists
existing_flavor = session.exec(
select(FlavorSchema)
.where(FlavorSchema.name == flavor.name)
.where(FlavorSchema.type == flavor.type)
.where(FlavorSchema.workspace_id == flavor.workspace)
.where(FlavorSchema.user_id == flavor.user)
).first()
if existing_flavor is not None:
raise EntityExistsError(
f"Unable to register '{flavor.type.value}' flavor "
f"with name '{flavor.name}': Found an existing "
f"flavor with the same name and type in the same "
f"'{flavor.workspace}' workspace owned by the same "
f"'{flavor.user}' user."
)
config_schema = json.dumps(flavor.config_schema)
if len(config_schema) > TEXT_FIELD_MAX_LENGTH:
raise ValueError(
"Json representation of configuration schema"
"exceeds max length."
)
else:
new_flavor = FlavorSchema(
name=flavor.name,
type=flavor.type,
source=flavor.source,
config_schema=config_schema,
integration=flavor.integration,
connector_type=flavor.connector_type,
connector_resource_type=flavor.connector_resource_type,
connector_resource_id_attr=flavor.connector_resource_id_attr,
workspace_id=flavor.workspace,
user_id=flavor.user,
logo_url=flavor.logo_url,
docs_url=flavor.docs_url,
sdk_docs_url=flavor.sdk_docs_url,
is_custom=flavor.is_custom,
)
session.add(new_flavor)
session.commit()
return new_flavor.to_model(include_metadata=True)
create_model(self, model)
Creates a new model.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model |
ModelRequest |
the Model to be created. |
required |
Returns:
| Type | Description |
|---|---|
ModelResponse |
The newly created model. |
Exceptions:
| Type | Description |
|---|---|
EntityExistsError |
If a workspace with the given name already exists. |
Source code in zenml/zen_stores/sql_zen_store.py
@track_decorator(AnalyticsEvent.CREATED_MODEL)
def create_model(self, model: ModelRequest) -> ModelResponse:
"""Creates a new model.
Args:
model: the Model to be created.
Returns:
The newly created model.
Raises:
EntityExistsError: If a workspace with the given name already exists.
"""
with Session(self.engine) as session:
existing_model = session.exec(
select(ModelSchema).where(ModelSchema.name == model.name)
).first()
if existing_model is not None:
raise EntityExistsError(
f"Unable to create model {model.name}: "
"A model with this name already exists."
)
model_schema = ModelSchema.from_request(model)
session.add(model_schema)
if model.tags:
self._attach_tags_to_resource(
tag_names=model.tags,
resource_id=model_schema.id,
resource_type=TaggableResourceTypes.MODEL,
)
session.commit()
return model_schema.to_model(include_metadata=True)
create_model_version(self, model_version)
Creates a new model version.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version |
ModelVersionRequest |
the Model Version to be created. |
required |
Returns:
| Type | Description |
|---|---|
ModelVersionResponse |
The newly created model version. |
Exceptions:
| Type | Description |
|---|---|
ValueError |
If |
EntityExistsError |
If a workspace with the given name already exists. |
Source code in zenml/zen_stores/sql_zen_store.py
@track_decorator(AnalyticsEvent.CREATED_MODEL_VERSION)
def create_model_version(
self, model_version: ModelVersionRequest
) -> ModelVersionResponse:
"""Creates a new model version.
Args:
model_version: the Model Version to be created.
Returns:
The newly created model version.
Raises:
ValueError: If `number` is not None during model version creation.
EntityExistsError: If a workspace with the given name already exists.
"""
if model_version.number is not None:
raise ValueError(
"`number` field must be None during model version creation."
)
with Session(self.engine) as session:
model_version_ = model_version.copy()
model = self.get_model(model_version_.model)
def _check(tolerance: int = 0) -> None:
query = session.exec(
select(ModelVersionSchema)
.where(ModelVersionSchema.model_id == model.id)
.where(ModelVersionSchema.name == model_version_.name)
)
existing_model_version = query.fetchmany(tolerance + 1)
if (
existing_model_version is not None
and len(existing_model_version) > tolerance
):
raise EntityExistsError(
f"Unable to create model version {model_version_.name}: "
f"A model version with this name already exists in {model.name} model."
)
_check()
all_versions = session.exec(
select(ModelVersionSchema)
.where(ModelVersionSchema.model_id == model.id)
.order_by(ModelVersionSchema.number.desc()) # type: ignore[attr-defined]
).first()
model_version_.number = (
all_versions.number + 1 if all_versions else 1
)
if model_version_.name is None:
model_version_.name = str(model_version_.number)
model_version_schema = ModelVersionSchema.from_request(
model_version_
)
session.add(model_version_schema)
if model_version_.tags:
self._attach_tags_to_resource(
tag_names=model_version_.tags,
resource_id=model_version_schema.id,
resource_type=TaggableResourceTypes.MODEL_VERSION,
)
try:
_check(1)
session.commit()
except EntityExistsError as e:
session.rollback()
raise e
return model_version_schema.to_model(include_metadata=True)
create_model_version_artifact_link(self, model_version_artifact_link)
Creates a new model version link.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_artifact_link |
ModelVersionArtifactRequest |
the Model Version to Artifact Link to be created. |
required |
Returns:
| Type | Description |
|---|---|
ModelVersionArtifactResponse |
The newly created model version to artifact link. |
Source code in zenml/zen_stores/sql_zen_store.py
def create_model_version_artifact_link(
self, model_version_artifact_link: ModelVersionArtifactRequest
) -> ModelVersionArtifactResponse:
"""Creates a new model version link.
Args:
model_version_artifact_link: the Model Version to Artifact Link
to be created.
Returns:
The newly created model version to artifact link.
"""
with Session(self.engine) as session:
# If the link already exists, return it
existing_model_version_artifact_link = session.exec(
select(ModelVersionArtifactSchema)
.where(
ModelVersionArtifactSchema.model_version_id
== model_version_artifact_link.model_version
)
.where(
ModelVersionArtifactSchema.artifact_version_id
== model_version_artifact_link.artifact_version,
)
).first()
if existing_model_version_artifact_link is not None:
return existing_model_version_artifact_link.to_model()
model_version_artifact_link_schema = (
ModelVersionArtifactSchema.from_request(
model_version_artifact_request=model_version_artifact_link,
)
)
session.add(model_version_artifact_link_schema)
session.commit()
return model_version_artifact_link_schema.to_model(
include_metadata=True
)
create_model_version_pipeline_run_link(self, model_version_pipeline_run_link)
Creates a new model version to pipeline run link.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_pipeline_run_link |
ModelVersionPipelineRunRequest |
the Model Version to Pipeline Run Link to be created. |
required |
Returns:
| Type | Description |
|---|---|
ModelVersionPipelineRunResponse |
|
Source code in zenml/zen_stores/sql_zen_store.py
def create_model_version_pipeline_run_link(
self,
model_version_pipeline_run_link: ModelVersionPipelineRunRequest,
) -> ModelVersionPipelineRunResponse:
"""Creates a new model version to pipeline run link.
Args:
model_version_pipeline_run_link: the Model Version to Pipeline Run
Link to be created.
Returns:
- If Model Version to Pipeline Run Link already exists - returns
the existing link.
- Otherwise, returns the newly created model version to pipeline
run link.
"""
with Session(self.engine) as session:
# If the link already exists, return it
existing_model_version_pipeline_run_link = session.exec(
select(ModelVersionPipelineRunSchema)
.where(
ModelVersionPipelineRunSchema.model_version_id
== model_version_pipeline_run_link.model_version
)
.where(
ModelVersionPipelineRunSchema.pipeline_run_id
== model_version_pipeline_run_link.pipeline_run,
)
).first()
if existing_model_version_pipeline_run_link is not None:
return existing_model_version_pipeline_run_link.to_model()
# Otherwise, create a new link
model_version_pipeline_run_link_schema = (
ModelVersionPipelineRunSchema.from_request(
model_version_pipeline_run_link
)
)
session.add(model_version_pipeline_run_link_schema)
session.commit()
return model_version_pipeline_run_link_schema.to_model(
include_metadata=True
)
create_pipeline(self, pipeline)
Creates a new pipeline in a workspace.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
pipeline |
PipelineRequest |
The pipeline to create. |
required |
Returns:
| Type | Description |
|---|---|
PipelineResponse |
The newly created pipeline. |
Exceptions:
| Type | Description |
|---|---|
EntityExistsError |
If an identical pipeline already exists. |
Source code in zenml/zen_stores/sql_zen_store.py
@track_decorator(AnalyticsEvent.CREATE_PIPELINE)
def create_pipeline(
self,
pipeline: PipelineRequest,
) -> PipelineResponse:
"""Creates a new pipeline in a workspace.
Args:
pipeline: The pipeline to create.
Returns:
The newly created pipeline.
Raises:
EntityExistsError: If an identical pipeline already exists.
"""
with Session(self.engine) as session:
# Check if pipeline with the given name already exists
existing_pipeline = session.exec(
select(PipelineSchema)
.where(PipelineSchema.name == pipeline.name)
.where(PipelineSchema.version_hash == pipeline.version_hash)
.where(PipelineSchema.workspace_id == pipeline.workspace)
).first()
if existing_pipeline is not None:
raise EntityExistsError(
f"Unable to create pipeline in workspace "
f"'{pipeline.workspace}': A pipeline with this name and "
f"version already exists."
)
# Create the pipeline
new_pipeline = PipelineSchema.from_request(pipeline)
session.add(new_pipeline)
session.commit()
session.refresh(new_pipeline)
return new_pipeline.to_model(include_metadata=True)
create_run(self, pipeline_run)
Creates a pipeline run.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
pipeline_run |
PipelineRunRequest |
The pipeline run to create. |
required |
Returns:
| Type | Description |
|---|---|
PipelineRunResponse |
The created pipeline run. |
Exceptions:
| Type | Description |
|---|---|
EntityExistsError |
If a run with the same name already exists. |
Source code in zenml/zen_stores/sql_zen_store.py
def create_run(
self, pipeline_run: PipelineRunRequest
) -> PipelineRunResponse:
"""Creates a pipeline run.
Args:
pipeline_run: The pipeline run to create.
Returns:
The created pipeline run.
Raises:
EntityExistsError: If a run with the same name already exists.
"""
with Session(self.engine) as session:
# Check if pipeline run with same name already exists.
existing_domain_run = session.exec(
select(PipelineRunSchema).where(
PipelineRunSchema.name == pipeline_run.name
)
).first()
if existing_domain_run is not None:
raise EntityExistsError(
f"Unable to create pipeline run: A pipeline run with name "
f"'{pipeline_run.name}' already exists."
)
# Create the pipeline run
new_run = PipelineRunSchema.from_request(pipeline_run)
session.add(new_run)
session.commit()
return new_run.to_model(include_metadata=True)
create_run_metadata(self, run_metadata)
Creates run metadata.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
run_metadata |
RunMetadataRequest |
The run metadata to create. |
required |
Returns:
| Type | Description |
|---|---|
List[zenml.models.v2.core.run_metadata.RunMetadataResponse] |
The created run metadata. |
Source code in zenml/zen_stores/sql_zen_store.py
def create_run_metadata(
self, run_metadata: RunMetadataRequest
) -> List[RunMetadataResponse]:
"""Creates run metadata.
Args:
run_metadata: The run metadata to create.
Returns:
The created run metadata.
"""
return_value: List[RunMetadataResponse] = []
with Session(self.engine) as session:
for key, value in run_metadata.values.items():
type_ = run_metadata.types[key]
run_metadata_schema = RunMetadataSchema(
workspace_id=run_metadata.workspace,
user_id=run_metadata.user,
resource_id=run_metadata.resource_id,
resource_type=run_metadata.resource_type.value,
stack_component_id=run_metadata.stack_component_id,
key=key,
value=json.dumps(value),
type=type_,
)
session.add(run_metadata_schema)
session.commit()
return_value.append(
run_metadata_schema.to_model(include_metadata=True)
)
return return_value
create_run_step(self, step_run)
Creates a step run.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
step_run |
StepRunRequest |
The step run to create. |
required |
Returns:
| Type | Description |
|---|---|
StepRunResponse |
The created step run. |
Exceptions:
| Type | Description |
|---|---|
EntityExistsError |
if the step run already exists. |
KeyError |
if the pipeline run doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def create_run_step(self, step_run: StepRunRequest) -> StepRunResponse:
"""Creates a step run.
Args:
step_run: The step run to create.
Returns:
The created step run.
Raises:
EntityExistsError: if the step run already exists.
KeyError: if the pipeline run doesn't exist.
"""
with Session(self.engine) as session:
# Check if the pipeline run exists
run = session.exec(
select(PipelineRunSchema).where(
PipelineRunSchema.id == step_run.pipeline_run_id
)
).first()
if run is None:
raise KeyError(
f"Unable to create step '{step_run.name}': No pipeline run "
f"with ID '{step_run.pipeline_run_id}' found."
)
# Check if the step name already exists in the pipeline run
existing_step_run = session.exec(
select(StepRunSchema)
.where(StepRunSchema.name == step_run.name)
.where(
StepRunSchema.pipeline_run_id == step_run.pipeline_run_id
)
).first()
if existing_step_run is not None:
raise EntityExistsError(
f"Unable to create step '{step_run.name}': A step with "
f"this name already exists in the pipeline run with ID "
f"'{step_run.pipeline_run_id}'."
)
# Create the step
step_schema = StepRunSchema.from_request(step_run)
session.add(step_schema)
# Add logs entry for the step if exists
if step_run.logs is not None:
log_entry = LogsSchema(
uri=step_run.logs.uri,
step_run_id=step_schema.id,
artifact_store_id=step_run.logs.artifact_store_id,
)
session.add(log_entry)
# Save parent step IDs into the database.
for parent_step_id in step_run.parent_step_ids:
self._set_run_step_parent_step(
child_id=step_schema.id,
parent_id=parent_step_id,
session=session,
)
# Save input artifact IDs into the database.
for input_name, artifact_version_id in step_run.inputs.items():
self._set_run_step_input_artifact(
run_step_id=step_schema.id,
artifact_version_id=artifact_version_id,
name=input_name,
input_type=StepRunInputArtifactType.DEFAULT,
session=session,
)
# Save output artifact IDs into the database.
for output_name, artifact_version_id in step_run.outputs.items():
self._set_run_step_output_artifact(
step_run_id=step_schema.id,
artifact_version_id=artifact_version_id,
name=output_name,
output_type=StepRunOutputArtifactType.DEFAULT,
session=session,
)
if step_run.status != ExecutionStatus.RUNNING:
self._update_pipeline_run_status(
pipeline_run_id=step_run.pipeline_run_id, session=session
)
session.commit()
return step_schema.to_model(include_metadata=True)
create_schedule(self, schedule)
Creates a new schedule.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
schedule |
ScheduleRequest |
The schedule to create. |
required |
Returns:
| Type | Description |
|---|---|
ScheduleResponse |
The newly created schedule. |
Source code in zenml/zen_stores/sql_zen_store.py
def create_schedule(self, schedule: ScheduleRequest) -> ScheduleResponse:
"""Creates a new schedule.
Args:
schedule: The schedule to create.
Returns:
The newly created schedule.
"""
with Session(self.engine) as session:
new_schedule = ScheduleSchema.from_request(schedule)
session.add(new_schedule)
session.commit()
return new_schedule.to_model(include_metadata=True)
create_secret(self, secret)
Creates a new secret.
The new secret is also validated against the scoping rules enforced in the secrets store:
- only one workspace-scoped secret with the given name can exist in the target workspace.
- only one user-scoped secret with the given name can exist in the target workspace for the target user.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret |
SecretRequest |
The secret to create. |
required |
Returns:
| Type | Description |
|---|---|
SecretResponse |
The newly created secret. |
Exceptions:
| Type | Description |
|---|---|
EntityExistsError |
If a secret with the same name already exists in the same scope. |
Source code in zenml/zen_stores/sql_zen_store.py
@track_decorator(AnalyticsEvent.CREATED_SECRET)
def create_secret(self, secret: SecretRequest) -> SecretResponse:
"""Creates a new secret.
The new secret is also validated against the scoping rules enforced in
the secrets store:
- only one workspace-scoped secret with the given name can exist
in the target workspace.
- only one user-scoped secret with the given name can exist in the
target workspace for the target user.
Args:
secret: The secret to create.
Returns:
The newly created secret.
Raises:
EntityExistsError: If a secret with the same name already exists in
the same scope.
"""
with Session(self.engine) as session:
# Check if a secret with the same name already exists in the same
# scope.
secret_exists, msg = self._check_sql_secret_scope(
session=session,
secret_name=secret.name,
scope=secret.scope,
workspace=secret.workspace,
user=secret.user,
)
if secret_exists:
raise EntityExistsError(msg)
new_secret = SecretSchema.from_request(
secret,
)
session.add(new_secret)
session.commit()
secret_model = new_secret.to_model(include_metadata=True)
try:
# Set the secret values in the configured secrets store
self._set_secret_values(
secret_id=new_secret.id, values=secret.secret_values
)
except:
# If setting the secret values fails, delete the secret from the
# database.
with Session(self.engine) as session:
session.delete(new_secret)
session.commit()
raise
secret_model.set_secrets(secret.secret_values)
return secret_model
create_service_account(self, service_account)
Creates a new service account.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account |
ServiceAccountRequest |
Service account to be created. |
required |
Returns:
| Type | Description |
|---|---|
ServiceAccountResponse |
The newly created service account. |
Exceptions:
| Type | Description |
|---|---|
EntityExistsError |
If a user or service account with the given name already exists. |
Source code in zenml/zen_stores/sql_zen_store.py
@track_decorator(AnalyticsEvent.CREATED_SERVICE_ACCOUNT)
def create_service_account(
self, service_account: ServiceAccountRequest
) -> ServiceAccountResponse:
"""Creates a new service account.
Args:
service_account: Service account to be created.
Returns:
The newly created service account.
Raises:
EntityExistsError: If a user or service account with the given name
already exists.
"""
with Session(self.engine) as session:
# Check if a service account with the given name already
# exists
err_msg = (
f"Unable to create service account with name "
f"'{service_account.name}': Found existing service "
"account with this name."
)
try:
self._get_account_schema(
service_account.name, session=session, service_account=True
)
raise EntityExistsError(err_msg)
except KeyError:
pass
# Create the service account
new_account = UserSchema.from_service_account_request(
service_account
)
session.add(new_account)
# on commit an IntegrityError may arise we let it bubble up
session.commit()
return new_account.to_service_account_model(include_metadata=True)
create_service_connector(self, service_connector)
Creates a new service connector.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_connector |
ServiceConnectorRequest |
Service connector to be created. |
required |
Returns:
| Type | Description |
|---|---|
ServiceConnectorResponse |
The newly created service connector. |
Exceptions:
| Type | Description |
|---|---|
Exception |
If anything goes wrong during the creation of the service connector. |
Source code in zenml/zen_stores/sql_zen_store.py
@track_decorator(AnalyticsEvent.CREATED_SERVICE_CONNECTOR)
def create_service_connector(
self, service_connector: ServiceConnectorRequest
) -> ServiceConnectorResponse:
"""Creates a new service connector.
Args:
service_connector: Service connector to be created.
Returns:
The newly created service connector.
Raises:
Exception: If anything goes wrong during the creation of the
service connector.
"""
# If the connector type is locally available, we validate the request
# against the connector type schema before storing it in the database
if service_connector_registry.is_registered(service_connector.type):
connector_type = (
service_connector_registry.get_service_connector_type(
service_connector.type
)
)
service_connector.validate_and_configure_resources(
connector_type=connector_type,
resource_types=service_connector.resource_types,
resource_id=service_connector.resource_id,
configuration=service_connector.configuration,
secrets=service_connector.secrets,
)
with Session(self.engine) as session:
self._fail_if_service_connector_with_name_exists(
name=service_connector.name,
workspace_id=service_connector.workspace,
session=session,
)
# Create the secret
secret_id = self._create_connector_secret(
connector_name=service_connector.name,
user=service_connector.user,
workspace=service_connector.workspace,
secrets=service_connector.secrets,
)
try:
# Create the service connector
new_service_connector = ServiceConnectorSchema.from_request(
service_connector,
secret_id=secret_id,
)
session.add(new_service_connector)
session.commit()
session.refresh(new_service_connector)
except Exception:
# Delete the secret if it was created
if secret_id:
try:
self.delete_secret(secret_id)
except Exception:
# Ignore any errors that occur while deleting the
# secret
pass
raise
connector = new_service_connector.to_model(include_metadata=True)
self._populate_connector_type(connector)
return connector
create_stack(self, stack)
Register a new stack.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
stack |
StackRequest |
The stack to register. |
required |
Returns:
| Type | Description |
|---|---|
StackResponse |
The registered stack. |
Source code in zenml/zen_stores/sql_zen_store.py
@track_decorator(AnalyticsEvent.REGISTERED_STACK)
def create_stack(self, stack: StackRequest) -> StackResponse:
"""Register a new stack.
Args:
stack: The stack to register.
Returns:
The registered stack.
"""
with Session(self.engine) as session:
self._fail_if_stack_with_name_exists(stack=stack, session=session)
# Get the Schemas of all components mentioned
component_ids = (
[
component_id
for list_of_component_ids in stack.components.values()
for component_id in list_of_component_ids
]
if stack.components is not None
else []
)
filters = [
(StackComponentSchema.id == component_id)
for component_id in component_ids
]
defined_components = session.exec(
select(StackComponentSchema).where(or_(*filters))
).all()
new_stack_schema = StackSchema(
workspace_id=stack.workspace,
user_id=stack.user,
stack_spec_path=stack.stack_spec_path,
name=stack.name,
description=stack.description,
components=defined_components,
)
session.add(new_stack_schema)
session.commit()
session.refresh(new_stack_schema)
return new_stack_schema.to_model(include_metadata=True)
create_stack_component(self, component)
Create a stack component.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
component |
ComponentRequest |
The stack component to create. |
required |
Returns:
| Type | Description |
|---|---|
ComponentResponse |
The created stack component. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the stack component references a non-existent connector. |
Source code in zenml/zen_stores/sql_zen_store.py
@track_decorator(AnalyticsEvent.REGISTERED_STACK_COMPONENT)
def create_stack_component(
self,
component: ComponentRequest,
) -> ComponentResponse:
"""Create a stack component.
Args:
component: The stack component to create.
Returns:
The created stack component.
Raises:
KeyError: if the stack component references a non-existent
connector.
"""
with Session(self.engine) as session:
self._fail_if_component_with_name_type_exists(
name=component.name,
component_type=component.type,
workspace_id=component.workspace,
session=session,
)
service_connector: Optional[ServiceConnectorSchema] = None
if component.connector:
service_connector = session.exec(
select(ServiceConnectorSchema).where(
ServiceConnectorSchema.id == component.connector
)
).first()
if service_connector is None:
raise KeyError(
f"Service connector with ID {component.connector} not "
"found."
)
# Create the component
new_component = StackComponentSchema(
name=component.name,
workspace_id=component.workspace,
user_id=component.user,
component_spec_path=component.component_spec_path,
type=component.type,
flavor=component.flavor,
configuration=base64.b64encode(
json.dumps(component.configuration).encode("utf-8")
),
labels=base64.b64encode(
json.dumps(component.labels).encode("utf-8")
),
connector=service_connector,
connector_resource_id=component.connector_resource_id,
)
session.add(new_component)
session.commit()
session.refresh(new_component)
return new_component.to_model(include_metadata=True)
create_tag(self, tag)
Creates a new tag.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
tag |
TagRequest |
the tag to be created. |
required |
Returns:
| Type | Description |
|---|---|
TagResponse |
The newly created tag. |
Exceptions:
| Type | Description |
|---|---|
EntityExistsError |
If a tag with the given name already exists. |
Source code in zenml/zen_stores/sql_zen_store.py
@track_decorator(AnalyticsEvent.CREATED_TAG)
def create_tag(self, tag: TagRequest) -> TagResponse:
"""Creates a new tag.
Args:
tag: the tag to be created.
Returns:
The newly created tag.
Raises:
EntityExistsError: If a tag with the given name already exists.
"""
with Session(self.engine) as session:
existing_tag = session.exec(
select(TagSchema).where(TagSchema.name == tag.name)
).first()
if existing_tag is not None:
raise EntityExistsError(
f"Unable to create tag {tag.name}: "
"A tag with this name already exists."
)
tag_schema = TagSchema.from_request(tag)
session.add(tag_schema)
session.commit()
return tag_schema.to_model(include_metadata=True)
create_tag_resource(self, tag_resource)
Creates a new tag resource relationship.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
tag_resource |
TagResourceRequest |
the tag resource relationship to be created. |
required |
Returns:
| Type | Description |
|---|---|
TagResourceResponse |
The newly created tag resource relationship. |
Exceptions:
| Type | Description |
|---|---|
EntityExistsError |
If a tag resource relationship with the given configuration already exists. |
Source code in zenml/zen_stores/sql_zen_store.py
def create_tag_resource(
self, tag_resource: TagResourceRequest
) -> TagResourceResponse:
"""Creates a new tag resource relationship.
Args:
tag_resource: the tag resource relationship to be created.
Returns:
The newly created tag resource relationship.
Raises:
EntityExistsError: If a tag resource relationship with the given
configuration already exists.
"""
with Session(self.engine) as session:
existing_tag_resource = session.exec(
select(TagResourceSchema).where(
TagResourceSchema.tag_id == tag_resource.tag_id,
TagResourceSchema.resource_id == tag_resource.resource_id,
TagResourceSchema.resource_type
== tag_resource.resource_type.value,
)
).first()
if existing_tag_resource is not None:
raise EntityExistsError(
f"Unable to create a tag "
f"{tag_resource.resource_type.name.lower()} "
f"relationship with IDs "
f"`{tag_resource.tag_id}`|`{tag_resource.resource_id}`. "
"This relationship already exists."
)
tag_resource_schema = TagResourceSchema.from_request(tag_resource)
session.add(tag_resource_schema)
session.commit()
return tag_resource_schema.to_model(include_metadata=True)
create_trigger(self, trigger)
Creates a new trigger.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
trigger |
TriggerRequest |
Trigger to be created. |
required |
Returns:
| Type | Description |
|---|---|
TriggerResponse |
The newly created trigger. |
Source code in zenml/zen_stores/sql_zen_store.py
@track_decorator(AnalyticsEvent.CREATED_TRIGGER)
def create_trigger(self, trigger: TriggerRequest) -> TriggerResponse:
"""Creates a new trigger.
Args:
trigger: Trigger to be created.
Returns:
The newly created trigger.
"""
with Session(self.engine) as session:
# Verify that the given event_source exists
self._get_event_source(
event_source_id=trigger.event_source_id, session=session
)
# Verify that the given service account exists
self._get_account_schema(
account_name_or_id=trigger.service_account_id,
session=session,
service_account=True,
)
# Verify that the trigger won't validate Unique
self._fail_if_trigger_with_name_exists(
trigger_name=trigger.name,
workspace_id=trigger.workspace,
session=session,
)
new_trigger = TriggerSchema.from_request(trigger)
session.add(new_trigger)
session.commit()
session.refresh(new_trigger)
return new_trigger.to_model(
include_metadata=True, include_resources=True
)
create_trigger_execution(self, trigger_execution)
Create a trigger execution.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
trigger_execution |
TriggerExecutionRequest |
The trigger execution to create. |
required |
Returns:
| Type | Description |
|---|---|
TriggerExecutionResponse |
The created trigger execution. |
Source code in zenml/zen_stores/sql_zen_store.py
def create_trigger_execution(
self, trigger_execution: TriggerExecutionRequest
) -> TriggerExecutionResponse:
"""Create a trigger execution.
Args:
trigger_execution: The trigger execution to create.
Returns:
The created trigger execution.
"""
with Session(self.engine) as session:
# TODO: Verify that the given trigger exists
new_execution = TriggerExecutionSchema.from_request(
trigger_execution
)
session.add(new_execution)
session.commit()
session.refresh(new_execution)
return new_execution.to_model(
include_metadata=True, include_resources=True
)
create_user(self, user)
Creates a new user.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
user |
UserRequest |
User to be created. |
required |
Returns:
| Type | Description |
|---|---|
UserResponse |
The newly created user. |
Exceptions:
| Type | Description |
|---|---|
EntityExistsError |
If a user or service account with the given name already exists. |
Source code in zenml/zen_stores/sql_zen_store.py
def create_user(self, user: UserRequest) -> UserResponse:
"""Creates a new user.
Args:
user: User to be created.
Returns:
The newly created user.
Raises:
EntityExistsError: If a user or service account with the given name
already exists.
"""
with Session(self.engine) as session:
# Check if a user account with the given name already exists
err_msg = (
f"Unable to create user with name '{user.name}': "
f"Found an existing user account with this name."
)
try:
self._get_account_schema(
user.name,
session=session,
# Filter out service accounts
service_account=False,
)
raise EntityExistsError(err_msg)
except KeyError:
pass
# Create the user
new_user = UserSchema.from_user_request(user)
session.add(new_user)
# on commit an IntegrityError may arise we let it bubble up
session.commit()
return new_user.to_model(include_metadata=True)
create_workspace(self, workspace)
Creates a new workspace.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
workspace |
WorkspaceRequest |
The workspace to create. |
required |
Returns:
| Type | Description |
|---|---|
WorkspaceResponse |
The newly created workspace. |
Exceptions:
| Type | Description |
|---|---|
EntityExistsError |
If a workspace with the given name already exists. |
Source code in zenml/zen_stores/sql_zen_store.py
@track_decorator(AnalyticsEvent.CREATED_WORKSPACE)
def create_workspace(
self, workspace: WorkspaceRequest
) -> WorkspaceResponse:
"""Creates a new workspace.
Args:
workspace: The workspace to create.
Returns:
The newly created workspace.
Raises:
EntityExistsError: If a workspace with the given name already exists.
"""
with Session(self.engine) as session:
# Check if workspace with the given name already exists
existing_workspace = session.exec(
select(WorkspaceSchema).where(
WorkspaceSchema.name == workspace.name
)
).first()
if existing_workspace is not None:
raise EntityExistsError(
f"Unable to create workspace {workspace.name}: "
"A workspace with this name already exists."
)
# Create the workspace
new_workspace = WorkspaceSchema.from_request(workspace)
session.add(new_workspace)
session.commit()
# Explicitly refresh the new_workspace schema
session.refresh(new_workspace)
workspace_model = new_workspace.to_model(include_metadata=True)
self._get_or_create_default_stack(workspace=workspace_model)
return workspace_model
delete_all_model_version_artifact_links(self, model_version_id, only_links=True)
Deletes all model version to artifact links.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_id |
UUID |
ID of the model version containing the link. |
required |
only_links |
bool |
Whether to only delete the link to the artifact. |
True |
Source code in zenml/zen_stores/sql_zen_store.py
def delete_all_model_version_artifact_links(
self,
model_version_id: UUID,
only_links: bool = True,
) -> None:
"""Deletes all model version to artifact links.
Args:
model_version_id: ID of the model version containing the link.
only_links: Whether to only delete the link to the artifact.
"""
with Session(self.engine) as session:
if not only_links:
artifact_version_ids = session.execute(
select(
ModelVersionArtifactSchema.artifact_version_id
).where(
ModelVersionArtifactSchema.model_version_id
== model_version_id
)
).fetchall()
session.execute(
delete(ArtifactVersionSchema).where(
col(ArtifactVersionSchema.id).in_(
[a[0] for a in artifact_version_ids]
)
),
)
session.execute(
delete(ModelVersionArtifactSchema).where(
ModelVersionArtifactSchema.model_version_id
== model_version_id
)
)
session.commit()
delete_api_key(self, service_account_id, api_key_name_or_id)
Delete an API key for a service account.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account_id |
UUID |
The ID of the service account for which to delete the API key. |
required |
api_key_name_or_id |
Union[str, uuid.UUID] |
The name or ID of the API key to delete. |
required |
Source code in zenml/zen_stores/sql_zen_store.py
def delete_api_key(
self,
service_account_id: UUID,
api_key_name_or_id: Union[str, UUID],
) -> None:
"""Delete an API key for a service account.
Args:
service_account_id: The ID of the service account for which to
delete the API key.
api_key_name_or_id: The name or ID of the API key to delete.
"""
with Session(self.engine) as session:
api_key = self._get_api_key(
service_account_id=service_account_id,
api_key_name_or_id=api_key_name_or_id,
session=session,
)
session.delete(api_key)
session.commit()
delete_artifact(self, artifact_id)
Deletes an artifact.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_id |
UUID |
The ID of the artifact to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the artifact doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def delete_artifact(self, artifact_id: UUID) -> None:
"""Deletes an artifact.
Args:
artifact_id: The ID of the artifact to delete.
Raises:
KeyError: if the artifact doesn't exist.
"""
with Session(self.engine) as session:
existing_artifact = session.exec(
select(ArtifactSchema).where(ArtifactSchema.id == artifact_id)
).first()
if not existing_artifact:
raise KeyError(f"Artifact with ID {artifact_id} not found.")
session.delete(existing_artifact)
session.commit()
delete_artifact_version(self, artifact_version_id)
Deletes an artifact version.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_version_id |
UUID |
The ID of the artifact version to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the artifact version doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def delete_artifact_version(self, artifact_version_id: UUID) -> None:
"""Deletes an artifact version.
Args:
artifact_version_id: The ID of the artifact version to delete.
Raises:
KeyError: if the artifact version doesn't exist.
"""
with Session(self.engine) as session:
artifact_version = session.exec(
select(ArtifactVersionSchema).where(
ArtifactVersionSchema.id == artifact_version_id
)
).first()
if artifact_version is None:
raise KeyError(
f"Unable to delete artifact version with ID "
f"{artifact_version_id}: No artifact version with this ID "
"found."
)
session.delete(artifact_version)
session.commit()
delete_authorized_device(self, device_id)
Deletes an OAuth 2.0 authorized device.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
device_id |
UUID |
The ID of the device to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no device with the given ID exists. |
Source code in zenml/zen_stores/sql_zen_store.py
def delete_authorized_device(self, device_id: UUID) -> None:
"""Deletes an OAuth 2.0 authorized device.
Args:
device_id: The ID of the device to delete.
Raises:
KeyError: If no device with the given ID exists.
"""
with Session(self.engine) as session:
existing_device = session.exec(
select(OAuthDeviceSchema).where(
OAuthDeviceSchema.id == device_id
)
).first()
if existing_device is None:
raise KeyError(
f"Unable to delete device with ID {device_id}: No device "
"with this ID found."
)
session.delete(existing_device)
session.commit()
delete_build(self, build_id)
Deletes a build.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
build_id |
UUID |
The ID of the build to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the build doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def delete_build(self, build_id: UUID) -> None:
"""Deletes a build.
Args:
build_id: The ID of the build to delete.
Raises:
KeyError: if the build doesn't exist.
"""
with Session(self.engine) as session:
# Check if build with the given ID exists
build = session.exec(
select(PipelineBuildSchema).where(
PipelineBuildSchema.id == build_id
)
).first()
if build is None:
raise KeyError(
f"Unable to delete build with ID {build_id}: "
f"No build with this ID found."
)
session.delete(build)
session.commit()
delete_code_repository(self, code_repository_id)
Deletes a code repository.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
code_repository_id |
UUID |
The ID of the code repository to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no code repository with the given ID exists. |
Source code in zenml/zen_stores/sql_zen_store.py
def delete_code_repository(self, code_repository_id: UUID) -> None:
"""Deletes a code repository.
Args:
code_repository_id: The ID of the code repository to delete.
Raises:
KeyError: If no code repository with the given ID exists.
"""
with Session(self.engine) as session:
existing_repo = session.exec(
select(CodeRepositorySchema).where(
CodeRepositorySchema.id == code_repository_id
)
).first()
if existing_repo is None:
raise KeyError(
f"Unable to delete code repository with ID "
f"{code_repository_id}: No code repository with this ID "
"found."
)
session.delete(existing_repo)
session.commit()
delete_deployment(self, deployment_id)
Deletes a deployment.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
deployment_id |
UUID |
The ID of the deployment to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If the deployment doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def delete_deployment(self, deployment_id: UUID) -> None:
"""Deletes a deployment.
Args:
deployment_id: The ID of the deployment to delete.
Raises:
KeyError: If the deployment doesn't exist.
"""
with Session(self.engine) as session:
# Check if build with the given ID exists
deployment = session.exec(
select(PipelineDeploymentSchema).where(
PipelineDeploymentSchema.id == deployment_id
)
).first()
if deployment is None:
raise KeyError(
f"Unable to delete deployment with ID {deployment_id}: "
f"No deployment with this ID found."
)
session.delete(deployment)
session.commit()
delete_event_source(self, event_source_id)
Delete an event_source.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
event_source_id |
UUID |
The ID of the event_source to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the event_source doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def delete_event_source(self, event_source_id: UUID) -> None:
"""Delete an event_source.
Args:
event_source_id: The ID of the event_source to delete.
Raises:
KeyError: if the event_source doesn't exist.
"""
with Session(self.engine) as session:
event_source = self._get_event_source(
event_source_id=event_source_id, session=session
)
if event_source is None:
raise KeyError(
f"Unable to delete event_source with ID `{event_source_id}`: "
f"No event_source with this ID found."
)
session.delete(event_source)
session.commit()
# TODO: catch and throw proper error if it can't be deleted due to
# not-null constraints on triggers
delete_expired_authorized_devices(self)
Deletes all expired OAuth 2.0 authorized devices.
Source code in zenml/zen_stores/sql_zen_store.py
def delete_expired_authorized_devices(self) -> None:
"""Deletes all expired OAuth 2.0 authorized devices."""
with Session(self.engine) as session:
expired_devices = session.exec(
select(OAuthDeviceSchema).where(OAuthDeviceSchema.user is None)
).all()
for device in expired_devices:
# Delete devices that have expired
if (
device.expires is not None
and device.expires < datetime.now()
and device.user_id is None
):
session.delete(device)
session.commit()
delete_flavor(self, flavor_id)
Delete a flavor.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
flavor_id |
UUID |
The id of the flavor to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the flavor doesn't exist. |
IllegalOperationError |
if the flavor is used by a stack component. |
Source code in zenml/zen_stores/sql_zen_store.py
def delete_flavor(self, flavor_id: UUID) -> None:
"""Delete a flavor.
Args:
flavor_id: The id of the flavor to delete.
Raises:
KeyError: if the flavor doesn't exist.
IllegalOperationError: if the flavor is used by a stack component.
"""
with Session(self.engine) as session:
try:
flavor_in_db = session.exec(
select(FlavorSchema).where(FlavorSchema.id == flavor_id)
).one()
if flavor_in_db is None:
raise KeyError(f"Flavor with ID {flavor_id} not found.")
components_of_flavor = session.exec(
select(StackComponentSchema).where(
StackComponentSchema.flavor == flavor_in_db.name
)
).all()
if len(components_of_flavor) > 0:
raise IllegalOperationError(
f"Stack Component `{flavor_in_db.name}` of type "
f"`{flavor_in_db.type} cannot be "
f"deleted as it is used by "
f"{len(components_of_flavor)} "
f"components. Before deleting this "
f"flavor, make sure to delete all "
f"associated components."
)
else:
session.delete(flavor_in_db)
session.commit()
except NoResultFound as error:
raise KeyError from error
delete_model(self, model_name_or_id)
Deletes a model.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_name_or_id |
Union[str, uuid.UUID] |
name or id of the model to be deleted. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
specified ID or name not found. |
Source code in zenml/zen_stores/sql_zen_store.py
def delete_model(self, model_name_or_id: Union[str, UUID]) -> None:
"""Deletes a model.
Args:
model_name_or_id: name or id of the model to be deleted.
Raises:
KeyError: specified ID or name not found.
"""
with Session(self.engine) as session:
model = self._get_model_schema(
model_name_or_id=model_name_or_id, session=session
)
if model is None:
raise KeyError(
f"Unable to delete model with ID `{model_name_or_id}`: "
f"No model with this ID found."
)
session.delete(model)
session.commit()
delete_model_version(self, model_version_id)
Deletes a model version.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_id |
UUID |
name or id of the model version to be deleted. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
specified ID or name not found. |
Source code in zenml/zen_stores/sql_zen_store.py
def delete_model_version(
self,
model_version_id: UUID,
) -> None:
"""Deletes a model version.
Args:
model_version_id: name or id of the model version to be deleted.
Raises:
KeyError: specified ID or name not found.
"""
with Session(self.engine) as session:
query = select(ModelVersionSchema).where(
ModelVersionSchema.id == model_version_id
)
model_version = session.exec(query).first()
if model_version is None:
raise KeyError(
"Unable to delete model version with id "
f"`{model_version_id}`: "
"No model version with this id found."
)
session.delete(model_version)
session.commit()
delete_model_version_artifact_link(self, model_version_id, model_version_artifact_link_name_or_id)
Deletes a model version to artifact link.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_id |
UUID |
ID of the model version containing the link. |
required |
model_version_artifact_link_name_or_id |
Union[str, uuid.UUID] |
name or ID of the model version to artifact link to be deleted. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
specified ID or name not found. |
Source code in zenml/zen_stores/sql_zen_store.py
def delete_model_version_artifact_link(
self,
model_version_id: UUID,
model_version_artifact_link_name_or_id: Union[str, UUID],
) -> None:
"""Deletes a model version to artifact link.
Args:
model_version_id: ID of the model version containing the link.
model_version_artifact_link_name_or_id: name or ID of the model
version to artifact link to be deleted.
Raises:
KeyError: specified ID or name not found.
"""
with Session(self.engine) as session:
model_version = self.get_model_version(model_version_id)
query = select(ModelVersionArtifactSchema).where(
ModelVersionArtifactSchema.model_version_id == model_version.id
)
try:
UUID(str(model_version_artifact_link_name_or_id))
query = query.where(
ModelVersionArtifactSchema.id
== model_version_artifact_link_name_or_id
)
except ValueError:
query = (
query.where(
ModelVersionArtifactSchema.artifact_version_id
== ArtifactVersionSchema.id
)
.where(
ArtifactVersionSchema.artifact_id == ArtifactSchema.id
)
.where(
ArtifactSchema.name
== model_version_artifact_link_name_or_id
)
)
model_version_artifact_link = session.exec(query).first()
if model_version_artifact_link is None:
raise KeyError(
f"Unable to delete model version link with name or ID "
f"`{model_version_artifact_link_name_or_id}`: "
f"No model version link with this name found."
)
session.delete(model_version_artifact_link)
session.commit()
delete_model_version_pipeline_run_link(self, model_version_id, model_version_pipeline_run_link_name_or_id)
Deletes a model version to pipeline run link.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_id |
UUID |
name or ID of the model version containing the link. |
required |
model_version_pipeline_run_link_name_or_id |
Union[str, uuid.UUID] |
name or ID of the model version to pipeline run link to be deleted. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
specified ID not found. |
Source code in zenml/zen_stores/sql_zen_store.py
def delete_model_version_pipeline_run_link(
self,
model_version_id: UUID,
model_version_pipeline_run_link_name_or_id: Union[str, UUID],
) -> None:
"""Deletes a model version to pipeline run link.
Args:
model_version_id: name or ID of the model version containing the
link.
model_version_pipeline_run_link_name_or_id: name or ID of the model
version to pipeline run link to be deleted.
Raises:
KeyError: specified ID not found.
"""
with Session(self.engine) as session:
model_version = self.get_model_version(
model_version_id=model_version_id
)
query = select(ModelVersionPipelineRunSchema).where(
ModelVersionPipelineRunSchema.model_version_id
== model_version.id
)
try:
UUID(str(model_version_pipeline_run_link_name_or_id))
query = query.where(
ModelVersionPipelineRunSchema.id
== model_version_pipeline_run_link_name_or_id
)
except ValueError:
query = query.where(
ModelVersionPipelineRunSchema.pipeline_run_id
== PipelineRunSchema.id
).where(
PipelineRunSchema.name
== model_version_pipeline_run_link_name_or_id
)
model_version_pipeline_run_link = session.exec(query).first()
if model_version_pipeline_run_link is None:
raise KeyError(
f"Unable to delete model version link with name "
f"`{model_version_pipeline_run_link_name_or_id}`: "
f"No model version link with this name found."
)
session.delete(model_version_pipeline_run_link)
session.commit()
delete_pipeline(self, pipeline_id)
Deletes a pipeline.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
pipeline_id |
UUID |
The ID of the pipeline to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the pipeline doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def delete_pipeline(self, pipeline_id: UUID) -> None:
"""Deletes a pipeline.
Args:
pipeline_id: The ID of the pipeline to delete.
Raises:
KeyError: if the pipeline doesn't exist.
"""
with Session(self.engine) as session:
# Check if pipeline with the given ID exists
pipeline = session.exec(
select(PipelineSchema).where(PipelineSchema.id == pipeline_id)
).first()
if pipeline is None:
raise KeyError(
f"Unable to delete pipeline with ID {pipeline_id}: "
f"No pipeline with this ID found."
)
session.delete(pipeline)
session.commit()
delete_run(self, run_id)
Deletes a pipeline run.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
run_id |
UUID |
The ID of the pipeline run to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the pipeline run doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def delete_run(self, run_id: UUID) -> None:
"""Deletes a pipeline run.
Args:
run_id: The ID of the pipeline run to delete.
Raises:
KeyError: if the pipeline run doesn't exist.
"""
with Session(self.engine) as session:
# Check if pipeline run with the given ID exists
existing_run = session.exec(
select(PipelineRunSchema).where(PipelineRunSchema.id == run_id)
).first()
if existing_run is None:
raise KeyError(
f"Unable to delete pipeline run with ID {run_id}: "
f"No pipeline run with this ID found."
)
# Delete the pipeline run
session.delete(existing_run)
session.commit()
delete_schedule(self, schedule_id)
Deletes a schedule.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
schedule_id |
UUID |
The ID of the schedule to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the schedule doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def delete_schedule(self, schedule_id: UUID) -> None:
"""Deletes a schedule.
Args:
schedule_id: The ID of the schedule to delete.
Raises:
KeyError: if the schedule doesn't exist.
"""
with Session(self.engine) as session:
# Check if schedule with the given ID exists
schedule = session.exec(
select(ScheduleSchema).where(ScheduleSchema.id == schedule_id)
).first()
if schedule is None:
raise KeyError(
f"Unable to delete schedule with ID {schedule_id}: "
f"No schedule with this ID found."
)
# Delete the schedule
session.delete(schedule)
session.commit()
delete_secret(self, secret_id)
Delete a secret.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
The id of the secret to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the secret doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def delete_secret(self, secret_id: UUID) -> None:
"""Delete a secret.
Args:
secret_id: The id of the secret to delete.
Raises:
KeyError: if the secret doesn't exist.
"""
# Delete the secret values in the configured secrets store
try:
self._delete_secret_values(secret_id=secret_id)
except KeyError:
# If the secret values don't exist in the secrets store, we don't
# need to raise an error.
pass
with Session(self.engine) as session:
try:
secret_in_db = session.exec(
select(SecretSchema).where(SecretSchema.id == secret_id)
).one()
session.delete(secret_in_db)
session.commit()
except NoResultFound:
raise KeyError(f"Secret with ID {secret_id} not found.")
delete_service_account(self, service_account_name_or_id)
Delete a service account.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account_name_or_id |
Union[str, uuid.UUID] |
The name or the ID of the service account to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
IllegalOperationError |
if the service account has already been used to create other resources. |
Source code in zenml/zen_stores/sql_zen_store.py
def delete_service_account(
self,
service_account_name_or_id: Union[str, UUID],
) -> None:
"""Delete a service account.
Args:
service_account_name_or_id: The name or the ID of the service
account to delete.
Raises:
IllegalOperationError: if the service account has already been used
to create other resources.
"""
with Session(self.engine) as session:
service_account = self._get_account_schema(
service_account_name_or_id,
session=session,
service_account=True,
)
# Check if the service account has any resources associated with it
# and raise an error if it does.
if self._account_owns_resources(service_account, session=session):
raise IllegalOperationError(
"The service account has already been used to create "
"other resources that it now owns and therefore cannot be "
"deleted. Please delete all resources owned by the service "
"account or consider deactivating it instead."
)
session.delete(service_account)
session.commit()
delete_service_connector(self, service_connector_id)
Deletes a service connector.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_connector_id |
UUID |
The ID of the service connector to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no service connector with the given ID exists. |
IllegalOperationError |
If the service connector is still referenced by one or more stack components. |
Source code in zenml/zen_stores/sql_zen_store.py
def delete_service_connector(self, service_connector_id: UUID) -> None:
"""Deletes a service connector.
Args:
service_connector_id: The ID of the service connector to delete.
Raises:
KeyError: If no service connector with the given ID exists.
IllegalOperationError: If the service connector is still referenced
by one or more stack components.
"""
with Session(self.engine) as session:
try:
service_connector = session.exec(
select(ServiceConnectorSchema).where(
ServiceConnectorSchema.id == service_connector_id
)
).one()
if service_connector is None:
raise KeyError(
f"Service connector with ID {service_connector_id} not "
"found."
)
if len(service_connector.components) > 0:
raise IllegalOperationError(
f"Service connector with ID {service_connector_id} "
f"cannot be deleted as it is still referenced by "
f"{len(service_connector.components)} "
"stack components. Before deleting this service "
"connector, make sure to remove it from all stack "
"components."
)
else:
session.delete(service_connector)
if service_connector.secret_id:
try:
self.delete_secret(service_connector.secret_id)
except KeyError:
# If the secret doesn't exist anymore, we can ignore
# this error
pass
except NoResultFound as error:
raise KeyError from error
session.commit()
delete_stack(self, stack_id)
Delete a stack.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
stack_id |
UUID |
The ID of the stack to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the stack doesn't exist. |
IllegalOperationError |
if the stack is a default stack. |
Source code in zenml/zen_stores/sql_zen_store.py
def delete_stack(self, stack_id: UUID) -> None:
"""Delete a stack.
Args:
stack_id: The ID of the stack to delete.
Raises:
KeyError: if the stack doesn't exist.
IllegalOperationError: if the stack is a default stack.
"""
with Session(self.engine) as session:
try:
stack = session.exec(
select(StackSchema).where(StackSchema.id == stack_id)
).one()
if stack is None:
raise KeyError(f"Stack with ID {stack_id} not found.")
if stack.name == DEFAULT_STACK_AND_COMPONENT_NAME:
raise IllegalOperationError(
"The default stack cannot be deleted."
)
session.delete(stack)
except NoResultFound as error:
raise KeyError from error
session.commit()
delete_stack_component(self, component_id)
Delete a stack component.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
component_id |
UUID |
The id of the stack component to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the stack component doesn't exist. |
IllegalOperationError |
if the stack component is part of one or more stacks, or if it's a default stack component. |
Source code in zenml/zen_stores/sql_zen_store.py
def delete_stack_component(self, component_id: UUID) -> None:
"""Delete a stack component.
Args:
component_id: The id of the stack component to delete.
Raises:
KeyError: if the stack component doesn't exist.
IllegalOperationError: if the stack component is part of one or
more stacks, or if it's a default stack component.
"""
with Session(self.engine) as session:
try:
stack_component = session.exec(
select(StackComponentSchema).where(
StackComponentSchema.id == component_id
)
).one()
if stack_component is None:
raise KeyError(f"Stack with ID {component_id} not found.")
if (
stack_component.name == DEFAULT_STACK_AND_COMPONENT_NAME
and stack_component.type
in [
StackComponentType.ORCHESTRATOR,
StackComponentType.ARTIFACT_STORE,
]
):
raise IllegalOperationError(
f"The default {stack_component.type} cannot be deleted."
)
if len(stack_component.stacks) > 0:
raise IllegalOperationError(
f"Stack Component `{stack_component.name}` of type "
f"`{stack_component.type} cannot be "
f"deleted as it is part of "
f"{len(stack_component.stacks)} stacks. "
f"Before deleting this stack "
f"component, make sure to remove it "
f"from all stacks."
)
else:
session.delete(stack_component)
except NoResultFound as error:
raise KeyError from error
session.commit()
delete_tag(self, tag_name_or_id)
Deletes a tag.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
tag_name_or_id |
Union[str, uuid.UUID] |
name or id of the tag to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
specified ID or name not found. |
Source code in zenml/zen_stores/sql_zen_store.py
def delete_tag(
self,
tag_name_or_id: Union[str, UUID],
) -> None:
"""Deletes a tag.
Args:
tag_name_or_id: name or id of the tag to delete.
Raises:
KeyError: specified ID or name not found.
"""
with Session(self.engine) as session:
tag = self._get_tag_schema(
tag_name_or_id=tag_name_or_id, session=session
)
if tag is None:
raise KeyError(
f"Unable to delete tag with ID `{tag_name_or_id}`: "
f"No tag with this ID found."
)
session.delete(tag)
session.commit()
delete_tag_resource(self, tag_id, resource_id, resource_type)
Deletes a tag resource relationship.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
tag_id |
UUID |
The ID of the tag to delete. |
required |
resource_id |
UUID |
The ID of the resource to delete. |
required |
resource_type |
TaggableResourceTypes |
The type of the resource to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
specified ID not found. |
Source code in zenml/zen_stores/sql_zen_store.py
def delete_tag_resource(
self,
tag_id: UUID,
resource_id: UUID,
resource_type: TaggableResourceTypes,
) -> None:
"""Deletes a tag resource relationship.
Args:
tag_id: The ID of the tag to delete.
resource_id: The ID of the resource to delete.
resource_type: The type of the resource to delete.
Raises:
KeyError: specified ID not found.
"""
with Session(self.engine) as session:
tag_model = self._get_tag_model_schema(
tag_id=tag_id,
resource_id=resource_id,
resource_type=resource_type,
session=session,
)
if tag_model is None:
raise KeyError(
f"Unable to delete tag<>resource with IDs: "
f"`tag_id`='{tag_id}' and `resource_id`='{resource_id}' "
f"and `resource_type`='{resource_type.value}': No "
"tag<>resource with these IDs found."
)
session.delete(tag_model)
session.commit()
delete_trigger(self, trigger_id)
Delete a trigger.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
trigger_id |
UUID |
The ID of the trigger to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the trigger doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def delete_trigger(self, trigger_id: UUID) -> None:
"""Delete a trigger.
Args:
trigger_id: The ID of the trigger to delete.
Raises:
KeyError: if the trigger doesn't exist.
"""
with Session(self.engine) as session:
try:
trigger = session.exec(
select(TriggerSchema).where(TriggerSchema.id == trigger_id)
).one()
if trigger is None:
raise KeyError(f"Trigger with ID {trigger_id} not found.")
session.delete(trigger)
except NoResultFound as error:
raise KeyError from error
session.commit()
delete_trigger_execution(self, trigger_execution_id)
Delete a trigger execution.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
trigger_execution_id |
UUID |
The ID of the trigger execution to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If the trigger execution doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def delete_trigger_execution(self, trigger_execution_id: UUID) -> None:
"""Delete a trigger execution.
Args:
trigger_execution_id: The ID of the trigger execution to delete.
Raises:
KeyError: If the trigger execution doesn't exist.
"""
with Session(self.engine) as session:
try:
execution = session.exec(
select(TriggerExecutionSchema).where(
TriggerExecutionSchema.id == trigger_execution_id
)
).one()
session.delete(execution)
session.commit()
except NoResultFound:
raise KeyError(
f"Execution with ID {trigger_execution_id} not found."
)
delete_user(self, user_name_or_id)
Deletes a user.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
user_name_or_id |
Union[str, uuid.UUID] |
The name or the ID of the user to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
IllegalOperationError |
If the user is the default user account or if the user already owns resources. |
Source code in zenml/zen_stores/sql_zen_store.py
def delete_user(self, user_name_or_id: Union[str, UUID]) -> None:
"""Deletes a user.
Args:
user_name_or_id: The name or the ID of the user to delete.
Raises:
IllegalOperationError: If the user is the default user account or
if the user already owns resources.
"""
with Session(self.engine) as session:
user = self._get_account_schema(
user_name_or_id, session=session, service_account=False
)
if user.name == self._default_user_name:
raise IllegalOperationError(
"The default user account cannot be deleted."
)
if self._account_owns_resources(user, session=session):
raise IllegalOperationError(
"The user account has already been used to create "
"other resources that it now owns and therefore cannot be "
"deleted. Please delete all resources owned by the user "
"account or consider deactivating it instead."
)
session.delete(user)
session.commit()
delete_workspace(self, workspace_name_or_id)
Deletes a workspace.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
workspace_name_or_id |
Union[str, uuid.UUID] |
Name or ID of the workspace to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
IllegalOperationError |
If the workspace is the default workspace. |
Source code in zenml/zen_stores/sql_zen_store.py
def delete_workspace(self, workspace_name_or_id: Union[str, UUID]) -> None:
"""Deletes a workspace.
Args:
workspace_name_or_id: Name or ID of the workspace to delete.
Raises:
IllegalOperationError: If the workspace is the default workspace.
"""
with Session(self.engine) as session:
# Check if workspace with the given name exists
workspace = self._get_workspace_schema(
workspace_name_or_id, session=session
)
if workspace.name == self._default_workspace_name:
raise IllegalOperationError(
"The default workspace cannot be deleted."
)
session.delete(workspace)
session.commit()
entity_exists(self, entity_id, schema_class)
Check whether an entity exists in the database.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
entity_id |
UUID |
The ID of the entity to check. |
required |
schema_class |
Type[~AnySchema] |
The schema class. |
required |
Returns:
| Type | Description |
|---|---|
bool |
If the entity exists. |
Source code in zenml/zen_stores/sql_zen_store.py
def entity_exists(
self, entity_id: UUID, schema_class: Type[AnySchema]
) -> bool:
"""Check whether an entity exists in the database.
Args:
entity_id: The ID of the entity to check.
schema_class: The schema class.
Returns:
If the entity exists.
"""
with Session(self.engine) as session:
schema = session.exec(
select(schema_class.id).where(schema_class.id == entity_id)
).first()
return False if schema is None else True
filter_and_paginate(session, query, table, filter_model, custom_schema_to_model_conversion=None, custom_fetch=None, hydrate=False)
classmethod
Given a query, return a Page instance with a list of filtered Models.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
session |
Session |
The SQLModel Session |
required |
query |
Union[sqlmodel.sql.expression.Select, sqlmodel.sql.expression.SelectOfScalar] |
The query to execute |
required |
table |
Type[~AnySchema] |
The table to select from |
required |
filter_model |
BaseFilter |
The filter to use, including pagination and sorting |
required |
custom_schema_to_model_conversion |
Optional[Callable[..., ~AnyResponse]] |
Callable to convert the schema into a model. This is used if the Model contains additional data that is not explicitly stored as a field or relationship on the model. |
None |
custom_fetch |
Optional[Callable[[sqlmodel.orm.session.Session, Union[sqlmodel.sql.expression.Select, sqlmodel.sql.expression.SelectOfScalar], zenml.models.v2.base.filter.BaseFilter], List[Any]]] |
Custom callable to use to fetch items from the
database for a given query. This is used if the items fetched
from the database need to be processed differently (e.g. to
perform additional filtering). The callable should take a
|
None |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[AnyResponse] |
The Domain Model representation of the DB resource |
Exceptions:
| Type | Description |
|---|---|
ValueError |
if the filtered page number is out of bounds. |
RuntimeError |
if the schema does not have a |
Source code in zenml/zen_stores/sql_zen_store.py
@classmethod
def filter_and_paginate(
cls,
session: Session,
query: Union[Select[Any], SelectOfScalar[Any]],
table: Type[AnySchema],
filter_model: BaseFilter,
custom_schema_to_model_conversion: Optional[
Callable[..., AnyResponse]
] = None,
custom_fetch: Optional[
Callable[
[
Session,
Union[Select[Any], SelectOfScalar[Any]],
BaseFilter,
],
List[Any],
]
] = None,
hydrate: bool = False,
) -> Page[AnyResponse]:
"""Given a query, return a Page instance with a list of filtered Models.
Args:
session: The SQLModel Session
query: The query to execute
table: The table to select from
filter_model: The filter to use, including pagination and sorting
custom_schema_to_model_conversion: Callable to convert the schema
into a model. This is used if the Model contains additional
data that is not explicitly stored as a field or relationship
on the model.
custom_fetch: Custom callable to use to fetch items from the
database for a given query. This is used if the items fetched
from the database need to be processed differently (e.g. to
perform additional filtering). The callable should take a
`Session`, a `Select` query and a `BaseFilterModel` filter as
arguments and return a `List` of items.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The Domain Model representation of the DB resource
Raises:
ValueError: if the filtered page number is out of bounds.
RuntimeError: if the schema does not have a `to_model` method.
"""
query = filter_model.apply_filter(query=query, table=table)
# Get the total amount of items in the database for a given query
custom_fetch_result: Optional[List[Any]] = None
if custom_fetch:
custom_fetch_result = custom_fetch(session, query, filter_model)
total = len(custom_fetch_result)
else:
total = session.scalar(
select([func.count("*")]).select_from(
query.options(noload("*")).subquery()
)
)
# Sorting
column, operand = filter_model.sorting_params
if operand == SorterOps.DESCENDING:
query = query.order_by(desc(getattr(table, column)))
else:
query = query.order_by(asc(getattr(table, column)))
# Get the total amount of pages in the database for a given query
if total == 0:
total_pages = 1
else:
total_pages = math.ceil(total / filter_model.size)
if filter_model.page > total_pages:
raise ValueError(
f"Invalid page {filter_model.page}. The requested page size is "
f"{filter_model.size} and there are a total of {total} items "
f"for this query. The maximum page value therefore is "
f"{total_pages}."
)
# Get a page of the actual data
item_schemas: List[AnySchema]
if custom_fetch:
assert custom_fetch_result is not None
item_schemas = custom_fetch_result
# select the items in the current page
item_schemas = item_schemas[
filter_model.offset : filter_model.offset + filter_model.size
]
else:
item_schemas = (
session.exec(
query.limit(filter_model.size).offset(filter_model.offset)
)
.unique()
.all()
)
# Convert this page of items from schemas to models.
items: List[AnyResponse] = []
for schema in item_schemas:
# If a custom conversion function is provided, use it.
if custom_schema_to_model_conversion:
items.append(custom_schema_to_model_conversion(schema))
continue
# Otherwise, try to use the `to_model` method of the schema.
to_model = getattr(schema, "to_model", None)
if callable(to_model):
items.append(to_model(include_metadata=hydrate))
continue
# If neither of the above work, raise an error.
raise RuntimeError(
f"Cannot convert schema `{schema.__class__.__name__}` to model "
"since it does not have a `to_model` method."
)
return Page[Any](
total=total,
total_pages=total_pages,
items=items,
index=filter_model.page,
max_size=filter_model.size,
)
get_api_key(self, service_account_id, api_key_name_or_id, hydrate=True)
Get an API key for a service account.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account_id |
UUID |
The ID of the service account for which to fetch the API key. |
required |
api_key_name_or_id |
Union[str, uuid.UUID] |
The name or ID of the API key to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
APIKeyResponse |
The API key with the given ID. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_api_key(
self,
service_account_id: UUID,
api_key_name_or_id: Union[str, UUID],
hydrate: bool = True,
) -> APIKeyResponse:
"""Get an API key for a service account.
Args:
service_account_id: The ID of the service account for which to fetch
the API key.
api_key_name_or_id: The name or ID of the API key to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The API key with the given ID.
"""
with Session(self.engine) as session:
api_key = self._get_api_key(
service_account_id=service_account_id,
api_key_name_or_id=api_key_name_or_id,
session=session,
)
return api_key.to_model(include_metadata=hydrate)
get_artifact(self, artifact_id, hydrate=True)
Gets an artifact.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_id |
UUID |
The ID of the artifact to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
ArtifactResponse |
The artifact. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the artifact doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_artifact(
self, artifact_id: UUID, hydrate: bool = True
) -> ArtifactResponse:
"""Gets an artifact.
Args:
artifact_id: The ID of the artifact to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The artifact.
Raises:
KeyError: if the artifact doesn't exist.
"""
with Session(self.engine) as session:
artifact = session.exec(
select(ArtifactSchema).where(ArtifactSchema.id == artifact_id)
).first()
if artifact is None:
raise KeyError(
f"Unable to get artifact with ID {artifact_id}: No "
"artifact with this ID found."
)
return artifact.to_model(include_metadata=hydrate)
get_artifact_version(self, artifact_version_id, hydrate=True)
Gets an artifact version.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_version_id |
UUID |
The ID of the artifact version to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
ArtifactVersionResponse |
The artifact version. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the artifact version doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_artifact_version(
self, artifact_version_id: UUID, hydrate: bool = True
) -> ArtifactVersionResponse:
"""Gets an artifact version.
Args:
artifact_version_id: The ID of the artifact version to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The artifact version.
Raises:
KeyError: if the artifact version doesn't exist.
"""
with Session(self.engine) as session:
artifact_version = session.exec(
select(ArtifactVersionSchema).where(
ArtifactVersionSchema.id == artifact_version_id
)
).first()
if artifact_version is None:
raise KeyError(
f"Unable to get artifact version with ID "
f"{artifact_version_id}: No artifact version with this ID "
f"found."
)
return artifact_version.to_model(include_metadata=hydrate)
get_artifact_visualization(self, artifact_visualization_id, hydrate=True)
Gets an artifact visualization.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_visualization_id |
UUID |
The ID of the artifact visualization to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
ArtifactVisualizationResponse |
The artifact visualization. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the code reference doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_artifact_visualization(
self, artifact_visualization_id: UUID, hydrate: bool = True
) -> ArtifactVisualizationResponse:
"""Gets an artifact visualization.
Args:
artifact_visualization_id: The ID of the artifact visualization to
get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The artifact visualization.
Raises:
KeyError: if the code reference doesn't exist.
"""
with Session(self.engine) as session:
artifact_visualization = session.exec(
select(ArtifactVisualizationSchema).where(
ArtifactVisualizationSchema.id == artifact_visualization_id
)
).first()
if artifact_visualization is None:
raise KeyError(
f"Unable to get artifact visualization with ID "
f"{artifact_visualization_id}: "
f"No artifact visualization with this ID found."
)
return artifact_visualization.to_model(include_metadata=hydrate)
get_auth_user(self, user_name_or_id)
Gets the auth model to a specific user.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
user_name_or_id |
Union[str, uuid.UUID] |
The name or ID of the user to get. |
required |
Returns:
| Type | Description |
|---|---|
UserAuthModel |
The requested user, if it was found. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_auth_user(
self, user_name_or_id: Union[str, UUID]
) -> UserAuthModel:
"""Gets the auth model to a specific user.
Args:
user_name_or_id: The name or ID of the user to get.
Returns:
The requested user, if it was found.
"""
with Session(self.engine) as session:
user = self._get_account_schema(
user_name_or_id, session=session, service_account=False
)
return UserAuthModel(
id=user.id,
name=user.name,
full_name=user.full_name,
email_opted_in=user.email_opted_in,
active=user.active,
created=user.created,
updated=user.updated,
password=user.password,
activation_token=user.activation_token,
is_service_account=False,
)
get_authorized_device(self, device_id, hydrate=True)
Gets a specific OAuth 2.0 authorized device.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
device_id |
UUID |
The ID of the device to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
OAuthDeviceResponse |
The requested device, if it was found. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no device with the given ID exists. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_authorized_device(
self, device_id: UUID, hydrate: bool = True
) -> OAuthDeviceResponse:
"""Gets a specific OAuth 2.0 authorized device.
Args:
device_id: The ID of the device to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested device, if it was found.
Raises:
KeyError: If no device with the given ID exists.
"""
with Session(self.engine) as session:
device = session.exec(
select(OAuthDeviceSchema).where(
OAuthDeviceSchema.id == device_id
)
).first()
if device is None:
raise KeyError(
f"Unable to get device with ID {device_id}: No device with "
"this ID found."
)
return device.to_model(include_metadata=hydrate)
get_build(self, build_id, hydrate=True)
Get a build with a given ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
build_id |
UUID |
ID of the build. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
PipelineBuildResponse |
The build. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If the build does not exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_build(
self, build_id: UUID, hydrate: bool = True
) -> PipelineBuildResponse:
"""Get a build with a given ID.
Args:
build_id: ID of the build.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The build.
Raises:
KeyError: If the build does not exist.
"""
with Session(self.engine) as session:
# Check if build with the given ID exists
build = session.exec(
select(PipelineBuildSchema).where(
PipelineBuildSchema.id == build_id
)
).first()
if build is None:
raise KeyError(
f"Unable to get build with ID '{build_id}': "
"No build with this ID found."
)
return build.to_model(include_metadata=hydrate)
get_code_reference(self, code_reference_id, hydrate=True)
Gets a code reference.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
code_reference_id |
UUID |
The ID of the code reference to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
CodeReferenceResponse |
The code reference. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the code reference doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_code_reference(
self, code_reference_id: UUID, hydrate: bool = True
) -> CodeReferenceResponse:
"""Gets a code reference.
Args:
code_reference_id: The ID of the code reference to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The code reference.
Raises:
KeyError: if the code reference doesn't exist.
"""
with Session(self.engine) as session:
code_reference = session.exec(
select(CodeReferenceSchema).where(
CodeRepositorySchema.id == code_reference_id
)
).first()
if code_reference is None:
raise KeyError(
f"Unable to get code reference with ID "
f"{code_reference_id}: "
f"No code reference with this ID found."
)
return code_reference.to_model(include_metadata=hydrate)
get_code_repository(self, code_repository_id, hydrate=True)
Gets a specific code repository.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
code_repository_id |
UUID |
The ID of the code repository to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
CodeRepositoryResponse |
The requested code repository, if it was found. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no code repository with the given ID exists. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_code_repository(
self, code_repository_id: UUID, hydrate: bool = True
) -> CodeRepositoryResponse:
"""Gets a specific code repository.
Args:
code_repository_id: The ID of the code repository to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested code repository, if it was found.
Raises:
KeyError: If no code repository with the given ID exists.
"""
with Session(self.engine) as session:
repo = session.exec(
select(CodeRepositorySchema).where(
CodeRepositorySchema.id == code_repository_id
)
).first()
if repo is None:
raise KeyError(
f"Unable to get code repository with ID "
f"'{code_repository_id}': No code repository with this "
"ID found."
)
return repo.to_model(include_metadata=hydrate)
get_deployment(self, deployment_id, hydrate=True)
Get a deployment with a given ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
deployment_id |
UUID |
ID of the deployment. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
PipelineDeploymentResponse |
The deployment. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If the deployment does not exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_deployment(
self, deployment_id: UUID, hydrate: bool = True
) -> PipelineDeploymentResponse:
"""Get a deployment with a given ID.
Args:
deployment_id: ID of the deployment.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The deployment.
Raises:
KeyError: If the deployment does not exist.
"""
with Session(self.engine) as session:
# Check if deployment with the given ID exists
deployment = session.exec(
select(PipelineDeploymentSchema).where(
PipelineDeploymentSchema.id == deployment_id
)
).first()
if deployment is None:
raise KeyError(
f"Unable to get deployment with ID '{deployment_id}': "
"No deployment with this ID found."
)
return deployment.to_model(include_metadata=hydrate)
get_deployment_id(self)
Get the ID of the deployment.
Returns:
| Type | Description |
|---|---|
UUID |
The ID of the deployment. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If the deployment ID could not be loaded from the database. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_deployment_id(self) -> UUID:
"""Get the ID of the deployment.
Returns:
The ID of the deployment.
Raises:
KeyError: If the deployment ID could not be loaded from the
database.
"""
# Fetch the deployment ID from the database
with Session(self.engine) as session:
identity = session.exec(select(IdentitySchema)).first()
if identity is None:
raise KeyError(
"The deployment ID could not be loaded from the database."
)
return identity.id
get_entity_by_id(self, entity_id, schema_class)
Get an entity by ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
entity_id |
UUID |
The ID of the entity to get. |
required |
schema_class |
Type[~AnySchema] |
The schema class. |
required |
Exceptions:
| Type | Description |
|---|---|
RuntimeError |
If the schema to model conversion failed. |
Returns:
| Type | Description |
|---|---|
Optional[~AnyIdentifiedResponse] |
The entity if it exists, None otherwise |
Source code in zenml/zen_stores/sql_zen_store.py
def get_entity_by_id(
self, entity_id: UUID, schema_class: Type[AnySchema]
) -> Optional[AnyIdentifiedResponse]:
"""Get an entity by ID.
Args:
entity_id: The ID of the entity to get.
schema_class: The schema class.
Raises:
RuntimeError: If the schema to model conversion failed.
Returns:
The entity if it exists, None otherwise
"""
with Session(self.engine) as session:
schema = session.exec(
select(schema_class).where(schema_class.id == entity_id)
).first()
if not schema:
return None
to_model = getattr(schema, "to_model", None)
if callable(to_model):
return cast(AnyIdentifiedResponse, to_model(hydrate=True))
else:
raise RuntimeError("Unable to convert schema to model.")
get_event_source(self, event_source_id, hydrate=True)
Get an event_source by ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
event_source_id |
UUID |
The ID of the event_source to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
EventSourceResponse |
The event_source. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_event_source(
self,
event_source_id: UUID,
hydrate: bool = True,
) -> EventSourceResponse:
"""Get an event_source by ID.
Args:
event_source_id: The ID of the event_source to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The event_source.
"""
with Session(self.engine) as session:
return self._get_event_source(
event_source_id=event_source_id, session=session
).to_model(include_metadata=hydrate, include_resources=True)
get_flavor(self, flavor_id, hydrate=True)
Get a flavor by ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
flavor_id |
UUID |
The ID of the flavor to fetch. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
FlavorResponse |
The stack component flavor. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the stack component flavor doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_flavor(
self, flavor_id: UUID, hydrate: bool = True
) -> FlavorResponse:
"""Get a flavor by ID.
Args:
flavor_id: The ID of the flavor to fetch.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The stack component flavor.
Raises:
KeyError: if the stack component flavor doesn't exist.
"""
with Session(self.engine) as session:
flavor_in_db = session.exec(
select(FlavorSchema).where(FlavorSchema.id == flavor_id)
).first()
if flavor_in_db is None:
raise KeyError(f"Flavor with ID {flavor_id} not found.")
return flavor_in_db.to_model(include_metadata=hydrate)
get_internal_api_key(self, api_key_id, hydrate=True)
Get internal details for an API key by its unique ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
api_key_id |
UUID |
The ID of the API key to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
APIKeyInternalResponse |
The internal details for the API key with the given ID. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the API key doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_internal_api_key(
self, api_key_id: UUID, hydrate: bool = True
) -> APIKeyInternalResponse:
"""Get internal details for an API key by its unique ID.
Args:
api_key_id: The ID of the API key to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The internal details for the API key with the given ID.
Raises:
KeyError: if the API key doesn't exist.
"""
with Session(self.engine) as session:
api_key = session.exec(
select(APIKeySchema).where(APIKeySchema.id == api_key_id)
).first()
if api_key is None:
raise KeyError(f"API key with ID {api_key_id} not found.")
return api_key.to_internal_model(hydrate=hydrate)
get_internal_authorized_device(self, device_id=None, client_id=None, hydrate=True)
Gets a specific OAuth 2.0 authorized device for internal use.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
client_id |
Optional[uuid.UUID] |
The client ID of the device to get. |
None |
device_id |
Optional[uuid.UUID] |
The ID of the device to get. |
None |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
OAuthDeviceInternalResponse |
The requested device, if it was found. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no device with the given client ID exists. |
ValueError |
If neither device ID nor client ID are provided. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_internal_authorized_device(
self,
device_id: Optional[UUID] = None,
client_id: Optional[UUID] = None,
hydrate: bool = True,
) -> OAuthDeviceInternalResponse:
"""Gets a specific OAuth 2.0 authorized device for internal use.
Args:
client_id: The client ID of the device to get.
device_id: The ID of the device to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested device, if it was found.
Raises:
KeyError: If no device with the given client ID exists.
ValueError: If neither device ID nor client ID are provided.
"""
with Session(self.engine) as session:
if device_id is not None:
device = session.exec(
select(OAuthDeviceSchema).where(
OAuthDeviceSchema.id == device_id
)
).first()
elif client_id is not None:
device = session.exec(
select(OAuthDeviceSchema).where(
OAuthDeviceSchema.client_id == client_id
)
).first()
else:
raise ValueError(
"Either device ID or client ID must be provided."
)
if device is None:
raise KeyError(
f"Unable to get device with client ID {client_id}: No "
"device with this client ID found."
)
return device.to_internal_model(hydrate=hydrate)
get_logs(self, logs_id, hydrate=True)
Gets logs with the given ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
logs_id |
UUID |
The ID of the logs to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
LogsResponse |
The logs. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the logs doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_logs(self, logs_id: UUID, hydrate: bool = True) -> LogsResponse:
"""Gets logs with the given ID.
Args:
logs_id: The ID of the logs to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The logs.
Raises:
KeyError: if the logs doesn't exist.
"""
with Session(self.engine) as session:
logs = session.exec(
select(LogsSchema).where(LogsSchema.id == logs_id)
).first()
if logs is None:
raise KeyError(
f"Unable to get logs with ID "
f"{logs_id}: "
f"No logs with this ID found."
)
return logs.to_model(include_metadata=hydrate)
get_model(self, model_name_or_id, hydrate=True)
Get an existing model.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_name_or_id |
Union[str, uuid.UUID] |
name or id of the model to be retrieved. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Exceptions:
| Type | Description |
|---|---|
KeyError |
specified ID or name not found. |
Returns:
| Type | Description |
|---|---|
ModelResponse |
The model of interest. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_model(
self,
model_name_or_id: Union[str, UUID],
hydrate: bool = True,
) -> ModelResponse:
"""Get an existing model.
Args:
model_name_or_id: name or id of the model to be retrieved.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Raises:
KeyError: specified ID or name not found.
Returns:
The model of interest.
"""
with Session(self.engine) as session:
model = self._get_model_schema(
model_name_or_id=model_name_or_id, session=session
)
if model is None:
raise KeyError(
f"Unable to get model with ID `{model_name_or_id}`: "
f"No model with this ID found."
)
return model.to_model(include_metadata=hydrate)
get_model_version(self, model_version_id, hydrate=True)
Get an existing model version.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_id |
UUID |
name, id, stage or number of the model version to be retrieved. If skipped - latest is retrieved. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
ModelVersionResponse |
The model version of interest. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
specified ID or name not found. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_model_version(
self, model_version_id: UUID, hydrate: bool = True
) -> ModelVersionResponse:
"""Get an existing model version.
Args:
model_version_id: name, id, stage or number of the model version to
be retrieved. If skipped - latest is retrieved.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The model version of interest.
Raises:
KeyError: specified ID or name not found.
"""
with Session(self.engine) as session:
model_version = self._get_schema_by_name_or_id(
object_name_or_id=model_version_id,
schema_class=ModelVersionSchema,
schema_name="model_version",
session=session,
)
if model_version is None:
raise KeyError(
f"Unable to get model version with ID "
f"`{model_version_id}`: No model version with this "
f"ID found."
)
return model_version.to_model(include_metadata=hydrate)
get_or_create_run(self, pipeline_run)
Gets or creates a pipeline run.
If a run with the same ID or name already exists, it is returned. Otherwise, a new run is created.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
pipeline_run |
PipelineRunRequest |
The pipeline run to get or create. |
required |
noqa: DAR401
Exceptions:
| Type | Description |
|---|---|
ValueError |
If the request does not contain an orchestrator run ID. |
EntityExistsError |
If a run with the same name already exists. |
RuntimeError |
If the run fetching failed unexpectedly. |
Returns:
| Type | Description |
|---|---|
Tuple[zenml.models.v2.core.pipeline_run.PipelineRunResponse, bool] |
The pipeline run, and a boolean indicating whether the run was created or not. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_or_create_run(
self, pipeline_run: PipelineRunRequest
) -> Tuple[PipelineRunResponse, bool]:
"""Gets or creates a pipeline run.
If a run with the same ID or name already exists, it is returned.
Otherwise, a new run is created.
Args:
pipeline_run: The pipeline run to get or create.
# noqa: DAR401
Raises:
ValueError: If the request does not contain an orchestrator run ID.
EntityExistsError: If a run with the same name already exists.
RuntimeError: If the run fetching failed unexpectedly.
Returns:
The pipeline run, and a boolean indicating whether the run was
created or not.
"""
if not pipeline_run.orchestrator_run_id:
raise ValueError(
"Unable to get or create run for request with missing "
"orchestrator run ID."
)
try:
return (
self._replace_placeholder_run(pipeline_run=pipeline_run),
True,
)
except KeyError:
# We were not able to find/replace a placeholder run. This could be
# due to one of the following three reasons:
# (1) There never was a placeholder run for the deployment. This is
# the case if the user ran the pipeline on a schedule.
# (2) There was a placeholder run, but a previous pipeline run
# already used it. This is the case if users rerun a pipeline
# run e.g. from the orchestrator UI, as they will use the same
# deployment_id with a new orchestrator_run_id.
# (3) A step of the same pipeline run already replaced the
# placeholder run.
pass
try:
# We now try to create a new run. The following will happen in the
# three cases described above:
# (1) The behavior depends on whether we're the first step of the
# pipeline run that's trying to create the run. If yes, the
# `self.create_run(...)` will succeed. If no, a run with the
# same deployment_id and orchestrator_run_id already exists and
# the `self.create_run(...)` call will fail due to the unique
# constraint on those columns.
# (2) Same as (1).
# (3) A step of the same pipeline run replaced the placeholder
# run, which now contains the deployment_id and
# orchestrator_run_id of the run that we're trying to create.
# -> The `self.create_run(...) call will fail due to the unique
# constraint on those columns.
return self.create_run(pipeline_run), True
except (EntityExistsError, IntegrityError) as create_error:
# Creating the run failed with an
# - IntegrityError: This happens when we violated a unique
# constraint, which in turn means a run with the same
# deployment_id and orchestrator_run_id exists. We now fetch and
# return that run.
# - EntityExistsError: This happens when a run with the same name
# already exists. This could be either a different run (in which
# case we want to fail) or a run created by a step of the same
# pipeline run (in which case we want to return it).
# Note: The IntegrityError might also be raised when other unique
# constraints get violated. The only other such constraint is the
# primary key constraint on the run ID, which means we randomly
# generated an existing UUID. In this case the call below will fail,
# but the chance of that happening is so low we don't handle it.
try:
return (
self._get_run_by_orchestrator_run_id(
orchestrator_run_id=pipeline_run.orchestrator_run_id,
deployment_id=pipeline_run.deployment,
),
False,
)
except KeyError:
if isinstance(create_error, EntityExistsError):
# There was a run with the same name which does not share
# the deployment_id and orchestrator_run_id -> We fail with
# the error that run names must be unique.
raise create_error from None
# This should never happen as the run creation failed with an
# IntegrityError which means a run with the deployment_id and
# orchestrator_run_id exists.
raise RuntimeError(
f"Failed to get or create run: {create_error}"
)
get_pipeline(self, pipeline_id, hydrate=True)
Get a pipeline with a given ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
pipeline_id |
UUID |
ID of the pipeline. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
PipelineResponse |
The pipeline. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the pipeline does not exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_pipeline(
self, pipeline_id: UUID, hydrate: bool = True
) -> PipelineResponse:
"""Get a pipeline with a given ID.
Args:
pipeline_id: ID of the pipeline.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The pipeline.
Raises:
KeyError: if the pipeline does not exist.
"""
with Session(self.engine) as session:
# Check if pipeline with the given ID exists
pipeline = session.exec(
select(PipelineSchema).where(PipelineSchema.id == pipeline_id)
).first()
if pipeline is None:
raise KeyError(
f"Unable to get pipeline with ID '{pipeline_id}': "
"No pipeline with this ID found."
)
return pipeline.to_model(include_metadata=hydrate)
get_run(self, run_name_or_id, hydrate=True)
Gets a pipeline run.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
run_name_or_id |
Union[str, uuid.UUID] |
The name or ID of the pipeline run to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
PipelineRunResponse |
The pipeline run. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_run(
self, run_name_or_id: Union[str, UUID], hydrate: bool = True
) -> PipelineRunResponse:
"""Gets a pipeline run.
Args:
run_name_or_id: The name or ID of the pipeline run to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The pipeline run.
"""
with Session(self.engine) as session:
return self._get_run_schema(
run_name_or_id, session=session
).to_model(include_metadata=hydrate)
get_run_metadata(self, run_metadata_id, hydrate=True)
Gets run metadata with the given ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
run_metadata_id |
UUID |
The ID of the run metadata to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
RunMetadataResponse |
The run metadata. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the run metadata doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_run_metadata(
self, run_metadata_id: UUID, hydrate: bool = True
) -> RunMetadataResponse:
"""Gets run metadata with the given ID.
Args:
run_metadata_id: The ID of the run metadata to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The run metadata.
Raises:
KeyError: if the run metadata doesn't exist.
"""
with Session(self.engine) as session:
run_metadata = session.exec(
select(RunMetadataSchema).where(
RunMetadataSchema.id == run_metadata_id
)
).first()
if run_metadata is None:
raise KeyError(
f"Unable to get run metadata with ID "
f"{run_metadata_id}: "
f"No run metadata with this ID found."
)
return run_metadata.to_model(include_metadata=hydrate)
get_run_step(self, step_run_id, hydrate=True)
Get a step run by ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
step_run_id |
UUID |
The ID of the step run to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
StepRunResponse |
The step run. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the step run doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_run_step(
self, step_run_id: UUID, hydrate: bool = True
) -> StepRunResponse:
"""Get a step run by ID.
Args:
step_run_id: The ID of the step run to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The step run.
Raises:
KeyError: if the step run doesn't exist.
"""
with Session(self.engine) as session:
step_run = session.exec(
select(StepRunSchema).where(StepRunSchema.id == step_run_id)
).first()
if step_run is None:
raise KeyError(
f"Unable to get step run with ID {step_run_id}: No step "
"run with this ID found."
)
return step_run.to_model(include_metadata=hydrate)
get_schedule(self, schedule_id, hydrate=True)
Get a schedule with a given ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
schedule_id |
UUID |
ID of the schedule. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
ScheduleResponse |
The schedule. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the schedule does not exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_schedule(
self, schedule_id: UUID, hydrate: bool = True
) -> ScheduleResponse:
"""Get a schedule with a given ID.
Args:
schedule_id: ID of the schedule.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The schedule.
Raises:
KeyError: if the schedule does not exist.
"""
with Session(self.engine) as session:
# Check if schedule with the given ID exists
schedule = session.exec(
select(ScheduleSchema).where(ScheduleSchema.id == schedule_id)
).first()
if schedule is None:
raise KeyError(
f"Unable to get schedule with ID '{schedule_id}': "
"No schedule with this ID found."
)
return schedule.to_model(include_metadata=hydrate)
get_secret(self, secret_id, hydrate=True)
Get a secret by ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
The ID of the secret to fetch. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
SecretResponse |
The secret. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the secret doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_secret(
self, secret_id: UUID, hydrate: bool = True
) -> SecretResponse:
"""Get a secret by ID.
Args:
secret_id: The ID of the secret to fetch.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The secret.
Raises:
KeyError: if the secret doesn't exist.
"""
with Session(self.engine) as session:
secret_in_db = session.exec(
select(SecretSchema).where(SecretSchema.id == secret_id)
).first()
if secret_in_db is None:
raise KeyError(f"Secret with ID {secret_id} not found.")
secret_model = secret_in_db.to_model(include_metadata=hydrate)
secret_model.set_secrets(self._get_secret_values(secret_id=secret_id))
return secret_model
get_service_account(self, service_account_name_or_id, hydrate=True)
Gets a specific service account.
Raises a KeyError in case a service account with that id does not exist.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account_name_or_id |
Union[str, uuid.UUID] |
The name or ID of the service account to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
ServiceAccountResponse |
The requested service account, if it was found. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_service_account(
self,
service_account_name_or_id: Union[str, UUID],
hydrate: bool = True,
) -> ServiceAccountResponse:
"""Gets a specific service account.
Raises a KeyError in case a service account with that id does not exist.
Args:
service_account_name_or_id: The name or ID of the service account to
get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested service account, if it was found.
"""
with Session(self.engine) as session:
account = self._get_account_schema(
service_account_name_or_id,
session=session,
service_account=True,
)
return account.to_service_account_model(include_metadata=hydrate)
get_service_connector(self, service_connector_id, hydrate=True)
Gets a specific service connector.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_connector_id |
UUID |
The ID of the service connector to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
ServiceConnectorResponse |
The requested service connector, if it was found. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no service connector with the given ID exists. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_service_connector(
self, service_connector_id: UUID, hydrate: bool = True
) -> ServiceConnectorResponse:
"""Gets a specific service connector.
Args:
service_connector_id: The ID of the service connector to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested service connector, if it was found.
Raises:
KeyError: If no service connector with the given ID exists.
"""
with Session(self.engine) as session:
service_connector = session.exec(
select(ServiceConnectorSchema).where(
ServiceConnectorSchema.id == service_connector_id
)
).first()
if service_connector is None:
raise KeyError(
f"Service connector with ID {service_connector_id} not "
"found."
)
connector = service_connector.to_model(include_metadata=hydrate)
self._populate_connector_type(connector)
return connector
get_service_connector_client(self, service_connector_id, resource_type=None, resource_id=None)
Get a service connector client for a service connector and given resource.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_connector_id |
UUID |
The ID of the base service connector to use. |
required |
resource_type |
Optional[str] |
The type of resource to get a client for. |
None |
resource_id |
Optional[str] |
The ID of the resource to get a client for. |
None |
Returns:
| Type | Description |
|---|---|
ServiceConnectorResponse |
A service connector client that can be used to access the given resource. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_service_connector_client(
self,
service_connector_id: UUID,
resource_type: Optional[str] = None,
resource_id: Optional[str] = None,
) -> ServiceConnectorResponse:
"""Get a service connector client for a service connector and given resource.
Args:
service_connector_id: The ID of the base service connector to use.
resource_type: The type of resource to get a client for.
resource_id: The ID of the resource to get a client for.
Returns:
A service connector client that can be used to access the given
resource.
"""
connector = self.get_service_connector(service_connector_id)
connector_instance = service_connector_registry.instantiate_connector(
model=connector
)
# Fetch the connector client
connector_client = connector_instance.get_connector_client(
resource_type=resource_type,
resource_id=resource_id,
)
# Return the model for the connector client
connector = connector_client.to_response_model(
user=connector.user,
workspace=connector.workspace,
description=connector.description,
labels=connector.labels,
)
self._populate_connector_type(connector)
return connector
get_service_connector_type(self, connector_type)
Returns the requested service connector type.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
connector_type |
str |
the service connector type identifier. |
required |
Returns:
| Type | Description |
|---|---|
ServiceConnectorTypeModel |
The requested service connector type. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_service_connector_type(
self,
connector_type: str,
) -> ServiceConnectorTypeModel:
"""Returns the requested service connector type.
Args:
connector_type: the service connector type identifier.
Returns:
The requested service connector type.
"""
return service_connector_registry.get_service_connector_type(
connector_type
)
get_stack(self, stack_id, hydrate=True)
Get a stack by its unique ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
stack_id |
UUID |
The ID of the stack to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
StackResponse |
The stack with the given ID. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the stack doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_stack(self, stack_id: UUID, hydrate: bool = True) -> StackResponse:
"""Get a stack by its unique ID.
Args:
stack_id: The ID of the stack to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The stack with the given ID.
Raises:
KeyError: if the stack doesn't exist.
"""
with Session(self.engine) as session:
stack = session.exec(
select(StackSchema).where(StackSchema.id == stack_id)
).first()
if stack is None:
raise KeyError(f"Stack with ID {stack_id} not found.")
return stack.to_model(include_metadata=hydrate)
get_stack_component(self, component_id, hydrate=True)
Get a stack component by ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
component_id |
UUID |
The ID of the stack component to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
ComponentResponse |
The stack component. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the stack component doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_stack_component(
self, component_id: UUID, hydrate: bool = True
) -> ComponentResponse:
"""Get a stack component by ID.
Args:
component_id: The ID of the stack component to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The stack component.
Raises:
KeyError: if the stack component doesn't exist.
"""
with Session(self.engine) as session:
stack_component = session.exec(
select(StackComponentSchema).where(
StackComponentSchema.id == component_id
)
).first()
if stack_component is None:
raise KeyError(
f"Stack component with ID {component_id} not found."
)
return stack_component.to_model(include_metadata=hydrate)
get_store_info(self)
Get information about the store.
Returns:
| Type | Description |
|---|---|
ServerModel |
Information about the store. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_store_info(self) -> ServerModel:
"""Get information about the store.
Returns:
Information about the store.
"""
model = super().get_store_info()
sql_url = make_url(self.config.url)
model.database_type = ServerDatabaseType(sql_url.drivername)
# Fetch the deployment ID from the database and use it to replace
# the one fetched from the global configuration
model.id = self.get_deployment_id()
return model
get_tag(self, tag_name_or_id, hydrate=True)
Get an existing tag.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
tag_name_or_id |
Union[str, uuid.UUID] |
name or id of the tag to be retrieved. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
TagResponse |
The tag of interest. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
specified ID or name not found. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_tag(
self, tag_name_or_id: Union[str, UUID], hydrate: bool = True
) -> TagResponse:
"""Get an existing tag.
Args:
tag_name_or_id: name or id of the tag to be retrieved.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The tag of interest.
Raises:
KeyError: specified ID or name not found.
"""
with Session(self.engine) as session:
tag = self._get_tag_schema(
tag_name_or_id=tag_name_or_id, session=session
)
if tag is None:
raise KeyError(
f"Unable to get tag with ID `{tag_name_or_id}`: "
f"No tag with this ID found."
)
return tag.to_model(include_metadata=hydrate)
get_trigger(self, trigger_id, hydrate=True)
Get a trigger by its unique ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
trigger_id |
UUID |
The ID of the trigger to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
TriggerResponse |
The trigger with the given ID. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the trigger doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_trigger(
self, trigger_id: UUID, hydrate: bool = True
) -> TriggerResponse:
"""Get a trigger by its unique ID.
Args:
trigger_id: The ID of the trigger to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The trigger with the given ID.
Raises:
KeyError: if the trigger doesn't exist.
"""
with Session(self.engine) as session:
trigger = session.exec(
select(TriggerSchema).where(TriggerSchema.id == trigger_id)
).first()
if trigger is None:
raise KeyError(f"Trigger with ID {trigger_id} not found.")
return trigger.to_model(
include_metadata=hydrate, include_resources=hydrate
)
get_trigger_execution(self, trigger_execution_id, hydrate=True)
Get an trigger execution by ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
trigger_execution_id |
UUID |
The ID of the trigger execution to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
TriggerExecutionResponse |
The trigger execution. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If the trigger execution doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_trigger_execution(
self,
trigger_execution_id: UUID,
hydrate: bool = True,
) -> TriggerExecutionResponse:
"""Get an trigger execution by ID.
Args:
trigger_execution_id: The ID of the trigger execution to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The trigger execution.
Raises:
KeyError: If the trigger execution doesn't exist.
"""
with Session(self.engine) as session:
execution = session.exec(
select(TriggerExecutionSchema).where(
TriggerExecutionSchema.id == trigger_execution_id
)
).first()
if execution is None:
raise KeyError(
f"Trigger execution with ID {trigger_execution_id} not found."
)
return execution.to_model(
include_metadata=hydrate, include_resources=True
)
get_user(self, user_name_or_id=None, include_private=False, hydrate=True)
Gets a specific user, when no id is specified the active user is returned.
noqa: DAR401
noqa: DAR402
Raises a KeyError in case a user with that name or id does not exist.
For backwards-compatibility reasons, this method can also be called to fetch service accounts by their ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
user_name_or_id |
Union[str, uuid.UUID] |
The name or ID of the user to get. |
None |
include_private |
bool |
Whether to include private user information |
False |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
UserResponse |
The requested user, if it was found. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If the user does not exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_user(
self,
user_name_or_id: Optional[Union[str, UUID]] = None,
include_private: bool = False,
hydrate: bool = True,
) -> UserResponse:
"""Gets a specific user, when no id is specified the active user is returned.
# noqa: DAR401
# noqa: DAR402
Raises a KeyError in case a user with that name or id does not exist.
For backwards-compatibility reasons, this method can also be called
to fetch service accounts by their ID.
Args:
user_name_or_id: The name or ID of the user to get.
include_private: Whether to include private user information
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested user, if it was found.
Raises:
KeyError: If the user does not exist.
"""
if not user_name_or_id:
user_name_or_id = self._default_user_name
with Session(self.engine) as session:
# If a UUID is passed, we also allow fetching service accounts
# with that ID.
service_account: Optional[bool] = False
if uuid_utils.is_valid_uuid(user_name_or_id):
service_account = None
user = self._get_account_schema(
user_name_or_id,
session=session,
service_account=service_account,
)
return user.to_model(
include_private=include_private, include_metadata=hydrate
)
get_workspace(self, workspace_name_or_id, hydrate=True)
Get an existing workspace by name or ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
workspace_name_or_id |
Union[str, uuid.UUID] |
Name or ID of the workspace to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
WorkspaceResponse |
The requested workspace if one was found. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_workspace(
self, workspace_name_or_id: Union[str, UUID], hydrate: bool = True
) -> WorkspaceResponse:
"""Get an existing workspace by name or ID.
Args:
workspace_name_or_id: Name or ID of the workspace to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested workspace if one was found.
"""
with Session(self.engine) as session:
workspace = self._get_workspace_schema(
workspace_name_or_id, session=session
)
return workspace.to_model(include_metadata=hydrate)
list_api_keys(self, service_account_id, filter_model, hydrate=False)
List all API keys for a service account matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account_id |
UUID |
The ID of the service account for which to list the API keys. |
required |
filter_model |
APIKeyFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[APIKeyResponse] |
A list of all API keys matching the filter criteria. |
Source code in zenml/zen_stores/sql_zen_store.py
def list_api_keys(
self,
service_account_id: UUID,
filter_model: APIKeyFilter,
hydrate: bool = False,
) -> Page[APIKeyResponse]:
"""List all API keys for a service account matching the given filter criteria.
Args:
service_account_id: The ID of the service account for which to list
the API keys.
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all API keys matching the filter criteria.
"""
with Session(self.engine) as session:
# Fetch the service account
service_account = self._get_account_schema(
service_account_id, session=session, service_account=True
)
filter_model.set_service_account(service_account.id)
query = select(APIKeySchema)
return self.filter_and_paginate(
session=session,
query=query,
table=APIKeySchema,
filter_model=filter_model,
hydrate=hydrate,
)
list_artifact_versions(self, artifact_version_filter_model, hydrate=False)
List all artifact versions matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_version_filter_model |
ArtifactVersionFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[ArtifactVersionResponse] |
A list of all artifact versions matching the filter criteria. |
Source code in zenml/zen_stores/sql_zen_store.py
def list_artifact_versions(
self,
artifact_version_filter_model: ArtifactVersionFilter,
hydrate: bool = False,
) -> Page[ArtifactVersionResponse]:
"""List all artifact versions matching the given filter criteria.
Args:
artifact_version_filter_model: All filter parameters including
pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all artifact versions matching the filter criteria.
"""
with Session(self.engine) as session:
query = select(ArtifactVersionSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=ArtifactVersionSchema,
filter_model=artifact_version_filter_model,
hydrate=hydrate,
)
list_artifacts(self, filter_model, hydrate=False)
List all artifacts matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
filter_model |
ArtifactFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[ArtifactResponse] |
A list of all artifacts matching the filter criteria. |
Source code in zenml/zen_stores/sql_zen_store.py
def list_artifacts(
self, filter_model: ArtifactFilter, hydrate: bool = False
) -> Page[ArtifactResponse]:
"""List all artifacts matching the given filter criteria.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all artifacts matching the filter criteria.
"""
with Session(self.engine) as session:
query = select(ArtifactSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=ArtifactSchema,
filter_model=filter_model,
hydrate=hydrate,
)
list_authorized_devices(self, filter_model, hydrate=False)
List all OAuth 2.0 authorized devices for a user.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
filter_model |
OAuthDeviceFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[OAuthDeviceResponse] |
A page of all matching OAuth 2.0 authorized devices. |
Source code in zenml/zen_stores/sql_zen_store.py
def list_authorized_devices(
self,
filter_model: OAuthDeviceFilter,
hydrate: bool = False,
) -> Page[OAuthDeviceResponse]:
"""List all OAuth 2.0 authorized devices for a user.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all matching OAuth 2.0 authorized devices.
"""
with Session(self.engine) as session:
query = select(OAuthDeviceSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=OAuthDeviceSchema,
filter_model=filter_model,
hydrate=hydrate,
)
list_builds(self, build_filter_model, hydrate=False)
List all builds matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
build_filter_model |
PipelineBuildFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[PipelineBuildResponse] |
A page of all builds matching the filter criteria. |
Source code in zenml/zen_stores/sql_zen_store.py
def list_builds(
self,
build_filter_model: PipelineBuildFilter,
hydrate: bool = False,
) -> Page[PipelineBuildResponse]:
"""List all builds matching the given filter criteria.
Args:
build_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all builds matching the filter criteria.
"""
with Session(self.engine) as session:
query = select(PipelineBuildSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=PipelineBuildSchema,
filter_model=build_filter_model,
hydrate=hydrate,
)
list_code_repositories(self, filter_model, hydrate=False)
List all code repositories.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
filter_model |
CodeRepositoryFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[CodeRepositoryResponse] |
A page of all code repositories. |
Source code in zenml/zen_stores/sql_zen_store.py
def list_code_repositories(
self,
filter_model: CodeRepositoryFilter,
hydrate: bool = False,
) -> Page[CodeRepositoryResponse]:
"""List all code repositories.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all code repositories.
"""
with Session(self.engine) as session:
query = select(CodeRepositorySchema)
return self.filter_and_paginate(
session=session,
query=query,
table=CodeRepositorySchema,
filter_model=filter_model,
hydrate=hydrate,
)
list_deployments(self, deployment_filter_model, hydrate=False)
List all deployments matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
deployment_filter_model |
PipelineDeploymentFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[PipelineDeploymentResponse] |
A page of all deployments matching the filter criteria. |
Source code in zenml/zen_stores/sql_zen_store.py
def list_deployments(
self,
deployment_filter_model: PipelineDeploymentFilter,
hydrate: bool = False,
) -> Page[PipelineDeploymentResponse]:
"""List all deployments matching the given filter criteria.
Args:
deployment_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all deployments matching the filter criteria.
"""
with Session(self.engine) as session:
query = select(PipelineDeploymentSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=PipelineDeploymentSchema,
filter_model=deployment_filter_model,
hydrate=hydrate,
)
list_event_sources(self, event_source_filter_model, hydrate=False)
List all event_sources matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
event_source_filter_model |
EventSourceFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[EventSourceResponse] |
A list of all event_sources matching the filter criteria. |
Source code in zenml/zen_stores/sql_zen_store.py
def list_event_sources(
self,
event_source_filter_model: EventSourceFilter,
hydrate: bool = False,
) -> Page[EventSourceResponse]:
"""List all event_sources matching the given filter criteria.
Args:
event_source_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all event_sources matching the filter criteria.
"""
with Session(self.engine) as session:
query = select(EventSourceSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=EventSourceSchema,
filter_model=event_source_filter_model,
hydrate=hydrate,
)
list_flavors(self, flavor_filter_model, hydrate=False)
List all stack component flavors matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
flavor_filter_model |
FlavorFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[FlavorResponse] |
List of all the stack component flavors matching the given criteria. |
Source code in zenml/zen_stores/sql_zen_store.py
def list_flavors(
self,
flavor_filter_model: FlavorFilter,
hydrate: bool = False,
) -> Page[FlavorResponse]:
"""List all stack component flavors matching the given filter criteria.
Args:
flavor_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
List of all the stack component flavors matching the given criteria.
"""
with Session(self.engine) as session:
query = select(FlavorSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=FlavorSchema,
filter_model=flavor_filter_model,
hydrate=hydrate,
)
list_model_version_artifact_links(self, model_version_artifact_link_filter_model, hydrate=False)
Get all model version to artifact links by filter.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_artifact_link_filter_model |
ModelVersionArtifactFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[ModelVersionArtifactResponse] |
A page of all model version to artifact links. |
Source code in zenml/zen_stores/sql_zen_store.py
def list_model_version_artifact_links(
self,
model_version_artifact_link_filter_model: ModelVersionArtifactFilter,
hydrate: bool = False,
) -> Page[ModelVersionArtifactResponse]:
"""Get all model version to artifact links by filter.
Args:
model_version_artifact_link_filter_model: All filter parameters
including pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all model version to artifact links.
"""
with Session(self.engine) as session:
query = select(ModelVersionArtifactSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=ModelVersionArtifactSchema,
filter_model=model_version_artifact_link_filter_model,
hydrate=hydrate,
)
list_model_version_pipeline_run_links(self, model_version_pipeline_run_link_filter_model, hydrate=False)
Get all model version to pipeline run links by filter.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_pipeline_run_link_filter_model |
ModelVersionPipelineRunFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[ModelVersionPipelineRunResponse] |
A page of all model version to pipeline run links. |
Source code in zenml/zen_stores/sql_zen_store.py
def list_model_version_pipeline_run_links(
self,
model_version_pipeline_run_link_filter_model: ModelVersionPipelineRunFilter,
hydrate: bool = False,
) -> Page[ModelVersionPipelineRunResponse]:
"""Get all model version to pipeline run links by filter.
Args:
model_version_pipeline_run_link_filter_model: All filter parameters
including pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all model version to pipeline run links.
"""
query = select(ModelVersionPipelineRunSchema)
with Session(self.engine) as session:
return self.filter_and_paginate(
session=session,
query=query,
table=ModelVersionPipelineRunSchema,
filter_model=model_version_pipeline_run_link_filter_model,
hydrate=hydrate,
)
list_model_versions(self, model_version_filter_model, model_name_or_id=None, hydrate=False)
Get all model versions by filter.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_name_or_id |
Union[str, uuid.UUID] |
name or id of the model containing the model versions. |
None |
model_version_filter_model |
ModelVersionFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[ModelVersionResponse] |
A page of all model versions. |
Source code in zenml/zen_stores/sql_zen_store.py
def list_model_versions(
self,
model_version_filter_model: ModelVersionFilter,
model_name_or_id: Optional[Union[str, UUID]] = None,
hydrate: bool = False,
) -> Page[ModelVersionResponse]:
"""Get all model versions by filter.
Args:
model_name_or_id: name or id of the model containing the model
versions.
model_version_filter_model: All filter parameters including
pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all model versions.
"""
with Session(self.engine) as session:
if model_name_or_id:
model = self.get_model(model_name_or_id)
model_version_filter_model.set_scope_model(model.id)
query = select(ModelVersionSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=ModelVersionSchema,
filter_model=model_version_filter_model,
hydrate=hydrate,
)
list_models(self, model_filter_model, hydrate=False)
Get all models by filter.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_filter_model |
ModelFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[ModelResponse] |
A page of all models. |
Source code in zenml/zen_stores/sql_zen_store.py
def list_models(
self,
model_filter_model: ModelFilter,
hydrate: bool = False,
) -> Page[ModelResponse]:
"""Get all models by filter.
Args:
model_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all models.
"""
with Session(self.engine) as session:
query = select(ModelSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=ModelSchema,
filter_model=model_filter_model,
hydrate=hydrate,
)
list_pipeline_namespaces(self, filter_model, hydrate=False)
List all pipeline namespaces matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
filter_model |
PipelineNamespaceFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[PipelineNamespaceResponse] |
A list of all pipeline namespaces matching the filter criteria. |
Source code in zenml/zen_stores/sql_zen_store.py
def list_pipeline_namespaces(
self,
filter_model: PipelineNamespaceFilter,
hydrate: bool = False,
) -> Page[PipelineNamespaceResponse]:
"""List all pipeline namespaces matching the given filter criteria.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all pipeline namespaces matching the filter criteria.
"""
def _custom_conversion(
row: Tuple[str, UUID, str],
) -> PipelineNamespaceResponse:
name, latest_run_id, latest_run_status = row
body = PipelineNamespaceResponseBody(
latest_run_id=latest_run_id,
latest_run_status=latest_run_status,
)
return PipelineNamespaceResponse(name=name, body=body)
def _custom_fetch(
session: Session,
query: Union[Select[Any], SelectOfScalar[Any]],
filter: BaseFilter,
) -> List[Any]:
return session.exec(query).unique().all()
with Session(self.engine) as session:
max_date_subquery = (
select( # type: ignore[call-overload]
PipelineSchema.name,
func.max(PipelineRunSchema.created).label("max_created"),
)
.outerjoin(
PipelineRunSchema,
PipelineSchema.id == PipelineRunSchema.pipeline_id,
)
.group_by(PipelineSchema.name)
.subquery()
)
query = (
select(
max_date_subquery.c.name,
PipelineRunSchema.id,
PipelineRunSchema.status,
)
.outerjoin(
PipelineSchema,
PipelineSchema.name == max_date_subquery.c.name,
)
.outerjoin(
PipelineRunSchema,
PipelineRunSchema.created
== max_date_subquery.c.max_created,
)
)
return self.filter_and_paginate(
session=session,
query=query,
table=PipelineSchema,
filter_model=filter_model,
hydrate=hydrate,
custom_fetch=_custom_fetch,
custom_schema_to_model_conversion=_custom_conversion,
)
list_pipelines(self, pipeline_filter_model, hydrate=False)
List all pipelines matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
pipeline_filter_model |
PipelineFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[PipelineResponse] |
A list of all pipelines matching the filter criteria. |
Source code in zenml/zen_stores/sql_zen_store.py
def list_pipelines(
self,
pipeline_filter_model: PipelineFilter,
hydrate: bool = False,
) -> Page[PipelineResponse]:
"""List all pipelines matching the given filter criteria.
Args:
pipeline_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all pipelines matching the filter criteria.
"""
with Session(self.engine) as session:
query = select(PipelineSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=PipelineSchema,
filter_model=pipeline_filter_model,
hydrate=hydrate,
)
list_run_metadata(self, run_metadata_filter_model, hydrate=False)
List run metadata.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
run_metadata_filter_model |
RunMetadataFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[RunMetadataResponse] |
The run metadata. |
Source code in zenml/zen_stores/sql_zen_store.py
def list_run_metadata(
self,
run_metadata_filter_model: RunMetadataFilter,
hydrate: bool = False,
) -> Page[RunMetadataResponse]:
"""List run metadata.
Args:
run_metadata_filter_model: All filter parameters including
pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The run metadata.
"""
with Session(self.engine) as session:
query = select(RunMetadataSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=RunMetadataSchema,
filter_model=run_metadata_filter_model,
hydrate=hydrate,
)
list_run_steps(self, step_run_filter_model, hydrate=False)
List all step runs matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
step_run_filter_model |
StepRunFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[StepRunResponse] |
A list of all step runs matching the filter criteria. |
Source code in zenml/zen_stores/sql_zen_store.py
def list_run_steps(
self,
step_run_filter_model: StepRunFilter,
hydrate: bool = False,
) -> Page[StepRunResponse]:
"""List all step runs matching the given filter criteria.
Args:
step_run_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all step runs matching the filter criteria.
"""
with Session(self.engine) as session:
query = select(StepRunSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=StepRunSchema,
filter_model=step_run_filter_model,
hydrate=hydrate,
)
list_runs(self, runs_filter_model, hydrate=False)
List all pipeline runs matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
runs_filter_model |
PipelineRunFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[PipelineRunResponse] |
A list of all pipeline runs matching the filter criteria. |
Source code in zenml/zen_stores/sql_zen_store.py
def list_runs(
self,
runs_filter_model: PipelineRunFilter,
hydrate: bool = False,
) -> Page[PipelineRunResponse]:
"""List all pipeline runs matching the given filter criteria.
Args:
runs_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all pipeline runs matching the filter criteria.
"""
with Session(self.engine) as session:
query = select(PipelineRunSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=PipelineRunSchema,
filter_model=runs_filter_model,
hydrate=hydrate,
)
list_schedules(self, schedule_filter_model, hydrate=False)
List all schedules in the workspace.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
schedule_filter_model |
ScheduleFilter |
All filter parameters including pagination params |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[ScheduleResponse] |
A list of schedules. |
Source code in zenml/zen_stores/sql_zen_store.py
def list_schedules(
self,
schedule_filter_model: ScheduleFilter,
hydrate: bool = False,
) -> Page[ScheduleResponse]:
"""List all schedules in the workspace.
Args:
schedule_filter_model: All filter parameters including pagination
params
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of schedules.
"""
with Session(self.engine) as session:
query = select(ScheduleSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=ScheduleSchema,
filter_model=schedule_filter_model,
hydrate=hydrate,
)
list_secrets(self, secret_filter_model, hydrate=False)
List all secrets matching the given filter criteria.
Note that returned secrets do not include any secret values. To fetch
the secret values, use get_secret.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_filter_model |
SecretFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[SecretResponse] |
A list of all secrets matching the filter criteria, with pagination
information and sorted according to the filter criteria. The
returned secrets do not include any secret values, only metadata. To
fetch the secret values, use |
Source code in zenml/zen_stores/sql_zen_store.py
def list_secrets(
self, secret_filter_model: SecretFilter, hydrate: bool = False
) -> Page[SecretResponse]:
"""List all secrets matching the given filter criteria.
Note that returned secrets do not include any secret values. To fetch
the secret values, use `get_secret`.
Args:
secret_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all secrets matching the filter criteria, with pagination
information and sorted according to the filter criteria. The
returned secrets do not include any secret values, only metadata. To
fetch the secret values, use `get_secret` individually with each
secret.
"""
with Session(self.engine) as session:
query = select(SecretSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=SecretSchema,
filter_model=secret_filter_model,
hydrate=hydrate,
)
list_service_accounts(self, filter_model, hydrate=False)
List all service accounts.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
filter_model |
ServiceAccountFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[ServiceAccountResponse] |
A list of filtered service accounts. |
Source code in zenml/zen_stores/sql_zen_store.py
def list_service_accounts(
self,
filter_model: ServiceAccountFilter,
hydrate: bool = False,
) -> Page[ServiceAccountResponse]:
"""List all service accounts.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of filtered service accounts.
"""
with Session(self.engine) as session:
query = select(UserSchema)
paged_service_accounts: Page[ServiceAccountResponse] = (
self.filter_and_paginate(
session=session,
query=query,
table=UserSchema,
filter_model=filter_model,
custom_schema_to_model_conversion=lambda user: user.to_service_account_model(
include_metadata=hydrate
),
hydrate=hydrate,
)
)
return paged_service_accounts
list_service_connector_resources(self, workspace_name_or_id, connector_type=None, resource_type=None, resource_id=None, filter_model=None)
List resources that can be accessed by service connectors.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
workspace_name_or_id |
Union[str, uuid.UUID] |
The name or ID of the workspace to scope to. |
required |
connector_type |
Optional[str] |
The type of service connector to scope to. |
None |
resource_type |
Optional[str] |
The type of resource to scope to. |
None |
resource_id |
Optional[str] |
The ID of the resource to scope to. |
None |
filter_model |
Optional[zenml.models.v2.core.service_connector.ServiceConnectorFilter] |
Optional filter model to use when fetching service connectors. |
None |
Returns:
| Type | Description |
|---|---|
List[zenml.models.v2.misc.service_connector_type.ServiceConnectorResourcesModel] |
The matching list of resources that available service connectors have access to. |
Source code in zenml/zen_stores/sql_zen_store.py
def list_service_connector_resources(
self,
workspace_name_or_id: Union[str, UUID],
connector_type: Optional[str] = None,
resource_type: Optional[str] = None,
resource_id: Optional[str] = None,
filter_model: Optional[ServiceConnectorFilter] = None,
) -> List[ServiceConnectorResourcesModel]:
"""List resources that can be accessed by service connectors.
Args:
workspace_name_or_id: The name or ID of the workspace to scope to.
connector_type: The type of service connector to scope to.
resource_type: The type of resource to scope to.
resource_id: The ID of the resource to scope to.
filter_model: Optional filter model to use when fetching service
connectors.
Returns:
The matching list of resources that available service
connectors have access to.
"""
workspace = self.get_workspace(workspace_name_or_id)
if not filter_model:
filter_model = ServiceConnectorFilter(
connector_type=connector_type,
resource_type=resource_type,
workspace_id=workspace.id,
)
service_connectors = self.list_service_connectors(
filter_model=filter_model
).items
resource_list: List[ServiceConnectorResourcesModel] = []
for connector in service_connectors:
if not service_connector_registry.is_registered(connector.type):
# For connectors that we can instantiate, i.e. those that have a
# connector type available locally, we return complete
# information about the resources that they have access to.
#
# For those that are not locally available, we only return
# rudimentary information extracted from the connector model
# without actively trying to discover the resources that they
# have access to.
if resource_id and connector.resource_id != resource_id:
# If an explicit resource ID is required, the connector
# has to be configured with it.
continue
resources = (
ServiceConnectorResourcesModel.from_connector_model(
connector,
resource_type=resource_type,
)
)
for r in resources.resources:
if not r.resource_ids:
r.error = (
f"The service '{connector.type}' connector type is "
"not available."
)
else:
try:
connector_instance = (
service_connector_registry.instantiate_connector(
model=connector
)
)
resources = connector_instance.verify(
resource_type=resource_type,
resource_id=resource_id,
list_resources=True,
)
except (ValueError, AuthorizationException) as e:
error = (
f'Failed to fetch {resource_type or "available"} '
f"resources from service connector {connector.name}/"
f"{connector.id}: {e}"
)
# Log an exception if debug logging is enabled
if logger.isEnabledFor(logging.DEBUG):
logger.exception(error)
else:
logger.error(error)
continue
resource_list.append(resources)
return resource_list
list_service_connector_types(self, connector_type=None, resource_type=None, auth_method=None)
Get a list of service connector types.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
connector_type |
Optional[str] |
Filter by connector type. |
None |
resource_type |
Optional[str] |
Filter by resource type. |
None |
auth_method |
Optional[str] |
Filter by authentication method. |
None |
Returns:
| Type | Description |
|---|---|
List[zenml.models.v2.misc.service_connector_type.ServiceConnectorTypeModel] |
List of service connector types. |
Source code in zenml/zen_stores/sql_zen_store.py
def list_service_connector_types(
self,
connector_type: Optional[str] = None,
resource_type: Optional[str] = None,
auth_method: Optional[str] = None,
) -> List[ServiceConnectorTypeModel]:
"""Get a list of service connector types.
Args:
connector_type: Filter by connector type.
resource_type: Filter by resource type.
auth_method: Filter by authentication method.
Returns:
List of service connector types.
"""
return service_connector_registry.list_service_connector_types(
connector_type=connector_type,
resource_type=resource_type,
auth_method=auth_method,
)
list_service_connectors(self, filter_model, hydrate=False)
List all service connectors.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
filter_model |
ServiceConnectorFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[ServiceConnectorResponse] |
A page of all service connectors. |
Source code in zenml/zen_stores/sql_zen_store.py
def list_service_connectors(
self,
filter_model: ServiceConnectorFilter,
hydrate: bool = False,
) -> Page[ServiceConnectorResponse]:
"""List all service connectors.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all service connectors.
"""
def fetch_connectors(
session: Session,
query: Union[
Select[ServiceConnectorSchema],
SelectOfScalar[ServiceConnectorSchema],
],
filter_model: BaseFilter,
) -> List[ServiceConnectorSchema]:
"""Custom fetch function for connector filtering and pagination.
Applies resource type and label filters to the query.
Args:
session: The database session.
query: The query to filter.
filter_model: The filter model.
Returns:
The filtered and paginated results.
"""
assert isinstance(filter_model, ServiceConnectorFilter)
items = self._list_filtered_service_connectors(
session=session, query=query, filter_model=filter_model
)
return items
with Session(self.engine) as session:
query = select(ServiceConnectorSchema)
paged_connectors: Page[ServiceConnectorResponse] = (
self.filter_and_paginate(
session=session,
query=query,
table=ServiceConnectorSchema,
filter_model=filter_model,
custom_fetch=fetch_connectors,
hydrate=hydrate,
)
)
self._populate_connector_type(*paged_connectors.items)
return paged_connectors
list_stack_components(self, component_filter_model, hydrate=False)
List all stack components matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
component_filter_model |
ComponentFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[ComponentResponse] |
A list of all stack components matching the filter criteria. |
Source code in zenml/zen_stores/sql_zen_store.py
def list_stack_components(
self,
component_filter_model: ComponentFilter,
hydrate: bool = False,
) -> Page[ComponentResponse]:
"""List all stack components matching the given filter criteria.
Args:
component_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all stack components matching the filter criteria.
"""
with Session(self.engine) as session:
query = select(StackComponentSchema)
paged_components: Page[ComponentResponse] = (
self.filter_and_paginate(
session=session,
query=query,
table=StackComponentSchema,
filter_model=component_filter_model,
hydrate=hydrate,
)
)
return paged_components
list_stacks(self, stack_filter_model, hydrate=False)
List all stacks matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
stack_filter_model |
StackFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[StackResponse] |
A list of all stacks matching the filter criteria. |
Source code in zenml/zen_stores/sql_zen_store.py
def list_stacks(
self,
stack_filter_model: StackFilter,
hydrate: bool = False,
) -> Page[StackResponse]:
"""List all stacks matching the given filter criteria.
Args:
stack_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all stacks matching the filter criteria.
"""
with Session(self.engine) as session:
query = select(StackSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=StackSchema,
filter_model=stack_filter_model,
hydrate=hydrate,
)
list_tags(self, tag_filter_model, hydrate=False)
Get all tags by filter.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
tag_filter_model |
TagFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[TagResponse] |
A page of all tags. |
Source code in zenml/zen_stores/sql_zen_store.py
def list_tags(
self,
tag_filter_model: TagFilter,
hydrate: bool = False,
) -> Page[TagResponse]:
"""Get all tags by filter.
Args:
tag_filter_model: All filter parameters including pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all tags.
"""
with Session(self.engine) as session:
query = select(TagSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=TagSchema,
filter_model=tag_filter_model,
hydrate=hydrate,
)
list_trigger_executions(self, trigger_execution_filter_model, hydrate=False)
List all trigger executions matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
trigger_execution_filter_model |
TriggerExecutionFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[TriggerExecutionResponse] |
A list of all trigger executions matching the filter criteria. |
Source code in zenml/zen_stores/sql_zen_store.py
def list_trigger_executions(
self,
trigger_execution_filter_model: TriggerExecutionFilter,
hydrate: bool = False,
) -> Page[TriggerExecutionResponse]:
"""List all trigger executions matching the given filter criteria.
Args:
trigger_execution_filter_model: All filter parameters including
pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all trigger executions matching the filter criteria.
"""
with Session(self.engine) as session:
query = select(TriggerExecutionSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=TriggerExecutionSchema,
filter_model=trigger_execution_filter_model,
hydrate=hydrate,
)
list_triggers(self, trigger_filter_model, hydrate=False)
List all trigger matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
trigger_filter_model |
TriggerFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[TriggerResponse] |
A list of all triggers matching the filter criteria. |
Source code in zenml/zen_stores/sql_zen_store.py
def list_triggers(
self,
trigger_filter_model: TriggerFilter,
hydrate: bool = False,
) -> Page[TriggerResponse]:
"""List all trigger matching the given filter criteria.
Args:
trigger_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all triggers matching the filter criteria.
"""
with Session(self.engine) as session:
query = select(TriggerSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=TriggerSchema,
filter_model=trigger_filter_model,
hydrate=hydrate,
)
list_users(self, user_filter_model, hydrate=False)
List all users.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
user_filter_model |
UserFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[UserResponse] |
A list of all users. |
Source code in zenml/zen_stores/sql_zen_store.py
def list_users(
self,
user_filter_model: UserFilter,
hydrate: bool = False,
) -> Page[UserResponse]:
"""List all users.
Args:
user_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all users.
"""
with Session(self.engine) as session:
query = select(UserSchema)
paged_user: Page[UserResponse] = self.filter_and_paginate(
session=session,
query=query,
table=UserSchema,
filter_model=user_filter_model,
hydrate=hydrate,
)
return paged_user
list_workspaces(self, workspace_filter_model, hydrate=False)
List all workspace matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
workspace_filter_model |
WorkspaceFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[WorkspaceResponse] |
A list of all workspace matching the filter criteria. |
Source code in zenml/zen_stores/sql_zen_store.py
def list_workspaces(
self,
workspace_filter_model: WorkspaceFilter,
hydrate: bool = False,
) -> Page[WorkspaceResponse]:
"""List all workspace matching the given filter criteria.
Args:
workspace_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all workspace matching the filter criteria.
"""
with Session(self.engine) as session:
query = select(WorkspaceSchema)
return self.filter_and_paginate(
session=session,
query=query,
table=WorkspaceSchema,
filter_model=workspace_filter_model,
hydrate=hydrate,
)
migrate_database(self)
Migrate the database to the head as defined by the python package.
Exceptions:
| Type | Description |
|---|---|
RuntimeError |
If the database exists and is not empty but has never been migrated with alembic before. |
Source code in zenml/zen_stores/sql_zen_store.py
def migrate_database(self) -> None:
"""Migrate the database to the head as defined by the python package.
Raises:
RuntimeError: If the database exists and is not empty but has never
been migrated with alembic before.
"""
alembic_logger = logging.getLogger("alembic")
# remove all existing handlers
while len(alembic_logger.handlers):
alembic_logger.removeHandler(alembic_logger.handlers[0])
logging_level = get_logging_level()
# suppress alembic info logging if the zenml logging level is not debug
if logging_level == LoggingLevels.DEBUG:
alembic_logger.setLevel(logging.DEBUG)
else:
alembic_logger.setLevel(logging.WARNING)
alembic_logger.addHandler(get_console_handler())
# We need to account for 3 distinct cases here:
# 1. the database is completely empty (not initialized)
# 2. the database is not empty and has been migrated with alembic before
# 3. the database is not empty, but has never been migrated with alembic
# before (i.e. was created with SQLModel back when alembic wasn't
# used). We don't support this direct upgrade case anymore.
current_revisions = self.alembic.current_revisions()
head_revisions = self.alembic.head_revisions()
if len(current_revisions) >= 1:
# Case 2: the database has been migrated with alembic before. Just
# upgrade to the latest revision.
if len(current_revisions) > 1:
logger.warning(
"The ZenML database has more than one migration head "
"revision. This is not expected and might indicate a "
"database migration problem. Please raise an issue on "
"GitHub if you encounter this."
)
logger.debug("Current revisions: %s", current_revisions)
logger.debug("Head revisions: %s", head_revisions)
# If the current revision and head revision don't match, a database
# migration that changes the database structure or contents may
# actually be performed, in which case we enable the backup
# functionality. We only enable the backup functionality if the
# database will actually be changed, to avoid the overhead for
# unnecessary backups.
backup_enabled = (
self.config.backup_strategy != DatabaseBackupStrategy.DISABLED
and set(current_revisions) != set(head_revisions)
)
backup_location: Optional[Any] = None
backup_location_msg: Optional[str] = None
if backup_enabled:
try:
logger.info("Backing up the database before migration.")
(
backup_location_msg,
backup_location,
) = self.backup_database(overwrite=True)
except Exception as e:
raise RuntimeError(
f"Failed to backup the database: {str(e)}. "
"Please check the logs for more details."
"If you would like to disable the database backup "
"functionality, set the `backup_strategy` attribute "
"of the store configuration to `disabled`."
) from e
else:
if backup_location is not None:
logger.info(
"Database successfully backed up to "
f"{backup_location_msg}. If something goes wrong "
"with the upgrade, ZenML will attempt to restore "
"the database from this backup automatically."
)
try:
self.alembic.upgrade()
except Exception as e:
if backup_enabled and backup_location:
logger.exception(
"Failed to migrate the database. Attempting to restore "
f"the database from {backup_location_msg}."
)
try:
self.restore_database(location=backup_location)
except Exception:
logger.exception(
"Failed to restore the database from "
f"{backup_location_msg}. Please "
"check the logs for more details. You might need "
"to restore the database manually."
)
else:
raise RuntimeError(
"The database migration failed, but the database "
"was successfully restored from the backup. "
"You can safely retry the upgrade or revert to "
"the previous version of ZenML. Please check the "
"logs for more details."
) from e
raise RuntimeError(
f"The database migration failed: {str(e)}"
) from e
else:
# We always remove the backup after a successful upgrade,
# not just to avoid cluttering the disk, but also to avoid
# reusing an outdated database from the backup in case of
# future upgrade failures.
try:
self.cleanup_database_backup()
except Exception:
logger.exception("Failed to cleanup the database backup.")
elif self.alembic.db_is_empty():
# Case 1: the database is empty. We can just create the
# tables from scratch with from SQLModel. After tables are
# created we put an alembic revision to latest and populate
# identity table with needed info.
logger.info("Creating database tables")
with self.engine.begin() as conn:
conn.run_callable(
SQLModel.metadata.create_all # type: ignore[arg-type]
)
with Session(self.engine) as session:
session.add(
IdentitySchema(
id=str(GlobalConfiguration().user_id).replace("-", "")
)
)
session.commit()
self.alembic.stamp("head")
else:
# Case 3: the database is not empty, but has never been
# migrated with alembic before. We don't support this direct
# upgrade case anymore. The user needs to run a two-step
# upgrade.
raise RuntimeError(
"The ZenML database has never been migrated with alembic "
"before. This can happen if you are performing a direct "
"upgrade from a really old version of ZenML. This direct "
"upgrade path is not supported anymore. Please upgrade "
"your ZenML installation first to 0.54.0 or an earlier "
"version and then to the latest version."
)
# If an alembic migration took place, all non-custom flavors are purged
# and the FlavorRegistry recreates all in-built and integration
# flavors in the db.
revisions_afterwards = self.alembic.current_revisions()
if current_revisions != revisions_afterwards:
self._sync_flavors()
prune_artifact_versions(self, only_versions=True)
Prunes unused artifact versions and their artifacts.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
only_versions |
bool |
Only delete artifact versions, keeping artifacts |
True |
Source code in zenml/zen_stores/sql_zen_store.py
def prune_artifact_versions(
self,
only_versions: bool = True,
) -> None:
"""Prunes unused artifact versions and their artifacts.
Args:
only_versions: Only delete artifact versions, keeping artifacts
"""
with Session(self.engine) as session:
unused_artifact_versions = [
a[0]
for a in session.execute(
select(ArtifactVersionSchema.id).where(
and_(
col(ArtifactVersionSchema.id).notin_(
select(StepRunOutputArtifactSchema.artifact_id)
),
col(ArtifactVersionSchema.id).notin_(
select(StepRunInputArtifactSchema.artifact_id)
),
)
)
).fetchall()
]
session.execute(
delete(ArtifactVersionSchema).where(
col(ArtifactVersionSchema.id).in_(
unused_artifact_versions
),
)
)
if not only_versions:
unused_artifacts = [
a[0]
for a in session.execute(
select(ArtifactSchema.id).where(
col(ArtifactSchema.id).notin_(
select(ArtifactVersionSchema.artifact_id)
)
)
).fetchall()
]
session.execute(
delete(ArtifactSchema).where(
col(ArtifactSchema.id).in_(unused_artifacts)
)
)
session.commit()
restore_database(self, strategy=None, location=None, cleanup=False)
Restore the database.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
strategy |
Optional[zenml.enums.DatabaseBackupStrategy] |
Custom backup strategy to use. If not set, the backup strategy from the store configuration will be used. |
None |
location |
Optional[Any] |
Custom target location to restore the database from. If not set, the configured backup location will be used. Depending on the backup strategy, this can be a file path, a database name or an in-memory database representation. |
None |
cleanup |
bool |
Whether to cleanup the backup after restoring the database. |
False |
Exceptions:
| Type | Description |
|---|---|
ValueError |
If the backup database name is not set when the backup database is requested or if the backup strategy is invalid. |
Source code in zenml/zen_stores/sql_zen_store.py
def restore_database(
self,
strategy: Optional[DatabaseBackupStrategy] = None,
location: Optional[Any] = None,
cleanup: bool = False,
) -> None:
"""Restore the database.
Args:
strategy: Custom backup strategy to use. If not set, the backup
strategy from the store configuration will be used.
location: Custom target location to restore the database from. If
not set, the configured backup location will be used. Depending
on the backup strategy, this can be a file path, a database
name or an in-memory database representation.
cleanup: Whether to cleanup the backup after restoring the database.
Raises:
ValueError: If the backup database name is not set when the backup
database is requested or if the backup strategy is invalid.
"""
strategy = strategy or self.config.backup_strategy
if (
strategy == DatabaseBackupStrategy.DUMP_FILE
or self.config.driver == SQLDatabaseDriver.SQLITE
):
dump_file = location or self._get_db_backup_file_path()
self.migration_utils.restore_database_from_file(
dump_file=dump_file
)
elif strategy == DatabaseBackupStrategy.DATABASE:
backup_db_name = location or self.config.backup_database
if not backup_db_name:
raise ValueError(
"The backup database name must be set in the store "
"configuration to use the backup database strategy."
)
self.migration_utils.restore_database_from_db(
backup_db_name=backup_db_name
)
elif strategy == DatabaseBackupStrategy.IN_MEMORY:
if location is None or not isinstance(location, list):
raise ValueError(
"The in-memory database representation must be provided "
"to restore the database from an in-memory backup."
)
self.migration_utils.restore_database_from_memory(db_dump=location)
else:
raise ValueError(f"Invalid backup strategy: {strategy}.")
if cleanup:
self.cleanup_database_backup()
restore_secrets(self, ignore_errors=False, delete_secrets=False)
Restore all secrets from the configured backup secrets store.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
ignore_errors |
bool |
Whether to ignore individual errors during the restore process and attempt to restore all secrets. |
False |
delete_secrets |
bool |
Whether to delete the secrets that have been successfully restored from the backup secrets store. Setting this flag effectively moves all secrets from the backup secrets store to the primary secrets store. |
False |
noqa: DAR401
Exceptions:
| Type | Description |
|---|---|
BackupSecretsStoreNotConfiguredError |
if no backup secrets store is configured. |
Source code in zenml/zen_stores/sql_zen_store.py
def restore_secrets(
self, ignore_errors: bool = False, delete_secrets: bool = False
) -> None:
"""Restore all secrets from the configured backup secrets store.
Args:
ignore_errors: Whether to ignore individual errors during the
restore process and attempt to restore all secrets.
delete_secrets: Whether to delete the secrets that have been
successfully restored from the backup secrets store. Setting
this flag effectively moves all secrets from the backup secrets
store to the primary secrets store.
# noqa: DAR401
Raises:
BackupSecretsStoreNotConfiguredError: if no backup secrets store is
configured.
"""
if not self.backup_secrets_store:
raise BackupSecretsStoreNotConfiguredError(
"Unable to restore secrets: No backup secrets store is "
"configured."
)
with Session(self.engine) as session:
secrets_in_db = session.exec(select(SecretSchema)).all()
for secret in secrets_in_db:
try:
values = self._get_backup_secret_values(secret_id=secret.id)
except Exception:
logger.exception(
f"Failed to get backup secret values for secret with ID "
f"{secret.id}."
)
if ignore_errors:
continue
raise
try:
self._update_secret_values(
secret_id=secret.id,
values=cast(Dict[str, Optional[str]], values),
overwrite=True,
backup=False,
)
except Exception:
logger.exception(
f"Failed to restore secret with ID {secret.id}. "
)
if ignore_errors:
continue
raise
if delete_secrets:
try:
self._delete_backup_secret_values(secret_id=secret.id)
except Exception:
logger.exception(
f"Failed to delete backup secret with ID {secret.id} "
f"from the backup secrets store after restoring it to "
f"the primary secrets store."
)
if ignore_errors:
continue
raise
rotate_api_key(self, service_account_id, api_key_name_or_id, rotate_request)
Rotate an API key for a service account.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account_id |
UUID |
The ID of the service account for which to rotate the API key. |
required |
api_key_name_or_id |
Union[str, uuid.UUID] |
The name or ID of the API key to rotate. |
required |
rotate_request |
APIKeyRotateRequest |
The rotate request on the API key. |
required |
Returns:
| Type | Description |
|---|---|
APIKeyResponse |
The updated API key. |
Source code in zenml/zen_stores/sql_zen_store.py
def rotate_api_key(
self,
service_account_id: UUID,
api_key_name_or_id: Union[str, UUID],
rotate_request: APIKeyRotateRequest,
) -> APIKeyResponse:
"""Rotate an API key for a service account.
Args:
service_account_id: The ID of the service account for which to
rotate the API key.
api_key_name_or_id: The name or ID of the API key to rotate.
rotate_request: The rotate request on the API key.
Returns:
The updated API key.
"""
with Session(self.engine) as session:
api_key = self._get_api_key(
service_account_id=service_account_id,
api_key_name_or_id=api_key_name_or_id,
session=session,
)
_, new_key = api_key.rotate(rotate_request)
session.add(api_key)
session.commit()
# Refresh the Model that was just created
session.refresh(api_key)
api_key_model = api_key.to_model()
api_key_model.set_key(new_key)
return api_key_model
update_api_key(self, service_account_id, api_key_name_or_id, api_key_update)
Update an API key for a service account.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account_id |
UUID |
The ID of the service account for which to update the API key. |
required |
api_key_name_or_id |
Union[str, uuid.UUID] |
The name or ID of the API key to update. |
required |
api_key_update |
APIKeyUpdate |
The update request on the API key. |
required |
Returns:
| Type | Description |
|---|---|
APIKeyResponse |
The updated API key. |
Exceptions:
| Type | Description |
|---|---|
EntityExistsError |
if the API key update would result in a name conflict with an existing API key for the same service account. |
Source code in zenml/zen_stores/sql_zen_store.py
def update_api_key(
self,
service_account_id: UUID,
api_key_name_or_id: Union[str, UUID],
api_key_update: APIKeyUpdate,
) -> APIKeyResponse:
"""Update an API key for a service account.
Args:
service_account_id: The ID of the service account for which to update
the API key.
api_key_name_or_id: The name or ID of the API key to update.
api_key_update: The update request on the API key.
Returns:
The updated API key.
Raises:
EntityExistsError: if the API key update would result in a name
conflict with an existing API key for the same service account.
"""
with Session(self.engine) as session:
api_key = self._get_api_key(
service_account_id=service_account_id,
api_key_name_or_id=api_key_name_or_id,
session=session,
)
if api_key_update.name and api_key.name != api_key_update.name:
# Check if a key with the new name already exists for the same
# service account
try:
self._get_api_key(
service_account_id=service_account_id,
api_key_name_or_id=api_key_update.name,
session=session,
)
raise EntityExistsError(
f"Unable to update API key with name "
f"'{api_key_update.name}': Found an existing API key "
"with the same name configured for the same "
f"'{api_key.service_account.name}' service account."
)
except KeyError:
pass
api_key.update(update=api_key_update)
session.add(api_key)
session.commit()
# Refresh the Model that was just created
session.refresh(api_key)
return api_key.to_model(include_metadata=True)
update_artifact(self, artifact_id, artifact_update)
Updates an artifact.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_id |
UUID |
The ID of the artifact to update. |
required |
artifact_update |
ArtifactUpdate |
The update to be applied to the artifact. |
required |
Returns:
| Type | Description |
|---|---|
ArtifactResponse |
The updated artifact. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the artifact doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def update_artifact(
self, artifact_id: UUID, artifact_update: ArtifactUpdate
) -> ArtifactResponse:
"""Updates an artifact.
Args:
artifact_id: The ID of the artifact to update.
artifact_update: The update to be applied to the artifact.
Returns:
The updated artifact.
Raises:
KeyError: if the artifact doesn't exist.
"""
with Session(self.engine) as session:
existing_artifact = session.exec(
select(ArtifactSchema).where(ArtifactSchema.id == artifact_id)
).first()
if not existing_artifact:
raise KeyError(f"Artifact with ID {artifact_id} not found.")
# Handle tag updates.
if artifact_update.add_tags:
self._attach_tags_to_resource(
tag_names=artifact_update.add_tags,
resource_id=existing_artifact.id,
resource_type=TaggableResourceTypes.ARTIFACT,
)
if artifact_update.remove_tags:
self._detach_tags_from_resource(
tag_names=artifact_update.remove_tags,
resource_id=existing_artifact.id,
resource_type=TaggableResourceTypes.ARTIFACT,
)
# Update the schema itself.
existing_artifact.update(artifact_update=artifact_update)
session.add(existing_artifact)
session.commit()
session.refresh(existing_artifact)
return existing_artifact.to_model(include_metadata=True)
update_artifact_version(self, artifact_version_id, artifact_version_update)
Updates an artifact version.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_version_id |
UUID |
The ID of the artifact version to update. |
required |
artifact_version_update |
ArtifactVersionUpdate |
The update to be applied to the artifact version. |
required |
Returns:
| Type | Description |
|---|---|
ArtifactVersionResponse |
The updated artifact version. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the artifact version doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def update_artifact_version(
self,
artifact_version_id: UUID,
artifact_version_update: ArtifactVersionUpdate,
) -> ArtifactVersionResponse:
"""Updates an artifact version.
Args:
artifact_version_id: The ID of the artifact version to update.
artifact_version_update: The update to be applied to the artifact
version.
Returns:
The updated artifact version.
Raises:
KeyError: if the artifact version doesn't exist.
"""
with Session(self.engine) as session:
existing_artifact_version = session.exec(
select(ArtifactVersionSchema).where(
ArtifactVersionSchema.id == artifact_version_id
)
).first()
if not existing_artifact_version:
raise KeyError(
f"Artifact version with ID {artifact_version_id} not found."
)
# Handle tag updates.
if artifact_version_update.add_tags:
self._attach_tags_to_resource(
tag_names=artifact_version_update.add_tags,
resource_id=existing_artifact_version.id,
resource_type=TaggableResourceTypes.ARTIFACT_VERSION,
)
if artifact_version_update.remove_tags:
self._detach_tags_from_resource(
tag_names=artifact_version_update.remove_tags,
resource_id=existing_artifact_version.id,
resource_type=TaggableResourceTypes.ARTIFACT_VERSION,
)
# Update the schema itself.
existing_artifact_version.update(
artifact_version_update=artifact_version_update
)
session.add(existing_artifact_version)
session.commit()
session.refresh(existing_artifact_version)
return existing_artifact_version.to_model(include_metadata=True)
update_authorized_device(self, device_id, update)
Updates an existing OAuth 2.0 authorized device for internal use.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
device_id |
UUID |
The ID of the device to update. |
required |
update |
OAuthDeviceUpdate |
The update to be applied to the device. |
required |
Returns:
| Type | Description |
|---|---|
OAuthDeviceResponse |
The updated OAuth 2.0 authorized device. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no device with the given ID exists. |
Source code in zenml/zen_stores/sql_zen_store.py
def update_authorized_device(
self, device_id: UUID, update: OAuthDeviceUpdate
) -> OAuthDeviceResponse:
"""Updates an existing OAuth 2.0 authorized device for internal use.
Args:
device_id: The ID of the device to update.
update: The update to be applied to the device.
Returns:
The updated OAuth 2.0 authorized device.
Raises:
KeyError: If no device with the given ID exists.
"""
with Session(self.engine) as session:
existing_device = session.exec(
select(OAuthDeviceSchema).where(
OAuthDeviceSchema.id == device_id
)
).first()
if existing_device is None:
raise KeyError(
f"Unable to update device with ID {device_id}: No "
"device with this ID found."
)
existing_device.update(update)
session.add(existing_device)
session.commit()
return existing_device.to_model(include_metadata=True)
update_code_repository(self, code_repository_id, update)
Updates an existing code repository.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
code_repository_id |
UUID |
The ID of the code repository to update. |
required |
update |
CodeRepositoryUpdate |
The update to be applied to the code repository. |
required |
Returns:
| Type | Description |
|---|---|
CodeRepositoryResponse |
The updated code repository. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no code repository with the given name exists. |
Source code in zenml/zen_stores/sql_zen_store.py
def update_code_repository(
self, code_repository_id: UUID, update: CodeRepositoryUpdate
) -> CodeRepositoryResponse:
"""Updates an existing code repository.
Args:
code_repository_id: The ID of the code repository to update.
update: The update to be applied to the code repository.
Returns:
The updated code repository.
Raises:
KeyError: If no code repository with the given name exists.
"""
with Session(self.engine) as session:
existing_repo = session.exec(
select(CodeRepositorySchema).where(
CodeRepositorySchema.id == code_repository_id
)
).first()
if existing_repo is None:
raise KeyError(
f"Unable to update code repository with ID "
f"{code_repository_id}: No code repository with this ID "
"found."
)
existing_repo.update(update)
session.add(existing_repo)
session.commit()
return existing_repo.to_model(include_metadata=True)
update_event_source(self, event_source_id, event_source_update)
Update an existing event_source.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
event_source_id |
UUID |
The ID of the event_source to update. |
required |
event_source_update |
EventSourceUpdate |
The update to be applied to the event_source. |
required |
Returns:
| Type | Description |
|---|---|
EventSourceResponse |
The updated event_source. |
Source code in zenml/zen_stores/sql_zen_store.py
def update_event_source(
self,
event_source_id: UUID,
event_source_update: EventSourceUpdate,
) -> EventSourceResponse:
"""Update an existing event_source.
Args:
event_source_id: The ID of the event_source to update.
event_source_update: The update to be applied to the event_source.
Returns:
The updated event_source.
"""
with Session(self.engine) as session:
event_source = self._get_event_source(
session=session, event_source_id=event_source_id
)
event_source.update(update=event_source_update)
session.add(event_source)
session.commit()
# Refresh the event_source that was just created
session.refresh(event_source)
return event_source.to_model(
include_metadata=True, include_resources=True
)
update_flavor(self, flavor_id, flavor_update)
Updates an existing user.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
flavor_id |
UUID |
The id of the flavor to update. |
required |
flavor_update |
FlavorUpdate |
The update to be applied to the flavor. |
required |
Returns:
| Type | Description |
|---|---|
FlavorResponse |
The updated flavor. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no flavor with the given id exists. |
Source code in zenml/zen_stores/sql_zen_store.py
def update_flavor(
self, flavor_id: UUID, flavor_update: FlavorUpdate
) -> FlavorResponse:
"""Updates an existing user.
Args:
flavor_id: The id of the flavor to update.
flavor_update: The update to be applied to the flavor.
Returns:
The updated flavor.
Raises:
KeyError: If no flavor with the given id exists.
"""
with Session(self.engine) as session:
existing_flavor = session.exec(
select(FlavorSchema).where(FlavorSchema.id == flavor_id)
).first()
if not existing_flavor:
raise KeyError(f"Flavor with ID {flavor_id} not found.")
existing_flavor.update(flavor_update=flavor_update)
session.add(existing_flavor)
session.commit()
# Refresh the Model that was just created
session.refresh(existing_flavor)
return existing_flavor.to_model(include_metadata=True)
update_internal_api_key(self, api_key_id, api_key_update)
Update an API key with internal details.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
api_key_id |
UUID |
The ID of the API key. |
required |
api_key_update |
APIKeyInternalUpdate |
The update request on the API key. |
required |
Returns:
| Type | Description |
|---|---|
APIKeyResponse |
The updated API key. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the API key doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def update_internal_api_key(
self, api_key_id: UUID, api_key_update: APIKeyInternalUpdate
) -> APIKeyResponse:
"""Update an API key with internal details.
Args:
api_key_id: The ID of the API key.
api_key_update: The update request on the API key.
Returns:
The updated API key.
Raises:
KeyError: if the API key doesn't exist.
"""
with Session(self.engine) as session:
api_key = session.exec(
select(APIKeySchema).where(APIKeySchema.id == api_key_id)
).first()
if not api_key:
raise KeyError(f"API key with ID {api_key_id} not found.")
api_key.internal_update(update=api_key_update)
session.add(api_key)
session.commit()
# Refresh the Model that was just created
session.refresh(api_key)
return api_key.to_model(include_metadata=True)
update_internal_authorized_device(self, device_id, update)
Updates an existing OAuth 2.0 authorized device.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
device_id |
UUID |
The ID of the device to update. |
required |
update |
OAuthDeviceInternalUpdate |
The update to be applied to the device. |
required |
Returns:
| Type | Description |
|---|---|
OAuthDeviceInternalResponse |
The updated OAuth 2.0 authorized device. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no device with the given ID exists. |
Source code in zenml/zen_stores/sql_zen_store.py
def update_internal_authorized_device(
self, device_id: UUID, update: OAuthDeviceInternalUpdate
) -> OAuthDeviceInternalResponse:
"""Updates an existing OAuth 2.0 authorized device.
Args:
device_id: The ID of the device to update.
update: The update to be applied to the device.
Returns:
The updated OAuth 2.0 authorized device.
Raises:
KeyError: If no device with the given ID exists.
"""
with Session(self.engine) as session:
existing_device = session.exec(
select(OAuthDeviceSchema).where(
OAuthDeviceSchema.id == device_id
)
).first()
if existing_device is None:
raise KeyError(
f"Unable to update device with ID {device_id}: No device "
"with this ID found."
)
(
_,
user_code,
device_code,
) = existing_device.internal_update(update)
session.add(existing_device)
session.commit()
device_model = existing_device.to_internal_model(hydrate=True)
if user_code:
# Replace the hashed user code with the original user code
device_model.user_code = user_code
if device_code:
# Replace the hashed device code with the original device code
device_model.device_code = device_code
return device_model
update_model(self, model_id, model_update)
Updates an existing model.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_id |
UUID |
UUID of the model to be updated. |
required |
model_update |
ModelUpdate |
the Model to be updated. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
specified ID not found. |
Returns:
| Type | Description |
|---|---|
ModelResponse |
The updated model. |
Source code in zenml/zen_stores/sql_zen_store.py
def update_model(
self,
model_id: UUID,
model_update: ModelUpdate,
) -> ModelResponse:
"""Updates an existing model.
Args:
model_id: UUID of the model to be updated.
model_update: the Model to be updated.
Raises:
KeyError: specified ID not found.
Returns:
The updated model.
"""
with Session(self.engine) as session:
existing_model = session.exec(
select(ModelSchema).where(ModelSchema.id == model_id)
).first()
if not existing_model:
raise KeyError(f"Model with ID {model_id} not found.")
if model_update.add_tags:
self._attach_tags_to_resource(
tag_names=model_update.add_tags,
resource_id=existing_model.id,
resource_type=TaggableResourceTypes.MODEL,
)
model_update.add_tags = None
if model_update.remove_tags:
self._detach_tags_from_resource(
tag_names=model_update.remove_tags,
resource_id=existing_model.id,
resource_type=TaggableResourceTypes.MODEL,
)
model_update.remove_tags = None
existing_model.update(model_update=model_update)
session.add(existing_model)
session.commit()
# Refresh the Model that was just created
session.refresh(existing_model)
return existing_model.to_model(include_metadata=True)
update_model_version(self, model_version_id, model_version_update_model)
Get all model versions by filter.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_id |
UUID |
The ID of model version to be updated. |
required |
model_version_update_model |
ModelVersionUpdate |
The model version to be updated. |
required |
Returns:
| Type | Description |
|---|---|
ModelVersionResponse |
An updated model version. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If the model version not found |
RuntimeError |
If there is a model version with target stage,
but |
Source code in zenml/zen_stores/sql_zen_store.py
def update_model_version(
self,
model_version_id: UUID,
model_version_update_model: ModelVersionUpdate,
) -> ModelVersionResponse:
"""Get all model versions by filter.
Args:
model_version_id: The ID of model version to be updated.
model_version_update_model: The model version to be updated.
Returns:
An updated model version.
Raises:
KeyError: If the model version not found
RuntimeError: If there is a model version with target stage,
but `force` flag is off
"""
with Session(self.engine) as session:
existing_model_version = session.exec(
select(ModelVersionSchema)
.where(
ModelVersionSchema.model_id
== model_version_update_model.model
)
.where(ModelVersionSchema.id == model_version_id)
).first()
if not existing_model_version:
raise KeyError(f"Model version {model_version_id} not found.")
stage = None
if (stage_ := model_version_update_model.stage) is not None:
stage = getattr(stage_, "value", stage_)
existing_model_version_in_target_stage = session.exec(
select(ModelVersionSchema)
.where(
ModelVersionSchema.model_id
== model_version_update_model.model
)
.where(ModelVersionSchema.stage == stage)
).first()
if (
existing_model_version_in_target_stage is not None
and existing_model_version_in_target_stage.id
!= existing_model_version.id
):
if not model_version_update_model.force:
raise RuntimeError(
f"Model version {existing_model_version_in_target_stage.name} is "
f"in {stage}, but `force` flag is False."
)
else:
existing_model_version_in_target_stage.update(
target_stage=ModelStages.ARCHIVED.value
)
session.add(existing_model_version_in_target_stage)
logger.info(
f"Model version {existing_model_version_in_target_stage.name} has been set to {ModelStages.ARCHIVED.value}."
)
if model_version_update_model.add_tags:
self._attach_tags_to_resource(
tag_names=model_version_update_model.add_tags,
resource_id=existing_model_version.id,
resource_type=TaggableResourceTypes.MODEL_VERSION,
)
if model_version_update_model.remove_tags:
self._detach_tags_from_resource(
tag_names=model_version_update_model.remove_tags,
resource_id=existing_model_version.id,
resource_type=TaggableResourceTypes.MODEL_VERSION,
)
existing_model_version.update(
target_stage=stage,
target_name=model_version_update_model.name,
target_description=model_version_update_model.description,
)
session.add(existing_model_version)
session.commit()
session.refresh(existing_model_version)
return existing_model_version.to_model(include_metadata=True)
update_pipeline(self, pipeline_id, pipeline_update)
Updates a pipeline.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
pipeline_id |
UUID |
The ID of the pipeline to be updated. |
required |
pipeline_update |
PipelineUpdate |
The update to be applied. |
required |
Returns:
| Type | Description |
|---|---|
PipelineResponse |
The updated pipeline. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the pipeline doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def update_pipeline(
self,
pipeline_id: UUID,
pipeline_update: PipelineUpdate,
) -> PipelineResponse:
"""Updates a pipeline.
Args:
pipeline_id: The ID of the pipeline to be updated.
pipeline_update: The update to be applied.
Returns:
The updated pipeline.
Raises:
KeyError: if the pipeline doesn't exist.
"""
with Session(self.engine) as session:
# Check if pipeline with the given ID exists
existing_pipeline = session.exec(
select(PipelineSchema).where(PipelineSchema.id == pipeline_id)
).first()
if existing_pipeline is None:
raise KeyError(
f"Unable to update pipeline with ID {pipeline_id}: "
f"No pipeline with this ID found."
)
# Update the pipeline
existing_pipeline.update(pipeline_update)
session.add(existing_pipeline)
session.commit()
return existing_pipeline.to_model(include_metadata=True)
update_run(self, run_id, run_update)
Updates a pipeline run.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
run_id |
UUID |
The ID of the pipeline run to update. |
required |
run_update |
PipelineRunUpdate |
The update to be applied to the pipeline run. |
required |
Returns:
| Type | Description |
|---|---|
PipelineRunResponse |
The updated pipeline run. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the pipeline run doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def update_run(
self, run_id: UUID, run_update: PipelineRunUpdate
) -> PipelineRunResponse:
"""Updates a pipeline run.
Args:
run_id: The ID of the pipeline run to update.
run_update: The update to be applied to the pipeline run.
Returns:
The updated pipeline run.
Raises:
KeyError: if the pipeline run doesn't exist.
"""
with Session(self.engine) as session:
# Check if pipeline run with the given ID exists
existing_run = session.exec(
select(PipelineRunSchema).where(PipelineRunSchema.id == run_id)
).first()
if existing_run is None:
raise KeyError(
f"Unable to update pipeline run with ID {run_id}: "
f"No pipeline run with this ID found."
)
# Update the pipeline run
existing_run.update(run_update=run_update)
session.add(existing_run)
session.commit()
session.refresh(existing_run)
return existing_run.to_model(include_metadata=True)
update_run_step(self, step_run_id, step_run_update)
Updates a step run.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
step_run_id |
UUID |
The ID of the step to update. |
required |
step_run_update |
StepRunUpdate |
The update to be applied to the step. |
required |
Returns:
| Type | Description |
|---|---|
StepRunResponse |
The updated step run. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the step run doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def update_run_step(
self,
step_run_id: UUID,
step_run_update: StepRunUpdate,
) -> StepRunResponse:
"""Updates a step run.
Args:
step_run_id: The ID of the step to update.
step_run_update: The update to be applied to the step.
Returns:
The updated step run.
Raises:
KeyError: if the step run doesn't exist.
"""
with Session(self.engine) as session:
# Check if the step exists
existing_step_run = session.exec(
select(StepRunSchema).where(StepRunSchema.id == step_run_id)
).first()
if existing_step_run is None:
raise KeyError(
f"Unable to update step with ID {step_run_id}: "
f"No step with this ID found."
)
# Update the step
existing_step_run.update(step_run_update)
session.add(existing_step_run)
# Update the output artifacts.
for name, artifact_version_id in step_run_update.outputs.items():
self._set_run_step_output_artifact(
step_run_id=step_run_id,
artifact_version_id=artifact_version_id,
name=name,
output_type=StepRunOutputArtifactType.DEFAULT,
session=session,
)
# Update saved artifacts
for (
artifact_name,
artifact_version_id,
) in step_run_update.saved_artifact_versions.items():
self._set_run_step_output_artifact(
step_run_id=step_run_id,
artifact_version_id=artifact_version_id,
name=artifact_name,
output_type=StepRunOutputArtifactType.MANUAL,
session=session,
)
# Update loaded artifacts.
for (
artifact_name,
artifact_version_id,
) in step_run_update.loaded_artifact_versions.items():
self._set_run_step_input_artifact(
run_step_id=step_run_id,
artifact_version_id=artifact_version_id,
name=artifact_name,
input_type=StepRunInputArtifactType.MANUAL,
session=session,
)
self._update_pipeline_run_status(
pipeline_run_id=existing_step_run.pipeline_run_id,
session=session,
)
session.commit()
session.refresh(existing_step_run)
return existing_step_run.to_model(include_metadata=True)
update_schedule(self, schedule_id, schedule_update)
Updates a schedule.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
schedule_id |
UUID |
The ID of the schedule to be updated. |
required |
schedule_update |
ScheduleUpdate |
The update to be applied. |
required |
Returns:
| Type | Description |
|---|---|
ScheduleResponse |
The updated schedule. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the schedule doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def update_schedule(
self,
schedule_id: UUID,
schedule_update: ScheduleUpdate,
) -> ScheduleResponse:
"""Updates a schedule.
Args:
schedule_id: The ID of the schedule to be updated.
schedule_update: The update to be applied.
Returns:
The updated schedule.
Raises:
KeyError: if the schedule doesn't exist.
"""
with Session(self.engine) as session:
# Check if schedule with the given ID exists
existing_schedule = session.exec(
select(ScheduleSchema).where(ScheduleSchema.id == schedule_id)
).first()
if existing_schedule is None:
raise KeyError(
f"Unable to update schedule with ID {schedule_id}: "
f"No schedule with this ID found."
)
# Update the schedule
existing_schedule = existing_schedule.update(schedule_update)
session.add(existing_schedule)
session.commit()
return existing_schedule.to_model(include_metadata=True)
update_secret(self, secret_id, secret_update)
Updates a secret.
Secret values that are specified as None in the update that are
present in the existing secret are removed from the existing secret.
Values that are present in both secrets are overwritten. All other
values in both the existing secret and the update are kept (merged).
If the update includes a change of name or scope, the scoping rules enforced in the secrets store are used to validate the update:
- only one workspace-scoped secret with the given name can exist in the target workspace.
- only one user-scoped secret with the given name can exist in the target workspace for the target user.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
The ID of the secret to be updated. |
required |
secret_update |
SecretUpdate |
The update to be applied. |
required |
Returns:
| Type | Description |
|---|---|
SecretResponse |
The updated secret. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the secret doesn't exist. |
EntityExistsError |
If a secret with the same name already exists in the same scope. |
Source code in zenml/zen_stores/sql_zen_store.py
def update_secret(
self, secret_id: UUID, secret_update: SecretUpdate
) -> SecretResponse:
"""Updates a secret.
Secret values that are specified as `None` in the update that are
present in the existing secret are removed from the existing secret.
Values that are present in both secrets are overwritten. All other
values in both the existing secret and the update are kept (merged).
If the update includes a change of name or scope, the scoping rules
enforced in the secrets store are used to validate the update:
- only one workspace-scoped secret with the given name can exist
in the target workspace.
- only one user-scoped secret with the given name can exist in the
target workspace for the target user.
Args:
secret_id: The ID of the secret to be updated.
secret_update: The update to be applied.
Returns:
The updated secret.
Raises:
KeyError: if the secret doesn't exist.
EntityExistsError: If a secret with the same name already exists in
the same scope.
"""
with Session(self.engine) as session:
existing_secret = session.exec(
select(SecretSchema).where(SecretSchema.id == secret_id)
).first()
if not existing_secret:
raise KeyError(f"Secret with ID {secret_id} not found.")
# A change in name or scope requires a check of the scoping rules.
if (
secret_update.name is not None
and existing_secret.name != secret_update.name
or secret_update.scope is not None
and existing_secret.scope != secret_update.scope
):
secret_exists, msg = self._check_sql_secret_scope(
session=session,
secret_name=secret_update.name or existing_secret.name,
scope=secret_update.scope
or SecretScope(existing_secret.scope),
workspace=existing_secret.workspace.id,
user=existing_secret.user.id,
exclude_secret_id=secret_id,
)
if secret_exists:
raise EntityExistsError(msg)
existing_secret.update(
secret_update=secret_update,
)
session.add(existing_secret)
session.commit()
# Refresh the Model that was just created
session.refresh(existing_secret)
secret_model = existing_secret.to_model(include_metadata=True)
if secret_update.values is not None:
# Update the secret values in the configured secrets store
updated_values = self._update_secret_values(
secret_id=secret_id,
values=secret_update.get_secret_values_update(),
)
secret_model.set_secrets(updated_values)
else:
secret_model.set_secrets(self._get_secret_values(secret_id))
return secret_model
update_service_account(self, service_account_name_or_id, service_account_update)
Updates an existing service account.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account_name_or_id |
Union[str, uuid.UUID] |
The name or the ID of the service account to update. |
required |
service_account_update |
ServiceAccountUpdate |
The update to be applied to the service account. |
required |
Returns:
| Type | Description |
|---|---|
ServiceAccountResponse |
The updated service account. |
Exceptions:
| Type | Description |
|---|---|
EntityExistsError |
If a user or service account with the given name already exists. |
Source code in zenml/zen_stores/sql_zen_store.py
def update_service_account(
self,
service_account_name_or_id: Union[str, UUID],
service_account_update: ServiceAccountUpdate,
) -> ServiceAccountResponse:
"""Updates an existing service account.
Args:
service_account_name_or_id: The name or the ID of the service
account to update.
service_account_update: The update to be applied to the service
account.
Returns:
The updated service account.
Raises:
EntityExistsError: If a user or service account with the given name
already exists.
"""
with Session(self.engine) as session:
existing_service_account = self._get_account_schema(
service_account_name_or_id,
session=session,
service_account=True,
)
if (
service_account_update.name is not None
and service_account_update.name
!= existing_service_account.name
):
try:
self._get_account_schema(
service_account_update.name,
session=session,
service_account=True,
)
raise EntityExistsError(
f"Unable to update service account with name "
f"'{service_account_update.name}': Found an existing "
"service account with this name."
)
except KeyError:
pass
existing_service_account.update_service_account(
service_account_update=service_account_update
)
session.add(existing_service_account)
session.commit()
# Refresh the Model that was just created
session.refresh(existing_service_account)
return existing_service_account.to_service_account_model(
include_metadata=True
)
update_service_connector(self, service_connector_id, update)
Updates an existing service connector.
The update model contains the fields to be updated. If a field value is set to None in the model, the field is not updated, but there are special rules concerning some fields:
- the
configurationandsecretsfields together represent a full valid configuration update, not just a partial update. If either is set (i.e. not None) in the update, their values are merged together and will replace the existing configuration and secrets values. - the
resource_idfield value is also a full replacement value: if set toNone, the resource ID is removed from the service connector. - the
expiration_secondsfield value is also a full replacement value: if set toNone, the expiration is removed from the service connector. - the
secret_idfield value in the update is ignored, given that secrets are managed internally by the ZenML store. - the
labelsfield is also a full labels update: if set (i.e. notNone), all existing labels are removed and replaced by the new labels in the update.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_connector_id |
UUID |
The ID of the service connector to update. |
required |
update |
ServiceConnectorUpdate |
The update to be applied to the service connector. |
required |
Returns:
| Type | Description |
|---|---|
ServiceConnectorResponse |
The updated service connector. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no service connector with the given ID exists. |
IllegalOperationError |
If the service connector is referenced by one or more stack components and the update would change the connector type, resource type or resource ID. |
Source code in zenml/zen_stores/sql_zen_store.py
def update_service_connector(
self, service_connector_id: UUID, update: ServiceConnectorUpdate
) -> ServiceConnectorResponse:
"""Updates an existing service connector.
The update model contains the fields to be updated. If a field value is
set to None in the model, the field is not updated, but there are
special rules concerning some fields:
* the `configuration` and `secrets` fields together represent a full
valid configuration update, not just a partial update. If either is
set (i.e. not None) in the update, their values are merged together and
will replace the existing configuration and secrets values.
* the `resource_id` field value is also a full replacement value: if set
to `None`, the resource ID is removed from the service connector.
* the `expiration_seconds` field value is also a full replacement value:
if set to `None`, the expiration is removed from the service connector.
* the `secret_id` field value in the update is ignored, given that
secrets are managed internally by the ZenML store.
* the `labels` field is also a full labels update: if set (i.e. not
`None`), all existing labels are removed and replaced by the new labels
in the update.
Args:
service_connector_id: The ID of the service connector to update.
update: The update to be applied to the service connector.
Returns:
The updated service connector.
Raises:
KeyError: If no service connector with the given ID exists.
IllegalOperationError: If the service connector is referenced by
one or more stack components and the update would change the
connector type, resource type or resource ID.
"""
with Session(self.engine) as session:
existing_connector = session.exec(
select(ServiceConnectorSchema).where(
ServiceConnectorSchema.id == service_connector_id
)
).first()
if existing_connector is None:
raise KeyError(
f"Unable to update service connector with ID "
f"'{service_connector_id}': Found no existing service "
"connector with this ID."
)
# In case of a renaming update, make sure no service connector uses
# that name already
if update.name and existing_connector.name != update.name:
self._fail_if_service_connector_with_name_exists(
name=update.name,
workspace_id=existing_connector.workspace_id,
session=session,
)
existing_connector_model = existing_connector.to_model(
include_metadata=True
)
if len(existing_connector.components):
# If the service connector is already used in one or more
# stack components, the update is no longer allowed to change
# the service connector's authentication method, connector type,
# resource type, or resource ID
if (
update.connector_type
and update.type != existing_connector_model.connector_type
):
raise IllegalOperationError(
"The service type of a service connector that is "
"already actively used in one or more stack components "
"cannot be changed."
)
if (
update.auth_method
and update.auth_method
!= existing_connector_model.auth_method
):
raise IllegalOperationError(
"The authentication method of a service connector that "
"is already actively used in one or more stack "
"components cannot be changed."
)
if (
update.resource_types
and update.resource_types
!= existing_connector_model.resource_types
):
raise IllegalOperationError(
"The resource type of a service connector that is "
"already actively used in one or more stack components "
"cannot be changed."
)
# The resource ID field cannot be used as a partial update: if
# set to None, the existing resource ID is also removed
if update.resource_id != existing_connector_model.resource_id:
raise IllegalOperationError(
"The resource ID of a service connector that is "
"already actively used in one or more stack components "
"cannot be changed."
)
# If the connector type is locally available, we validate the update
# against the connector type schema before storing it in the
# database
if service_connector_registry.is_registered(
existing_connector.connector_type
):
connector_type = (
service_connector_registry.get_service_connector_type(
existing_connector.connector_type
)
)
# We need the auth method to be set to be able to validate the
# configuration
update.auth_method = (
update.auth_method or existing_connector_model.auth_method
)
# Validate the configuration update. If the configuration or
# secrets fields are set, together they are merged into a
# full configuration that is validated against the connector
# type schema and replaces the existing configuration and
# secrets values
update.validate_and_configure_resources(
connector_type=connector_type,
resource_types=update.resource_types,
resource_id=update.resource_id,
configuration=update.configuration,
secrets=update.secrets,
)
# Update secret
secret_id = self._update_connector_secret(
existing_connector=existing_connector_model,
updated_connector=update,
)
existing_connector.update(
connector_update=update, secret_id=secret_id
)
session.add(existing_connector)
session.commit()
connector = existing_connector.to_model(include_metadata=True)
self._populate_connector_type(connector)
return connector
update_stack(self, stack_id, stack_update)
Update a stack.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
stack_id |
UUID |
The ID of the stack update. |
required |
stack_update |
StackUpdate |
The update request on the stack. |
required |
Returns:
| Type | Description |
|---|---|
StackResponse |
The updated stack. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the stack doesn't exist. |
IllegalOperationError |
if the stack is a default stack. |
Source code in zenml/zen_stores/sql_zen_store.py
@track_decorator(AnalyticsEvent.UPDATED_STACK)
def update_stack(
self, stack_id: UUID, stack_update: StackUpdate
) -> StackResponse:
"""Update a stack.
Args:
stack_id: The ID of the stack update.
stack_update: The update request on the stack.
Returns:
The updated stack.
Raises:
KeyError: if the stack doesn't exist.
IllegalOperationError: if the stack is a default stack.
"""
with Session(self.engine) as session:
# Check if stack with the domain key (name, workspace, owner)
# already exists
existing_stack = session.exec(
select(StackSchema).where(StackSchema.id == stack_id)
).first()
if existing_stack is None:
raise KeyError(
f"Unable to update stack with id '{stack_id}': Found no"
f"existing stack with this id."
)
if existing_stack.name == DEFAULT_STACK_AND_COMPONENT_NAME:
raise IllegalOperationError(
"The default stack cannot be modified."
)
# In case of a renaming update, make sure no stack already exists
# with that name
if stack_update.name:
if existing_stack.name != stack_update.name:
self._fail_if_stack_with_name_exists(
stack=stack_update,
session=session,
)
components = []
if stack_update.components:
filters = [
(StackComponentSchema.id == component_id)
for list_of_component_ids in stack_update.components.values()
for component_id in list_of_component_ids
]
components = session.exec(
select(StackComponentSchema).where(or_(*filters))
).all()
existing_stack.update(
stack_update=stack_update,
components=components,
)
session.add(existing_stack)
session.commit()
session.refresh(existing_stack)
return existing_stack.to_model(include_metadata=True)
update_stack_component(self, component_id, component_update)
Update an existing stack component.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
component_id |
UUID |
The ID of the stack component to update. |
required |
component_update |
ComponentUpdate |
The update to be applied to the stack component. |
required |
Returns:
| Type | Description |
|---|---|
ComponentResponse |
The updated stack component. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the stack component doesn't exist. |
IllegalOperationError |
if the stack component is a default stack component. |
Source code in zenml/zen_stores/sql_zen_store.py
def update_stack_component(
self, component_id: UUID, component_update: ComponentUpdate
) -> ComponentResponse:
"""Update an existing stack component.
Args:
component_id: The ID of the stack component to update.
component_update: The update to be applied to the stack component.
Returns:
The updated stack component.
Raises:
KeyError: if the stack component doesn't exist.
IllegalOperationError: if the stack component is a default stack
component.
"""
with Session(self.engine) as session:
existing_component = session.exec(
select(StackComponentSchema).where(
StackComponentSchema.id == component_id
)
).first()
if existing_component is None:
raise KeyError(
f"Unable to update component with id "
f"'{component_id}': Found no"
f"existing component with this id."
)
if (
existing_component.name == DEFAULT_STACK_AND_COMPONENT_NAME
and existing_component.type
in [
StackComponentType.ORCHESTRATOR,
StackComponentType.ARTIFACT_STORE,
]
):
raise IllegalOperationError(
f"The default {existing_component.type} cannot be modified."
)
# In case of a renaming update, make sure no component of the same
# type already exists with that name
if component_update.name:
if existing_component.name != component_update.name:
self._fail_if_component_with_name_type_exists(
name=component_update.name,
component_type=existing_component.type,
workspace_id=existing_component.workspace_id,
session=session,
)
existing_component.update(component_update=component_update)
if component_update.connector:
service_connector = session.exec(
select(ServiceConnectorSchema).where(
ServiceConnectorSchema.id == component_update.connector
)
).first()
if service_connector is None:
raise KeyError(
"Service connector with ID "
f"{component_update.connector} not found."
)
existing_component.connector = service_connector
existing_component.connector_resource_id = (
component_update.connector_resource_id
)
else:
existing_component.connector = None
existing_component.connector_resource_id = None
session.add(existing_component)
session.commit()
return existing_component.to_model(include_metadata=True)
update_tag(self, tag_name_or_id, tag_update_model)
Update tag.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
tag_name_or_id |
Union[str, uuid.UUID] |
name or id of the tag to be updated. |
required |
tag_update_model |
TagUpdate |
Tag to use for the update. |
required |
Returns:
| Type | Description |
|---|---|
TagResponse |
An updated tag. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If the tag is not found |
Source code in zenml/zen_stores/sql_zen_store.py
def update_tag(
self,
tag_name_or_id: Union[str, UUID],
tag_update_model: TagUpdate,
) -> TagResponse:
"""Update tag.
Args:
tag_name_or_id: name or id of the tag to be updated.
tag_update_model: Tag to use for the update.
Returns:
An updated tag.
Raises:
KeyError: If the tag is not found
"""
with Session(self.engine) as session:
tag = self._get_tag_schema(
tag_name_or_id=tag_name_or_id, session=session
)
if not tag:
raise KeyError(f"Tag with ID `{tag_name_or_id}` not found.")
tag.update(update=tag_update_model)
session.add(tag)
session.commit()
# Refresh the tag that was just created
session.refresh(tag)
return tag.to_model(include_metadata=True)
update_trigger(self, trigger_id, trigger_update)
Update a trigger.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
trigger_id |
UUID |
The ID of the trigger update. |
required |
trigger_update |
TriggerUpdate |
The update request on the trigger. |
required |
Returns:
| Type | Description |
|---|---|
TriggerResponse |
The updated trigger. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the trigger doesn't exist. |
Source code in zenml/zen_stores/sql_zen_store.py
@track_decorator(AnalyticsEvent.UPDATED_TRIGGER)
def update_trigger(
self, trigger_id: UUID, trigger_update: TriggerUpdate
) -> TriggerResponse:
"""Update a trigger.
Args:
trigger_id: The ID of the trigger update.
trigger_update: The update request on the trigger.
Returns:
The updated trigger.
Raises:
KeyError: if the trigger doesn't exist.
"""
with Session(self.engine) as session:
# Check if trigger with the domain key (name, workspace, owner)
# already exists
existing_trigger = session.exec(
select(TriggerSchema).where(TriggerSchema.id == trigger_id)
).first()
if existing_trigger is None:
raise KeyError(
f"Unable to update trigger with id '{trigger_id}': Found no"
f"existing trigger with this id."
)
if trigger_update.service_account_id:
# Verify that the given service account exists
self._get_account_schema(
account_name_or_id=trigger_update.service_account_id,
session=session,
service_account=True,
)
# In case of a renaming update, make sure no trigger already exists
# with that name
if trigger_update.name:
if existing_trigger.name != trigger_update.name:
self._fail_if_trigger_with_name_exists(
trigger_name=trigger_update.name,
workspace_id=existing_trigger.workspace.id,
session=session,
)
existing_trigger.update(
trigger_update=trigger_update,
)
session.add(existing_trigger)
session.commit()
session.refresh(existing_trigger)
return existing_trigger.to_model(
include_metadata=True, include_resources=True
)
update_user(self, user_id, user_update)
Updates an existing user.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
user_id |
UUID |
The id of the user to update. |
required |
user_update |
UserUpdate |
The update to be applied to the user. |
required |
Returns:
| Type | Description |
|---|---|
UserResponse |
The updated user. |
Exceptions:
| Type | Description |
|---|---|
IllegalOperationError |
If the request tries to update the username for the default user account. |
EntityExistsError |
If the request tries to update the username to a name that is already taken by another user or service account. |
Source code in zenml/zen_stores/sql_zen_store.py
def update_user(
self, user_id: UUID, user_update: UserUpdate
) -> UserResponse:
"""Updates an existing user.
Args:
user_id: The id of the user to update.
user_update: The update to be applied to the user.
Returns:
The updated user.
Raises:
IllegalOperationError: If the request tries to update the username
for the default user account.
EntityExistsError: If the request tries to update the username to
a name that is already taken by another user or service account.
"""
with Session(self.engine) as session:
existing_user = self._get_account_schema(
user_id, session=session, service_account=False
)
if (
user_update.name is not None
and user_update.name != existing_user.name
):
if existing_user.name == self._default_user_name:
raise IllegalOperationError(
"The username of the default user account cannot be "
"changed."
)
try:
self._get_account_schema(
user_update.name,
session=session,
service_account=False,
)
raise EntityExistsError(
f"Unable to update user account with name "
f"'{user_update.name}': Found an existing user "
"account with this name."
)
except KeyError:
pass
existing_user.update_user(user_update=user_update)
session.add(existing_user)
session.commit()
# Refresh the Model that was just created
session.refresh(existing_user)
return existing_user.to_model(include_metadata=True)
update_workspace(self, workspace_id, workspace_update)
Update an existing workspace.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
workspace_id |
UUID |
The ID of the workspace to be updated. |
required |
workspace_update |
WorkspaceUpdate |
The update to be applied to the workspace. |
required |
Returns:
| Type | Description |
|---|---|
WorkspaceResponse |
The updated workspace. |
Exceptions:
| Type | Description |
|---|---|
IllegalOperationError |
if the workspace is the default workspace. |
KeyError |
if the workspace does not exist. |
Source code in zenml/zen_stores/sql_zen_store.py
def update_workspace(
self, workspace_id: UUID, workspace_update: WorkspaceUpdate
) -> WorkspaceResponse:
"""Update an existing workspace.
Args:
workspace_id: The ID of the workspace to be updated.
workspace_update: The update to be applied to the workspace.
Returns:
The updated workspace.
Raises:
IllegalOperationError: if the workspace is the default workspace.
KeyError: if the workspace does not exist.
"""
with Session(self.engine) as session:
existing_workspace = session.exec(
select(WorkspaceSchema).where(
WorkspaceSchema.id == workspace_id
)
).first()
if existing_workspace is None:
raise KeyError(
f"Unable to update workspace with id "
f"'{workspace_id}': Found no"
f"existing workspaces with this id."
)
if (
existing_workspace.name == self._default_workspace_name
and "name" in workspace_update.__fields_set__
and workspace_update.name != existing_workspace.name
):
raise IllegalOperationError(
"The name of the default workspace cannot be changed."
)
# Update the workspace
existing_workspace.update(workspace_update=workspace_update)
session.add(existing_workspace)
session.commit()
# Refresh the Model that was just created
session.refresh(existing_workspace)
return existing_workspace.to_model(include_metadata=True)
verify_service_connector(self, service_connector_id, resource_type=None, resource_id=None, list_resources=True)
Verifies if a service connector instance has access to one or more resources.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_connector_id |
UUID |
The ID of the service connector to verify. |
required |
resource_type |
Optional[str] |
The type of resource to verify access to. |
None |
resource_id |
Optional[str] |
The ID of the resource to verify access to. |
None |
list_resources |
bool |
If True, the list of all resources accessible through the service connector and matching the supplied resource type and ID are returned. |
True |
Returns:
| Type | Description |
|---|---|
ServiceConnectorResourcesModel |
The list of resources that the service connector has access to, scoped to the supplied resource type and ID, if provided. |
Source code in zenml/zen_stores/sql_zen_store.py
def verify_service_connector(
self,
service_connector_id: UUID,
resource_type: Optional[str] = None,
resource_id: Optional[str] = None,
list_resources: bool = True,
) -> ServiceConnectorResourcesModel:
"""Verifies if a service connector instance has access to one or more resources.
Args:
service_connector_id: The ID of the service connector to verify.
resource_type: The type of resource to verify access to.
resource_id: The ID of the resource to verify access to.
list_resources: If True, the list of all resources accessible
through the service connector and matching the supplied resource
type and ID are returned.
Returns:
The list of resources that the service connector has access to,
scoped to the supplied resource type and ID, if provided.
"""
connector = self.get_service_connector(service_connector_id)
connector_instance = service_connector_registry.instantiate_connector(
model=connector
)
return connector_instance.verify(
resource_type=resource_type,
resource_id=resource_id,
list_resources=list_resources,
)
verify_service_connector_config(self, service_connector, list_resources=True)
Verifies if a service connector configuration has access to resources.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_connector |
ServiceConnectorRequest |
The service connector configuration to verify. |
required |
list_resources |
bool |
If True, the list of all resources accessible through the service connector is returned. |
True |
Returns:
| Type | Description |
|---|---|
ServiceConnectorResourcesModel |
The list of resources that the service connector configuration has access to. |
Source code in zenml/zen_stores/sql_zen_store.py
def verify_service_connector_config(
self,
service_connector: ServiceConnectorRequest,
list_resources: bool = True,
) -> ServiceConnectorResourcesModel:
"""Verifies if a service connector configuration has access to resources.
Args:
service_connector: The service connector configuration to verify.
list_resources: If True, the list of all resources accessible
through the service connector is returned.
Returns:
The list of resources that the service connector configuration has
access to.
"""
connector_instance = service_connector_registry.instantiate_connector(
model=service_connector
)
return connector_instance.verify(list_resources=list_resources)
SqlZenStoreConfiguration (StoreConfiguration)
pydantic-model
SQL ZenML store configuration.
Attributes:
| Name | Type | Description |
|---|---|---|
type |
StoreType |
The type of the store. |
secrets_store |
Optional[zenml.config.secrets_store_config.SecretsStoreConfiguration] |
The configuration of the secrets store to use. This defaults to a SQL secrets store that extends the SQL ZenML store. |
backup_secrets_store |
Optional[zenml.config.secrets_store_config.SecretsStoreConfiguration] |
The configuration of a backup secrets store to use in addition to the primary one as an intermediate step during the migration to a new secrets store. |
driver |
Optional[zenml.zen_stores.sql_zen_store.SQLDatabaseDriver] |
The SQL database driver. |
database |
Optional[str] |
database name. If not already present on the server, it will be created automatically on first access. |
username |
Optional[str] |
The database username. |
password |
Optional[str] |
The database password. |
ssl_ca |
Optional[str] |
certificate authority certificate. Required for SSL enabled authentication if the CA certificate is not part of the certificates shipped by the operating system. |
ssl_cert |
Optional[str] |
client certificate. Required for SSL enabled authentication if client certificates are used. |
ssl_key |
Optional[str] |
client certificate private key. Required for SSL enabled if client certificates are used. |
ssl_verify_server_cert |
bool |
set to verify the identity of the server against the provided server certificate. |
pool_size |
int |
The maximum number of connections to keep in the SQLAlchemy pool. |
max_overflow |
int |
The maximum number of connections to allow in the SQLAlchemy pool in addition to the pool_size. |
pool_pre_ping |
bool |
Enable emitting a test statement on the SQL connection at the start of each connection pool checkout, to test that the database connection is still viable. |
Source code in zenml/zen_stores/sql_zen_store.py
class SqlZenStoreConfiguration(StoreConfiguration):
"""SQL ZenML store configuration.
Attributes:
type: The type of the store.
secrets_store: The configuration of the secrets store to use.
This defaults to a SQL secrets store that extends the SQL ZenML
store.
backup_secrets_store: The configuration of a backup secrets store to
use in addition to the primary one as an intermediate step during
the migration to a new secrets store.
driver: The SQL database driver.
database: database name. If not already present on the server, it will
be created automatically on first access.
username: The database username.
password: The database password.
ssl_ca: certificate authority certificate. Required for SSL
enabled authentication if the CA certificate is not part of the
certificates shipped by the operating system.
ssl_cert: client certificate. Required for SSL enabled
authentication if client certificates are used.
ssl_key: client certificate private key. Required for SSL
enabled if client certificates are used.
ssl_verify_server_cert: set to verify the identity of the server
against the provided server certificate.
pool_size: The maximum number of connections to keep in the SQLAlchemy
pool.
max_overflow: The maximum number of connections to allow in the
SQLAlchemy pool in addition to the pool_size.
pool_pre_ping: Enable emitting a test statement on the SQL connection
at the start of each connection pool checkout, to test that the
database connection is still viable.
"""
type: StoreType = StoreType.SQL
secrets_store: Optional[SecretsStoreConfiguration] = None
backup_secrets_store: Optional[SecretsStoreConfiguration] = None
driver: Optional[SQLDatabaseDriver] = None
database: Optional[str] = None
username: Optional[str] = None
password: Optional[str] = None
ssl_ca: Optional[str] = None
ssl_cert: Optional[str] = None
ssl_key: Optional[str] = None
ssl_verify_server_cert: bool = False
pool_size: int = 20
max_overflow: int = 20
pool_pre_ping: bool = True
backup_strategy: DatabaseBackupStrategy = DatabaseBackupStrategy.IN_MEMORY
# database backup directory
backup_directory: str = Field(
default_factory=lambda: os.path.join(
GlobalConfiguration().config_directory,
SQL_STORE_BACKUP_DIRECTORY_NAME,
)
)
backup_database: Optional[str] = None
@validator("secrets_store")
def validate_secrets_store(
cls, secrets_store: Optional[SecretsStoreConfiguration]
) -> SecretsStoreConfiguration:
"""Ensures that the secrets store is initialized with a default SQL secrets store.
Args:
secrets_store: The secrets store config to be validated.
Returns:
The validated secrets store config.
"""
if secrets_store is None:
secrets_store = SqlSecretsStoreConfiguration()
return secrets_store
@root_validator(pre=True)
def _remove_grpc_attributes(cls, values: Dict[str, Any]) -> Dict[str, Any]:
"""Removes old GRPC attributes.
Args:
values: All model attribute values.
Returns:
The model attribute values
"""
grpc_attribute_keys = [
"grpc_metadata_host",
"grpc_metadata_port",
"grpc_metadata_ssl_ca",
"grpc_metadata_ssl_key",
"grpc_metadata_ssl_cert",
]
grpc_values = [values.pop(key, None) for key in grpc_attribute_keys]
if any(grpc_values):
logger.warning(
"The GRPC attributes %s are unused and will be removed soon. "
"Please remove them from SQLZenStore configuration. This will "
"become an error in future versions of ZenML."
)
return values
@root_validator
def _validate_backup_strategy(
cls, values: Dict[str, Any]
) -> Dict[str, Any]:
"""Validate the backup strategy.
Args:
values: All model attribute values.
Returns:
The model attribute values.
Raises:
ValueError: If the backup database name is not set when the backup
database is requested.
"""
backup_strategy = values.get("backup_strategy")
if backup_strategy == DatabaseBackupStrategy.DATABASE and (
not values.get("backup_database")
):
raise ValueError(
"The `backup_database` attribute must also be set if the "
"backup strategy is set to use a backup database."
)
return values
@root_validator
def _validate_url(cls, values: Dict[str, Any]) -> Dict[str, Any]:
"""Validate the SQL URL.
The validator also moves the MySQL username, password and database
parameters from the URL into the other configuration arguments, if they
are present in the URL.
Args:
values: The values to validate.
Returns:
The validated values.
Raises:
ValueError: If the URL is invalid or the SQL driver is not
supported.
"""
url = values.get("url")
if url is None:
return values
# When running inside a container, if the URL uses localhost, the
# target service will not be available. We try to replace localhost
# with one of the special Docker or K3D internal hostnames.
url = replace_localhost_with_internal_hostname(url)
try:
sql_url = make_url(url)
except ArgumentError as e:
raise ValueError(
"Invalid SQL URL `%s`: %s. The URL must be in the format "
"`driver://[[username:password@]hostname:port]/database["
"?<extra-args>]`.",
url,
str(e),
)
if sql_url.drivername not in SQLDatabaseDriver.values():
raise ValueError(
"Invalid SQL driver value `%s`: The driver must be one of: %s.",
url,
", ".join(SQLDatabaseDriver.values()),
)
values["driver"] = SQLDatabaseDriver(sql_url.drivername)
if sql_url.drivername == SQLDatabaseDriver.SQLITE:
if (
sql_url.username
or sql_url.password
or sql_url.query
or sql_url.database is None
):
raise ValueError(
"Invalid SQLite URL `%s`: The URL must be in the "
"format `sqlite:///path/to/database.db`.",
url,
)
if values.get("username") or values.get("password"):
raise ValueError(
"Invalid SQLite configuration: The username and password "
"must not be set",
url,
)
values["database"] = sql_url.database
elif sql_url.drivername == SQLDatabaseDriver.MYSQL:
if sql_url.username:
values["username"] = sql_url.username
sql_url = sql_url._replace(username=None)
if sql_url.password:
values["password"] = sql_url.password
sql_url = sql_url._replace(password=None)
if sql_url.database:
values["database"] = sql_url.database
sql_url = sql_url._replace(database=None)
if sql_url.query:
for k, v in sql_url.query.items():
if k == "ssl_ca":
values["ssl_ca"] = v
elif k == "ssl_cert":
values["ssl_cert"] = v
elif k == "ssl_key":
values["ssl_key"] = v
elif k == "ssl_verify_server_cert":
values["ssl_verify_server_cert"] = v
else:
raise ValueError(
"Invalid MySQL URL query parameter `%s`: The "
"parameter must be one of: ssl_ca, ssl_cert, "
"ssl_key, or ssl_verify_server_cert.",
k,
)
sql_url = sql_url._replace(query={})
database = values.get("database")
if (
not values.get("username")
or not values.get("password")
or not database
):
raise ValueError(
"Invalid MySQL configuration: The username, password and "
"database must be set in the URL or as configuration "
"attributes",
)
regexp = r"^[^\\/?%*:|\"<>.-]{1,64}$"
match = re.match(regexp, database)
if not match:
raise ValueError(
f"The database name does not conform to the required "
f"format "
f"rules ({regexp}): {database}"
)
# Save the certificates in a secure location on disk
secret_folder = Path(
GlobalConfiguration().local_stores_path,
"certificates",
)
for key in ["ssl_key", "ssl_ca", "ssl_cert"]:
content = values.get(key)
if content and not os.path.isfile(content):
fileio.makedirs(str(secret_folder))
file_path = Path(secret_folder, f"{key}.pem")
with open(file_path, "w") as f:
f.write(content)
file_path.chmod(0o600)
values[key] = str(file_path)
values["url"] = str(sql_url)
return values
@staticmethod
def get_local_url(path: str) -> str:
"""Get a local SQL url for a given local path.
Args:
path: The path to the local sqlite file.
Returns:
The local SQL url for the given path.
"""
return f"sqlite:///{path}/{ZENML_SQLITE_DB_FILENAME}"
@classmethod
def supports_url_scheme(cls, url: str) -> bool:
"""Check if a URL scheme is supported by this store.
Args:
url: The URL to check.
Returns:
True if the URL scheme is supported, False otherwise.
"""
return make_url(url).drivername in SQLDatabaseDriver.values()
def expand_certificates(self) -> None:
"""Expands the certificates in the verify_ssl field."""
# Load the certificate values back into the configuration
for key in ["ssl_key", "ssl_ca", "ssl_cert"]:
file_path = getattr(self, key, None)
if file_path and os.path.isfile(file_path):
with open(file_path, "r") as f:
setattr(self, key, f.read())
def get_sqlalchemy_config(
self,
database: Optional[str] = None,
) -> Tuple[URL, Dict[str, Any], Dict[str, Any]]:
"""Get the SQLAlchemy engine configuration for the SQL ZenML store.
Args:
database: Custom database name to use. If not set, the database name
from the configuration will be used.
Returns:
The URL and connection arguments for the SQLAlchemy engine.
Raises:
NotImplementedError: If the SQL driver is not supported.
"""
sql_url = make_url(self.url)
sqlalchemy_connect_args: Dict[str, Any] = {}
engine_args = {}
if sql_url.drivername == SQLDatabaseDriver.SQLITE:
assert self.database is not None
# The following default value is needed for sqlite to avoid the
# Error:
# sqlite3.ProgrammingError: SQLite objects created in a thread can
# only be used in that same thread.
sqlalchemy_connect_args = {"check_same_thread": False}
elif sql_url.drivername == SQLDatabaseDriver.MYSQL:
# all these are guaranteed by our root validator
assert self.database is not None
assert self.username is not None
assert self.password is not None
assert sql_url.host is not None
if not database:
database = self.database
engine_args = {
"pool_size": self.pool_size,
"max_overflow": self.max_overflow,
"pool_pre_ping": self.pool_pre_ping,
}
sql_url = sql_url._replace(
drivername="mysql+pymysql",
username=self.username,
password=self.password,
database=database,
)
sqlalchemy_ssl_args: Dict[str, Any] = {}
# Handle SSL params
for key in ["ssl_key", "ssl_ca", "ssl_cert"]:
ssl_setting = getattr(self, key)
if not ssl_setting:
continue
if not os.path.isfile(ssl_setting):
logger.warning(
f"Database SSL setting `{key}` is not a file. "
)
sqlalchemy_ssl_args[key.lstrip("ssl_")] = ssl_setting
if len(sqlalchemy_ssl_args) > 0:
sqlalchemy_ssl_args["check_hostname"] = (
self.ssl_verify_server_cert
)
sqlalchemy_connect_args["ssl"] = sqlalchemy_ssl_args
else:
raise NotImplementedError(
f"SQL driver `{sql_url.drivername}` is not supported."
)
return sql_url, sqlalchemy_connect_args, engine_args
class Config:
"""Pydantic configuration class."""
# Don't validate attributes when assigning them. This is necessary
# because the certificate attributes can be expanded to the contents
# of the certificate files.
validate_assignment = False
# Forbid extra attributes set in the class.
extra = "forbid"
Config
Pydantic configuration class.
Source code in zenml/zen_stores/sql_zen_store.py
class Config:
"""Pydantic configuration class."""
# Don't validate attributes when assigning them. This is necessary
# because the certificate attributes can be expanded to the contents
# of the certificate files.
validate_assignment = False
# Forbid extra attributes set in the class.
extra = "forbid"
expand_certificates(self)
Expands the certificates in the verify_ssl field.
Source code in zenml/zen_stores/sql_zen_store.py
def expand_certificates(self) -> None:
"""Expands the certificates in the verify_ssl field."""
# Load the certificate values back into the configuration
for key in ["ssl_key", "ssl_ca", "ssl_cert"]:
file_path = getattr(self, key, None)
if file_path and os.path.isfile(file_path):
with open(file_path, "r") as f:
setattr(self, key, f.read())
get_local_url(path)
staticmethod
Get a local SQL url for a given local path.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
path |
str |
The path to the local sqlite file. |
required |
Returns:
| Type | Description |
|---|---|
str |
The local SQL url for the given path. |
Source code in zenml/zen_stores/sql_zen_store.py
@staticmethod
def get_local_url(path: str) -> str:
"""Get a local SQL url for a given local path.
Args:
path: The path to the local sqlite file.
Returns:
The local SQL url for the given path.
"""
return f"sqlite:///{path}/{ZENML_SQLITE_DB_FILENAME}"
get_sqlalchemy_config(self, database=None)
Get the SQLAlchemy engine configuration for the SQL ZenML store.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
database |
Optional[str] |
Custom database name to use. If not set, the database name from the configuration will be used. |
None |
Returns:
| Type | Description |
|---|---|
Tuple[sqlalchemy.engine.url.URL, Dict[str, Any], Dict[str, Any]] |
The URL and connection arguments for the SQLAlchemy engine. |
Exceptions:
| Type | Description |
|---|---|
NotImplementedError |
If the SQL driver is not supported. |
Source code in zenml/zen_stores/sql_zen_store.py
def get_sqlalchemy_config(
self,
database: Optional[str] = None,
) -> Tuple[URL, Dict[str, Any], Dict[str, Any]]:
"""Get the SQLAlchemy engine configuration for the SQL ZenML store.
Args:
database: Custom database name to use. If not set, the database name
from the configuration will be used.
Returns:
The URL and connection arguments for the SQLAlchemy engine.
Raises:
NotImplementedError: If the SQL driver is not supported.
"""
sql_url = make_url(self.url)
sqlalchemy_connect_args: Dict[str, Any] = {}
engine_args = {}
if sql_url.drivername == SQLDatabaseDriver.SQLITE:
assert self.database is not None
# The following default value is needed for sqlite to avoid the
# Error:
# sqlite3.ProgrammingError: SQLite objects created in a thread can
# only be used in that same thread.
sqlalchemy_connect_args = {"check_same_thread": False}
elif sql_url.drivername == SQLDatabaseDriver.MYSQL:
# all these are guaranteed by our root validator
assert self.database is not None
assert self.username is not None
assert self.password is not None
assert sql_url.host is not None
if not database:
database = self.database
engine_args = {
"pool_size": self.pool_size,
"max_overflow": self.max_overflow,
"pool_pre_ping": self.pool_pre_ping,
}
sql_url = sql_url._replace(
drivername="mysql+pymysql",
username=self.username,
password=self.password,
database=database,
)
sqlalchemy_ssl_args: Dict[str, Any] = {}
# Handle SSL params
for key in ["ssl_key", "ssl_ca", "ssl_cert"]:
ssl_setting = getattr(self, key)
if not ssl_setting:
continue
if not os.path.isfile(ssl_setting):
logger.warning(
f"Database SSL setting `{key}` is not a file. "
)
sqlalchemy_ssl_args[key.lstrip("ssl_")] = ssl_setting
if len(sqlalchemy_ssl_args) > 0:
sqlalchemy_ssl_args["check_hostname"] = (
self.ssl_verify_server_cert
)
sqlalchemy_connect_args["ssl"] = sqlalchemy_ssl_args
else:
raise NotImplementedError(
f"SQL driver `{sql_url.drivername}` is not supported."
)
return sql_url, sqlalchemy_connect_args, engine_args
supports_url_scheme(url)
classmethod
Check if a URL scheme is supported by this store.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
url |
str |
The URL to check. |
required |
Returns:
| Type | Description |
|---|---|
bool |
True if the URL scheme is supported, False otherwise. |
Source code in zenml/zen_stores/sql_zen_store.py
@classmethod
def supports_url_scheme(cls, url: str) -> bool:
"""Check if a URL scheme is supported by this store.
Args:
url: The URL to check.
Returns:
True if the URL scheme is supported, False otherwise.
"""
return make_url(url).drivername in SQLDatabaseDriver.values()
validate_secrets_store(secrets_store)
classmethod
Ensures that the secrets store is initialized with a default SQL secrets store.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secrets_store |
Optional[zenml.config.secrets_store_config.SecretsStoreConfiguration] |
The secrets store config to be validated. |
required |
Returns:
| Type | Description |
|---|---|
SecretsStoreConfiguration |
The validated secrets store config. |
Source code in zenml/zen_stores/sql_zen_store.py
@validator("secrets_store")
def validate_secrets_store(
cls, secrets_store: Optional[SecretsStoreConfiguration]
) -> SecretsStoreConfiguration:
"""Ensures that the secrets store is initialized with a default SQL secrets store.
Args:
secrets_store: The secrets store config to be validated.
Returns:
The validated secrets store config.
"""
if secrets_store is None:
secrets_store = SqlSecretsStoreConfiguration()
return secrets_store
zen_store_interface
ZenML Store interface.
ZenStoreInterface (ABC)
ZenML store interface.
All ZenML stores must implement the methods in this interface.
The methods in this interface are organized in the following way:
-
they are grouped into categories based on the type of resource that they operate on (e.g. stacks, stack components, etc.)
-
each category has a set of CRUD methods (create, read, update, delete) that operate on the resources in that category. The order of the methods in each category should be:
-
create methods - store a new resource. These methods should fill in generated fields (e.g. UUIDs, creation timestamps) in the resource and return the updated resource.
- get methods - retrieve a single existing resource identified by a unique key or identifier from the store. These methods should always return a resource and raise an exception if the resource does not exist.
- list methods - retrieve a list of resources from the store. These methods should accept a set of filter parameters that can be used to filter the list of resources retrieved from the store.
- update methods - update an existing resource in the store. These methods should expect the updated resource to be correctly identified by its unique key or identifier and raise an exception if the resource does not exist.
- delete methods - delete an existing resource from the store. These methods should expect the resource to be correctly identified by its unique key or identifier. If the resource does not exist, an exception should be raised.
Best practices for implementing and keeping this interface clean and easy to maintain and extend:
- keep methods organized by resource type and ordered by CRUD operation
- for resources with multiple keys, don't implement multiple get or list methods here if the same functionality can be achieved by a single get or list method. Instead, implement them in the BaseZenStore class and have them call the generic get or list method in this interface.
- keep the logic required to convert between ZenML domain Model classes and internal store representations outside the ZenML domain Model classes
- methods for resources that have two or more unique keys (e.g. a Workspace
is uniquely identified by its name as well as its UUID) should reflect
that in the method variants and/or method arguments:
- methods that take in a resource identifier as argument should accept
all variants of the identifier (e.g.
workspace_name_or_uuidfor methods that get/list/update/delete Workspaces) - if a compound key is involved, separate get methods should be
implemented (e.g.
get_pipelineto get a pipeline by ID andget_pipeline_in_workspaceto get a pipeline by its name and the ID of the workspace it belongs to)
- methods that take in a resource identifier as argument should accept
all variants of the identifier (e.g.
- methods for resources that are scoped as children of other resources
(e.g. a Stack is always owned by a Workspace) should reflect the
key(s) of the parent resource in the provided methods and method
arguments:
- create methods should take the parent resource UUID(s) as an argument
(e.g.
create_stacktakes in the workspace ID) - get methods should be provided to retrieve a resource by the compound key that includes the parent resource key(s)
- list methods should feature optional filter arguments that reflect the parent resource key(s)
- create methods should take the parent resource UUID(s) as an argument
(e.g.
Source code in zenml/zen_stores/zen_store_interface.py
class ZenStoreInterface(ABC):
"""ZenML store interface.
All ZenML stores must implement the methods in this interface.
The methods in this interface are organized in the following way:
* they are grouped into categories based on the type of resource
that they operate on (e.g. stacks, stack components, etc.)
* each category has a set of CRUD methods (create, read, update, delete)
that operate on the resources in that category. The order of the methods
in each category should be:
* create methods - store a new resource. These methods
should fill in generated fields (e.g. UUIDs, creation timestamps) in
the resource and return the updated resource.
* get methods - retrieve a single existing resource identified by a
unique key or identifier from the store. These methods should always
return a resource and raise an exception if the resource does not
exist.
* list methods - retrieve a list of resources from the store. These
methods should accept a set of filter parameters that can be used to
filter the list of resources retrieved from the store.
* update methods - update an existing resource in the store. These
methods should expect the updated resource to be correctly identified
by its unique key or identifier and raise an exception if the resource
does not exist.
* delete methods - delete an existing resource from the store. These
methods should expect the resource to be correctly identified by its
unique key or identifier. If the resource does not exist,
an exception should be raised.
Best practices for implementing and keeping this interface clean and easy to
maintain and extend:
* keep methods organized by resource type and ordered by CRUD operation
* for resources with multiple keys, don't implement multiple get or list
methods here if the same functionality can be achieved by a single get or
list method. Instead, implement them in the BaseZenStore class and have
them call the generic get or list method in this interface.
* keep the logic required to convert between ZenML domain Model classes
and internal store representations outside the ZenML domain Model classes
* methods for resources that have two or more unique keys (e.g. a Workspace
is uniquely identified by its name as well as its UUID) should reflect
that in the method variants and/or method arguments:
* methods that take in a resource identifier as argument should accept
all variants of the identifier (e.g. `workspace_name_or_uuid` for methods
that get/list/update/delete Workspaces)
* if a compound key is involved, separate get methods should be
implemented (e.g. `get_pipeline` to get a pipeline by ID and
`get_pipeline_in_workspace` to get a pipeline by its name and the ID of
the workspace it belongs to)
* methods for resources that are scoped as children of other resources
(e.g. a Stack is always owned by a Workspace) should reflect the
key(s) of the parent resource in the provided methods and method
arguments:
* create methods should take the parent resource UUID(s) as an argument
(e.g. `create_stack` takes in the workspace ID)
* get methods should be provided to retrieve a resource by the compound
key that includes the parent resource key(s)
* list methods should feature optional filter arguments that reflect
the parent resource key(s)
"""
# ---------------------------------
# Initialization and configuration
# ---------------------------------
@abstractmethod
def _initialize(self) -> None:
"""Initialize the store.
This method is called immediately after the store is created. It should
be used to set up the backend (database, connection etc.).
"""
@abstractmethod
def get_store_info(self) -> ServerModel:
"""Get information about the store.
Returns:
Information about the store.
"""
@abstractmethod
def get_deployment_id(self) -> UUID:
"""Get the ID of the deployment.
Returns:
The ID of the deployment.
"""
# -------------------- API Keys --------------------
@abstractmethod
def create_api_key(
self, service_account_id: UUID, api_key: APIKeyRequest
) -> APIKeyResponse:
"""Create a new API key for a service account.
Args:
service_account_id: The ID of the service account for which to
create the API key.
api_key: The API key to create.
Returns:
The created API key.
Raises:
KeyError: If the service account doesn't exist.
EntityExistsError: If an API key with the same name is already
configured for the same service account.
"""
@abstractmethod
def get_api_key(
self,
service_account_id: UUID,
api_key_name_or_id: Union[str, UUID],
hydrate: bool = True,
) -> APIKeyResponse:
"""Get an API key for a service account.
Args:
service_account_id: The ID of the service account for which to fetch
the API key.
api_key_name_or_id: The name or ID of the API key to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The API key with the given ID.
Raises:
KeyError: if an API key with the given name or ID is not configured
for the given service account.
"""
@abstractmethod
def list_api_keys(
self,
service_account_id: UUID,
filter_model: APIKeyFilter,
hydrate: bool = False,
) -> Page[APIKeyResponse]:
"""List all API keys for a service account matching the given filter criteria.
Args:
service_account_id: The ID of the service account for which to list
the API keys.
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all API keys matching the filter criteria.
"""
@abstractmethod
def update_api_key(
self,
service_account_id: UUID,
api_key_name_or_id: Union[str, UUID],
api_key_update: APIKeyUpdate,
) -> APIKeyResponse:
"""Update an API key for a service account.
Args:
service_account_id: The ID of the service account for which to update
the API key.
api_key_name_or_id: The name or ID of the API key to update.
api_key_update: The update request on the API key.
Returns:
The updated API key.
Raises:
KeyError: if an API key with the given name or ID is not configured
for the given service account.
EntityExistsError: if the API key update would result in a name
conflict with an existing API key for the same service account.
"""
@abstractmethod
def rotate_api_key(
self,
service_account_id: UUID,
api_key_name_or_id: Union[str, UUID],
rotate_request: APIKeyRotateRequest,
) -> APIKeyResponse:
"""Rotate an API key for a service account.
Args:
service_account_id: The ID of the service account for which to
rotate the API key.
api_key_name_or_id: The name or ID of the API key to rotate.
rotate_request: The rotate request on the API key.
Returns:
The updated API key.
Raises:
KeyError: if an API key with the given name or ID is not configured
for the given service account.
"""
@abstractmethod
def delete_api_key(
self,
service_account_id: UUID,
api_key_name_or_id: Union[str, UUID],
) -> None:
"""Delete an API key for a service account.
Args:
service_account_id: The ID of the service account for which to
delete the API key.
api_key_name_or_id: The name or ID of the API key to delete.
Raises:
KeyError: if an API key with the given name or ID is not configured
for the given service account.
"""
# -------------------- Artifacts --------------------
@abstractmethod
def create_artifact(self, artifact: ArtifactRequest) -> ArtifactResponse:
"""Creates a new artifact.
Args:
artifact: The artifact to create.
Returns:
The newly created artifact.
Raises:
EntityExistsError: If an artifact with the same name already exists.
"""
@abstractmethod
def get_artifact(
self, artifact_id: UUID, hydrate: bool = True
) -> ArtifactResponse:
"""Gets an artifact.
Args:
artifact_id: The ID of the artifact to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The artifact.
Raises:
KeyError: if the artifact doesn't exist.
"""
@abstractmethod
def list_artifacts(
self, filter_model: ArtifactFilter, hydrate: bool = False
) -> Page[ArtifactResponse]:
"""List all artifacts matching the given filter criteria.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all artifacts matching the filter criteria.
"""
@abstractmethod
def update_artifact(
self, artifact_id: UUID, artifact_update: ArtifactUpdate
) -> ArtifactResponse:
"""Updates an artifact.
Args:
artifact_id: The ID of the artifact to update.
artifact_update: The update to be applied to the artifact.
Returns:
The updated artifact.
Raises:
KeyError: if the artifact doesn't exist.
"""
@abstractmethod
def delete_artifact(self, artifact_id: UUID) -> None:
"""Deletes an artifact.
Args:
artifact_id: The ID of the artifact to delete.
Raises:
KeyError: if the artifact doesn't exist.
"""
# -------------------- Artifact Versions --------------------
@abstractmethod
def create_artifact_version(
self, artifact_version: ArtifactVersionRequest
) -> ArtifactVersionResponse:
"""Creates an artifact version.
Args:
artifact_version: The artifact version to create.
Returns:
The created artifact version.
"""
@abstractmethod
def get_artifact_version(
self, artifact_version_id: UUID, hydrate: bool = True
) -> ArtifactVersionResponse:
"""Gets an artifact version.
Args:
artifact_version_id: The ID of the artifact version to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The artifact version.
Raises:
KeyError: if the artifact version doesn't exist.
"""
@abstractmethod
def list_artifact_versions(
self,
artifact_version_filter_model: ArtifactVersionFilter,
hydrate: bool = False,
) -> Page[ArtifactVersionResponse]:
"""List all artifact versions matching the given filter criteria.
Args:
artifact_version_filter_model: All filter parameters including
pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all artifact versions matching the filter criteria.
"""
@abstractmethod
def update_artifact_version(
self,
artifact_version_id: UUID,
artifact_version_update: ArtifactVersionUpdate,
) -> ArtifactVersionResponse:
"""Updates an artifact version.
Args:
artifact_version_id: The ID of the artifact version to update.
artifact_version_update: The update to be applied to the artifact
version.
Returns:
The updated artifact version.
Raises:
KeyError: if the artifact version doesn't exist.
"""
@abstractmethod
def delete_artifact_version(self, artifact_version_id: UUID) -> None:
"""Deletes an artifact version.
Args:
artifact_version_id: The ID of the artifact version to delete.
Raises:
KeyError: if the artifact version doesn't exist.
"""
@abstractmethod
def prune_artifact_versions(
self,
only_versions: bool = True,
) -> None:
"""Prunes unused artifact versions and their artifacts.
Args:
only_versions: Only delete artifact versions, keeping artifacts
"""
# -------------------- Artifact Visualization --------------------
@abstractmethod
def get_artifact_visualization(
self, artifact_visualization_id: UUID, hydrate: bool = True
) -> ArtifactVisualizationResponse:
"""Gets an artifact visualization.
Args:
artifact_visualization_id: The ID of the artifact visualization
to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The artifact visualization.
Raises:
KeyError: if the artifact visualization doesn't exist.
"""
# -------------------- Code References --------------------
@abstractmethod
def get_code_reference(
self, code_reference_id: UUID, hydrate: bool = True
) -> CodeReferenceResponse:
"""Gets a specific code reference.
Args:
code_reference_id: The ID of the code reference to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested code reference, if it was found.
Raises:
KeyError: If no code reference with the given ID exists.
"""
# -------------------- Code repositories --------------------
@abstractmethod
def create_code_repository(
self, code_repository: CodeRepositoryRequest
) -> CodeRepositoryResponse:
"""Creates a new code repository.
Args:
code_repository: Code repository to be created.
Returns:
The newly created code repository.
Raises:
EntityExistsError: If a code repository with the given name already
exists.
"""
@abstractmethod
def get_code_repository(
self, code_repository_id: UUID, hydrate: bool = True
) -> CodeRepositoryResponse:
"""Gets a specific code repository.
Args:
code_repository_id: The ID of the code repository to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested code repository, if it was found.
Raises:
KeyError: If no code repository with the given ID exists.
"""
@abstractmethod
def list_code_repositories(
self, filter_model: CodeRepositoryFilter, hydrate: bool = False
) -> Page[CodeRepositoryResponse]:
"""List all code repositories.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all code repositories.
"""
@abstractmethod
def update_code_repository(
self, code_repository_id: UUID, update: CodeRepositoryUpdate
) -> CodeRepositoryResponse:
"""Updates an existing code repository.
Args:
code_repository_id: The ID of the code repository to update.
update: The update to be applied to the code repository.
Returns:
The updated code repository.
Raises:
KeyError: If no code repository with the given name exists.
"""
@abstractmethod
def delete_code_repository(self, code_repository_id: UUID) -> None:
"""Deletes a code repository.
Args:
code_repository_id: The ID of the code repository to delete.
Raises:
KeyError: If no code repository with the given ID exists.
"""
# -------------------- Components --------------------
@abstractmethod
def create_stack_component(
self, component: ComponentRequest
) -> ComponentResponse:
"""Create a stack component.
Args:
component: The stack component to create.
Returns:
The created stack component.
Raises:
StackComponentExistsError: If a stack component with the same name
and type is already owned by this user in this workspace.
"""
@abstractmethod
def get_stack_component(
self,
component_id: UUID,
hydrate: bool = True,
) -> ComponentResponse:
"""Get a stack component by ID.
Args:
component_id: The ID of the stack component to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The stack component.
Raises:
KeyError: if the stack component doesn't exist.
"""
@abstractmethod
def list_stack_components(
self,
component_filter_model: ComponentFilter,
hydrate: bool = False,
) -> Page[ComponentResponse]:
"""List all stack components matching the given filter criteria.
Args:
component_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all stack components matching the filter criteria.
"""
@abstractmethod
def update_stack_component(
self,
component_id: UUID,
component_update: ComponentUpdate,
) -> ComponentResponse:
"""Update an existing stack component.
Args:
component_id: The ID of the stack component to update.
component_update: The update to be applied to the stack component.
Returns:
The updated stack component.
Raises:
KeyError: if the stack component doesn't exist.
"""
@abstractmethod
def delete_stack_component(self, component_id: UUID) -> None:
"""Delete a stack component.
Args:
component_id: The ID of the stack component to delete.
Raises:
KeyError: if the stack component doesn't exist.
ValueError: if the stack component is part of one or more stacks.
"""
# -------------------- Devices --------------------
@abstractmethod
def get_authorized_device(
self, device_id: UUID, hydrate: bool = True
) -> OAuthDeviceResponse:
"""Gets a specific OAuth 2.0 authorized device.
Args:
device_id: The ID of the device to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested device, if it was found.
Raises:
KeyError: If no device with the given ID exists.
"""
@abstractmethod
def list_authorized_devices(
self, filter_model: OAuthDeviceFilter, hydrate: bool = False
) -> Page[OAuthDeviceResponse]:
"""List all OAuth 2.0 authorized devices for a user.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all matching OAuth 2.0 authorized devices.
"""
@abstractmethod
def update_authorized_device(
self, device_id: UUID, update: OAuthDeviceUpdate
) -> OAuthDeviceResponse:
"""Updates an existing OAuth 2.0 authorized device for internal use.
Args:
device_id: The ID of the device to update.
update: The update to be applied to the device.
Returns:
The updated OAuth 2.0 authorized device.
Raises:
KeyError: If no device with the given ID exists.
"""
@abstractmethod
def delete_authorized_device(self, device_id: UUID) -> None:
"""Deletes an OAuth 2.0 authorized device.
Args:
device_id: The ID of the device to delete.
Raises:
KeyError: If no device with the given ID exists.
"""
# -------------------- Flavors --------------------
@abstractmethod
def create_flavor(
self,
flavor: FlavorRequest,
) -> FlavorResponse:
"""Creates a new stack component flavor.
Args:
flavor: The stack component flavor to create.
Returns:
The newly created flavor.
Raises:
EntityExistsError: If a flavor with the same name and type
is already owned by this user in this workspace.
"""
@abstractmethod
def get_flavor(
self, flavor_id: UUID, hydrate: bool = True
) -> FlavorResponse:
"""Get a stack component flavor by ID.
Args:
flavor_id: The ID of the flavor to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The stack component flavor.
Raises:
KeyError: if the stack component flavor doesn't exist.
"""
@abstractmethod
def update_flavor(
self, flavor_id: UUID, flavor_update: FlavorUpdate
) -> FlavorResponse:
"""Updates an existing user.
Args:
flavor_id: The id of the flavor to update.
flavor_update: The update to be applied to the flavor.
Returns:
The updated flavor.
"""
@abstractmethod
def list_flavors(
self,
flavor_filter_model: FlavorFilter,
hydrate: bool = False,
) -> Page[FlavorResponse]:
"""List all stack component flavors matching the given filter criteria.
Args:
flavor_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
List of all the stack component flavors matching the given criteria.
"""
@abstractmethod
def delete_flavor(self, flavor_id: UUID) -> None:
"""Delete a stack component flavor.
Args:
flavor_id: The ID of the stack component flavor to delete.
Raises:
KeyError: if the stack component flavor doesn't exist.
"""
# -------------------- Logs --------------------
@abstractmethod
def get_logs(self, logs_id: UUID, hydrate: bool = True) -> LogsResponse:
"""Get logs by its unique ID.
Args:
logs_id: The ID of the logs to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The logs with the given ID.
Raises:
KeyError: if the logs doesn't exist.
"""
# -------------------- Pipelines --------------------
@abstractmethod
def create_pipeline(
self,
pipeline: PipelineRequest,
) -> PipelineResponse:
"""Creates a new pipeline in a workspace.
Args:
pipeline: The pipeline to create.
Returns:
The newly created pipeline.
Raises:
KeyError: if the workspace does not exist.
EntityExistsError: If an identical pipeline already exists.
"""
@abstractmethod
def get_pipeline(
self, pipeline_id: UUID, hydrate: bool = True
) -> PipelineResponse:
"""Get a pipeline with a given ID.
Args:
pipeline_id: ID of the pipeline.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The pipeline.
Raises:
KeyError: if the pipeline does not exist.
"""
@abstractmethod
def list_pipelines(
self,
pipeline_filter_model: PipelineFilter,
hydrate: bool = False,
) -> Page[PipelineResponse]:
"""List all pipelines matching the given filter criteria.
Args:
pipeline_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all pipelines matching the filter criteria.
"""
@abstractmethod
def update_pipeline(
self,
pipeline_id: UUID,
pipeline_update: PipelineUpdate,
) -> PipelineResponse:
"""Updates a pipeline.
Args:
pipeline_id: The ID of the pipeline to be updated.
pipeline_update: The update to be applied.
Returns:
The updated pipeline.
Raises:
KeyError: if the pipeline doesn't exist.
"""
@abstractmethod
def delete_pipeline(self, pipeline_id: UUID) -> None:
"""Deletes a pipeline.
Args:
pipeline_id: The ID of the pipeline to delete.
Raises:
KeyError: if the pipeline doesn't exist.
"""
# -------------------- Pipeline builds --------------------
@abstractmethod
def create_build(
self,
build: PipelineBuildRequest,
) -> PipelineBuildResponse:
"""Creates a new build in a workspace.
Args:
build: The build to create.
Returns:
The newly created build.
Raises:
KeyError: If the workspace does not exist.
EntityExistsError: If an identical build already exists.
"""
@abstractmethod
def get_build(
self, build_id: UUID, hydrate: bool = True
) -> PipelineBuildResponse:
"""Get a build with a given ID.
Args:
build_id: ID of the build.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The build.
Raises:
KeyError: If the build does not exist.
"""
@abstractmethod
def list_builds(
self,
build_filter_model: PipelineBuildFilter,
hydrate: bool = False,
) -> Page[PipelineBuildResponse]:
"""List all builds matching the given filter criteria.
Args:
build_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all builds matching the filter criteria.
"""
@abstractmethod
def delete_build(self, build_id: UUID) -> None:
"""Deletes a build.
Args:
build_id: The ID of the build to delete.
Raises:
KeyError: if the build doesn't exist.
"""
# -------------------- Pipeline deployments --------------------
@abstractmethod
def create_deployment(
self,
deployment: PipelineDeploymentRequest,
) -> PipelineDeploymentResponse:
"""Creates a new deployment in a workspace.
Args:
deployment: The deployment to create.
Returns:
The newly created deployment.
Raises:
KeyError: If the workspace does not exist.
EntityExistsError: If an identical deployment already exists.
"""
@abstractmethod
def get_deployment(
self, deployment_id: UUID, hydrate: bool = True
) -> PipelineDeploymentResponse:
"""Get a deployment with a given ID.
Args:
deployment_id: ID of the deployment.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The deployment.
Raises:
KeyError: If the deployment does not exist.
"""
@abstractmethod
def list_deployments(
self,
deployment_filter_model: PipelineDeploymentFilter,
hydrate: bool = False,
) -> Page[PipelineDeploymentResponse]:
"""List all deployments matching the given filter criteria.
Args:
deployment_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all deployments matching the filter criteria.
"""
@abstractmethod
def delete_deployment(self, deployment_id: UUID) -> None:
"""Deletes a deployment.
Args:
deployment_id: The ID of the deployment to delete.
Raises:
KeyError: If the deployment doesn't exist.
"""
# -------------------- Event Sources --------------------
@abstractmethod
def create_event_source(
self, event_source: EventSourceRequest
) -> EventSourceResponse:
"""Create an event_source.
Args:
event_source: The event_source to create.
Returns:
The created event_source.
"""
@abstractmethod
def get_event_source(
self,
event_source_id: UUID,
hydrate: bool = True,
) -> EventSourceResponse:
"""Get an event_source by ID.
Args:
event_source_id: The ID of the event_source to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The event_source.
Raises:
KeyError: if the stack event_source doesn't exist.
"""
@abstractmethod
def list_event_sources(
self,
event_source_filter_model: EventSourceFilter,
hydrate: bool = False,
) -> Page[EventSourceResponse]:
"""List all event_sources matching the given filter criteria.
Args:
event_source_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all event_sources matching the filter criteria.
"""
@abstractmethod
def update_event_source(
self,
event_source_id: UUID,
event_source_update: EventSourceUpdate,
) -> EventSourceResponse:
"""Update an existing event_source.
Args:
event_source_id: The ID of the event_source to update.
event_source_update: The update to be applied to the event_source.
Returns:
The updated event_source.
Raises:
KeyError: if the event_source doesn't exist.
"""
@abstractmethod
def delete_event_source(self, event_source_id: UUID) -> None:
"""Delete an event_source.
Args:
event_source_id: The ID of the event_source to delete.
Raises:
KeyError: if the event_source doesn't exist.
"""
# -------------------- Pipeline runs --------------------
@abstractmethod
def create_run(
self, pipeline_run: PipelineRunRequest
) -> PipelineRunResponse:
"""Creates a pipeline run.
Args:
pipeline_run: The pipeline run to create.
Returns:
The created pipeline run.
Raises:
EntityExistsError: If an identical pipeline run already exists.
KeyError: If the pipeline does not exist.
"""
@abstractmethod
def get_run(
self, run_name_or_id: Union[str, UUID], hydrate: bool = True
) -> PipelineRunResponse:
"""Gets a pipeline run.
Args:
run_name_or_id: The name or ID of the pipeline run to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The pipeline run.
Raises:
KeyError: if the pipeline run doesn't exist.
"""
@abstractmethod
def list_runs(
self,
runs_filter_model: PipelineRunFilter,
hydrate: bool = False,
) -> Page[PipelineRunResponse]:
"""List all pipeline runs matching the given filter criteria.
Args:
runs_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all pipeline runs matching the filter criteria.
"""
@abstractmethod
def update_run(
self, run_id: UUID, run_update: PipelineRunUpdate
) -> PipelineRunResponse:
"""Updates a pipeline run.
Args:
run_id: The ID of the pipeline run to update.
run_update: The update to be applied to the pipeline run.
Returns:
The updated pipeline run.
Raises:
KeyError: if the pipeline run doesn't exist.
"""
@abstractmethod
def delete_run(self, run_id: UUID) -> None:
"""Deletes a pipeline run.
Args:
run_id: The ID of the pipeline run to delete.
Raises:
KeyError: if the pipeline run doesn't exist.
"""
@abstractmethod
def get_or_create_run(
self, pipeline_run: PipelineRunRequest
) -> Tuple[PipelineRunResponse, bool]:
"""Gets or creates a pipeline run.
If a run with the same ID or name already exists, it is returned.
Otherwise, a new run is created.
Args:
pipeline_run: The pipeline run to get or create.
Returns:
The pipeline run, and a boolean indicating whether the run was
created or not.
"""
# -------------------- Run metadata --------------------
@abstractmethod
def create_run_metadata(
self, run_metadata: RunMetadataRequest
) -> List[RunMetadataResponse]:
"""Creates run metadata.
Args:
run_metadata: The run metadata to create.
Returns:
The created run metadata.
"""
@abstractmethod
def get_run_metadata(
self, run_metadata_id: UUID, hydrate: bool = True
) -> RunMetadataResponse:
"""Get run metadata by its unique ID.
Args:
run_metadata_id: The ID of the run metadata to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The run metadata with the given ID.
Raises:
KeyError: if the run metadata doesn't exist.
"""
@abstractmethod
def list_run_metadata(
self,
run_metadata_filter_model: RunMetadataFilter,
hydrate: bool = False,
) -> Page[RunMetadataResponse]:
"""List run metadata.
Args:
run_metadata_filter_model: All filter parameters including
pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The run metadata.
"""
# -------------------- Schedules --------------------
@abstractmethod
def create_schedule(self, schedule: ScheduleRequest) -> ScheduleResponse:
"""Creates a new schedule.
Args:
schedule: The schedule to create.
Returns:
The newly created schedule.
"""
@abstractmethod
def get_schedule(
self, schedule_id: UUID, hydrate: bool = True
) -> ScheduleResponse:
"""Get a schedule with a given ID.
Args:
schedule_id: ID of the schedule.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The schedule.
Raises:
KeyError: if the schedule does not exist.
"""
@abstractmethod
def list_schedules(
self,
schedule_filter_model: ScheduleFilter,
hydrate: bool = False,
) -> Page[ScheduleResponse]:
"""List all schedules in the workspace.
Args:
schedule_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of schedules.
"""
@abstractmethod
def update_schedule(
self,
schedule_id: UUID,
schedule_update: ScheduleUpdate,
) -> ScheduleResponse:
"""Updates a schedule.
Args:
schedule_id: The ID of the schedule to be updated.
schedule_update: The update to be applied.
Returns:
The updated schedule.
Raises:
KeyError: if the schedule doesn't exist.
"""
@abstractmethod
def delete_schedule(self, schedule_id: UUID) -> None:
"""Deletes a schedule.
Args:
schedule_id: The ID of the schedule to delete.
Raises:
KeyError: if the schedule doesn't exist.
"""
# -------------------- Secrets --------------------
@abstractmethod
def create_secret(
self,
secret: SecretRequest,
) -> SecretResponse:
"""Creates a new secret.
The new secret is also validated against the scoping rules enforced in
the secrets store:
- only one workspace-scoped secret with the given name can exist
in the target workspace.
- only one user-scoped secret with the given name can exist in the
target workspace for the target user.
Args:
secret: The secret to create.
Returns:
The newly created secret.
Raises:
KeyError: if the user or workspace does not exist.
EntityExistsError: If a secret with the same name already exists in
the same scope.
"""
@abstractmethod
def get_secret(
self, secret_id: UUID, hydrate: bool = True
) -> SecretResponse:
"""Get a secret with a given name.
Args:
secret_id: ID of the secret.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The secret.
Raises:
KeyError: if the secret does not exist.
"""
@abstractmethod
def list_secrets(
self, secret_filter_model: SecretFilter, hydrate: bool = False
) -> Page[SecretResponse]:
"""List all secrets matching the given filter criteria.
Note that returned secrets do not include any secret values. To fetch
the secret values, use `get_secret`.
Args:
secret_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all secrets matching the filter criteria, with pagination
information and sorted according to the filter criteria. The
returned secrets do not include any secret values, only metadata. To
fetch the secret values, use `get_secret` individually with each
secret.
"""
@abstractmethod
def update_secret(
self,
secret_id: UUID,
secret_update: SecretUpdate,
) -> SecretResponse:
"""Updates a secret.
Secret values that are specified as `None` in the update that are
present in the existing secret are removed from the existing secret.
Values that are present in both secrets are overwritten. All other
values in both the existing secret and the update are kept (merged).
If the update includes a change of name or scope, the scoping rules
enforced in the secrets store are used to validate the update:
- only one workspace-scoped secret with the given name can exist
in the target workspace.
- only one user-scoped secret with the given name can exist in the
target workspace for the target user.
Args:
secret_id: The ID of the secret to be updated.
secret_update: The update to be applied.
Returns:
The updated secret.
Raises:
KeyError: if the secret doesn't exist.
EntityExistsError: If a secret with the same name already exists in
the same scope.
"""
@abstractmethod
def delete_secret(self, secret_id: UUID) -> None:
"""Deletes a secret.
Args:
secret_id: The ID of the secret to delete.
Raises:
KeyError: if the secret doesn't exist.
"""
@abstractmethod
def backup_secrets(
self, ignore_errors: bool = True, delete_secrets: bool = False
) -> None:
"""Backs up all secrets to the configured backup secrets store.
Args:
ignore_errors: Whether to ignore individual errors during the backup
process and attempt to backup all secrets.
delete_secrets: Whether to delete the secrets that have been
successfully backed up from the primary secrets store. Setting
this flag effectively moves all secrets from the primary secrets
store to the backup secrets store.
Raises:
BackupSecretsStoreNotConfiguredError: if no backup secrets store is
configured.
"""
@abstractmethod
def restore_secrets(
self, ignore_errors: bool = False, delete_secrets: bool = False
) -> None:
"""Restore all secrets from the configured backup secrets store.
Args:
ignore_errors: Whether to ignore individual errors during the
restore process and attempt to restore all secrets.
delete_secrets: Whether to delete the secrets that have been
successfully restored from the backup secrets store. Setting
this flag effectively moves all secrets from the backup secrets
store to the primary secrets store.
Raises:
BackupSecretsStoreNotConfiguredError: if no backup secrets store is
configured.
"""
# -------------------- Service Accounts --------------------
@abstractmethod
def create_service_account(
self, service_account: ServiceAccountRequest
) -> ServiceAccountResponse:
"""Creates a new service account.
Args:
service_account: Service account to be created.
Returns:
The newly created service account.
Raises:
EntityExistsError: If a user or service account with the given name
already exists.
"""
@abstractmethod
def get_service_account(
self,
service_account_name_or_id: Union[str, UUID],
hydrate: bool = True,
) -> ServiceAccountResponse:
"""Gets a specific service account.
Args:
service_account_name_or_id: The name or ID of the service account to
get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested service account, if it was found.
Raises:
KeyError: If no service account with the given name or ID exists.
"""
@abstractmethod
def list_service_accounts(
self,
filter_model: ServiceAccountFilter,
hydrate: bool = False,
) -> Page[ServiceAccountResponse]:
"""List all service accounts.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of filtered service accounts.
"""
@abstractmethod
def update_service_account(
self,
service_account_name_or_id: Union[str, UUID],
service_account_update: ServiceAccountUpdate,
) -> ServiceAccountResponse:
"""Updates an existing service account.
Args:
service_account_name_or_id: The name or the ID of the service
account to update.
service_account_update: The update to be applied to the service
account.
Returns:
The updated service account.
Raises:
KeyError: If no service account with the given name exists.
"""
@abstractmethod
def delete_service_account(
self,
service_account_name_or_id: Union[str, UUID],
) -> None:
"""Delete a service account.
Args:
service_account_name_or_id: The name or the ID of the service
account to delete.
Raises:
IllegalOperationError: if the service account has already been used
to create other resources.
"""
# -------------------- Service Connectors --------------------
@abstractmethod
def create_service_connector(
self,
service_connector: ServiceConnectorRequest,
) -> ServiceConnectorResponse:
"""Creates a new service connector.
Args:
service_connector: Service connector to be created.
Returns:
The newly created service connector.
Raises:
EntityExistsError: If a service connector with the given name
is already owned by this user in this workspace.
"""
@abstractmethod
def get_service_connector(
self, service_connector_id: UUID, hydrate: bool = True
) -> ServiceConnectorResponse:
"""Gets a specific service connector.
Args:
service_connector_id: The ID of the service connector to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested service connector, if it was found.
Raises:
KeyError: If no service connector with the given ID exists.
"""
@abstractmethod
def list_service_connectors(
self,
filter_model: ServiceConnectorFilter,
hydrate: bool = False,
) -> Page[ServiceConnectorResponse]:
"""List all service connectors.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all service connectors.
"""
@abstractmethod
def update_service_connector(
self, service_connector_id: UUID, update: ServiceConnectorUpdate
) -> ServiceConnectorResponse:
"""Updates an existing service connector.
The update model contains the fields to be updated. If a field value is
set to None in the model, the field is not updated, but there are
special rules concerning some fields:
* the `configuration` and `secrets` fields together represent a full
valid configuration update, not just a partial update. If either is
set (i.e. not None) in the update, their values are merged together and
will replace the existing configuration and secrets values.
* the `resource_id` field value is also a full replacement value: if set
to `None`, the resource ID is removed from the service connector.
* the `expiration_seconds` field value is also a full replacement value:
if set to `None`, the expiration is removed from the service connector.
* the `secret_id` field value in the update is ignored, given that
secrets are managed internally by the ZenML store.
* the `labels` field is also a full labels update: if set (i.e. not
`None`), all existing labels are removed and replaced by the new labels
in the update.
Args:
service_connector_id: The ID of the service connector to update.
update: The update to be applied to the service connector.
Returns:
The updated service connector.
Raises:
KeyError: If no service connector with the given name exists.
"""
@abstractmethod
def delete_service_connector(self, service_connector_id: UUID) -> None:
"""Deletes a service connector.
Args:
service_connector_id: The ID of the service connector to delete.
Raises:
KeyError: If no service connector with the given ID exists.
"""
@abstractmethod
def verify_service_connector_config(
self,
service_connector: ServiceConnectorRequest,
list_resources: bool = True,
) -> ServiceConnectorResourcesModel:
"""Verifies if a service connector configuration has access to resources.
Args:
service_connector: The service connector configuration to verify.
list_resources: If True, the list of all resources accessible
through the service connector is returned.
Returns:
The list of resources that the service connector configuration has
access to.
Raises:
NotImplementError: If the service connector cannot be verified
on the store e.g. due to missing package dependencies.
"""
@abstractmethod
def verify_service_connector(
self,
service_connector_id: UUID,
resource_type: Optional[str] = None,
resource_id: Optional[str] = None,
list_resources: bool = True,
) -> ServiceConnectorResourcesModel:
"""Verifies if a service connector instance has access to one or more resources.
Args:
service_connector_id: The ID of the service connector to verify.
resource_type: The type of resource to verify access to.
resource_id: The ID of the resource to verify access to.
list_resources: If True, the list of all resources accessible
through the service connector and matching the supplied resource
type and ID are returned.
Returns:
The list of resources that the service connector has access to,
scoped to the supplied resource type and ID, if provided.
Raises:
KeyError: If no service connector with the given name exists.
NotImplementError: If the service connector cannot be verified
e.g. due to missing package dependencies.
"""
@abstractmethod
def get_service_connector_client(
self,
service_connector_id: UUID,
resource_type: Optional[str] = None,
resource_id: Optional[str] = None,
) -> ServiceConnectorResponse:
"""Get a service connector client for a service connector and given resource.
Args:
service_connector_id: The ID of the base service connector to use.
resource_type: The type of resource to get a client for.
resource_id: The ID of the resource to get a client for.
Returns:
A service connector client that can be used to access the given
resource.
Raises:
KeyError: If no service connector with the given name exists.
NotImplementError: If the service connector cannot be instantiated
on the store e.g. due to missing package dependencies.
"""
@abstractmethod
def list_service_connector_resources(
self,
workspace_name_or_id: Union[str, UUID],
connector_type: Optional[str] = None,
resource_type: Optional[str] = None,
resource_id: Optional[str] = None,
) -> List[ServiceConnectorResourcesModel]:
"""List resources that can be accessed by service connectors.
Args:
workspace_name_or_id: The name or ID of the workspace to scope to.
connector_type: The type of service connector to scope to.
resource_type: The type of resource to scope to.
resource_id: The ID of the resource to scope to.
Returns:
The matching list of resources that available service
connectors have access to.
"""
@abstractmethod
def list_service_connector_types(
self,
connector_type: Optional[str] = None,
resource_type: Optional[str] = None,
auth_method: Optional[str] = None,
) -> List[ServiceConnectorTypeModel]:
"""Get a list of service connector types.
Args:
connector_type: Filter by connector type.
resource_type: Filter by resource type.
auth_method: Filter by authentication method.
Returns:
List of service connector types.
"""
@abstractmethod
def get_service_connector_type(
self,
connector_type: str,
) -> ServiceConnectorTypeModel:
"""Returns the requested service connector type.
Args:
connector_type: the service connector type identifier.
Returns:
The requested service connector type.
Raises:
KeyError: If no service connector type with the given ID exists.
"""
# -------------------- Stacks --------------------
@abstractmethod
def create_stack(self, stack: StackRequest) -> StackResponse:
"""Create a new stack.
Args:
stack: The stack to create.
Returns:
The created stack.
Raises:
StackExistsError: If a stack with the same name is already owned
by this user in this workspace.
"""
@abstractmethod
def get_stack(self, stack_id: UUID, hydrate: bool = True) -> StackResponse:
"""Get a stack by its unique ID.
Args:
stack_id: The ID of the stack to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The stack with the given ID.
Raises:
KeyError: if the stack doesn't exist.
"""
@abstractmethod
def list_stacks(
self,
stack_filter_model: StackFilter,
hydrate: bool = False,
) -> Page[StackResponse]:
"""List all stacks matching the given filter criteria.
Args:
stack_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all stacks matching the filter criteria.
"""
@abstractmethod
def update_stack(
self, stack_id: UUID, stack_update: StackUpdate
) -> StackResponse:
"""Update a stack.
Args:
stack_id: The ID of the stack update.
stack_update: The update request on the stack.
Returns:
The updated stack.
Raises:
KeyError: if the stack doesn't exist.
"""
@abstractmethod
def delete_stack(self, stack_id: UUID) -> None:
"""Delete a stack.
Args:
stack_id: The ID of the stack to delete.
Raises:
KeyError: if the stack doesn't exist.
"""
# -------------------- Step runs --------------------
@abstractmethod
def create_run_step(self, step_run: StepRunRequest) -> StepRunResponse:
"""Creates a step run.
Args:
step_run: The step run to create.
Returns:
The created step run.
Raises:
EntityExistsError: if the step run already exists.
KeyError: if the pipeline run doesn't exist.
"""
@abstractmethod
def get_run_step(
self, step_run_id: UUID, hydrate: bool = True
) -> StepRunResponse:
"""Get a step run by ID.
Args:
step_run_id: The ID of the step run to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The step run.
Raises:
KeyError: if the step run doesn't exist.
"""
@abstractmethod
def list_run_steps(
self,
step_run_filter_model: StepRunFilter,
hydrate: bool = False,
) -> Page[StepRunResponse]:
"""List all step runs matching the given filter criteria.
Args:
step_run_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all step runs matching the filter criteria.
"""
@abstractmethod
def update_run_step(
self,
step_run_id: UUID,
step_run_update: StepRunUpdate,
) -> StepRunResponse:
"""Updates a step run.
Args:
step_run_id: The ID of the step to update.
step_run_update: The update to be applied to the step.
Returns:
The updated step run.
Raises:
KeyError: if the step run doesn't exist.
"""
# -------------------- Triggers --------------------
@abstractmethod
def create_trigger(self, trigger: TriggerRequest) -> TriggerResponse:
"""Create an trigger.
Args:
trigger: The trigger to create.
Returns:
The created trigger.
"""
@abstractmethod
def get_trigger(
self,
trigger_id: UUID,
hydrate: bool = True,
) -> TriggerResponse:
"""Get an trigger by ID.
Args:
trigger_id: The ID of the trigger to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The trigger.
Raises:
KeyError: if the stack trigger doesn't exist.
"""
@abstractmethod
def list_triggers(
self,
trigger_filter_model: TriggerFilter,
hydrate: bool = False,
) -> Page[TriggerResponse]:
"""List all triggers matching the given filter criteria.
Args:
trigger_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all triggers matching the filter criteria.
"""
@abstractmethod
def update_trigger(
self,
trigger_id: UUID,
trigger_update: TriggerUpdate,
) -> TriggerResponse:
"""Update an existing trigger.
Args:
trigger_id: The ID of the trigger to update.
trigger_update: The update to be applied to the trigger.
Returns:
The updated trigger.
Raises:
KeyError: if the trigger doesn't exist.
"""
@abstractmethod
def delete_trigger(self, trigger_id: UUID) -> None:
"""Delete an trigger.
Args:
trigger_id: The ID of the trigger to delete.
Raises:
KeyError: if the trigger doesn't exist.
"""
# -------------------- Trigger Executions --------------------
@abstractmethod
def get_trigger_execution(
self,
trigger_execution_id: UUID,
hydrate: bool = True,
) -> TriggerExecutionResponse:
"""Get an trigger execution by ID.
Args:
trigger_execution_id: The ID of the trigger execution to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The trigger execution.
Raises:
KeyError: If the trigger execution doesn't exist.
"""
@abstractmethod
def list_trigger_executions(
self,
trigger_execution_filter_model: TriggerExecutionFilter,
hydrate: bool = False,
) -> Page[TriggerExecutionResponse]:
"""List all trigger executions matching the given filter criteria.
Args:
trigger_execution_filter_model: All filter parameters including
pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all trigger executions matching the filter criteria.
"""
@abstractmethod
def delete_trigger_execution(self, trigger_execution_id: UUID) -> None:
"""Delete a trigger execution.
Args:
trigger_execution_id: The ID of the trigger execution to delete.
Raises:
KeyError: If the trigger execution doesn't exist.
"""
# -------------------- Users --------------------
@abstractmethod
def create_user(self, user: UserRequest) -> UserResponse:
"""Creates a new user.
Args:
user: User to be created.
Returns:
The newly created user.
Raises:
EntityExistsError: If a user with the given name already exists.
"""
@abstractmethod
def get_user(
self,
user_name_or_id: Optional[Union[str, UUID]] = None,
include_private: bool = False,
hydrate: bool = True,
) -> UserResponse:
"""Gets a specific user, when no id is specified the active user is returned.
Args:
user_name_or_id: The name or ID of the user to get.
include_private: Whether to include private user information.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested user, if it was found.
Raises:
KeyError: If no user with the given name or ID exists.
"""
@abstractmethod
def list_users(
self,
user_filter_model: UserFilter,
hydrate: bool = False,
) -> Page[UserResponse]:
"""List all users.
Args:
user_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all users.
"""
@abstractmethod
def update_user(
self, user_id: UUID, user_update: UserUpdate
) -> UserResponse:
"""Updates an existing user.
Args:
user_id: The id of the user to update.
user_update: The update to be applied to the user.
Returns:
The updated user.
Raises:
KeyError: If no user with the given name exists.
"""
@abstractmethod
def delete_user(self, user_name_or_id: Union[str, UUID]) -> None:
"""Deletes a user.
Args:
user_name_or_id: The name or ID of the user to delete.
Raises:
KeyError: If no user with the given ID exists.
"""
# -------------------- Workspaces --------------------
@abstractmethod
def create_workspace(
self, workspace: WorkspaceRequest
) -> WorkspaceResponse:
"""Creates a new workspace.
Args:
workspace: The workspace to create.
Returns:
The newly created workspace.
Raises:
EntityExistsError: If a workspace with the given name already exists.
"""
@abstractmethod
def get_workspace(
self, workspace_name_or_id: Union[UUID, str], hydrate: bool = True
) -> WorkspaceResponse:
"""Get an existing workspace by name or ID.
Args:
workspace_name_or_id: Name or ID of the workspace to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested workspace.
Raises:
KeyError: If there is no such workspace.
"""
@abstractmethod
def list_workspaces(
self,
workspace_filter_model: WorkspaceFilter,
hydrate: bool = False,
) -> Page[WorkspaceResponse]:
"""List all workspace matching the given filter criteria.
Args:
workspace_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all workspace matching the filter criteria.
"""
@abstractmethod
def update_workspace(
self, workspace_id: UUID, workspace_update: WorkspaceUpdate
) -> WorkspaceResponse:
"""Update an existing workspace.
Args:
workspace_id: The ID of the workspace to be updated.
workspace_update: The update to be applied to the workspace.
Returns:
The updated workspace.
Raises:
KeyError: if the workspace does not exist.
"""
@abstractmethod
def delete_workspace(self, workspace_name_or_id: Union[str, UUID]) -> None:
"""Deletes a workspace.
Args:
workspace_name_or_id: Name or ID of the workspace to delete.
Raises:
KeyError: If no workspace with the given name exists.
"""
# -------------------- Models --------------------
@abstractmethod
def create_model(self, model: ModelRequest) -> ModelResponse:
"""Creates a new model.
Args:
model: the Model to be created.
Returns:
The newly created model.
Raises:
EntityExistsError: If a model with the given name already exists.
"""
@abstractmethod
def delete_model(self, model_name_or_id: Union[str, UUID]) -> None:
"""Deletes a model.
Args:
model_name_or_id: name or id of the model to be deleted.
Raises:
KeyError: specified ID or name not found.
"""
@abstractmethod
def update_model(
self,
model_id: UUID,
model_update: ModelUpdate,
) -> ModelResponse:
"""Updates an existing model.
Args:
model_id: UUID of the model to be updated.
model_update: the Model to be updated.
Returns:
The updated model.
"""
@abstractmethod
def get_model(
self, model_name_or_id: Union[str, UUID], hydrate: bool = True
) -> ModelResponse:
"""Get an existing model.
Args:
model_name_or_id: name or id of the model to be retrieved.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The model of interest.
Raises:
KeyError: specified ID or name not found.
"""
@abstractmethod
def list_models(
self,
model_filter_model: ModelFilter,
hydrate: bool = False,
) -> Page[ModelResponse]:
"""Get all models by filter.
Args:
model_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all models.
"""
# -------------------- Model versions --------------------
@abstractmethod
def create_model_version(
self, model_version: ModelVersionRequest
) -> ModelVersionResponse:
"""Creates a new model version.
Args:
model_version: the Model Version to be created.
Returns:
The newly created model version.
Raises:
ValueError: If `number` is not None during model version creation.
EntityExistsError: If a model version with the given name already
exists.
"""
@abstractmethod
def delete_model_version(
self,
model_version_id: UUID,
) -> None:
"""Deletes a model version.
Args:
model_version_id: id of the model version to be deleted.
Raises:
KeyError: specified ID or name not found.
"""
@abstractmethod
def get_model_version(
self, model_version_id: UUID, hydrate: bool = True
) -> ModelVersionResponse:
"""Get an existing model version.
Args:
model_version_id: name, id, stage or number of the model version to
be retrieved. If skipped - latest is retrieved.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The model version of interest.
Raises:
KeyError: specified ID or name not found.
"""
@abstractmethod
def list_model_versions(
self,
model_version_filter_model: ModelVersionFilter,
model_name_or_id: Optional[Union[str, UUID]] = None,
hydrate: bool = False,
) -> Page[ModelVersionResponse]:
"""Get all model versions by filter.
Args:
model_name_or_id: name or id of the model containing the model
versions.
model_version_filter_model: All filter parameters including
pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all model versions.
"""
@abstractmethod
def update_model_version(
self,
model_version_id: UUID,
model_version_update_model: ModelVersionUpdate,
) -> ModelVersionResponse:
"""Get all model versions by filter.
Args:
model_version_id: The ID of model version to be updated.
model_version_update_model: The model version to be updated.
Returns:
An updated model version.
Raises:
KeyError: If the model version not found
RuntimeError: If there is a model version with target stage,
but `force` flag is off
"""
# -------------------- Model Versions Artifacts --------------------
@abstractmethod
def create_model_version_artifact_link(
self, model_version_artifact_link: ModelVersionArtifactRequest
) -> ModelVersionArtifactResponse:
"""Creates a new model version link.
Args:
model_version_artifact_link: the Model Version to Artifact Link
to be created.
Returns:
The newly created model version to artifact link.
Raises:
EntityExistsError: If a link with the given name already exists.
"""
@abstractmethod
def list_model_version_artifact_links(
self,
model_version_artifact_link_filter_model: ModelVersionArtifactFilter,
hydrate: bool = False,
) -> Page[ModelVersionArtifactResponse]:
"""Get all model version to artifact links by filter.
Args:
model_version_artifact_link_filter_model: All filter parameters
including pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all model version to artifact links.
"""
@abstractmethod
def delete_model_version_artifact_link(
self,
model_version_id: UUID,
model_version_artifact_link_name_or_id: Union[str, UUID],
) -> None:
"""Deletes a model version to artifact link.
Args:
model_version_id: ID of the model version containing the link.
model_version_artifact_link_name_or_id: name or ID of the model
version to artifact link to be deleted.
Raises:
KeyError: specified ID or name not found.
"""
@abstractmethod
def delete_all_model_version_artifact_links(
self,
model_version_id: UUID,
only_links: bool = True,
) -> None:
"""Deletes all model version to artifact links.
Args:
model_version_id: ID of the model version containing the link.
only_links: Flag deciding whether to delete only links or all.
"""
# -------------------- Model Versions Pipeline Runs --------------------
@abstractmethod
def create_model_version_pipeline_run_link(
self,
model_version_pipeline_run_link: ModelVersionPipelineRunRequest,
) -> ModelVersionPipelineRunResponse:
"""Creates a new model version to pipeline run link.
Args:
model_version_pipeline_run_link: the Model Version to Pipeline Run
Link to be created.
Returns:
- If Model Version to Pipeline Run Link already exists - returns
the existing link.
- Otherwise, returns the newly created model version to pipeline
run link.
"""
@abstractmethod
def list_model_version_pipeline_run_links(
self,
model_version_pipeline_run_link_filter_model: ModelVersionPipelineRunFilter,
hydrate: bool = False,
) -> Page[ModelVersionPipelineRunResponse]:
"""Get all model version to pipeline run links by filter.
Args:
model_version_pipeline_run_link_filter_model: All filter parameters
including pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all model version to pipeline run links.
"""
@abstractmethod
def delete_model_version_pipeline_run_link(
self,
model_version_id: UUID,
model_version_pipeline_run_link_name_or_id: Union[str, UUID],
) -> None:
"""Deletes a model version to pipeline run link.
Args:
model_version_id: ID of the model version containing the link.
model_version_pipeline_run_link_name_or_id: name or ID of the model
version to pipeline run link to be deleted.
Raises:
KeyError: specified ID not found.
"""
#################
# Tags
#################
@abstractmethod
def create_tag(self, tag: TagRequest) -> TagResponse:
"""Creates a new tag.
Args:
tag: the tag to be created.
Returns:
The newly created tag.
Raises:
EntityExistsError: If a tag with the given name already exists.
"""
@abstractmethod
def delete_tag(
self,
tag_name_or_id: Union[str, UUID],
) -> None:
"""Deletes a tag.
Args:
tag_name_or_id: name or id of the tag to delete.
Raises:
KeyError: specified ID or name not found.
"""
@abstractmethod
def get_tag(
self, tag_name_or_id: Union[str, UUID], hydrate: bool = True
) -> TagResponse:
"""Get an existing tag.
Args:
tag_name_or_id: name or id of the tag to be retrieved.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The tag of interest.
Raises:
KeyError: specified ID or name not found.
"""
@abstractmethod
def list_tags(
self,
tag_filter_model: TagFilter,
hydrate: bool = False,
) -> Page[TagResponse]:
"""Get all tags by filter.
Args:
tag_filter_model: All filter parameters including pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all tags.
"""
@abstractmethod
def update_tag(
self,
tag_name_or_id: Union[str, UUID],
tag_update_model: TagUpdate,
) -> TagResponse:
"""Update tag.
Args:
tag_name_or_id: name or id of the tag to be updated.
tag_update_model: Tag to use for the update.
Returns:
An updated tag.
Raises:
KeyError: If the tag is not found
"""
backup_secrets(self, ignore_errors=True, delete_secrets=False)
Backs up all secrets to the configured backup secrets store.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
ignore_errors |
bool |
Whether to ignore individual errors during the backup process and attempt to backup all secrets. |
True |
delete_secrets |
bool |
Whether to delete the secrets that have been successfully backed up from the primary secrets store. Setting this flag effectively moves all secrets from the primary secrets store to the backup secrets store. |
False |
Exceptions:
| Type | Description |
|---|---|
BackupSecretsStoreNotConfiguredError |
if no backup secrets store is configured. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def backup_secrets(
self, ignore_errors: bool = True, delete_secrets: bool = False
) -> None:
"""Backs up all secrets to the configured backup secrets store.
Args:
ignore_errors: Whether to ignore individual errors during the backup
process and attempt to backup all secrets.
delete_secrets: Whether to delete the secrets that have been
successfully backed up from the primary secrets store. Setting
this flag effectively moves all secrets from the primary secrets
store to the backup secrets store.
Raises:
BackupSecretsStoreNotConfiguredError: if no backup secrets store is
configured.
"""
create_api_key(self, service_account_id, api_key)
Create a new API key for a service account.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account_id |
UUID |
The ID of the service account for which to create the API key. |
required |
api_key |
APIKeyRequest |
The API key to create. |
required |
Returns:
| Type | Description |
|---|---|
APIKeyResponse |
The created API key. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If the service account doesn't exist. |
EntityExistsError |
If an API key with the same name is already configured for the same service account. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def create_api_key(
self, service_account_id: UUID, api_key: APIKeyRequest
) -> APIKeyResponse:
"""Create a new API key for a service account.
Args:
service_account_id: The ID of the service account for which to
create the API key.
api_key: The API key to create.
Returns:
The created API key.
Raises:
KeyError: If the service account doesn't exist.
EntityExistsError: If an API key with the same name is already
configured for the same service account.
"""
create_artifact(self, artifact)
Creates a new artifact.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact |
ArtifactRequest |
The artifact to create. |
required |
Returns:
| Type | Description |
|---|---|
ArtifactResponse |
The newly created artifact. |
Exceptions:
| Type | Description |
|---|---|
EntityExistsError |
If an artifact with the same name already exists. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def create_artifact(self, artifact: ArtifactRequest) -> ArtifactResponse:
"""Creates a new artifact.
Args:
artifact: The artifact to create.
Returns:
The newly created artifact.
Raises:
EntityExistsError: If an artifact with the same name already exists.
"""
create_artifact_version(self, artifact_version)
Creates an artifact version.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_version |
ArtifactVersionRequest |
The artifact version to create. |
required |
Returns:
| Type | Description |
|---|---|
ArtifactVersionResponse |
The created artifact version. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def create_artifact_version(
self, artifact_version: ArtifactVersionRequest
) -> ArtifactVersionResponse:
"""Creates an artifact version.
Args:
artifact_version: The artifact version to create.
Returns:
The created artifact version.
"""
create_build(self, build)
Creates a new build in a workspace.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
build |
PipelineBuildRequest |
The build to create. |
required |
Returns:
| Type | Description |
|---|---|
PipelineBuildResponse |
The newly created build. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If the workspace does not exist. |
EntityExistsError |
If an identical build already exists. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def create_build(
self,
build: PipelineBuildRequest,
) -> PipelineBuildResponse:
"""Creates a new build in a workspace.
Args:
build: The build to create.
Returns:
The newly created build.
Raises:
KeyError: If the workspace does not exist.
EntityExistsError: If an identical build already exists.
"""
create_code_repository(self, code_repository)
Creates a new code repository.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
code_repository |
CodeRepositoryRequest |
Code repository to be created. |
required |
Returns:
| Type | Description |
|---|---|
CodeRepositoryResponse |
The newly created code repository. |
Exceptions:
| Type | Description |
|---|---|
EntityExistsError |
If a code repository with the given name already exists. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def create_code_repository(
self, code_repository: CodeRepositoryRequest
) -> CodeRepositoryResponse:
"""Creates a new code repository.
Args:
code_repository: Code repository to be created.
Returns:
The newly created code repository.
Raises:
EntityExistsError: If a code repository with the given name already
exists.
"""
create_deployment(self, deployment)
Creates a new deployment in a workspace.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
deployment |
PipelineDeploymentRequest |
The deployment to create. |
required |
Returns:
| Type | Description |
|---|---|
PipelineDeploymentResponse |
The newly created deployment. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If the workspace does not exist. |
EntityExistsError |
If an identical deployment already exists. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def create_deployment(
self,
deployment: PipelineDeploymentRequest,
) -> PipelineDeploymentResponse:
"""Creates a new deployment in a workspace.
Args:
deployment: The deployment to create.
Returns:
The newly created deployment.
Raises:
KeyError: If the workspace does not exist.
EntityExistsError: If an identical deployment already exists.
"""
create_event_source(self, event_source)
Create an event_source.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
event_source |
EventSourceRequest |
The event_source to create. |
required |
Returns:
| Type | Description |
|---|---|
EventSourceResponse |
The created event_source. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def create_event_source(
self, event_source: EventSourceRequest
) -> EventSourceResponse:
"""Create an event_source.
Args:
event_source: The event_source to create.
Returns:
The created event_source.
"""
create_flavor(self, flavor)
Creates a new stack component flavor.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
flavor |
FlavorRequest |
The stack component flavor to create. |
required |
Returns:
| Type | Description |
|---|---|
FlavorResponse |
The newly created flavor. |
Exceptions:
| Type | Description |
|---|---|
EntityExistsError |
If a flavor with the same name and type is already owned by this user in this workspace. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def create_flavor(
self,
flavor: FlavorRequest,
) -> FlavorResponse:
"""Creates a new stack component flavor.
Args:
flavor: The stack component flavor to create.
Returns:
The newly created flavor.
Raises:
EntityExistsError: If a flavor with the same name and type
is already owned by this user in this workspace.
"""
create_model(self, model)
Creates a new model.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model |
ModelRequest |
the Model to be created. |
required |
Returns:
| Type | Description |
|---|---|
ModelResponse |
The newly created model. |
Exceptions:
| Type | Description |
|---|---|
EntityExistsError |
If a model with the given name already exists. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def create_model(self, model: ModelRequest) -> ModelResponse:
"""Creates a new model.
Args:
model: the Model to be created.
Returns:
The newly created model.
Raises:
EntityExistsError: If a model with the given name already exists.
"""
create_model_version(self, model_version)
Creates a new model version.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version |
ModelVersionRequest |
the Model Version to be created. |
required |
Returns:
| Type | Description |
|---|---|
ModelVersionResponse |
The newly created model version. |
Exceptions:
| Type | Description |
|---|---|
ValueError |
If |
EntityExistsError |
If a model version with the given name already exists. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def create_model_version(
self, model_version: ModelVersionRequest
) -> ModelVersionResponse:
"""Creates a new model version.
Args:
model_version: the Model Version to be created.
Returns:
The newly created model version.
Raises:
ValueError: If `number` is not None during model version creation.
EntityExistsError: If a model version with the given name already
exists.
"""
create_model_version_artifact_link(self, model_version_artifact_link)
Creates a new model version link.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_artifact_link |
ModelVersionArtifactRequest |
the Model Version to Artifact Link to be created. |
required |
Returns:
| Type | Description |
|---|---|
ModelVersionArtifactResponse |
The newly created model version to artifact link. |
Exceptions:
| Type | Description |
|---|---|
EntityExistsError |
If a link with the given name already exists. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def create_model_version_artifact_link(
self, model_version_artifact_link: ModelVersionArtifactRequest
) -> ModelVersionArtifactResponse:
"""Creates a new model version link.
Args:
model_version_artifact_link: the Model Version to Artifact Link
to be created.
Returns:
The newly created model version to artifact link.
Raises:
EntityExistsError: If a link with the given name already exists.
"""
create_model_version_pipeline_run_link(self, model_version_pipeline_run_link)
Creates a new model version to pipeline run link.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_pipeline_run_link |
ModelVersionPipelineRunRequest |
the Model Version to Pipeline Run Link to be created. |
required |
Returns:
| Type | Description |
|---|---|
ModelVersionPipelineRunResponse |
|
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def create_model_version_pipeline_run_link(
self,
model_version_pipeline_run_link: ModelVersionPipelineRunRequest,
) -> ModelVersionPipelineRunResponse:
"""Creates a new model version to pipeline run link.
Args:
model_version_pipeline_run_link: the Model Version to Pipeline Run
Link to be created.
Returns:
- If Model Version to Pipeline Run Link already exists - returns
the existing link.
- Otherwise, returns the newly created model version to pipeline
run link.
"""
create_pipeline(self, pipeline)
Creates a new pipeline in a workspace.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
pipeline |
PipelineRequest |
The pipeline to create. |
required |
Returns:
| Type | Description |
|---|---|
PipelineResponse |
The newly created pipeline. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the workspace does not exist. |
EntityExistsError |
If an identical pipeline already exists. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def create_pipeline(
self,
pipeline: PipelineRequest,
) -> PipelineResponse:
"""Creates a new pipeline in a workspace.
Args:
pipeline: The pipeline to create.
Returns:
The newly created pipeline.
Raises:
KeyError: if the workspace does not exist.
EntityExistsError: If an identical pipeline already exists.
"""
create_run(self, pipeline_run)
Creates a pipeline run.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
pipeline_run |
PipelineRunRequest |
The pipeline run to create. |
required |
Returns:
| Type | Description |
|---|---|
PipelineRunResponse |
The created pipeline run. |
Exceptions:
| Type | Description |
|---|---|
EntityExistsError |
If an identical pipeline run already exists. |
KeyError |
If the pipeline does not exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def create_run(
self, pipeline_run: PipelineRunRequest
) -> PipelineRunResponse:
"""Creates a pipeline run.
Args:
pipeline_run: The pipeline run to create.
Returns:
The created pipeline run.
Raises:
EntityExistsError: If an identical pipeline run already exists.
KeyError: If the pipeline does not exist.
"""
create_run_metadata(self, run_metadata)
Creates run metadata.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
run_metadata |
RunMetadataRequest |
The run metadata to create. |
required |
Returns:
| Type | Description |
|---|---|
List[zenml.models.v2.core.run_metadata.RunMetadataResponse] |
The created run metadata. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def create_run_metadata(
self, run_metadata: RunMetadataRequest
) -> List[RunMetadataResponse]:
"""Creates run metadata.
Args:
run_metadata: The run metadata to create.
Returns:
The created run metadata.
"""
create_run_step(self, step_run)
Creates a step run.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
step_run |
StepRunRequest |
The step run to create. |
required |
Returns:
| Type | Description |
|---|---|
StepRunResponse |
The created step run. |
Exceptions:
| Type | Description |
|---|---|
EntityExistsError |
if the step run already exists. |
KeyError |
if the pipeline run doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def create_run_step(self, step_run: StepRunRequest) -> StepRunResponse:
"""Creates a step run.
Args:
step_run: The step run to create.
Returns:
The created step run.
Raises:
EntityExistsError: if the step run already exists.
KeyError: if the pipeline run doesn't exist.
"""
create_schedule(self, schedule)
Creates a new schedule.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
schedule |
ScheduleRequest |
The schedule to create. |
required |
Returns:
| Type | Description |
|---|---|
ScheduleResponse |
The newly created schedule. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def create_schedule(self, schedule: ScheduleRequest) -> ScheduleResponse:
"""Creates a new schedule.
Args:
schedule: The schedule to create.
Returns:
The newly created schedule.
"""
create_secret(self, secret)
Creates a new secret.
The new secret is also validated against the scoping rules enforced in the secrets store:
- only one workspace-scoped secret with the given name can exist in the target workspace.
- only one user-scoped secret with the given name can exist in the target workspace for the target user.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret |
SecretRequest |
The secret to create. |
required |
Returns:
| Type | Description |
|---|---|
SecretResponse |
The newly created secret. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the user or workspace does not exist. |
EntityExistsError |
If a secret with the same name already exists in the same scope. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def create_secret(
self,
secret: SecretRequest,
) -> SecretResponse:
"""Creates a new secret.
The new secret is also validated against the scoping rules enforced in
the secrets store:
- only one workspace-scoped secret with the given name can exist
in the target workspace.
- only one user-scoped secret with the given name can exist in the
target workspace for the target user.
Args:
secret: The secret to create.
Returns:
The newly created secret.
Raises:
KeyError: if the user or workspace does not exist.
EntityExistsError: If a secret with the same name already exists in
the same scope.
"""
create_service_account(self, service_account)
Creates a new service account.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account |
ServiceAccountRequest |
Service account to be created. |
required |
Returns:
| Type | Description |
|---|---|
ServiceAccountResponse |
The newly created service account. |
Exceptions:
| Type | Description |
|---|---|
EntityExistsError |
If a user or service account with the given name already exists. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def create_service_account(
self, service_account: ServiceAccountRequest
) -> ServiceAccountResponse:
"""Creates a new service account.
Args:
service_account: Service account to be created.
Returns:
The newly created service account.
Raises:
EntityExistsError: If a user or service account with the given name
already exists.
"""
create_service_connector(self, service_connector)
Creates a new service connector.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_connector |
ServiceConnectorRequest |
Service connector to be created. |
required |
Returns:
| Type | Description |
|---|---|
ServiceConnectorResponse |
The newly created service connector. |
Exceptions:
| Type | Description |
|---|---|
EntityExistsError |
If a service connector with the given name is already owned by this user in this workspace. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def create_service_connector(
self,
service_connector: ServiceConnectorRequest,
) -> ServiceConnectorResponse:
"""Creates a new service connector.
Args:
service_connector: Service connector to be created.
Returns:
The newly created service connector.
Raises:
EntityExistsError: If a service connector with the given name
is already owned by this user in this workspace.
"""
create_stack(self, stack)
Create a new stack.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
stack |
StackRequest |
The stack to create. |
required |
Returns:
| Type | Description |
|---|---|
StackResponse |
The created stack. |
Exceptions:
| Type | Description |
|---|---|
StackExistsError |
If a stack with the same name is already owned by this user in this workspace. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def create_stack(self, stack: StackRequest) -> StackResponse:
"""Create a new stack.
Args:
stack: The stack to create.
Returns:
The created stack.
Raises:
StackExistsError: If a stack with the same name is already owned
by this user in this workspace.
"""
create_stack_component(self, component)
Create a stack component.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
component |
ComponentRequest |
The stack component to create. |
required |
Returns:
| Type | Description |
|---|---|
ComponentResponse |
The created stack component. |
Exceptions:
| Type | Description |
|---|---|
StackComponentExistsError |
If a stack component with the same name and type is already owned by this user in this workspace. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def create_stack_component(
self, component: ComponentRequest
) -> ComponentResponse:
"""Create a stack component.
Args:
component: The stack component to create.
Returns:
The created stack component.
Raises:
StackComponentExistsError: If a stack component with the same name
and type is already owned by this user in this workspace.
"""
create_tag(self, tag)
Creates a new tag.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
tag |
TagRequest |
the tag to be created. |
required |
Returns:
| Type | Description |
|---|---|
TagResponse |
The newly created tag. |
Exceptions:
| Type | Description |
|---|---|
EntityExistsError |
If a tag with the given name already exists. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def create_tag(self, tag: TagRequest) -> TagResponse:
"""Creates a new tag.
Args:
tag: the tag to be created.
Returns:
The newly created tag.
Raises:
EntityExistsError: If a tag with the given name already exists.
"""
create_trigger(self, trigger)
Create an trigger.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
trigger |
TriggerRequest |
The trigger to create. |
required |
Returns:
| Type | Description |
|---|---|
TriggerResponse |
The created trigger. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def create_trigger(self, trigger: TriggerRequest) -> TriggerResponse:
"""Create an trigger.
Args:
trigger: The trigger to create.
Returns:
The created trigger.
"""
create_user(self, user)
Creates a new user.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
user |
UserRequest |
User to be created. |
required |
Returns:
| Type | Description |
|---|---|
UserResponse |
The newly created user. |
Exceptions:
| Type | Description |
|---|---|
EntityExistsError |
If a user with the given name already exists. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def create_user(self, user: UserRequest) -> UserResponse:
"""Creates a new user.
Args:
user: User to be created.
Returns:
The newly created user.
Raises:
EntityExistsError: If a user with the given name already exists.
"""
create_workspace(self, workspace)
Creates a new workspace.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
workspace |
WorkspaceRequest |
The workspace to create. |
required |
Returns:
| Type | Description |
|---|---|
WorkspaceResponse |
The newly created workspace. |
Exceptions:
| Type | Description |
|---|---|
EntityExistsError |
If a workspace with the given name already exists. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def create_workspace(
self, workspace: WorkspaceRequest
) -> WorkspaceResponse:
"""Creates a new workspace.
Args:
workspace: The workspace to create.
Returns:
The newly created workspace.
Raises:
EntityExistsError: If a workspace with the given name already exists.
"""
delete_all_model_version_artifact_links(self, model_version_id, only_links=True)
Deletes all model version to artifact links.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_id |
UUID |
ID of the model version containing the link. |
required |
only_links |
bool |
Flag deciding whether to delete only links or all. |
True |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def delete_all_model_version_artifact_links(
self,
model_version_id: UUID,
only_links: bool = True,
) -> None:
"""Deletes all model version to artifact links.
Args:
model_version_id: ID of the model version containing the link.
only_links: Flag deciding whether to delete only links or all.
"""
delete_api_key(self, service_account_id, api_key_name_or_id)
Delete an API key for a service account.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account_id |
UUID |
The ID of the service account for which to delete the API key. |
required |
api_key_name_or_id |
Union[str, uuid.UUID] |
The name or ID of the API key to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if an API key with the given name or ID is not configured for the given service account. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def delete_api_key(
self,
service_account_id: UUID,
api_key_name_or_id: Union[str, UUID],
) -> None:
"""Delete an API key for a service account.
Args:
service_account_id: The ID of the service account for which to
delete the API key.
api_key_name_or_id: The name or ID of the API key to delete.
Raises:
KeyError: if an API key with the given name or ID is not configured
for the given service account.
"""
delete_artifact(self, artifact_id)
Deletes an artifact.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_id |
UUID |
The ID of the artifact to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the artifact doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def delete_artifact(self, artifact_id: UUID) -> None:
"""Deletes an artifact.
Args:
artifact_id: The ID of the artifact to delete.
Raises:
KeyError: if the artifact doesn't exist.
"""
delete_artifact_version(self, artifact_version_id)
Deletes an artifact version.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_version_id |
UUID |
The ID of the artifact version to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the artifact version doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def delete_artifact_version(self, artifact_version_id: UUID) -> None:
"""Deletes an artifact version.
Args:
artifact_version_id: The ID of the artifact version to delete.
Raises:
KeyError: if the artifact version doesn't exist.
"""
delete_authorized_device(self, device_id)
Deletes an OAuth 2.0 authorized device.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
device_id |
UUID |
The ID of the device to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no device with the given ID exists. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def delete_authorized_device(self, device_id: UUID) -> None:
"""Deletes an OAuth 2.0 authorized device.
Args:
device_id: The ID of the device to delete.
Raises:
KeyError: If no device with the given ID exists.
"""
delete_build(self, build_id)
Deletes a build.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
build_id |
UUID |
The ID of the build to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the build doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def delete_build(self, build_id: UUID) -> None:
"""Deletes a build.
Args:
build_id: The ID of the build to delete.
Raises:
KeyError: if the build doesn't exist.
"""
delete_code_repository(self, code_repository_id)
Deletes a code repository.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
code_repository_id |
UUID |
The ID of the code repository to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no code repository with the given ID exists. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def delete_code_repository(self, code_repository_id: UUID) -> None:
"""Deletes a code repository.
Args:
code_repository_id: The ID of the code repository to delete.
Raises:
KeyError: If no code repository with the given ID exists.
"""
delete_deployment(self, deployment_id)
Deletes a deployment.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
deployment_id |
UUID |
The ID of the deployment to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If the deployment doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def delete_deployment(self, deployment_id: UUID) -> None:
"""Deletes a deployment.
Args:
deployment_id: The ID of the deployment to delete.
Raises:
KeyError: If the deployment doesn't exist.
"""
delete_event_source(self, event_source_id)
Delete an event_source.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
event_source_id |
UUID |
The ID of the event_source to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the event_source doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def delete_event_source(self, event_source_id: UUID) -> None:
"""Delete an event_source.
Args:
event_source_id: The ID of the event_source to delete.
Raises:
KeyError: if the event_source doesn't exist.
"""
delete_flavor(self, flavor_id)
Delete a stack component flavor.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
flavor_id |
UUID |
The ID of the stack component flavor to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the stack component flavor doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def delete_flavor(self, flavor_id: UUID) -> None:
"""Delete a stack component flavor.
Args:
flavor_id: The ID of the stack component flavor to delete.
Raises:
KeyError: if the stack component flavor doesn't exist.
"""
delete_model(self, model_name_or_id)
Deletes a model.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_name_or_id |
Union[str, uuid.UUID] |
name or id of the model to be deleted. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
specified ID or name not found. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def delete_model(self, model_name_or_id: Union[str, UUID]) -> None:
"""Deletes a model.
Args:
model_name_or_id: name or id of the model to be deleted.
Raises:
KeyError: specified ID or name not found.
"""
delete_model_version(self, model_version_id)
Deletes a model version.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_id |
UUID |
id of the model version to be deleted. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
specified ID or name not found. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def delete_model_version(
self,
model_version_id: UUID,
) -> None:
"""Deletes a model version.
Args:
model_version_id: id of the model version to be deleted.
Raises:
KeyError: specified ID or name not found.
"""
delete_model_version_artifact_link(self, model_version_id, model_version_artifact_link_name_or_id)
Deletes a model version to artifact link.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_id |
UUID |
ID of the model version containing the link. |
required |
model_version_artifact_link_name_or_id |
Union[str, uuid.UUID] |
name or ID of the model version to artifact link to be deleted. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
specified ID or name not found. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def delete_model_version_artifact_link(
self,
model_version_id: UUID,
model_version_artifact_link_name_or_id: Union[str, UUID],
) -> None:
"""Deletes a model version to artifact link.
Args:
model_version_id: ID of the model version containing the link.
model_version_artifact_link_name_or_id: name or ID of the model
version to artifact link to be deleted.
Raises:
KeyError: specified ID or name not found.
"""
delete_model_version_pipeline_run_link(self, model_version_id, model_version_pipeline_run_link_name_or_id)
Deletes a model version to pipeline run link.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_id |
UUID |
ID of the model version containing the link. |
required |
model_version_pipeline_run_link_name_or_id |
Union[str, uuid.UUID] |
name or ID of the model version to pipeline run link to be deleted. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
specified ID not found. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def delete_model_version_pipeline_run_link(
self,
model_version_id: UUID,
model_version_pipeline_run_link_name_or_id: Union[str, UUID],
) -> None:
"""Deletes a model version to pipeline run link.
Args:
model_version_id: ID of the model version containing the link.
model_version_pipeline_run_link_name_or_id: name or ID of the model
version to pipeline run link to be deleted.
Raises:
KeyError: specified ID not found.
"""
delete_pipeline(self, pipeline_id)
Deletes a pipeline.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
pipeline_id |
UUID |
The ID of the pipeline to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the pipeline doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def delete_pipeline(self, pipeline_id: UUID) -> None:
"""Deletes a pipeline.
Args:
pipeline_id: The ID of the pipeline to delete.
Raises:
KeyError: if the pipeline doesn't exist.
"""
delete_run(self, run_id)
Deletes a pipeline run.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
run_id |
UUID |
The ID of the pipeline run to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the pipeline run doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def delete_run(self, run_id: UUID) -> None:
"""Deletes a pipeline run.
Args:
run_id: The ID of the pipeline run to delete.
Raises:
KeyError: if the pipeline run doesn't exist.
"""
delete_schedule(self, schedule_id)
Deletes a schedule.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
schedule_id |
UUID |
The ID of the schedule to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the schedule doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def delete_schedule(self, schedule_id: UUID) -> None:
"""Deletes a schedule.
Args:
schedule_id: The ID of the schedule to delete.
Raises:
KeyError: if the schedule doesn't exist.
"""
delete_secret(self, secret_id)
Deletes a secret.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
The ID of the secret to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the secret doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def delete_secret(self, secret_id: UUID) -> None:
"""Deletes a secret.
Args:
secret_id: The ID of the secret to delete.
Raises:
KeyError: if the secret doesn't exist.
"""
delete_service_account(self, service_account_name_or_id)
Delete a service account.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account_name_or_id |
Union[str, uuid.UUID] |
The name or the ID of the service account to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
IllegalOperationError |
if the service account has already been used to create other resources. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def delete_service_account(
self,
service_account_name_or_id: Union[str, UUID],
) -> None:
"""Delete a service account.
Args:
service_account_name_or_id: The name or the ID of the service
account to delete.
Raises:
IllegalOperationError: if the service account has already been used
to create other resources.
"""
delete_service_connector(self, service_connector_id)
Deletes a service connector.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_connector_id |
UUID |
The ID of the service connector to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no service connector with the given ID exists. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def delete_service_connector(self, service_connector_id: UUID) -> None:
"""Deletes a service connector.
Args:
service_connector_id: The ID of the service connector to delete.
Raises:
KeyError: If no service connector with the given ID exists.
"""
delete_stack(self, stack_id)
Delete a stack.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
stack_id |
UUID |
The ID of the stack to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the stack doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def delete_stack(self, stack_id: UUID) -> None:
"""Delete a stack.
Args:
stack_id: The ID of the stack to delete.
Raises:
KeyError: if the stack doesn't exist.
"""
delete_stack_component(self, component_id)
Delete a stack component.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
component_id |
UUID |
The ID of the stack component to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the stack component doesn't exist. |
ValueError |
if the stack component is part of one or more stacks. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def delete_stack_component(self, component_id: UUID) -> None:
"""Delete a stack component.
Args:
component_id: The ID of the stack component to delete.
Raises:
KeyError: if the stack component doesn't exist.
ValueError: if the stack component is part of one or more stacks.
"""
delete_tag(self, tag_name_or_id)
Deletes a tag.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
tag_name_or_id |
Union[str, uuid.UUID] |
name or id of the tag to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
specified ID or name not found. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def delete_tag(
self,
tag_name_or_id: Union[str, UUID],
) -> None:
"""Deletes a tag.
Args:
tag_name_or_id: name or id of the tag to delete.
Raises:
KeyError: specified ID or name not found.
"""
delete_trigger(self, trigger_id)
Delete an trigger.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
trigger_id |
UUID |
The ID of the trigger to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the trigger doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def delete_trigger(self, trigger_id: UUID) -> None:
"""Delete an trigger.
Args:
trigger_id: The ID of the trigger to delete.
Raises:
KeyError: if the trigger doesn't exist.
"""
delete_trigger_execution(self, trigger_execution_id)
Delete a trigger execution.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
trigger_execution_id |
UUID |
The ID of the trigger execution to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If the trigger execution doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def delete_trigger_execution(self, trigger_execution_id: UUID) -> None:
"""Delete a trigger execution.
Args:
trigger_execution_id: The ID of the trigger execution to delete.
Raises:
KeyError: If the trigger execution doesn't exist.
"""
delete_user(self, user_name_or_id)
Deletes a user.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
user_name_or_id |
Union[str, uuid.UUID] |
The name or ID of the user to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no user with the given ID exists. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def delete_user(self, user_name_or_id: Union[str, UUID]) -> None:
"""Deletes a user.
Args:
user_name_or_id: The name or ID of the user to delete.
Raises:
KeyError: If no user with the given ID exists.
"""
delete_workspace(self, workspace_name_or_id)
Deletes a workspace.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
workspace_name_or_id |
Union[str, uuid.UUID] |
Name or ID of the workspace to delete. |
required |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no workspace with the given name exists. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def delete_workspace(self, workspace_name_or_id: Union[str, UUID]) -> None:
"""Deletes a workspace.
Args:
workspace_name_or_id: Name or ID of the workspace to delete.
Raises:
KeyError: If no workspace with the given name exists.
"""
get_api_key(self, service_account_id, api_key_name_or_id, hydrate=True)
Get an API key for a service account.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account_id |
UUID |
The ID of the service account for which to fetch the API key. |
required |
api_key_name_or_id |
Union[str, uuid.UUID] |
The name or ID of the API key to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
APIKeyResponse |
The API key with the given ID. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if an API key with the given name or ID is not configured for the given service account. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_api_key(
self,
service_account_id: UUID,
api_key_name_or_id: Union[str, UUID],
hydrate: bool = True,
) -> APIKeyResponse:
"""Get an API key for a service account.
Args:
service_account_id: The ID of the service account for which to fetch
the API key.
api_key_name_or_id: The name or ID of the API key to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The API key with the given ID.
Raises:
KeyError: if an API key with the given name or ID is not configured
for the given service account.
"""
get_artifact(self, artifact_id, hydrate=True)
Gets an artifact.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_id |
UUID |
The ID of the artifact to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
ArtifactResponse |
The artifact. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the artifact doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_artifact(
self, artifact_id: UUID, hydrate: bool = True
) -> ArtifactResponse:
"""Gets an artifact.
Args:
artifact_id: The ID of the artifact to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The artifact.
Raises:
KeyError: if the artifact doesn't exist.
"""
get_artifact_version(self, artifact_version_id, hydrate=True)
Gets an artifact version.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_version_id |
UUID |
The ID of the artifact version to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
ArtifactVersionResponse |
The artifact version. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the artifact version doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_artifact_version(
self, artifact_version_id: UUID, hydrate: bool = True
) -> ArtifactVersionResponse:
"""Gets an artifact version.
Args:
artifact_version_id: The ID of the artifact version to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The artifact version.
Raises:
KeyError: if the artifact version doesn't exist.
"""
get_artifact_visualization(self, artifact_visualization_id, hydrate=True)
Gets an artifact visualization.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_visualization_id |
UUID |
The ID of the artifact visualization to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
ArtifactVisualizationResponse |
The artifact visualization. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the artifact visualization doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_artifact_visualization(
self, artifact_visualization_id: UUID, hydrate: bool = True
) -> ArtifactVisualizationResponse:
"""Gets an artifact visualization.
Args:
artifact_visualization_id: The ID of the artifact visualization
to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The artifact visualization.
Raises:
KeyError: if the artifact visualization doesn't exist.
"""
get_authorized_device(self, device_id, hydrate=True)
Gets a specific OAuth 2.0 authorized device.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
device_id |
UUID |
The ID of the device to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
OAuthDeviceResponse |
The requested device, if it was found. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no device with the given ID exists. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_authorized_device(
self, device_id: UUID, hydrate: bool = True
) -> OAuthDeviceResponse:
"""Gets a specific OAuth 2.0 authorized device.
Args:
device_id: The ID of the device to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested device, if it was found.
Raises:
KeyError: If no device with the given ID exists.
"""
get_build(self, build_id, hydrate=True)
Get a build with a given ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
build_id |
UUID |
ID of the build. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
PipelineBuildResponse |
The build. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If the build does not exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_build(
self, build_id: UUID, hydrate: bool = True
) -> PipelineBuildResponse:
"""Get a build with a given ID.
Args:
build_id: ID of the build.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The build.
Raises:
KeyError: If the build does not exist.
"""
get_code_reference(self, code_reference_id, hydrate=True)
Gets a specific code reference.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
code_reference_id |
UUID |
The ID of the code reference to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
CodeReferenceResponse |
The requested code reference, if it was found. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no code reference with the given ID exists. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_code_reference(
self, code_reference_id: UUID, hydrate: bool = True
) -> CodeReferenceResponse:
"""Gets a specific code reference.
Args:
code_reference_id: The ID of the code reference to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested code reference, if it was found.
Raises:
KeyError: If no code reference with the given ID exists.
"""
get_code_repository(self, code_repository_id, hydrate=True)
Gets a specific code repository.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
code_repository_id |
UUID |
The ID of the code repository to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
CodeRepositoryResponse |
The requested code repository, if it was found. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no code repository with the given ID exists. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_code_repository(
self, code_repository_id: UUID, hydrate: bool = True
) -> CodeRepositoryResponse:
"""Gets a specific code repository.
Args:
code_repository_id: The ID of the code repository to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested code repository, if it was found.
Raises:
KeyError: If no code repository with the given ID exists.
"""
get_deployment(self, deployment_id, hydrate=True)
Get a deployment with a given ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
deployment_id |
UUID |
ID of the deployment. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
PipelineDeploymentResponse |
The deployment. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If the deployment does not exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_deployment(
self, deployment_id: UUID, hydrate: bool = True
) -> PipelineDeploymentResponse:
"""Get a deployment with a given ID.
Args:
deployment_id: ID of the deployment.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The deployment.
Raises:
KeyError: If the deployment does not exist.
"""
get_deployment_id(self)
Get the ID of the deployment.
Returns:
| Type | Description |
|---|---|
UUID |
The ID of the deployment. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_deployment_id(self) -> UUID:
"""Get the ID of the deployment.
Returns:
The ID of the deployment.
"""
get_event_source(self, event_source_id, hydrate=True)
Get an event_source by ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
event_source_id |
UUID |
The ID of the event_source to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
EventSourceResponse |
The event_source. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the stack event_source doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_event_source(
self,
event_source_id: UUID,
hydrate: bool = True,
) -> EventSourceResponse:
"""Get an event_source by ID.
Args:
event_source_id: The ID of the event_source to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The event_source.
Raises:
KeyError: if the stack event_source doesn't exist.
"""
get_flavor(self, flavor_id, hydrate=True)
Get a stack component flavor by ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
flavor_id |
UUID |
The ID of the flavor to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
FlavorResponse |
The stack component flavor. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the stack component flavor doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_flavor(
self, flavor_id: UUID, hydrate: bool = True
) -> FlavorResponse:
"""Get a stack component flavor by ID.
Args:
flavor_id: The ID of the flavor to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The stack component flavor.
Raises:
KeyError: if the stack component flavor doesn't exist.
"""
get_logs(self, logs_id, hydrate=True)
Get logs by its unique ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
logs_id |
UUID |
The ID of the logs to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
LogsResponse |
The logs with the given ID. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the logs doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_logs(self, logs_id: UUID, hydrate: bool = True) -> LogsResponse:
"""Get logs by its unique ID.
Args:
logs_id: The ID of the logs to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The logs with the given ID.
Raises:
KeyError: if the logs doesn't exist.
"""
get_model(self, model_name_or_id, hydrate=True)
Get an existing model.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_name_or_id |
Union[str, uuid.UUID] |
name or id of the model to be retrieved. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
ModelResponse |
The model of interest. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
specified ID or name not found. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_model(
self, model_name_or_id: Union[str, UUID], hydrate: bool = True
) -> ModelResponse:
"""Get an existing model.
Args:
model_name_or_id: name or id of the model to be retrieved.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The model of interest.
Raises:
KeyError: specified ID or name not found.
"""
get_model_version(self, model_version_id, hydrate=True)
Get an existing model version.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_id |
UUID |
name, id, stage or number of the model version to be retrieved. If skipped - latest is retrieved. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
ModelVersionResponse |
The model version of interest. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
specified ID or name not found. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_model_version(
self, model_version_id: UUID, hydrate: bool = True
) -> ModelVersionResponse:
"""Get an existing model version.
Args:
model_version_id: name, id, stage or number of the model version to
be retrieved. If skipped - latest is retrieved.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The model version of interest.
Raises:
KeyError: specified ID or name not found.
"""
get_or_create_run(self, pipeline_run)
Gets or creates a pipeline run.
If a run with the same ID or name already exists, it is returned. Otherwise, a new run is created.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
pipeline_run |
PipelineRunRequest |
The pipeline run to get or create. |
required |
Returns:
| Type | Description |
|---|---|
Tuple[zenml.models.v2.core.pipeline_run.PipelineRunResponse, bool] |
The pipeline run, and a boolean indicating whether the run was created or not. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_or_create_run(
self, pipeline_run: PipelineRunRequest
) -> Tuple[PipelineRunResponse, bool]:
"""Gets or creates a pipeline run.
If a run with the same ID or name already exists, it is returned.
Otherwise, a new run is created.
Args:
pipeline_run: The pipeline run to get or create.
Returns:
The pipeline run, and a boolean indicating whether the run was
created or not.
"""
get_pipeline(self, pipeline_id, hydrate=True)
Get a pipeline with a given ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
pipeline_id |
UUID |
ID of the pipeline. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
PipelineResponse |
The pipeline. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the pipeline does not exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_pipeline(
self, pipeline_id: UUID, hydrate: bool = True
) -> PipelineResponse:
"""Get a pipeline with a given ID.
Args:
pipeline_id: ID of the pipeline.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The pipeline.
Raises:
KeyError: if the pipeline does not exist.
"""
get_run(self, run_name_or_id, hydrate=True)
Gets a pipeline run.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
run_name_or_id |
Union[str, uuid.UUID] |
The name or ID of the pipeline run to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
PipelineRunResponse |
The pipeline run. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the pipeline run doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_run(
self, run_name_or_id: Union[str, UUID], hydrate: bool = True
) -> PipelineRunResponse:
"""Gets a pipeline run.
Args:
run_name_or_id: The name or ID of the pipeline run to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The pipeline run.
Raises:
KeyError: if the pipeline run doesn't exist.
"""
get_run_metadata(self, run_metadata_id, hydrate=True)
Get run metadata by its unique ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
run_metadata_id |
UUID |
The ID of the run metadata to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
RunMetadataResponse |
The run metadata with the given ID. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the run metadata doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_run_metadata(
self, run_metadata_id: UUID, hydrate: bool = True
) -> RunMetadataResponse:
"""Get run metadata by its unique ID.
Args:
run_metadata_id: The ID of the run metadata to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The run metadata with the given ID.
Raises:
KeyError: if the run metadata doesn't exist.
"""
get_run_step(self, step_run_id, hydrate=True)
Get a step run by ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
step_run_id |
UUID |
The ID of the step run to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
StepRunResponse |
The step run. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the step run doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_run_step(
self, step_run_id: UUID, hydrate: bool = True
) -> StepRunResponse:
"""Get a step run by ID.
Args:
step_run_id: The ID of the step run to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The step run.
Raises:
KeyError: if the step run doesn't exist.
"""
get_schedule(self, schedule_id, hydrate=True)
Get a schedule with a given ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
schedule_id |
UUID |
ID of the schedule. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
ScheduleResponse |
The schedule. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the schedule does not exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_schedule(
self, schedule_id: UUID, hydrate: bool = True
) -> ScheduleResponse:
"""Get a schedule with a given ID.
Args:
schedule_id: ID of the schedule.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The schedule.
Raises:
KeyError: if the schedule does not exist.
"""
get_secret(self, secret_id, hydrate=True)
Get a secret with a given name.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
ID of the secret. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
SecretResponse |
The secret. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the secret does not exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_secret(
self, secret_id: UUID, hydrate: bool = True
) -> SecretResponse:
"""Get a secret with a given name.
Args:
secret_id: ID of the secret.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The secret.
Raises:
KeyError: if the secret does not exist.
"""
get_service_account(self, service_account_name_or_id, hydrate=True)
Gets a specific service account.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account_name_or_id |
Union[str, uuid.UUID] |
The name or ID of the service account to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
ServiceAccountResponse |
The requested service account, if it was found. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no service account with the given name or ID exists. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_service_account(
self,
service_account_name_or_id: Union[str, UUID],
hydrate: bool = True,
) -> ServiceAccountResponse:
"""Gets a specific service account.
Args:
service_account_name_or_id: The name or ID of the service account to
get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested service account, if it was found.
Raises:
KeyError: If no service account with the given name or ID exists.
"""
get_service_connector(self, service_connector_id, hydrate=True)
Gets a specific service connector.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_connector_id |
UUID |
The ID of the service connector to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
ServiceConnectorResponse |
The requested service connector, if it was found. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no service connector with the given ID exists. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_service_connector(
self, service_connector_id: UUID, hydrate: bool = True
) -> ServiceConnectorResponse:
"""Gets a specific service connector.
Args:
service_connector_id: The ID of the service connector to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested service connector, if it was found.
Raises:
KeyError: If no service connector with the given ID exists.
"""
get_service_connector_client(self, service_connector_id, resource_type=None, resource_id=None)
Get a service connector client for a service connector and given resource.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_connector_id |
UUID |
The ID of the base service connector to use. |
required |
resource_type |
Optional[str] |
The type of resource to get a client for. |
None |
resource_id |
Optional[str] |
The ID of the resource to get a client for. |
None |
Returns:
| Type | Description |
|---|---|
ServiceConnectorResponse |
A service connector client that can be used to access the given resource. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no service connector with the given name exists. |
NotImplementError |
If the service connector cannot be instantiated on the store e.g. due to missing package dependencies. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_service_connector_client(
self,
service_connector_id: UUID,
resource_type: Optional[str] = None,
resource_id: Optional[str] = None,
) -> ServiceConnectorResponse:
"""Get a service connector client for a service connector and given resource.
Args:
service_connector_id: The ID of the base service connector to use.
resource_type: The type of resource to get a client for.
resource_id: The ID of the resource to get a client for.
Returns:
A service connector client that can be used to access the given
resource.
Raises:
KeyError: If no service connector with the given name exists.
NotImplementError: If the service connector cannot be instantiated
on the store e.g. due to missing package dependencies.
"""
get_service_connector_type(self, connector_type)
Returns the requested service connector type.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
connector_type |
str |
the service connector type identifier. |
required |
Returns:
| Type | Description |
|---|---|
ServiceConnectorTypeModel |
The requested service connector type. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no service connector type with the given ID exists. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_service_connector_type(
self,
connector_type: str,
) -> ServiceConnectorTypeModel:
"""Returns the requested service connector type.
Args:
connector_type: the service connector type identifier.
Returns:
The requested service connector type.
Raises:
KeyError: If no service connector type with the given ID exists.
"""
get_stack(self, stack_id, hydrate=True)
Get a stack by its unique ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
stack_id |
UUID |
The ID of the stack to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
StackResponse |
The stack with the given ID. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the stack doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_stack(self, stack_id: UUID, hydrate: bool = True) -> StackResponse:
"""Get a stack by its unique ID.
Args:
stack_id: The ID of the stack to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The stack with the given ID.
Raises:
KeyError: if the stack doesn't exist.
"""
get_stack_component(self, component_id, hydrate=True)
Get a stack component by ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
component_id |
UUID |
The ID of the stack component to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
ComponentResponse |
The stack component. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the stack component doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_stack_component(
self,
component_id: UUID,
hydrate: bool = True,
) -> ComponentResponse:
"""Get a stack component by ID.
Args:
component_id: The ID of the stack component to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The stack component.
Raises:
KeyError: if the stack component doesn't exist.
"""
get_store_info(self)
Get information about the store.
Returns:
| Type | Description |
|---|---|
ServerModel |
Information about the store. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_store_info(self) -> ServerModel:
"""Get information about the store.
Returns:
Information about the store.
"""
get_tag(self, tag_name_or_id, hydrate=True)
Get an existing tag.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
tag_name_or_id |
Union[str, uuid.UUID] |
name or id of the tag to be retrieved. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
TagResponse |
The tag of interest. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
specified ID or name not found. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_tag(
self, tag_name_or_id: Union[str, UUID], hydrate: bool = True
) -> TagResponse:
"""Get an existing tag.
Args:
tag_name_or_id: name or id of the tag to be retrieved.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The tag of interest.
Raises:
KeyError: specified ID or name not found.
"""
get_trigger(self, trigger_id, hydrate=True)
Get an trigger by ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
trigger_id |
UUID |
The ID of the trigger to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
TriggerResponse |
The trigger. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the stack trigger doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_trigger(
self,
trigger_id: UUID,
hydrate: bool = True,
) -> TriggerResponse:
"""Get an trigger by ID.
Args:
trigger_id: The ID of the trigger to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The trigger.
Raises:
KeyError: if the stack trigger doesn't exist.
"""
get_trigger_execution(self, trigger_execution_id, hydrate=True)
Get an trigger execution by ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
trigger_execution_id |
UUID |
The ID of the trigger execution to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
TriggerExecutionResponse |
The trigger execution. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If the trigger execution doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_trigger_execution(
self,
trigger_execution_id: UUID,
hydrate: bool = True,
) -> TriggerExecutionResponse:
"""Get an trigger execution by ID.
Args:
trigger_execution_id: The ID of the trigger execution to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The trigger execution.
Raises:
KeyError: If the trigger execution doesn't exist.
"""
get_user(self, user_name_or_id=None, include_private=False, hydrate=True)
Gets a specific user, when no id is specified the active user is returned.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
user_name_or_id |
Union[str, uuid.UUID] |
The name or ID of the user to get. |
None |
include_private |
bool |
Whether to include private user information. |
False |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
UserResponse |
The requested user, if it was found. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no user with the given name or ID exists. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_user(
self,
user_name_or_id: Optional[Union[str, UUID]] = None,
include_private: bool = False,
hydrate: bool = True,
) -> UserResponse:
"""Gets a specific user, when no id is specified the active user is returned.
Args:
user_name_or_id: The name or ID of the user to get.
include_private: Whether to include private user information.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested user, if it was found.
Raises:
KeyError: If no user with the given name or ID exists.
"""
get_workspace(self, workspace_name_or_id, hydrate=True)
Get an existing workspace by name or ID.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
workspace_name_or_id |
Union[uuid.UUID, str] |
Name or ID of the workspace to get. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
True |
Returns:
| Type | Description |
|---|---|
WorkspaceResponse |
The requested workspace. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If there is no such workspace. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def get_workspace(
self, workspace_name_or_id: Union[UUID, str], hydrate: bool = True
) -> WorkspaceResponse:
"""Get an existing workspace by name or ID.
Args:
workspace_name_or_id: Name or ID of the workspace to get.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The requested workspace.
Raises:
KeyError: If there is no such workspace.
"""
list_api_keys(self, service_account_id, filter_model, hydrate=False)
List all API keys for a service account matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account_id |
UUID |
The ID of the service account for which to list the API keys. |
required |
filter_model |
APIKeyFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[APIKeyResponse] |
A list of all API keys matching the filter criteria. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def list_api_keys(
self,
service_account_id: UUID,
filter_model: APIKeyFilter,
hydrate: bool = False,
) -> Page[APIKeyResponse]:
"""List all API keys for a service account matching the given filter criteria.
Args:
service_account_id: The ID of the service account for which to list
the API keys.
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all API keys matching the filter criteria.
"""
list_artifact_versions(self, artifact_version_filter_model, hydrate=False)
List all artifact versions matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_version_filter_model |
ArtifactVersionFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[ArtifactVersionResponse] |
A list of all artifact versions matching the filter criteria. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def list_artifact_versions(
self,
artifact_version_filter_model: ArtifactVersionFilter,
hydrate: bool = False,
) -> Page[ArtifactVersionResponse]:
"""List all artifact versions matching the given filter criteria.
Args:
artifact_version_filter_model: All filter parameters including
pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all artifact versions matching the filter criteria.
"""
list_artifacts(self, filter_model, hydrate=False)
List all artifacts matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
filter_model |
ArtifactFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[ArtifactResponse] |
A list of all artifacts matching the filter criteria. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def list_artifacts(
self, filter_model: ArtifactFilter, hydrate: bool = False
) -> Page[ArtifactResponse]:
"""List all artifacts matching the given filter criteria.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all artifacts matching the filter criteria.
"""
list_authorized_devices(self, filter_model, hydrate=False)
List all OAuth 2.0 authorized devices for a user.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
filter_model |
OAuthDeviceFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[OAuthDeviceResponse] |
A page of all matching OAuth 2.0 authorized devices. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def list_authorized_devices(
self, filter_model: OAuthDeviceFilter, hydrate: bool = False
) -> Page[OAuthDeviceResponse]:
"""List all OAuth 2.0 authorized devices for a user.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all matching OAuth 2.0 authorized devices.
"""
list_builds(self, build_filter_model, hydrate=False)
List all builds matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
build_filter_model |
PipelineBuildFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[PipelineBuildResponse] |
A page of all builds matching the filter criteria. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def list_builds(
self,
build_filter_model: PipelineBuildFilter,
hydrate: bool = False,
) -> Page[PipelineBuildResponse]:
"""List all builds matching the given filter criteria.
Args:
build_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all builds matching the filter criteria.
"""
list_code_repositories(self, filter_model, hydrate=False)
List all code repositories.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
filter_model |
CodeRepositoryFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[CodeRepositoryResponse] |
A page of all code repositories. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def list_code_repositories(
self, filter_model: CodeRepositoryFilter, hydrate: bool = False
) -> Page[CodeRepositoryResponse]:
"""List all code repositories.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all code repositories.
"""
list_deployments(self, deployment_filter_model, hydrate=False)
List all deployments matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
deployment_filter_model |
PipelineDeploymentFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[PipelineDeploymentResponse] |
A page of all deployments matching the filter criteria. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def list_deployments(
self,
deployment_filter_model: PipelineDeploymentFilter,
hydrate: bool = False,
) -> Page[PipelineDeploymentResponse]:
"""List all deployments matching the given filter criteria.
Args:
deployment_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all deployments matching the filter criteria.
"""
list_event_sources(self, event_source_filter_model, hydrate=False)
List all event_sources matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
event_source_filter_model |
EventSourceFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[EventSourceResponse] |
A list of all event_sources matching the filter criteria. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def list_event_sources(
self,
event_source_filter_model: EventSourceFilter,
hydrate: bool = False,
) -> Page[EventSourceResponse]:
"""List all event_sources matching the given filter criteria.
Args:
event_source_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all event_sources matching the filter criteria.
"""
list_flavors(self, flavor_filter_model, hydrate=False)
List all stack component flavors matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
flavor_filter_model |
FlavorFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[FlavorResponse] |
List of all the stack component flavors matching the given criteria. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def list_flavors(
self,
flavor_filter_model: FlavorFilter,
hydrate: bool = False,
) -> Page[FlavorResponse]:
"""List all stack component flavors matching the given filter criteria.
Args:
flavor_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
List of all the stack component flavors matching the given criteria.
"""
list_model_version_artifact_links(self, model_version_artifact_link_filter_model, hydrate=False)
Get all model version to artifact links by filter.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_artifact_link_filter_model |
ModelVersionArtifactFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[ModelVersionArtifactResponse] |
A page of all model version to artifact links. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def list_model_version_artifact_links(
self,
model_version_artifact_link_filter_model: ModelVersionArtifactFilter,
hydrate: bool = False,
) -> Page[ModelVersionArtifactResponse]:
"""Get all model version to artifact links by filter.
Args:
model_version_artifact_link_filter_model: All filter parameters
including pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all model version to artifact links.
"""
list_model_version_pipeline_run_links(self, model_version_pipeline_run_link_filter_model, hydrate=False)
Get all model version to pipeline run links by filter.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_pipeline_run_link_filter_model |
ModelVersionPipelineRunFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[ModelVersionPipelineRunResponse] |
A page of all model version to pipeline run links. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def list_model_version_pipeline_run_links(
self,
model_version_pipeline_run_link_filter_model: ModelVersionPipelineRunFilter,
hydrate: bool = False,
) -> Page[ModelVersionPipelineRunResponse]:
"""Get all model version to pipeline run links by filter.
Args:
model_version_pipeline_run_link_filter_model: All filter parameters
including pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all model version to pipeline run links.
"""
list_model_versions(self, model_version_filter_model, model_name_or_id=None, hydrate=False)
Get all model versions by filter.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_name_or_id |
Union[str, uuid.UUID] |
name or id of the model containing the model versions. |
None |
model_version_filter_model |
ModelVersionFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[ModelVersionResponse] |
A page of all model versions. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def list_model_versions(
self,
model_version_filter_model: ModelVersionFilter,
model_name_or_id: Optional[Union[str, UUID]] = None,
hydrate: bool = False,
) -> Page[ModelVersionResponse]:
"""Get all model versions by filter.
Args:
model_name_or_id: name or id of the model containing the model
versions.
model_version_filter_model: All filter parameters including
pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all model versions.
"""
list_models(self, model_filter_model, hydrate=False)
Get all models by filter.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_filter_model |
ModelFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[ModelResponse] |
A page of all models. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def list_models(
self,
model_filter_model: ModelFilter,
hydrate: bool = False,
) -> Page[ModelResponse]:
"""Get all models by filter.
Args:
model_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all models.
"""
list_pipelines(self, pipeline_filter_model, hydrate=False)
List all pipelines matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
pipeline_filter_model |
PipelineFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[PipelineResponse] |
A list of all pipelines matching the filter criteria. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def list_pipelines(
self,
pipeline_filter_model: PipelineFilter,
hydrate: bool = False,
) -> Page[PipelineResponse]:
"""List all pipelines matching the given filter criteria.
Args:
pipeline_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all pipelines matching the filter criteria.
"""
list_run_metadata(self, run_metadata_filter_model, hydrate=False)
List run metadata.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
run_metadata_filter_model |
RunMetadataFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[RunMetadataResponse] |
The run metadata. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def list_run_metadata(
self,
run_metadata_filter_model: RunMetadataFilter,
hydrate: bool = False,
) -> Page[RunMetadataResponse]:
"""List run metadata.
Args:
run_metadata_filter_model: All filter parameters including
pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
The run metadata.
"""
list_run_steps(self, step_run_filter_model, hydrate=False)
List all step runs matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
step_run_filter_model |
StepRunFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[StepRunResponse] |
A list of all step runs matching the filter criteria. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def list_run_steps(
self,
step_run_filter_model: StepRunFilter,
hydrate: bool = False,
) -> Page[StepRunResponse]:
"""List all step runs matching the given filter criteria.
Args:
step_run_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all step runs matching the filter criteria.
"""
list_runs(self, runs_filter_model, hydrate=False)
List all pipeline runs matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
runs_filter_model |
PipelineRunFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[PipelineRunResponse] |
A list of all pipeline runs matching the filter criteria. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def list_runs(
self,
runs_filter_model: PipelineRunFilter,
hydrate: bool = False,
) -> Page[PipelineRunResponse]:
"""List all pipeline runs matching the given filter criteria.
Args:
runs_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all pipeline runs matching the filter criteria.
"""
list_schedules(self, schedule_filter_model, hydrate=False)
List all schedules in the workspace.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
schedule_filter_model |
ScheduleFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[ScheduleResponse] |
A list of schedules. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def list_schedules(
self,
schedule_filter_model: ScheduleFilter,
hydrate: bool = False,
) -> Page[ScheduleResponse]:
"""List all schedules in the workspace.
Args:
schedule_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of schedules.
"""
list_secrets(self, secret_filter_model, hydrate=False)
List all secrets matching the given filter criteria.
Note that returned secrets do not include any secret values. To fetch
the secret values, use get_secret.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_filter_model |
SecretFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[SecretResponse] |
A list of all secrets matching the filter criteria, with pagination
information and sorted according to the filter criteria. The
returned secrets do not include any secret values, only metadata. To
fetch the secret values, use |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def list_secrets(
self, secret_filter_model: SecretFilter, hydrate: bool = False
) -> Page[SecretResponse]:
"""List all secrets matching the given filter criteria.
Note that returned secrets do not include any secret values. To fetch
the secret values, use `get_secret`.
Args:
secret_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all secrets matching the filter criteria, with pagination
information and sorted according to the filter criteria. The
returned secrets do not include any secret values, only metadata. To
fetch the secret values, use `get_secret` individually with each
secret.
"""
list_service_accounts(self, filter_model, hydrate=False)
List all service accounts.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
filter_model |
ServiceAccountFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[ServiceAccountResponse] |
A list of filtered service accounts. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def list_service_accounts(
self,
filter_model: ServiceAccountFilter,
hydrate: bool = False,
) -> Page[ServiceAccountResponse]:
"""List all service accounts.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of filtered service accounts.
"""
list_service_connector_resources(self, workspace_name_or_id, connector_type=None, resource_type=None, resource_id=None)
List resources that can be accessed by service connectors.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
workspace_name_or_id |
Union[str, uuid.UUID] |
The name or ID of the workspace to scope to. |
required |
connector_type |
Optional[str] |
The type of service connector to scope to. |
None |
resource_type |
Optional[str] |
The type of resource to scope to. |
None |
resource_id |
Optional[str] |
The ID of the resource to scope to. |
None |
Returns:
| Type | Description |
|---|---|
List[zenml.models.v2.misc.service_connector_type.ServiceConnectorResourcesModel] |
The matching list of resources that available service connectors have access to. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def list_service_connector_resources(
self,
workspace_name_or_id: Union[str, UUID],
connector_type: Optional[str] = None,
resource_type: Optional[str] = None,
resource_id: Optional[str] = None,
) -> List[ServiceConnectorResourcesModel]:
"""List resources that can be accessed by service connectors.
Args:
workspace_name_or_id: The name or ID of the workspace to scope to.
connector_type: The type of service connector to scope to.
resource_type: The type of resource to scope to.
resource_id: The ID of the resource to scope to.
Returns:
The matching list of resources that available service
connectors have access to.
"""
list_service_connector_types(self, connector_type=None, resource_type=None, auth_method=None)
Get a list of service connector types.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
connector_type |
Optional[str] |
Filter by connector type. |
None |
resource_type |
Optional[str] |
Filter by resource type. |
None |
auth_method |
Optional[str] |
Filter by authentication method. |
None |
Returns:
| Type | Description |
|---|---|
List[zenml.models.v2.misc.service_connector_type.ServiceConnectorTypeModel] |
List of service connector types. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def list_service_connector_types(
self,
connector_type: Optional[str] = None,
resource_type: Optional[str] = None,
auth_method: Optional[str] = None,
) -> List[ServiceConnectorTypeModel]:
"""Get a list of service connector types.
Args:
connector_type: Filter by connector type.
resource_type: Filter by resource type.
auth_method: Filter by authentication method.
Returns:
List of service connector types.
"""
list_service_connectors(self, filter_model, hydrate=False)
List all service connectors.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
filter_model |
ServiceConnectorFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[ServiceConnectorResponse] |
A page of all service connectors. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def list_service_connectors(
self,
filter_model: ServiceConnectorFilter,
hydrate: bool = False,
) -> Page[ServiceConnectorResponse]:
"""List all service connectors.
Args:
filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all service connectors.
"""
list_stack_components(self, component_filter_model, hydrate=False)
List all stack components matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
component_filter_model |
ComponentFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[ComponentResponse] |
A list of all stack components matching the filter criteria. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def list_stack_components(
self,
component_filter_model: ComponentFilter,
hydrate: bool = False,
) -> Page[ComponentResponse]:
"""List all stack components matching the given filter criteria.
Args:
component_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all stack components matching the filter criteria.
"""
list_stacks(self, stack_filter_model, hydrate=False)
List all stacks matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
stack_filter_model |
StackFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[StackResponse] |
A list of all stacks matching the filter criteria. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def list_stacks(
self,
stack_filter_model: StackFilter,
hydrate: bool = False,
) -> Page[StackResponse]:
"""List all stacks matching the given filter criteria.
Args:
stack_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all stacks matching the filter criteria.
"""
list_tags(self, tag_filter_model, hydrate=False)
Get all tags by filter.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
tag_filter_model |
TagFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[TagResponse] |
A page of all tags. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def list_tags(
self,
tag_filter_model: TagFilter,
hydrate: bool = False,
) -> Page[TagResponse]:
"""Get all tags by filter.
Args:
tag_filter_model: All filter parameters including pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A page of all tags.
"""
list_trigger_executions(self, trigger_execution_filter_model, hydrate=False)
List all trigger executions matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
trigger_execution_filter_model |
TriggerExecutionFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[TriggerExecutionResponse] |
A list of all trigger executions matching the filter criteria. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def list_trigger_executions(
self,
trigger_execution_filter_model: TriggerExecutionFilter,
hydrate: bool = False,
) -> Page[TriggerExecutionResponse]:
"""List all trigger executions matching the given filter criteria.
Args:
trigger_execution_filter_model: All filter parameters including
pagination params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all trigger executions matching the filter criteria.
"""
list_triggers(self, trigger_filter_model, hydrate=False)
List all triggers matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
trigger_filter_model |
TriggerFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[TriggerResponse] |
A list of all triggers matching the filter criteria. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def list_triggers(
self,
trigger_filter_model: TriggerFilter,
hydrate: bool = False,
) -> Page[TriggerResponse]:
"""List all triggers matching the given filter criteria.
Args:
trigger_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all triggers matching the filter criteria.
"""
list_users(self, user_filter_model, hydrate=False)
List all users.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
user_filter_model |
UserFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[UserResponse] |
A list of all users. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def list_users(
self,
user_filter_model: UserFilter,
hydrate: bool = False,
) -> Page[UserResponse]:
"""List all users.
Args:
user_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all users.
"""
list_workspaces(self, workspace_filter_model, hydrate=False)
List all workspace matching the given filter criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
workspace_filter_model |
WorkspaceFilter |
All filter parameters including pagination params. |
required |
hydrate |
bool |
Flag deciding whether to hydrate the output model(s) by including metadata fields in the response. |
False |
Returns:
| Type | Description |
|---|---|
Page[WorkspaceResponse] |
A list of all workspace matching the filter criteria. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def list_workspaces(
self,
workspace_filter_model: WorkspaceFilter,
hydrate: bool = False,
) -> Page[WorkspaceResponse]:
"""List all workspace matching the given filter criteria.
Args:
workspace_filter_model: All filter parameters including pagination
params.
hydrate: Flag deciding whether to hydrate the output model(s)
by including metadata fields in the response.
Returns:
A list of all workspace matching the filter criteria.
"""
prune_artifact_versions(self, only_versions=True)
Prunes unused artifact versions and their artifacts.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
only_versions |
bool |
Only delete artifact versions, keeping artifacts |
True |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def prune_artifact_versions(
self,
only_versions: bool = True,
) -> None:
"""Prunes unused artifact versions and their artifacts.
Args:
only_versions: Only delete artifact versions, keeping artifacts
"""
restore_secrets(self, ignore_errors=False, delete_secrets=False)
Restore all secrets from the configured backup secrets store.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
ignore_errors |
bool |
Whether to ignore individual errors during the restore process and attempt to restore all secrets. |
False |
delete_secrets |
bool |
Whether to delete the secrets that have been successfully restored from the backup secrets store. Setting this flag effectively moves all secrets from the backup secrets store to the primary secrets store. |
False |
Exceptions:
| Type | Description |
|---|---|
BackupSecretsStoreNotConfiguredError |
if no backup secrets store is configured. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def restore_secrets(
self, ignore_errors: bool = False, delete_secrets: bool = False
) -> None:
"""Restore all secrets from the configured backup secrets store.
Args:
ignore_errors: Whether to ignore individual errors during the
restore process and attempt to restore all secrets.
delete_secrets: Whether to delete the secrets that have been
successfully restored from the backup secrets store. Setting
this flag effectively moves all secrets from the backup secrets
store to the primary secrets store.
Raises:
BackupSecretsStoreNotConfiguredError: if no backup secrets store is
configured.
"""
rotate_api_key(self, service_account_id, api_key_name_or_id, rotate_request)
Rotate an API key for a service account.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account_id |
UUID |
The ID of the service account for which to rotate the API key. |
required |
api_key_name_or_id |
Union[str, uuid.UUID] |
The name or ID of the API key to rotate. |
required |
rotate_request |
APIKeyRotateRequest |
The rotate request on the API key. |
required |
Returns:
| Type | Description |
|---|---|
APIKeyResponse |
The updated API key. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if an API key with the given name or ID is not configured for the given service account. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def rotate_api_key(
self,
service_account_id: UUID,
api_key_name_or_id: Union[str, UUID],
rotate_request: APIKeyRotateRequest,
) -> APIKeyResponse:
"""Rotate an API key for a service account.
Args:
service_account_id: The ID of the service account for which to
rotate the API key.
api_key_name_or_id: The name or ID of the API key to rotate.
rotate_request: The rotate request on the API key.
Returns:
The updated API key.
Raises:
KeyError: if an API key with the given name or ID is not configured
for the given service account.
"""
update_api_key(self, service_account_id, api_key_name_or_id, api_key_update)
Update an API key for a service account.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account_id |
UUID |
The ID of the service account for which to update the API key. |
required |
api_key_name_or_id |
Union[str, uuid.UUID] |
The name or ID of the API key to update. |
required |
api_key_update |
APIKeyUpdate |
The update request on the API key. |
required |
Returns:
| Type | Description |
|---|---|
APIKeyResponse |
The updated API key. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if an API key with the given name or ID is not configured for the given service account. |
EntityExistsError |
if the API key update would result in a name conflict with an existing API key for the same service account. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def update_api_key(
self,
service_account_id: UUID,
api_key_name_or_id: Union[str, UUID],
api_key_update: APIKeyUpdate,
) -> APIKeyResponse:
"""Update an API key for a service account.
Args:
service_account_id: The ID of the service account for which to update
the API key.
api_key_name_or_id: The name or ID of the API key to update.
api_key_update: The update request on the API key.
Returns:
The updated API key.
Raises:
KeyError: if an API key with the given name or ID is not configured
for the given service account.
EntityExistsError: if the API key update would result in a name
conflict with an existing API key for the same service account.
"""
update_artifact(self, artifact_id, artifact_update)
Updates an artifact.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_id |
UUID |
The ID of the artifact to update. |
required |
artifact_update |
ArtifactUpdate |
The update to be applied to the artifact. |
required |
Returns:
| Type | Description |
|---|---|
ArtifactResponse |
The updated artifact. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the artifact doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def update_artifact(
self, artifact_id: UUID, artifact_update: ArtifactUpdate
) -> ArtifactResponse:
"""Updates an artifact.
Args:
artifact_id: The ID of the artifact to update.
artifact_update: The update to be applied to the artifact.
Returns:
The updated artifact.
Raises:
KeyError: if the artifact doesn't exist.
"""
update_artifact_version(self, artifact_version_id, artifact_version_update)
Updates an artifact version.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
artifact_version_id |
UUID |
The ID of the artifact version to update. |
required |
artifact_version_update |
ArtifactVersionUpdate |
The update to be applied to the artifact version. |
required |
Returns:
| Type | Description |
|---|---|
ArtifactVersionResponse |
The updated artifact version. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the artifact version doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def update_artifact_version(
self,
artifact_version_id: UUID,
artifact_version_update: ArtifactVersionUpdate,
) -> ArtifactVersionResponse:
"""Updates an artifact version.
Args:
artifact_version_id: The ID of the artifact version to update.
artifact_version_update: The update to be applied to the artifact
version.
Returns:
The updated artifact version.
Raises:
KeyError: if the artifact version doesn't exist.
"""
update_authorized_device(self, device_id, update)
Updates an existing OAuth 2.0 authorized device for internal use.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
device_id |
UUID |
The ID of the device to update. |
required |
update |
OAuthDeviceUpdate |
The update to be applied to the device. |
required |
Returns:
| Type | Description |
|---|---|
OAuthDeviceResponse |
The updated OAuth 2.0 authorized device. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no device with the given ID exists. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def update_authorized_device(
self, device_id: UUID, update: OAuthDeviceUpdate
) -> OAuthDeviceResponse:
"""Updates an existing OAuth 2.0 authorized device for internal use.
Args:
device_id: The ID of the device to update.
update: The update to be applied to the device.
Returns:
The updated OAuth 2.0 authorized device.
Raises:
KeyError: If no device with the given ID exists.
"""
update_code_repository(self, code_repository_id, update)
Updates an existing code repository.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
code_repository_id |
UUID |
The ID of the code repository to update. |
required |
update |
CodeRepositoryUpdate |
The update to be applied to the code repository. |
required |
Returns:
| Type | Description |
|---|---|
CodeRepositoryResponse |
The updated code repository. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no code repository with the given name exists. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def update_code_repository(
self, code_repository_id: UUID, update: CodeRepositoryUpdate
) -> CodeRepositoryResponse:
"""Updates an existing code repository.
Args:
code_repository_id: The ID of the code repository to update.
update: The update to be applied to the code repository.
Returns:
The updated code repository.
Raises:
KeyError: If no code repository with the given name exists.
"""
update_event_source(self, event_source_id, event_source_update)
Update an existing event_source.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
event_source_id |
UUID |
The ID of the event_source to update. |
required |
event_source_update |
EventSourceUpdate |
The update to be applied to the event_source. |
required |
Returns:
| Type | Description |
|---|---|
EventSourceResponse |
The updated event_source. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the event_source doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def update_event_source(
self,
event_source_id: UUID,
event_source_update: EventSourceUpdate,
) -> EventSourceResponse:
"""Update an existing event_source.
Args:
event_source_id: The ID of the event_source to update.
event_source_update: The update to be applied to the event_source.
Returns:
The updated event_source.
Raises:
KeyError: if the event_source doesn't exist.
"""
update_flavor(self, flavor_id, flavor_update)
Updates an existing user.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
flavor_id |
UUID |
The id of the flavor to update. |
required |
flavor_update |
FlavorUpdate |
The update to be applied to the flavor. |
required |
Returns:
| Type | Description |
|---|---|
FlavorResponse |
The updated flavor. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def update_flavor(
self, flavor_id: UUID, flavor_update: FlavorUpdate
) -> FlavorResponse:
"""Updates an existing user.
Args:
flavor_id: The id of the flavor to update.
flavor_update: The update to be applied to the flavor.
Returns:
The updated flavor.
"""
update_model(self, model_id, model_update)
Updates an existing model.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_id |
UUID |
UUID of the model to be updated. |
required |
model_update |
ModelUpdate |
the Model to be updated. |
required |
Returns:
| Type | Description |
|---|---|
ModelResponse |
The updated model. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def update_model(
self,
model_id: UUID,
model_update: ModelUpdate,
) -> ModelResponse:
"""Updates an existing model.
Args:
model_id: UUID of the model to be updated.
model_update: the Model to be updated.
Returns:
The updated model.
"""
update_model_version(self, model_version_id, model_version_update_model)
Get all model versions by filter.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_version_id |
UUID |
The ID of model version to be updated. |
required |
model_version_update_model |
ModelVersionUpdate |
The model version to be updated. |
required |
Returns:
| Type | Description |
|---|---|
ModelVersionResponse |
An updated model version. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If the model version not found |
RuntimeError |
If there is a model version with target stage,
but |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def update_model_version(
self,
model_version_id: UUID,
model_version_update_model: ModelVersionUpdate,
) -> ModelVersionResponse:
"""Get all model versions by filter.
Args:
model_version_id: The ID of model version to be updated.
model_version_update_model: The model version to be updated.
Returns:
An updated model version.
Raises:
KeyError: If the model version not found
RuntimeError: If there is a model version with target stage,
but `force` flag is off
"""
update_pipeline(self, pipeline_id, pipeline_update)
Updates a pipeline.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
pipeline_id |
UUID |
The ID of the pipeline to be updated. |
required |
pipeline_update |
PipelineUpdate |
The update to be applied. |
required |
Returns:
| Type | Description |
|---|---|
PipelineResponse |
The updated pipeline. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the pipeline doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def update_pipeline(
self,
pipeline_id: UUID,
pipeline_update: PipelineUpdate,
) -> PipelineResponse:
"""Updates a pipeline.
Args:
pipeline_id: The ID of the pipeline to be updated.
pipeline_update: The update to be applied.
Returns:
The updated pipeline.
Raises:
KeyError: if the pipeline doesn't exist.
"""
update_run(self, run_id, run_update)
Updates a pipeline run.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
run_id |
UUID |
The ID of the pipeline run to update. |
required |
run_update |
PipelineRunUpdate |
The update to be applied to the pipeline run. |
required |
Returns:
| Type | Description |
|---|---|
PipelineRunResponse |
The updated pipeline run. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the pipeline run doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def update_run(
self, run_id: UUID, run_update: PipelineRunUpdate
) -> PipelineRunResponse:
"""Updates a pipeline run.
Args:
run_id: The ID of the pipeline run to update.
run_update: The update to be applied to the pipeline run.
Returns:
The updated pipeline run.
Raises:
KeyError: if the pipeline run doesn't exist.
"""
update_run_step(self, step_run_id, step_run_update)
Updates a step run.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
step_run_id |
UUID |
The ID of the step to update. |
required |
step_run_update |
StepRunUpdate |
The update to be applied to the step. |
required |
Returns:
| Type | Description |
|---|---|
StepRunResponse |
The updated step run. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the step run doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def update_run_step(
self,
step_run_id: UUID,
step_run_update: StepRunUpdate,
) -> StepRunResponse:
"""Updates a step run.
Args:
step_run_id: The ID of the step to update.
step_run_update: The update to be applied to the step.
Returns:
The updated step run.
Raises:
KeyError: if the step run doesn't exist.
"""
update_schedule(self, schedule_id, schedule_update)
Updates a schedule.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
schedule_id |
UUID |
The ID of the schedule to be updated. |
required |
schedule_update |
ScheduleUpdate |
The update to be applied. |
required |
Returns:
| Type | Description |
|---|---|
ScheduleResponse |
The updated schedule. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the schedule doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def update_schedule(
self,
schedule_id: UUID,
schedule_update: ScheduleUpdate,
) -> ScheduleResponse:
"""Updates a schedule.
Args:
schedule_id: The ID of the schedule to be updated.
schedule_update: The update to be applied.
Returns:
The updated schedule.
Raises:
KeyError: if the schedule doesn't exist.
"""
update_secret(self, secret_id, secret_update)
Updates a secret.
Secret values that are specified as None in the update that are
present in the existing secret are removed from the existing secret.
Values that are present in both secrets are overwritten. All other
values in both the existing secret and the update are kept (merged).
If the update includes a change of name or scope, the scoping rules enforced in the secrets store are used to validate the update:
- only one workspace-scoped secret with the given name can exist in the target workspace.
- only one user-scoped secret with the given name can exist in the target workspace for the target user.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
secret_id |
UUID |
The ID of the secret to be updated. |
required |
secret_update |
SecretUpdate |
The update to be applied. |
required |
Returns:
| Type | Description |
|---|---|
SecretResponse |
The updated secret. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the secret doesn't exist. |
EntityExistsError |
If a secret with the same name already exists in the same scope. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def update_secret(
self,
secret_id: UUID,
secret_update: SecretUpdate,
) -> SecretResponse:
"""Updates a secret.
Secret values that are specified as `None` in the update that are
present in the existing secret are removed from the existing secret.
Values that are present in both secrets are overwritten. All other
values in both the existing secret and the update are kept (merged).
If the update includes a change of name or scope, the scoping rules
enforced in the secrets store are used to validate the update:
- only one workspace-scoped secret with the given name can exist
in the target workspace.
- only one user-scoped secret with the given name can exist in the
target workspace for the target user.
Args:
secret_id: The ID of the secret to be updated.
secret_update: The update to be applied.
Returns:
The updated secret.
Raises:
KeyError: if the secret doesn't exist.
EntityExistsError: If a secret with the same name already exists in
the same scope.
"""
update_service_account(self, service_account_name_or_id, service_account_update)
Updates an existing service account.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_account_name_or_id |
Union[str, uuid.UUID] |
The name or the ID of the service account to update. |
required |
service_account_update |
ServiceAccountUpdate |
The update to be applied to the service account. |
required |
Returns:
| Type | Description |
|---|---|
ServiceAccountResponse |
The updated service account. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no service account with the given name exists. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def update_service_account(
self,
service_account_name_or_id: Union[str, UUID],
service_account_update: ServiceAccountUpdate,
) -> ServiceAccountResponse:
"""Updates an existing service account.
Args:
service_account_name_or_id: The name or the ID of the service
account to update.
service_account_update: The update to be applied to the service
account.
Returns:
The updated service account.
Raises:
KeyError: If no service account with the given name exists.
"""
update_service_connector(self, service_connector_id, update)
Updates an existing service connector.
The update model contains the fields to be updated. If a field value is set to None in the model, the field is not updated, but there are special rules concerning some fields:
- the
configurationandsecretsfields together represent a full valid configuration update, not just a partial update. If either is set (i.e. not None) in the update, their values are merged together and will replace the existing configuration and secrets values. - the
resource_idfield value is also a full replacement value: if set toNone, the resource ID is removed from the service connector. - the
expiration_secondsfield value is also a full replacement value: if set toNone, the expiration is removed from the service connector. - the
secret_idfield value in the update is ignored, given that secrets are managed internally by the ZenML store. - the
labelsfield is also a full labels update: if set (i.e. notNone), all existing labels are removed and replaced by the new labels in the update.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_connector_id |
UUID |
The ID of the service connector to update. |
required |
update |
ServiceConnectorUpdate |
The update to be applied to the service connector. |
required |
Returns:
| Type | Description |
|---|---|
ServiceConnectorResponse |
The updated service connector. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no service connector with the given name exists. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def update_service_connector(
self, service_connector_id: UUID, update: ServiceConnectorUpdate
) -> ServiceConnectorResponse:
"""Updates an existing service connector.
The update model contains the fields to be updated. If a field value is
set to None in the model, the field is not updated, but there are
special rules concerning some fields:
* the `configuration` and `secrets` fields together represent a full
valid configuration update, not just a partial update. If either is
set (i.e. not None) in the update, their values are merged together and
will replace the existing configuration and secrets values.
* the `resource_id` field value is also a full replacement value: if set
to `None`, the resource ID is removed from the service connector.
* the `expiration_seconds` field value is also a full replacement value:
if set to `None`, the expiration is removed from the service connector.
* the `secret_id` field value in the update is ignored, given that
secrets are managed internally by the ZenML store.
* the `labels` field is also a full labels update: if set (i.e. not
`None`), all existing labels are removed and replaced by the new labels
in the update.
Args:
service_connector_id: The ID of the service connector to update.
update: The update to be applied to the service connector.
Returns:
The updated service connector.
Raises:
KeyError: If no service connector with the given name exists.
"""
update_stack(self, stack_id, stack_update)
Update a stack.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
stack_id |
UUID |
The ID of the stack update. |
required |
stack_update |
StackUpdate |
The update request on the stack. |
required |
Returns:
| Type | Description |
|---|---|
StackResponse |
The updated stack. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the stack doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def update_stack(
self, stack_id: UUID, stack_update: StackUpdate
) -> StackResponse:
"""Update a stack.
Args:
stack_id: The ID of the stack update.
stack_update: The update request on the stack.
Returns:
The updated stack.
Raises:
KeyError: if the stack doesn't exist.
"""
update_stack_component(self, component_id, component_update)
Update an existing stack component.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
component_id |
UUID |
The ID of the stack component to update. |
required |
component_update |
ComponentUpdate |
The update to be applied to the stack component. |
required |
Returns:
| Type | Description |
|---|---|
ComponentResponse |
The updated stack component. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the stack component doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def update_stack_component(
self,
component_id: UUID,
component_update: ComponentUpdate,
) -> ComponentResponse:
"""Update an existing stack component.
Args:
component_id: The ID of the stack component to update.
component_update: The update to be applied to the stack component.
Returns:
The updated stack component.
Raises:
KeyError: if the stack component doesn't exist.
"""
update_tag(self, tag_name_or_id, tag_update_model)
Update tag.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
tag_name_or_id |
Union[str, uuid.UUID] |
name or id of the tag to be updated. |
required |
tag_update_model |
TagUpdate |
Tag to use for the update. |
required |
Returns:
| Type | Description |
|---|---|
TagResponse |
An updated tag. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If the tag is not found |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def update_tag(
self,
tag_name_or_id: Union[str, UUID],
tag_update_model: TagUpdate,
) -> TagResponse:
"""Update tag.
Args:
tag_name_or_id: name or id of the tag to be updated.
tag_update_model: Tag to use for the update.
Returns:
An updated tag.
Raises:
KeyError: If the tag is not found
"""
update_trigger(self, trigger_id, trigger_update)
Update an existing trigger.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
trigger_id |
UUID |
The ID of the trigger to update. |
required |
trigger_update |
TriggerUpdate |
The update to be applied to the trigger. |
required |
Returns:
| Type | Description |
|---|---|
TriggerResponse |
The updated trigger. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the trigger doesn't exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def update_trigger(
self,
trigger_id: UUID,
trigger_update: TriggerUpdate,
) -> TriggerResponse:
"""Update an existing trigger.
Args:
trigger_id: The ID of the trigger to update.
trigger_update: The update to be applied to the trigger.
Returns:
The updated trigger.
Raises:
KeyError: if the trigger doesn't exist.
"""
update_user(self, user_id, user_update)
Updates an existing user.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
user_id |
UUID |
The id of the user to update. |
required |
user_update |
UserUpdate |
The update to be applied to the user. |
required |
Returns:
| Type | Description |
|---|---|
UserResponse |
The updated user. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no user with the given name exists. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def update_user(
self, user_id: UUID, user_update: UserUpdate
) -> UserResponse:
"""Updates an existing user.
Args:
user_id: The id of the user to update.
user_update: The update to be applied to the user.
Returns:
The updated user.
Raises:
KeyError: If no user with the given name exists.
"""
update_workspace(self, workspace_id, workspace_update)
Update an existing workspace.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
workspace_id |
UUID |
The ID of the workspace to be updated. |
required |
workspace_update |
WorkspaceUpdate |
The update to be applied to the workspace. |
required |
Returns:
| Type | Description |
|---|---|
WorkspaceResponse |
The updated workspace. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
if the workspace does not exist. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def update_workspace(
self, workspace_id: UUID, workspace_update: WorkspaceUpdate
) -> WorkspaceResponse:
"""Update an existing workspace.
Args:
workspace_id: The ID of the workspace to be updated.
workspace_update: The update to be applied to the workspace.
Returns:
The updated workspace.
Raises:
KeyError: if the workspace does not exist.
"""
verify_service_connector(self, service_connector_id, resource_type=None, resource_id=None, list_resources=True)
Verifies if a service connector instance has access to one or more resources.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_connector_id |
UUID |
The ID of the service connector to verify. |
required |
resource_type |
Optional[str] |
The type of resource to verify access to. |
None |
resource_id |
Optional[str] |
The ID of the resource to verify access to. |
None |
list_resources |
bool |
If True, the list of all resources accessible through the service connector and matching the supplied resource type and ID are returned. |
True |
Returns:
| Type | Description |
|---|---|
ServiceConnectorResourcesModel |
The list of resources that the service connector has access to, scoped to the supplied resource type and ID, if provided. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no service connector with the given name exists. |
NotImplementError |
If the service connector cannot be verified e.g. due to missing package dependencies. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def verify_service_connector(
self,
service_connector_id: UUID,
resource_type: Optional[str] = None,
resource_id: Optional[str] = None,
list_resources: bool = True,
) -> ServiceConnectorResourcesModel:
"""Verifies if a service connector instance has access to one or more resources.
Args:
service_connector_id: The ID of the service connector to verify.
resource_type: The type of resource to verify access to.
resource_id: The ID of the resource to verify access to.
list_resources: If True, the list of all resources accessible
through the service connector and matching the supplied resource
type and ID are returned.
Returns:
The list of resources that the service connector has access to,
scoped to the supplied resource type and ID, if provided.
Raises:
KeyError: If no service connector with the given name exists.
NotImplementError: If the service connector cannot be verified
e.g. due to missing package dependencies.
"""
verify_service_connector_config(self, service_connector, list_resources=True)
Verifies if a service connector configuration has access to resources.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_connector |
ServiceConnectorRequest |
The service connector configuration to verify. |
required |
list_resources |
bool |
If True, the list of all resources accessible through the service connector is returned. |
True |
Returns:
| Type | Description |
|---|---|
ServiceConnectorResourcesModel |
The list of resources that the service connector configuration has access to. |
Exceptions:
| Type | Description |
|---|---|
NotImplementError |
If the service connector cannot be verified on the store e.g. due to missing package dependencies. |
Source code in zenml/zen_stores/zen_store_interface.py
@abstractmethod
def verify_service_connector_config(
self,
service_connector: ServiceConnectorRequest,
list_resources: bool = True,
) -> ServiceConnectorResourcesModel:
"""Verifies if a service connector configuration has access to resources.
Args:
service_connector: The service connector configuration to verify.
list_resources: If True, the list of all resources accessible
through the service connector is returned.
Returns:
The list of resources that the service connector configuration has
access to.
Raises:
NotImplementError: If the service connector cannot be verified
on the store e.g. due to missing package dependencies.
"""