Service Connectors
zenml.service_connectors
special
ZenML Service Connectors.
docker_service_connector
Docker Service Connector.
The Docker Service Connector is responsible for authenticating with a Docker (or compatible) registry.
DockerAuthenticationMethods (StrEnum)
Docker Authentication methods.
Source code in zenml/service_connectors/docker_service_connector.py
class DockerAuthenticationMethods(StrEnum):
"""Docker Authentication methods."""
PASSWORD = "password"
DockerConfiguration (DockerCredentials)
Docker client configuration.
Source code in zenml/service_connectors/docker_service_connector.py
class DockerConfiguration(DockerCredentials):
"""Docker client configuration."""
registry: Optional[str] = Field(
default=None,
title="Registry server URL. Omit to use DockerHub.",
)
DockerCredentials (AuthenticationConfig)
Docker client authentication credentials.
Source code in zenml/service_connectors/docker_service_connector.py
class DockerCredentials(AuthenticationConfig):
"""Docker client authentication credentials."""
username: PlainSerializedSecretStr = Field(
title="Username",
)
password: PlainSerializedSecretStr = Field(
title="Password",
)
DockerServiceConnector (ServiceConnector)
Docker service connector.
Source code in zenml/service_connectors/docker_service_connector.py
class DockerServiceConnector(ServiceConnector):
"""Docker service connector."""
config: DockerConfiguration
@classmethod
def _get_connector_type(cls) -> ServiceConnectorTypeModel:
"""Get the service connector specification.
Returns:
The service connector specification.
"""
return DOCKER_SERVICE_CONNECTOR_TYPE_SPEC
@classmethod
def _parse_resource_id(
cls,
resource_id: str,
) -> str:
"""Validate and convert a Docker resource ID into a Docker registry name.
Args:
resource_id: The resource ID to convert.
Returns:
The Docker registry name.
Raises:
ValueError: If the provided resource ID is not a valid Docker
registry.
"""
registry: Optional[str] = None
if re.match(
r"^(https?://)?[a-zA-Z0-9-]+(\.[a-zA-Z0-9-]+)*(:[0-9]+)?(/.+)*$",
resource_id,
):
# The resource ID is a repository URL
if resource_id.startswith("https://") or resource_id.startswith(
"http://"
):
registry = resource_id.split("/")[2]
else:
registry = resource_id.split("/")[0]
else:
raise ValueError(
f"Invalid resource ID for a Docker registry: {resource_id}. "
f"Please provide a valid repository name or URL in the "
f"following format:\n"
"DockerHub: docker.io or [https://]index.docker.io/v1/[/<repository-name>]"
"generic OCI registry URI: http[s]://host[:port][/<repository-name>]"
)
if registry == f"index.{DOCKER_REGISTRY_NAME}":
registry = DOCKER_REGISTRY_NAME
return registry
def _canonical_resource_id(
self, resource_type: str, resource_id: str
) -> str:
"""Convert a resource ID to its canonical form.
Args:
resource_type: The resource type to canonicalize.
resource_id: The resource ID to canonicalize.
Returns:
The canonical resource ID.
"""
return self._parse_resource_id(resource_id)
def _get_default_resource_id(self, resource_type: str) -> str:
"""Get the default resource ID for a resource type.
Args:
resource_type: The type of the resource to get a default resource ID
for. Only called with resource types that do not support
multiple instances.
Returns:
The default resource ID for the resource type.
"""
return self._canonical_resource_id(
resource_type, self.config.registry or DOCKER_REGISTRY_NAME
)
def _authorize_client(
self,
docker_client: DockerClient,
resource_id: str,
) -> None:
"""Authorize a Docker client to have access to the configured Docker registry.
Args:
docker_client: The Docker client to authenticate.
resource_id: The resource ID to authorize the client for.
Raises:
AuthorizationException: If the client could not be authenticated.
"""
cfg = self.config
registry = self._parse_resource_id(resource_id)
try:
docker_client.login(
username=cfg.username.get_secret_value(),
password=cfg.password.get_secret_value(),
registry=registry
if registry != DOCKER_REGISTRY_NAME
else None,
reauth=True,
)
except DockerException as e:
raise AuthorizationException(
f"failed to authenticate with Docker registry {registry}: {e}"
)
def _connect_to_resource(
self,
**kwargs: Any,
) -> Any:
"""Authenticate and connect to a Docker/OCI registry.
Initialize, authenticate and return a python-docker client.
Args:
kwargs: Additional implementation specific keyword arguments to pass
to the session or client constructor.
Returns:
An authenticated python-docker client object.
"""
assert self.resource_id is not None
# The reason we need to configure the local client here instead of
# using the `docker_client.login(...)` method is the following:
# When calling the login method on the python client, it stores the
# credentials in memory, but doesn't actually use them in future calls
# to push/pull images in case a credential store or credential helper is
# configured. If the cred store/helper contains invalid/expired
# credentials for the registry, these calls will fail.
# This solution is not ideal as we're now replacing potentially
# long-lived credentials in the cred store with our short lived ones,
# but the best we can do without modifying the docker library.
self._configure_local_client()
docker_client = docker_utils._try_get_docker_client_from_env()
self._authorize_client(docker_client, self.resource_id)
return docker_client
def _configure_local_client(
self,
**kwargs: Any,
) -> None:
"""Configure the local Docker client to authenticate to a Docker/OCI registry.
Args:
kwargs: Additional implementation specific keyword arguments to use
to configure the client.
Raises:
AuthorizationException: If authentication failed.
"""
# Call the docker CLI to authenticate to the Docker registry
cfg = self.config
assert self.resource_id is not None
registry = self._parse_resource_id(self.resource_id)
docker_login_cmd = [
"docker",
"login",
"-u",
cfg.username.get_secret_value(),
"--password-stdin",
]
if registry != DOCKER_REGISTRY_NAME:
docker_login_cmd.append(registry)
try:
subprocess.run(
docker_login_cmd,
check=True,
input=cfg.password.get_secret_value().encode(),
)
except subprocess.CalledProcessError as e:
raise AuthorizationException(
f"Failed to authenticate to Docker registry "
f"'{self.resource_id}': {e}"
) from e
@classmethod
def _auto_configure(
cls,
auth_method: Optional[str] = None,
resource_type: Optional[str] = None,
resource_id: Optional[str] = None,
**kwargs: Any,
) -> "DockerServiceConnector":
"""Auto-configure the connector.
Not supported by the Docker connector.
Args:
auth_method: The particular authentication method to use. If not
specified, the connector implementation must decide which
authentication method to use or raise an exception.
resource_type: The type of resource to configure.
resource_id: The ID of the resource to configure. The
implementation may choose to either require or ignore this
parameter if it does not support or detect an resource type that
supports multiple instances.
kwargs: Additional implementation specific keyword arguments to use.
Raises:
NotImplementedError: If the connector auto-configuration fails or
is not supported.
"""
raise NotImplementedError(
"Auto-configuration is not supported by the Docker connector."
)
def _verify(
self,
resource_type: Optional[str] = None,
resource_id: Optional[str] = None,
) -> List[str]:
"""Verify that the connector can authenticate and access resources.
Args:
resource_type: The type of resource to verify. Must be set to the
Docker resource type.
resource_id: The Docker registry name or URL to connect to.
Returns:
The name of the Docker registry that this connector can access.
"""
# The docker server isn't available on the ZenML server, so we can't
# verify the credentials there.
try:
docker_client = DockerClient.from_env()
except DockerException as e:
logger.warning(
f"Failed to connect to Docker daemon: {e}"
f"\nSkipping Docker connector verification."
)
else:
assert resource_id is not None
self._authorize_client(docker_client, resource_id)
docker_client.close()
return [resource_id] if resource_id else []
service_connector
Base ZenML Service Connector class.
AuthenticationConfig (BaseModel)
Base authentication configuration.
Source code in zenml/service_connectors/service_connector.py
class AuthenticationConfig(BaseModel):
"""Base authentication configuration."""
@property
def secret_values(self) -> Dict[str, SecretStr]:
"""Get the secret values as a dictionary.
Returns:
A dictionary of all secret values in the configuration.
"""
return {
k: v
for k, v in self.model_dump(exclude_none=True).items()
if isinstance(v, SecretStr)
}
@property
def non_secret_values(self) -> Dict[str, str]:
"""Get the non-secret values as a dictionary.
Returns:
A dictionary of all non-secret values in the configuration.
"""
return {
k: v
for k, v in self.model_dump(exclude_none=True).items()
if not isinstance(v, SecretStr)
}
@property
def all_values(self) -> Dict[str, Any]:
"""Get all values as a dictionary.
Returns:
A dictionary of all values in the configuration.
"""
return self.model_dump(exclude_none=True)
all_values: Dict[str, Any]
property
readonly
Get all values as a dictionary.
Returns:
| Type | Description |
|---|---|
Dict[str, Any] |
A dictionary of all values in the configuration. |
non_secret_values: Dict[str, str]
property
readonly
Get the non-secret values as a dictionary.
Returns:
| Type | Description |
|---|---|
Dict[str, str] |
A dictionary of all non-secret values in the configuration. |
secret_values: Dict[str, pydantic.types.SecretStr]
property
readonly
Get the secret values as a dictionary.
Returns:
| Type | Description |
|---|---|
Dict[str, pydantic.types.SecretStr] |
A dictionary of all secret values in the configuration. |
ServiceConnector (BaseModel)
Base service connector class.
Service connectors are standalone components that can be used to link ZenML to external resources. They are responsible for validating and storing authentication configuration and sensitive credentials and for providing authentication services to other ZenML components. Service connectors are built on top of the (otherwise opaque) ZenML secrets and secrets store mechanisms and add secret auto-configuration, secret discovery and secret schema validation capabilities.
The implementation independent service connector abstraction is made possible through the use of generic "resource types" and "resource IDs". These constitute the "contract" between connectors and the consumers of the authentication services that they provide. In a nutshell, a connector instance advertises what resource(s) it can be used to gain access to, whereas a consumer may run a query to search for compatible connectors by specifying the resource(s) that they need to access and then use a matching connector instance to connect to said resource(s).
The resource types and authentication methods supported by a connector are declared in the connector type specification. The role of this specification is two-fold:
- it declares a schema for the configuration that needs to be provided to configure the connector. This can be used to validate the configuration without having to instantiate the connector itself (e.g. in the CLI and dashboard), which also makes it possible to configure connectors and store their configuration without having to instantiate them.
- it provides a way for ZenML to keep a registry of available connector implementations and configured connector instances. Users who want to connect ZenML to external resources via connectors can use this registry to discover what types of connectors are available and what types of resources they can be configured to access. Consumers can also use the registry to find connector instances that are compatible with the types of resources that they need to access.
Source code in zenml/service_connectors/service_connector.py
class ServiceConnector(BaseModel, metaclass=ServiceConnectorMeta):
"""Base service connector class.
Service connectors are standalone components that can be used to link ZenML
to external resources. They are responsible for validating and storing
authentication configuration and sensitive credentials and for providing
authentication services to other ZenML components. Service connectors are
built on top of the (otherwise opaque) ZenML secrets and secrets store
mechanisms and add secret auto-configuration, secret discovery and secret
schema validation capabilities.
The implementation independent service connector abstraction is made
possible through the use of generic "resource types" and "resource IDs".
These constitute the "contract" between connectors and the consumers of the
authentication services that they provide. In a nutshell, a connector
instance advertises what resource(s) it can be used to gain access to,
whereas a consumer may run a query to search for compatible connectors by
specifying the resource(s) that they need to access and then use a
matching connector instance to connect to said resource(s).
The resource types and authentication methods supported by a connector are
declared in the connector type specification. The role of this specification
is two-fold:
- it declares a schema for the configuration that needs to be provided to
configure the connector. This can be used to validate the configuration
without having to instantiate the connector itself (e.g. in the CLI and
dashboard), which also makes it possible to configure connectors and
store their configuration without having to instantiate them.
- it provides a way for ZenML to keep a registry of available connector
implementations and configured connector instances. Users who want to
connect ZenML to external resources via connectors can use this registry
to discover what types of connectors are available and what types of
resources they can be configured to access. Consumers can also use the
registry to find connector instances that are compatible with the
types of resources that they need to access.
"""
id: Optional[UUID] = None
name: Optional[str] = None
auth_method: str
resource_type: Optional[str] = None
resource_id: Optional[str] = None
expires_at: Optional[datetime] = None
expires_skew_tolerance: Optional[int] = None
expiration_seconds: Optional[int] = None
config: AuthenticationConfig
allow_implicit_auth_methods: bool = False
_TYPE: ClassVar[Optional[ServiceConnectorTypeModel]] = None
def __init__(self, **kwargs: Any) -> None:
"""Initialize a new service connector instance.
Args:
kwargs: Additional keyword arguments to pass to the base class
constructor.
"""
super().__init__(**kwargs)
# Convert the resource ID to its canonical form. For resource types
# that don't support multiple instances:
# - if a resource ID is not provided, we use the default resource ID for
# the resource type
# - if a resource ID is provided, we verify that it matches the default
# resource ID for the resource type
if self.resource_type:
try:
self.resource_id = self._validate_resource_id(
self.resource_type, self.resource_id
)
except AuthorizationException as e:
error = (
f"Authorization error validating resource ID "
f"{self.resource_id} for resource type "
f"{self.resource_type}: {e}"
)
# Log an exception if debug logging is enabled
if logger.isEnabledFor(logging.DEBUG):
logger.exception(error)
else:
logger.warning(error)
self.resource_id = None
@classmethod
@abstractmethod
def _get_connector_type(cls) -> ServiceConnectorTypeModel:
"""Get the connector type specification.
Returns:
The connector type specification.
"""
def _canonical_resource_id(
self, resource_type: str, resource_id: str
) -> str:
"""Convert a resource ID to its canonical form.
This method is used to canonicalize the resource ID before it is
stored in the connector instance. The default implementation simply
returns the supplied resource ID as-is.
Args:
resource_type: The resource type to canonicalize.
resource_id: The resource ID to canonicalize.
Returns:
The canonical resource ID.
"""
return resource_id
def _get_default_resource_id(self, resource_type: str) -> str:
"""Get the default resource ID for a resource type.
Service connector implementations must override this method and provide
a default resource ID for resources that do not support multiple
instances.
Args:
resource_type: The type of the resource to get a default resource ID
for. Only called with resource types that do not support
multiple instances.
Raises:
RuntimeError: If the resource type does not support multiple
instances and the connector implementation did not provide a
default resource ID.
"""
# If a resource type does not support multiple instances, raise an
# exception; the connector implementation must override this method and
# provide a default resource ID in this case.
raise RuntimeError(
f"Resource type '{resource_type}' does not support multiple "
f"instances and the connector implementation didn't provide "
f"a default resource ID."
)
@abstractmethod
def _connect_to_resource(
self,
**kwargs: Any,
) -> Any:
"""Authenticate and connect to a resource.
This method initializes and returns an implementation specific object
representing an authenticated service client, connection or session that
can be used to access the resource that the connector instance is
configured to connect to.
The implementation should assume that the the resource type and resource
ID configured in the connector instance are both set, valid and ready to
be used.
Args:
kwargs: Additional implementation specific keyword arguments to use
to configure the client.
Returns:
An implementation specific object representing the authenticated
service client, connection or session.
Raises:
AuthorizationException: If authentication failed.
"""
@abstractmethod
def _configure_local_client(
self,
**kwargs: Any,
) -> None:
"""Configure a local client to authenticate and connect to a resource.
This method configures a local client or SDK installed on the localhost
to connect to the resource that the connector instance is configured
to access.
The implementation should assume that the the resource type and resource
ID configured in the connector instance are both set, valid and ready to
be used.
Args:
kwargs: Additional implementation specific keyword arguments to use
to configure the client.
Raises:
AuthorizationException: If authentication failed.
NotImplementedError: If the connector instance does not support
local configuration for the configured resource type or
authentication method.
"""
@classmethod
@abstractmethod
def _auto_configure(
cls,
auth_method: Optional[str] = None,
resource_type: Optional[str] = None,
resource_id: Optional[str] = None,
**kwargs: Any,
) -> "ServiceConnector":
"""Auto-configure a connector instance.
Instantiate a connector with a configuration extracted from the
authentication configuration available in the environment (e.g.
environment variables or local client/SDK configuration files).
Args:
auth_method: The particular authentication method to use. If not
specified, the connector implementation must decide which
authentication method to use or raise an exception.
resource_type: The type of resource to configure. If not specified,
the connector implementation must return a connector instance
configured to access any of the supported resource types or
decide to use a default resource type or raise an exception.
resource_id: The ID of the resource to configure. The
implementation may choose to either require or ignore this
parameter if it does not support or detect a resource type that
supports multiple instances.
kwargs: Additional implementation specific keyword arguments to use.
Returns:
A connector instance configured with authentication credentials
automatically extracted from the environment.
Raises:
NotImplementedError: If the connector auto-configuration fails or
is not supported.
"""
@abstractmethod
def _verify(
self,
resource_type: Optional[str] = None,
resource_id: Optional[str] = None,
) -> List[str]:
"""Verify and list all the resources that the connector can access.
This method uses the connector's configuration to verify that it can
authenticate and access the indicated resource(s). A non-empty list of
resource IDs in canonical format MUST be returned if the resource type
is supplied, otherwise the connector is marked as being in an error
state that doesn't allow it to be used to access any resources.
The implementation should not rely on the resource type and resource
ID configured in the connector instance because they might be
missing or different than the ones supplied to this method (e.g. if
this is a multi-type or multi-instance connector).
If a resource type is not supplied, the implementation must verify that
it can authenticate and connect to any of the supported resource types
and should not return any resource IDs. A list of resource IDs may be
returned in this case, but is not required.
For resource types that do not support multiple instances, the
resource ID parameter, if supplied, is the same as the default
resource ID for the resource type as returned by
`_get_default_resource_id`, in which case, the implementation should
return it unmodified.
For resource types that do support multiple instances, if the resource
ID is not supplied, the implementation MUST return a non-empty list of
resource IDs in canonical format identifying all the resources that the
connector can access of the specified type.
Args:
resource_type: The type of the resource to verify. If omitted and
if the connector supports multiple resource types, the
implementation must verify that it can authenticate and connect
to any and all of the supported resource types.
resource_id: The ID of the resource to connect to. Omitted if a
resource type is not specified. It has the same value as the
default resource ID if the supplied resource type doesn't
support multiple instances. If the supplied resource type does
allows multiple instances, this parameter may still be omitted
to fetch a list of resource IDs identifying all the resources
of the indicated type that the connector can access.
Returns:
The list of resources IDs in canonical format identifying the
resources that the connector can access. This list may be empty only
if the resource type is not specified (i.e. for multi-type
connectors).
Raises:
ValueError: If the connector configuration is invalid.
AuthorizationException: If authentication failed.
"""
def _get_connector_client(
self,
resource_type: str,
resource_id: str,
) -> "ServiceConnector":
"""Get a connector instance that can be used to connect to a resource.
This method should return a connector instance that is fully configured
and ready to use to access the indicated resource:
- has proper authentication configuration and credentials. These can be
either the same as the ones configured in this connector instance or
different ones (e.g. if this connector is able to generate temporary
credentials for a particular resource).
- has a resource type
- has a resource ID
This method is useful in cases where the connector capable of
authenticating against the target service and accessing the configured
resource is different than the connector configured by the user. Some
example use-cases for this are:
- a connector is configured with long-lived credentials or credentials
with wide permissions but is able to generate temporary credentials or
credentials with a narrower permissions scope for a particular resource.
In this case, the "main connector" instance stores the long-lived
credentials and is used to generate temporary credentials that are used
by the "connector client" instance to authenticate against the target
service and access the resource.
- a connector is configured to access multiple types of resources (e.g.
cloud providers) or multiple resource instances. In this case, the "main
connector" instance is configured without a resource type or without a
resource ID and is able to grant access to any resource type/resource
ID. It can instantiate "connector clients" for a particular
resource type and resource ID.
- a connector is configured with a resource type but it is able to
generate configurations for a different resource type. In this case,
the "main connector" and the "connector client" can even belong to
different connector implementations and the "main connector" can
generate a "connector client" configuration of a different resource type
that is used to access the final resource (e.g. the AWS connector can
instantiate a Kubernetes connector client to access an EKS resource as
if it were a generic Kubernetes cluster).
The default implementation returns this connector instance itself, or a
copy of it if the resource type or resource ID are different than the
ones configured in the connector instance.
Args:
resource_type: The type of the resources to connect to.
resource_id: The ID of a particular resource to connect to.
Returns:
A service connector client instance that can be used to connect to
the indicated resource.
"""
if (
self.resource_type == resource_type
and self.resource_id == resource_id
):
return self
copy = self.model_copy()
copy.resource_type = resource_type
copy.resource_id = resource_id
return copy
def _validate_resource_id(
self, resource_type: str, resource_id: Optional[str]
) -> Optional[str]:
"""Validate a resource ID value of a certain type against the connector configuration.
Args:
resource_type: The type of resource to validate.
resource_id: The resource ID to validate.
Returns:
The validated resource ID, or a default resource ID if the resource
type supports multiple instances and one was not supplied.
Raises:
AuthorizationException: If the connector is not authorized to
access the provided resource ID.
"""
# Fetch the resource type specification
resource_type_spec = self.type.resource_type_dict[resource_type]
# If the resource type supports multiple instances, return the supplied
# resource converted to canonical format, if supplied
if resource_type_spec.supports_instances:
if resource_id is None:
return None
return self._canonical_resource_id(resource_type, resource_id)
# If the resource type does not support multiple instances, the
# connector implementation must provide a default resource ID based
# on the connector configuration
default_resource_id = self._get_default_resource_id(resource_type)
if resource_id is None:
return default_resource_id
resource_id = self._canonical_resource_id(resource_type, resource_id)
if resource_id != default_resource_id:
raise AuthorizationException(
f"The connector does not allow access to the provided "
f"'{resource_id}' {resource_type_spec.name} resource. It "
f"only allows access to the following resource: "
f"'{default_resource_id}'."
)
return resource_id
def _check_implicit_auth_method_allowed(self) -> None:
"""Check if implicit authentication methods are allowed.
Raises:
AuthorizationException: If implicit authentication methods are
not enabled.
"""
# If the connector instance is especially configured to allow implicit
# authentication methods, skip the check.
if self.allow_implicit_auth_methods:
return
if not handle_bool_env_var(ENV_ZENML_ENABLE_IMPLICIT_AUTH_METHODS):
raise AuthorizationException(
"Implicit authentication methods for service connectors are "
"implicitly disabled for security reasons. To enabled them, "
f"the {ENV_ZENML_ENABLE_IMPLICIT_AUTH_METHODS} environment "
"variable must be set for the ZenML deployment."
)
@classmethod
def get_type(cls) -> ServiceConnectorTypeModel:
"""Get the connector type specification.
Returns:
The connector type specification.
"""
if cls._TYPE is not None:
return cls._TYPE
connector_type = cls._get_connector_type()
connector_type.set_connector_class(cls)
cls._TYPE = connector_type
return cls._TYPE
@property
def type(self) -> ServiceConnectorTypeModel:
"""Get the connector type specification.
Returns:
The connector type specification.
"""
return self.get_type()
@property
def supported_resource_types(self) -> List[str]:
"""The resource types supported by this connector instance.
Returns:
A list with the resource types supported by this connector instance.
"""
spec = self.get_type()
# An unset resource type means that the connector is configured to
# access any of the supported resource types (a multi-type connector).
# In that case, we report all the supported resource types to
# allow it to be discovered as compatible with any of them.
if self.resource_type:
resource_types = [self.resource_type]
else:
resource_types = list(spec.resource_type_dict.keys())
return resource_types
@classmethod
def from_model(
cls,
model: Union["ServiceConnectorRequest", "ServiceConnectorResponse"],
) -> "ServiceConnector":
"""Creates a service connector instance from a service connector model.
Args:
model: The service connector model.
Returns:
The created service connector instance.
Raises:
ValueError: If the connector configuration is invalid.
"""
# Validate the connector configuration model
spec = cls.get_type()
# Multiple resource types in the model means that the connector
# instance is configured to access any of the supported resource
# types (a multi-type connector). We represent that here by setting the
# resource type to None.
resource_type: Optional[str] = None
if len(model.resource_types) == 1:
resource_type = model.resource_types[0]
expiration_seconds: Optional[int] = None
try:
method_spec, _ = spec.find_resource_specifications(
model.auth_method,
resource_type,
)
expiration_seconds = method_spec.validate_expiration(
model.expiration_seconds
)
except (KeyError, ValueError) as e:
raise ValueError(
f"connector configuration is not valid: {e}"
) from e
# Unpack the authentication configuration
config = model.configuration.copy()
if isinstance(model, ServiceConnectorResponse) and model.secret_id:
try:
secret = Client().get_secret(model.secret_id)
except KeyError as e:
raise ValueError(
f"could not fetch secret with ID '{model.secret_id}' "
f"referenced in the connector configuration: {e}"
) from e
if secret.has_missing_values:
raise ValueError(
f"secret with ID '{model.secret_id}' referenced in the "
"connector configuration has missing values. This can "
"happen for example if your user lacks the permissions "
"required to access the secret."
)
config.update(secret.secret_values)
if model.secrets:
config.update(
{
k: v.get_secret_value()
for k, v in model.secrets.items()
if v
}
)
if method_spec.config_class is None:
raise ValueError(
f"the implementation of the {model.name} connector type is "
"not available in the environment. Please check that you "
"have installed the required dependencies."
)
# Validate the authentication configuration
try:
auth_config = method_spec.config_class(**config)
except ValidationError as e:
raise ValueError(
f"connector configuration is not valid: {e}"
) from e
assert isinstance(auth_config, AuthenticationConfig)
connector = cls(
auth_method=model.auth_method,
resource_type=resource_type,
resource_id=model.resource_id,
config=auth_config,
expires_at=model.expires_at,
expires_skew_tolerance=model.expires_skew_tolerance,
expiration_seconds=expiration_seconds,
)
if isinstance(model, ServiceConnectorResponse):
connector.id = model.id
connector.name = model.name
return connector
def to_model(
self,
user: UUID,
workspace: UUID,
name: Optional[str] = None,
description: str = "",
labels: Optional[Dict[str, str]] = None,
) -> "ServiceConnectorRequest":
"""Convert the connector instance to a service connector model.
Args:
name: The name of the connector.
user: The ID of the user that created the connector.
workspace: The ID of the workspace that the connector belongs to.
description: The description of the connector.
labels: The labels of the connector.
Returns:
The service connector model corresponding to the connector
instance.
Raises:
ValueError: If the connector configuration is not valid.
"""
spec = self.get_type()
name = name or self.name
if name is None:
raise ValueError(
"connector configuration is not valid: name must be set"
)
model = ServiceConnectorRequest(
connector_type=spec.connector_type,
name=name,
description=description,
user=user,
workspace=workspace,
auth_method=self.auth_method,
expires_at=self.expires_at,
expires_skew_tolerance=self.expires_skew_tolerance,
expiration_seconds=self.expiration_seconds,
labels=labels or {},
)
# Validate the connector configuration.
model.validate_and_configure_resources(
connector_type=spec,
resource_types=self.resource_type,
resource_id=self.resource_id,
configuration=self.config.non_secret_values,
secrets=self.config.secret_values, # type: ignore[arg-type]
)
return model
def to_response_model(
self,
workspace: WorkspaceResponse,
user: Optional[UserResponse] = None,
name: Optional[str] = None,
id: Optional[UUID] = None,
description: str = "",
labels: Optional[Dict[str, str]] = None,
) -> "ServiceConnectorResponse":
"""Convert the connector instance to a service connector response model.
Args:
workspace: The workspace that the connector belongs to.
user: The user that created the connector.
name: The name of the connector.
id: The ID of the connector.
description: The description of the connector.
labels: The labels of the connector.
Returns:
The service connector response model corresponding to the connector
instance.
Raises:
ValueError: If the connector configuration is not valid.
"""
spec = self.get_type()
name = name or self.name
id = id or self.id
if name is None or id is None:
raise ValueError(
"connector configuration is not valid: name and ID must be set"
)
model = ServiceConnectorResponse(
id=id,
name=name,
body=ServiceConnectorResponseBody(
user=user,
created=datetime.utcnow(),
updated=datetime.utcnow(),
description=description,
connector_type=self.get_type(),
auth_method=self.auth_method,
expires_at=self.expires_at,
expires_skew_tolerance=self.expires_skew_tolerance,
),
metadata=ServiceConnectorResponseMetadata(
workspace=workspace,
expiration_seconds=self.expiration_seconds,
labels=labels or {},
),
)
# Validate the connector configuration.
model.validate_and_configure_resources(
connector_type=spec,
resource_types=self.resource_type,
resource_id=self.resource_id,
configuration=self.config.non_secret_values,
secrets=self.config.secret_values, # type: ignore[arg-type]
)
return model
def has_expired(self) -> bool:
"""Check if the connector authentication credentials have expired.
Verify that the authentication credentials associated with the connector
have not expired by checking the expiration time against the current
time.
Returns:
True if the connector has expired, False otherwise.
"""
if not self.expires_at:
return False
expires_at = self.expires_at.replace(tzinfo=timezone.utc)
# Subtract some time to account for clock skew or other delays.
expires_at = expires_at - timedelta(
seconds=self.expires_skew_tolerance
if self.expires_skew_tolerance is not None
else SERVICE_CONNECTOR_SKEW_TOLERANCE_SECONDS
)
delta = expires_at - datetime.now(timezone.utc)
result = delta < timedelta(seconds=0)
logger.debug(
f"Checking if connector {self.name} has expired.\n"
f"Expires at: {self.expires_at}\n"
f"Expires at (+skew): {expires_at}\n"
f"Current UTC time: {datetime.now(timezone.utc)}\n"
f"Delta: {delta}\n"
f"Result: {result}\n"
)
return result
def validate_runtime_args(
self,
resource_type: Optional[str],
resource_id: Optional[str] = None,
require_resource_type: bool = False,
require_resource_id: bool = False,
**kwargs: Any,
) -> Tuple[Optional[str], Optional[str]]:
"""Validate the runtime arguments against the connector configuration.
Validate that the supplied runtime arguments are compatible with the
connector configuration and its specification. This includes validating
that the resource type and resource ID are compatible with the connector
configuration and its capabilities.
Args:
resource_type: The type of the resource supplied at runtime by the
connector's consumer. Must be the same as the resource type that
the connector is configured to access, unless the connector is
configured to access any resource type.
resource_id: The ID of the resource requested by the connector's
consumer. Can be different than the resource ID that the
connector is configured to access, e.g. if it is not in the
canonical form.
require_resource_type: Whether the resource type is required.
require_resource_id: Whether the resource ID is required.
kwargs: Additional runtime arguments.
Returns:
The validated resource type and resource ID.
Raises:
ValueError: If the runtime arguments are not valid.
"""
if (
self.resource_type
and resource_type
and (self.resource_type != resource_type)
):
raise ValueError(
f"the connector is configured to provide access to a "
f"'{self.resource_type}' resource type, but a different "
f"resource type was requested: '{resource_type}'."
)
resource_type = resource_type or self.resource_type
resource_id = resource_id or self.resource_id
if require_resource_type and not resource_type:
raise ValueError(
"the connector is configured to provide access to multiple "
"resource types. A resource type must be specified when "
"requesting access to a resource."
)
spec = self.get_type()
try:
# Get the resource specification corresponding to the
# connector configuration.
_, resource_spec = spec.find_resource_specifications(
self.auth_method,
resource_type,
)
except (KeyError, ValueError) as e:
raise ValueError(
f"connector configuration is not valid: {e}"
) from e
if not resource_type or not resource_spec:
if resource_id:
raise ValueError(
"the connector is configured to provide access to multiple "
"resource types, but only a resource name was specified. A "
"resource type must also be specified when "
"requesting access to a resource."
)
return resource_type, resource_id
# Validate and convert the resource ID to its canonical form.
# A default resource ID is returned for resource types that do not
# support instances, if no resource ID is specified.
resource_id = self._validate_resource_id(
resource_type=resource_type,
resource_id=resource_id,
)
if resource_id:
if self.resource_id and self.resource_id != resource_id:
raise ValueError(
f"the connector is configured to provide access to a "
f"single {resource_spec.name} resource with a "
f"resource name of '{self.resource_id}', but a "
f"different resource name was requested: "
f"'{resource_id}'."
)
else:
if not self.resource_id and require_resource_id:
raise ValueError(
f"the connector is configured to provide access to "
f"multiple {resource_spec.name} resources. A resource name "
"must be specified when requesting access to a resource."
)
return resource_type, resource_id
def connect(
self,
verify: bool = True,
**kwargs: Any,
) -> Any:
"""Authenticate and connect to a resource.
Initialize and return an implementation specific object representing an
authenticated service client, connection or session that can be used
to access the resource that the connector is configured to access.
The connector has to be fully configured for this method to succeed
(i.e. the connector's configuration must be valid, a resource type and
a resource ID must be configured). This method should only be called on
a connector client retrieved by calling `get_connector_client` on the
main service connector.
Args:
verify: Whether to verify that the connector can access the
configured resource before connecting to it.
kwargs: Additional implementation specific keyword arguments to use
to configure the client.
Returns:
An implementation specific object representing the authenticated
service client, connection or session.
Raises:
AuthorizationException: If the connector's authentication
credentials have expired.
"""
if verify:
resource_type, resource_id = self.validate_runtime_args(
resource_type=self.resource_type,
resource_id=self.resource_id,
require_resource_type=True,
require_resource_id=True,
)
if self.has_expired():
raise AuthorizationException(
"the connector's authentication credentials have expired."
)
self._verify(
resource_type=resource_type,
resource_id=resource_id,
)
return self._connect_to_resource(
**kwargs,
)
@classmethod
def auto_configure(
cls,
auth_method: Optional[str] = None,
resource_type: Optional[str] = None,
resource_id: Optional[str] = None,
**kwargs: Any,
) -> Optional["ServiceConnector"]:
"""Auto-configure a connector instance.
Instantiate a connector with a configuration extracted from the
authentication configuration available in the environment (e.g.
environment variables or local client/SDK configuration files).
Args:
auth_method: The particular authentication method to use. If
omitted and if the connector implementation cannot decide which
authentication method to use, it may raise an exception.
resource_type: The type of resource to configure. If not specified,
the method returns a connector instance configured to access any
of the supported resource types (multi-type connector) or
configured to use a default resource type. If the connector
doesn't support multi-type configurations or if it cannot decide
which resource type to use, it may raise an exception.
resource_id: The ID of the resource instance to configure. The
connector implementation may choose to either require or ignore
this parameter if it does not support or detect a resource type
that supports multiple instances.
kwargs: Additional implementation specific keyword arguments to use.
Returns:
A connector instance configured with authentication credentials
automatically extracted from the environment or None if
auto-configuration is not supported.
Raises:
ValueError: If the connector does not support the requested
authentication method or resource type.
AuthorizationException: If the connector's authentication
credentials have expired.
"""
spec = cls.get_type()
if not spec.supports_auto_configuration:
return None
if auth_method and auth_method not in spec.auth_method_dict:
raise ValueError(
f"connector type {spec.name} does not support authentication "
f"method: '{auth_method}'"
)
if resource_type and resource_type not in spec.resource_type_dict:
raise ValueError(
f"connector type {spec.name} does not support resource type: "
f"'{resource_type}'"
)
connector = cls._auto_configure(
auth_method=auth_method,
resource_type=resource_type,
resource_id=resource_id,
**kwargs,
)
if connector.has_expired():
raise AuthorizationException(
"the connector's auto-configured authentication credentials "
"have expired."
)
connector._verify(
resource_type=connector.resource_type,
resource_id=connector.resource_id,
)
return connector
def configure_local_client(
self,
**kwargs: Any,
) -> None:
"""Configure a local client to authenticate and connect to a resource.
This method uses the connector's configuration to configure a local
client or SDK installed on the localhost so that it can authenticate
and connect to the resource that the connector is configured to access.
The connector has to be fully configured for this method to succeed
(i.e. the connector's configuration must be valid, a resource type must
be specified and the resource ID must be specified if the resource type
supports multiple instances). This method should only be called on a
connector client retrieved by calling `get_connector_client` on the
main service connector.
Args:
kwargs: Additional implementation specific keyword arguments to use
to configure the client.
Raises:
AuthorizationException: If the connector's authentication
credentials have expired.
"""
resource_type, resource_id = self.validate_runtime_args(
resource_type=self.resource_type,
resource_id=self.resource_id,
require_resource_type=True,
require_resource_id=True,
)
if self.has_expired():
raise AuthorizationException(
"the connector's authentication credentials have expired."
)
self._verify(
resource_type=resource_type,
resource_id=resource_id,
)
self._configure_local_client(
**kwargs,
)
def verify(
self,
resource_type: Optional[str] = None,
resource_id: Optional[str] = None,
list_resources: bool = True,
) -> ServiceConnectorResourcesModel:
"""Verify and optionally list all the resources that the connector can access.
This method uses the connector's configuration to verify that it can
authenticate and access the indicated resource(s).
If `list_resources` is set, the list of resources that the connector can
access, scoped to the supplied resource type and resource ID is included
in the response, otherwise the connector only verifies that it can
globally authenticate and doesn't verify or return resource information
(i.e. the `resource_ids` fields in the response are empty).
Args:
resource_type: The type of the resource to verify. If the connector
instance is already configured with a resource type, this
argument must be the same as the one configured if supplied.
resource_id: The ID of a particular resource instance to check
whether the connector can access. If the connector instance is
already configured with a resource ID that is not the same or
equivalent to the one requested, a `ValueError` exception is
raised.
list_resources: Whether to list the resources that the connector can
access.
Returns:
A list of resources that the connector can access.
Raises:
ValueError: If the arguments or the connector configuration are
not valid.
"""
spec = self.get_type()
resources = ServiceConnectorResourcesModel(
connector_type=spec,
id=self.id,
name=self.name,
)
name_msg = f" '{self.name}'" if self.name else ""
resource_types = self.supported_resource_types
if resource_type:
if resource_type not in resource_types:
raise ValueError(
f"connector{name_msg} does not support resource type: "
f"'{resource_type}'. Supported resource types are: "
f"{', '.join(resource_types)}"
)
resource_types = [resource_type]
# Pre-populate the list of resources with entries corresponding to the
# supported resource types and scoped to the supplied resource type
resources.resources = [
ServiceConnectorTypedResourcesModel(
resource_type=rt,
)
for rt in resource_types
]
if self.has_expired():
error = "the connector's authentication credentials have expired."
# Log the error in the resources object
resources.set_error(error)
return resources
verify_resource_types: List[Optional[str]] = []
verify_resource_id = None
if not list_resources and not resource_id:
# If we're not listing resources, we're only verifying that the
# connector can authenticate globally (i.e. without supplying a
# resource type or resource ID). This is the same as if no resource
# type or resource ID was supplied. The only exception is when the
# verification scope is already set to a single resource ID, in
# which case we still perform the verification on that resource ID.
verify_resource_types = [None]
verify_resource_id = None
else:
if len(resource_types) > 1:
# This forces the connector to verify that it can authenticate
# globally (i.e. without supplying a resource type or resource
# ID) before listing individual resources in the case of
# multi-type service connectors.
verify_resource_types = [None]
verify_resource_types.extend(resource_types)
if len(verify_resource_types) == 1:
verify_resource_id = resource_id
# Here we go through each resource type and attempt to verify and list
# the resources that the connector can access for that resource type.
# This list may start with a `None` resource type, which indicates that
# the connector should verify that it can authenticate globally.
for resource_type in verify_resource_types:
try:
resource_type, resource_id = self.validate_runtime_args(
resource_type=resource_type,
resource_id=verify_resource_id,
require_resource_type=False,
require_resource_id=False,
)
resource_ids = self._verify(
resource_type=resource_type,
resource_id=resource_id,
)
except ValueError as exc:
raise ValueError(
f"The connector configuration is incomplete or invalid: "
f"{exc}",
)
except AuthorizationException as exc:
error = f"connector{name_msg} authorization failure: {exc}"
# Log an exception if debug logging is enabled
if logger.isEnabledFor(logging.DEBUG):
logger.exception(error)
else:
logger.warning(error)
# Log the error in the resources object
resources.set_error(error, resource_type=resource_type)
if resource_type:
continue
else:
# We stop on a global failure
break
except Exception as exc:
error = (
f"connector{name_msg} verification failed with "
f"unexpected error: {exc}"
)
# Log an exception if debug logging is enabled
if logger.isEnabledFor(logging.DEBUG):
logger.exception(error)
else:
logger.warning(error)
error = (
"an unexpected error occurred while verifying the "
"connector."
)
# Log the error in the resources object
resources.set_error(error, resource_type=resource_type)
if resource_type:
continue
else:
# We stop on a global failure
break
if not resource_type:
# If a resource type is not provided as argument, we don't
# expect any resources to be listed
continue
resource_type_spec = spec.resource_type_dict[resource_type]
if resource_id:
# A single resource was requested, so we expect a single
# resource to be listed
if [resource_id] != resource_ids:
logger.error(
f"a different resource ID '{resource_ids}' was "
f"returned than the one requested: {resource_ids}. "
f"This is likely a bug in the {self.__class__} "
"connector implementation."
)
resources.set_resource_ids(resource_type, [resource_id])
elif not resource_ids:
# If no resources were listed, signal this as an error that the
# connector cannot access any resources.
error = (
f"connector{name_msg} didn't list any "
f"{resource_type_spec.name} resources. This is likely "
"caused by the connector credentials not being valid or "
"not having sufficient permissions to list or access "
"resources of this type. Please check the connector "
"configuration and its credentials and try again."
)
logger.debug(error)
resources.set_error(error, resource_type=resource_type)
else:
resources.set_resource_ids(resource_type, resource_ids)
return resources
def get_connector_client(
self,
resource_type: Optional[str] = None,
resource_id: Optional[str] = None,
) -> "ServiceConnector":
"""Get a connector client that can be used to connect to a resource.
The connector client can be used by consumers to connect to a resource
(i.e. make calls to `connect` and `configure_local_client`).
The returned connector may be the same as the original connector
or it may a different instance configured with different credentials or
even of a different connector type.
Args:
resource_type: The type of the resource to connect to.
resource_id: The ID of a particular resource to connect to.
Returns:
A service connector client that can be used to connect to the
resource.
Raises:
AuthorizationException: If authentication failed.
"""
resource_type, resource_id = self.validate_runtime_args(
resource_type=resource_type,
resource_id=resource_id,
require_resource_type=True,
require_resource_id=True,
)
if self.has_expired():
raise AuthorizationException(
"the connector's authentication credentials have expired."
)
# Verify if the connector allows access to the requested resource type
# and instance.
self._verify(
resource_type=resource_type,
resource_id=resource_id,
)
assert resource_type is not None
assert resource_id is not None
connector_client = self._get_connector_client(
resource_type=resource_type,
resource_id=resource_id,
)
# Transfer the expiration skew tolerance to the connector client
# if an expiration time is set for the connector client credentials.
if connector_client.expires_at is not None:
connector_client.expires_skew_tolerance = (
self.expires_skew_tolerance
)
if connector_client.has_expired():
raise AuthorizationException(
"the connector's authentication credentials have expired."
)
connector_client._verify(
resource_type=resource_type,
resource_id=connector_client.resource_id,
)
return connector_client
supported_resource_types: List[str]
property
readonly
The resource types supported by this connector instance.
Returns:
| Type | Description |
|---|---|
List[str] |
A list with the resource types supported by this connector instance. |
type: ServiceConnectorTypeModel
property
readonly
Get the connector type specification.
Returns:
| Type | Description |
|---|---|
ServiceConnectorTypeModel |
The connector type specification. |
__init__(self, **kwargs)
special
Initialize a new service connector instance.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
kwargs |
Any |
Additional keyword arguments to pass to the base class constructor. |
{} |
Source code in zenml/service_connectors/service_connector.py
def __init__(self, **kwargs: Any) -> None:
"""Initialize a new service connector instance.
Args:
kwargs: Additional keyword arguments to pass to the base class
constructor.
"""
super().__init__(**kwargs)
# Convert the resource ID to its canonical form. For resource types
# that don't support multiple instances:
# - if a resource ID is not provided, we use the default resource ID for
# the resource type
# - if a resource ID is provided, we verify that it matches the default
# resource ID for the resource type
if self.resource_type:
try:
self.resource_id = self._validate_resource_id(
self.resource_type, self.resource_id
)
except AuthorizationException as e:
error = (
f"Authorization error validating resource ID "
f"{self.resource_id} for resource type "
f"{self.resource_type}: {e}"
)
# Log an exception if debug logging is enabled
if logger.isEnabledFor(logging.DEBUG):
logger.exception(error)
else:
logger.warning(error)
self.resource_id = None
auto_configure(auth_method=None, resource_type=None, resource_id=None, **kwargs)
classmethod
Auto-configure a connector instance.
Instantiate a connector with a configuration extracted from the authentication configuration available in the environment (e.g. environment variables or local client/SDK configuration files).
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
auth_method |
Optional[str] |
The particular authentication method to use. If omitted and if the connector implementation cannot decide which authentication method to use, it may raise an exception. |
None |
resource_type |
Optional[str] |
The type of resource to configure. If not specified, the method returns a connector instance configured to access any of the supported resource types (multi-type connector) or configured to use a default resource type. If the connector doesn't support multi-type configurations or if it cannot decide which resource type to use, it may raise an exception. |
None |
resource_id |
Optional[str] |
The ID of the resource instance to configure. The connector implementation may choose to either require or ignore this parameter if it does not support or detect a resource type that supports multiple instances. |
None |
kwargs |
Any |
Additional implementation specific keyword arguments to use. |
{} |
Returns:
| Type | Description |
|---|---|
Optional[ServiceConnector] |
A connector instance configured with authentication credentials automatically extracted from the environment or None if auto-configuration is not supported. |
Exceptions:
| Type | Description |
|---|---|
ValueError |
If the connector does not support the requested authentication method or resource type. |
AuthorizationException |
If the connector's authentication credentials have expired. |
Source code in zenml/service_connectors/service_connector.py
@classmethod
def auto_configure(
cls,
auth_method: Optional[str] = None,
resource_type: Optional[str] = None,
resource_id: Optional[str] = None,
**kwargs: Any,
) -> Optional["ServiceConnector"]:
"""Auto-configure a connector instance.
Instantiate a connector with a configuration extracted from the
authentication configuration available in the environment (e.g.
environment variables or local client/SDK configuration files).
Args:
auth_method: The particular authentication method to use. If
omitted and if the connector implementation cannot decide which
authentication method to use, it may raise an exception.
resource_type: The type of resource to configure. If not specified,
the method returns a connector instance configured to access any
of the supported resource types (multi-type connector) or
configured to use a default resource type. If the connector
doesn't support multi-type configurations or if it cannot decide
which resource type to use, it may raise an exception.
resource_id: The ID of the resource instance to configure. The
connector implementation may choose to either require or ignore
this parameter if it does not support or detect a resource type
that supports multiple instances.
kwargs: Additional implementation specific keyword arguments to use.
Returns:
A connector instance configured with authentication credentials
automatically extracted from the environment or None if
auto-configuration is not supported.
Raises:
ValueError: If the connector does not support the requested
authentication method or resource type.
AuthorizationException: If the connector's authentication
credentials have expired.
"""
spec = cls.get_type()
if not spec.supports_auto_configuration:
return None
if auth_method and auth_method not in spec.auth_method_dict:
raise ValueError(
f"connector type {spec.name} does not support authentication "
f"method: '{auth_method}'"
)
if resource_type and resource_type not in spec.resource_type_dict:
raise ValueError(
f"connector type {spec.name} does not support resource type: "
f"'{resource_type}'"
)
connector = cls._auto_configure(
auth_method=auth_method,
resource_type=resource_type,
resource_id=resource_id,
**kwargs,
)
if connector.has_expired():
raise AuthorizationException(
"the connector's auto-configured authentication credentials "
"have expired."
)
connector._verify(
resource_type=connector.resource_type,
resource_id=connector.resource_id,
)
return connector
configure_local_client(self, **kwargs)
Configure a local client to authenticate and connect to a resource.
This method uses the connector's configuration to configure a local client or SDK installed on the localhost so that it can authenticate and connect to the resource that the connector is configured to access.
The connector has to be fully configured for this method to succeed
(i.e. the connector's configuration must be valid, a resource type must
be specified and the resource ID must be specified if the resource type
supports multiple instances). This method should only be called on a
connector client retrieved by calling get_connector_client on the
main service connector.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
kwargs |
Any |
Additional implementation specific keyword arguments to use to configure the client. |
{} |
Exceptions:
| Type | Description |
|---|---|
AuthorizationException |
If the connector's authentication credentials have expired. |
Source code in zenml/service_connectors/service_connector.py
def configure_local_client(
self,
**kwargs: Any,
) -> None:
"""Configure a local client to authenticate and connect to a resource.
This method uses the connector's configuration to configure a local
client or SDK installed on the localhost so that it can authenticate
and connect to the resource that the connector is configured to access.
The connector has to be fully configured for this method to succeed
(i.e. the connector's configuration must be valid, a resource type must
be specified and the resource ID must be specified if the resource type
supports multiple instances). This method should only be called on a
connector client retrieved by calling `get_connector_client` on the
main service connector.
Args:
kwargs: Additional implementation specific keyword arguments to use
to configure the client.
Raises:
AuthorizationException: If the connector's authentication
credentials have expired.
"""
resource_type, resource_id = self.validate_runtime_args(
resource_type=self.resource_type,
resource_id=self.resource_id,
require_resource_type=True,
require_resource_id=True,
)
if self.has_expired():
raise AuthorizationException(
"the connector's authentication credentials have expired."
)
self._verify(
resource_type=resource_type,
resource_id=resource_id,
)
self._configure_local_client(
**kwargs,
)
connect(self, verify=True, **kwargs)
Authenticate and connect to a resource.
Initialize and return an implementation specific object representing an authenticated service client, connection or session that can be used to access the resource that the connector is configured to access.
The connector has to be fully configured for this method to succeed
(i.e. the connector's configuration must be valid, a resource type and
a resource ID must be configured). This method should only be called on
a connector client retrieved by calling get_connector_client on the
main service connector.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
verify |
bool |
Whether to verify that the connector can access the configured resource before connecting to it. |
True |
kwargs |
Any |
Additional implementation specific keyword arguments to use to configure the client. |
{} |
Returns:
| Type | Description |
|---|---|
Any |
An implementation specific object representing the authenticated service client, connection or session. |
Exceptions:
| Type | Description |
|---|---|
AuthorizationException |
If the connector's authentication credentials have expired. |
Source code in zenml/service_connectors/service_connector.py
def connect(
self,
verify: bool = True,
**kwargs: Any,
) -> Any:
"""Authenticate and connect to a resource.
Initialize and return an implementation specific object representing an
authenticated service client, connection or session that can be used
to access the resource that the connector is configured to access.
The connector has to be fully configured for this method to succeed
(i.e. the connector's configuration must be valid, a resource type and
a resource ID must be configured). This method should only be called on
a connector client retrieved by calling `get_connector_client` on the
main service connector.
Args:
verify: Whether to verify that the connector can access the
configured resource before connecting to it.
kwargs: Additional implementation specific keyword arguments to use
to configure the client.
Returns:
An implementation specific object representing the authenticated
service client, connection or session.
Raises:
AuthorizationException: If the connector's authentication
credentials have expired.
"""
if verify:
resource_type, resource_id = self.validate_runtime_args(
resource_type=self.resource_type,
resource_id=self.resource_id,
require_resource_type=True,
require_resource_id=True,
)
if self.has_expired():
raise AuthorizationException(
"the connector's authentication credentials have expired."
)
self._verify(
resource_type=resource_type,
resource_id=resource_id,
)
return self._connect_to_resource(
**kwargs,
)
from_model(model)
classmethod
Creates a service connector instance from a service connector model.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model |
Union[ServiceConnectorRequest, ServiceConnectorResponse] |
The service connector model. |
required |
Returns:
| Type | Description |
|---|---|
ServiceConnector |
The created service connector instance. |
Exceptions:
| Type | Description |
|---|---|
ValueError |
If the connector configuration is invalid. |
Source code in zenml/service_connectors/service_connector.py
@classmethod
def from_model(
cls,
model: Union["ServiceConnectorRequest", "ServiceConnectorResponse"],
) -> "ServiceConnector":
"""Creates a service connector instance from a service connector model.
Args:
model: The service connector model.
Returns:
The created service connector instance.
Raises:
ValueError: If the connector configuration is invalid.
"""
# Validate the connector configuration model
spec = cls.get_type()
# Multiple resource types in the model means that the connector
# instance is configured to access any of the supported resource
# types (a multi-type connector). We represent that here by setting the
# resource type to None.
resource_type: Optional[str] = None
if len(model.resource_types) == 1:
resource_type = model.resource_types[0]
expiration_seconds: Optional[int] = None
try:
method_spec, _ = spec.find_resource_specifications(
model.auth_method,
resource_type,
)
expiration_seconds = method_spec.validate_expiration(
model.expiration_seconds
)
except (KeyError, ValueError) as e:
raise ValueError(
f"connector configuration is not valid: {e}"
) from e
# Unpack the authentication configuration
config = model.configuration.copy()
if isinstance(model, ServiceConnectorResponse) and model.secret_id:
try:
secret = Client().get_secret(model.secret_id)
except KeyError as e:
raise ValueError(
f"could not fetch secret with ID '{model.secret_id}' "
f"referenced in the connector configuration: {e}"
) from e
if secret.has_missing_values:
raise ValueError(
f"secret with ID '{model.secret_id}' referenced in the "
"connector configuration has missing values. This can "
"happen for example if your user lacks the permissions "
"required to access the secret."
)
config.update(secret.secret_values)
if model.secrets:
config.update(
{
k: v.get_secret_value()
for k, v in model.secrets.items()
if v
}
)
if method_spec.config_class is None:
raise ValueError(
f"the implementation of the {model.name} connector type is "
"not available in the environment. Please check that you "
"have installed the required dependencies."
)
# Validate the authentication configuration
try:
auth_config = method_spec.config_class(**config)
except ValidationError as e:
raise ValueError(
f"connector configuration is not valid: {e}"
) from e
assert isinstance(auth_config, AuthenticationConfig)
connector = cls(
auth_method=model.auth_method,
resource_type=resource_type,
resource_id=model.resource_id,
config=auth_config,
expires_at=model.expires_at,
expires_skew_tolerance=model.expires_skew_tolerance,
expiration_seconds=expiration_seconds,
)
if isinstance(model, ServiceConnectorResponse):
connector.id = model.id
connector.name = model.name
return connector
get_connector_client(self, resource_type=None, resource_id=None)
Get a connector client that can be used to connect to a resource.
The connector client can be used by consumers to connect to a resource
(i.e. make calls to connect and configure_local_client).
The returned connector may be the same as the original connector or it may a different instance configured with different credentials or even of a different connector type.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
resource_type |
Optional[str] |
The type of the resource to connect to. |
None |
resource_id |
Optional[str] |
The ID of a particular resource to connect to. |
None |
Returns:
| Type | Description |
|---|---|
ServiceConnector |
A service connector client that can be used to connect to the resource. |
Exceptions:
| Type | Description |
|---|---|
AuthorizationException |
If authentication failed. |
Source code in zenml/service_connectors/service_connector.py
def get_connector_client(
self,
resource_type: Optional[str] = None,
resource_id: Optional[str] = None,
) -> "ServiceConnector":
"""Get a connector client that can be used to connect to a resource.
The connector client can be used by consumers to connect to a resource
(i.e. make calls to `connect` and `configure_local_client`).
The returned connector may be the same as the original connector
or it may a different instance configured with different credentials or
even of a different connector type.
Args:
resource_type: The type of the resource to connect to.
resource_id: The ID of a particular resource to connect to.
Returns:
A service connector client that can be used to connect to the
resource.
Raises:
AuthorizationException: If authentication failed.
"""
resource_type, resource_id = self.validate_runtime_args(
resource_type=resource_type,
resource_id=resource_id,
require_resource_type=True,
require_resource_id=True,
)
if self.has_expired():
raise AuthorizationException(
"the connector's authentication credentials have expired."
)
# Verify if the connector allows access to the requested resource type
# and instance.
self._verify(
resource_type=resource_type,
resource_id=resource_id,
)
assert resource_type is not None
assert resource_id is not None
connector_client = self._get_connector_client(
resource_type=resource_type,
resource_id=resource_id,
)
# Transfer the expiration skew tolerance to the connector client
# if an expiration time is set for the connector client credentials.
if connector_client.expires_at is not None:
connector_client.expires_skew_tolerance = (
self.expires_skew_tolerance
)
if connector_client.has_expired():
raise AuthorizationException(
"the connector's authentication credentials have expired."
)
connector_client._verify(
resource_type=resource_type,
resource_id=connector_client.resource_id,
)
return connector_client
get_type()
classmethod
Get the connector type specification.
Returns:
| Type | Description |
|---|---|
ServiceConnectorTypeModel |
The connector type specification. |
Source code in zenml/service_connectors/service_connector.py
@classmethod
def get_type(cls) -> ServiceConnectorTypeModel:
"""Get the connector type specification.
Returns:
The connector type specification.
"""
if cls._TYPE is not None:
return cls._TYPE
connector_type = cls._get_connector_type()
connector_type.set_connector_class(cls)
cls._TYPE = connector_type
return cls._TYPE
has_expired(self)
Check if the connector authentication credentials have expired.
Verify that the authentication credentials associated with the connector have not expired by checking the expiration time against the current time.
Returns:
| Type | Description |
|---|---|
bool |
True if the connector has expired, False otherwise. |
Source code in zenml/service_connectors/service_connector.py
def has_expired(self) -> bool:
"""Check if the connector authentication credentials have expired.
Verify that the authentication credentials associated with the connector
have not expired by checking the expiration time against the current
time.
Returns:
True if the connector has expired, False otherwise.
"""
if not self.expires_at:
return False
expires_at = self.expires_at.replace(tzinfo=timezone.utc)
# Subtract some time to account for clock skew or other delays.
expires_at = expires_at - timedelta(
seconds=self.expires_skew_tolerance
if self.expires_skew_tolerance is not None
else SERVICE_CONNECTOR_SKEW_TOLERANCE_SECONDS
)
delta = expires_at - datetime.now(timezone.utc)
result = delta < timedelta(seconds=0)
logger.debug(
f"Checking if connector {self.name} has expired.\n"
f"Expires at: {self.expires_at}\n"
f"Expires at (+skew): {expires_at}\n"
f"Current UTC time: {datetime.now(timezone.utc)}\n"
f"Delta: {delta}\n"
f"Result: {result}\n"
)
return result
to_model(self, user, workspace, name=None, description='', labels=None)
Convert the connector instance to a service connector model.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
name |
Optional[str] |
The name of the connector. |
None |
user |
UUID |
The ID of the user that created the connector. |
required |
workspace |
UUID |
The ID of the workspace that the connector belongs to. |
required |
description |
str |
The description of the connector. |
'' |
labels |
Optional[Dict[str, str]] |
The labels of the connector. |
None |
Returns:
| Type | Description |
|---|---|
ServiceConnectorRequest |
The service connector model corresponding to the connector instance. |
Exceptions:
| Type | Description |
|---|---|
ValueError |
If the connector configuration is not valid. |
Source code in zenml/service_connectors/service_connector.py
def to_model(
self,
user: UUID,
workspace: UUID,
name: Optional[str] = None,
description: str = "",
labels: Optional[Dict[str, str]] = None,
) -> "ServiceConnectorRequest":
"""Convert the connector instance to a service connector model.
Args:
name: The name of the connector.
user: The ID of the user that created the connector.
workspace: The ID of the workspace that the connector belongs to.
description: The description of the connector.
labels: The labels of the connector.
Returns:
The service connector model corresponding to the connector
instance.
Raises:
ValueError: If the connector configuration is not valid.
"""
spec = self.get_type()
name = name or self.name
if name is None:
raise ValueError(
"connector configuration is not valid: name must be set"
)
model = ServiceConnectorRequest(
connector_type=spec.connector_type,
name=name,
description=description,
user=user,
workspace=workspace,
auth_method=self.auth_method,
expires_at=self.expires_at,
expires_skew_tolerance=self.expires_skew_tolerance,
expiration_seconds=self.expiration_seconds,
labels=labels or {},
)
# Validate the connector configuration.
model.validate_and_configure_resources(
connector_type=spec,
resource_types=self.resource_type,
resource_id=self.resource_id,
configuration=self.config.non_secret_values,
secrets=self.config.secret_values, # type: ignore[arg-type]
)
return model
to_response_model(self, workspace, user=None, name=None, id=None, description='', labels=None)
Convert the connector instance to a service connector response model.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
workspace |
WorkspaceResponse |
The workspace that the connector belongs to. |
required |
user |
Optional[zenml.models.v2.core.user.UserResponse] |
The user that created the connector. |
None |
name |
Optional[str] |
The name of the connector. |
None |
id |
Optional[uuid.UUID] |
The ID of the connector. |
None |
description |
str |
The description of the connector. |
'' |
labels |
Optional[Dict[str, str]] |
The labels of the connector. |
None |
Returns:
| Type | Description |
|---|---|
ServiceConnectorResponse |
The service connector response model corresponding to the connector instance. |
Exceptions:
| Type | Description |
|---|---|
ValueError |
If the connector configuration is not valid. |
Source code in zenml/service_connectors/service_connector.py
def to_response_model(
self,
workspace: WorkspaceResponse,
user: Optional[UserResponse] = None,
name: Optional[str] = None,
id: Optional[UUID] = None,
description: str = "",
labels: Optional[Dict[str, str]] = None,
) -> "ServiceConnectorResponse":
"""Convert the connector instance to a service connector response model.
Args:
workspace: The workspace that the connector belongs to.
user: The user that created the connector.
name: The name of the connector.
id: The ID of the connector.
description: The description of the connector.
labels: The labels of the connector.
Returns:
The service connector response model corresponding to the connector
instance.
Raises:
ValueError: If the connector configuration is not valid.
"""
spec = self.get_type()
name = name or self.name
id = id or self.id
if name is None or id is None:
raise ValueError(
"connector configuration is not valid: name and ID must be set"
)
model = ServiceConnectorResponse(
id=id,
name=name,
body=ServiceConnectorResponseBody(
user=user,
created=datetime.utcnow(),
updated=datetime.utcnow(),
description=description,
connector_type=self.get_type(),
auth_method=self.auth_method,
expires_at=self.expires_at,
expires_skew_tolerance=self.expires_skew_tolerance,
),
metadata=ServiceConnectorResponseMetadata(
workspace=workspace,
expiration_seconds=self.expiration_seconds,
labels=labels or {},
),
)
# Validate the connector configuration.
model.validate_and_configure_resources(
connector_type=spec,
resource_types=self.resource_type,
resource_id=self.resource_id,
configuration=self.config.non_secret_values,
secrets=self.config.secret_values, # type: ignore[arg-type]
)
return model
validate_runtime_args(self, resource_type, resource_id=None, require_resource_type=False, require_resource_id=False, **kwargs)
Validate the runtime arguments against the connector configuration.
Validate that the supplied runtime arguments are compatible with the connector configuration and its specification. This includes validating that the resource type and resource ID are compatible with the connector configuration and its capabilities.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
resource_type |
Optional[str] |
The type of the resource supplied at runtime by the connector's consumer. Must be the same as the resource type that the connector is configured to access, unless the connector is configured to access any resource type. |
required |
resource_id |
Optional[str] |
The ID of the resource requested by the connector's consumer. Can be different than the resource ID that the connector is configured to access, e.g. if it is not in the canonical form. |
None |
require_resource_type |
bool |
Whether the resource type is required. |
False |
require_resource_id |
bool |
Whether the resource ID is required. |
False |
kwargs |
Any |
Additional runtime arguments. |
{} |
Returns:
| Type | Description |
|---|---|
Tuple[Optional[str], Optional[str]] |
The validated resource type and resource ID. |
Exceptions:
| Type | Description |
|---|---|
ValueError |
If the runtime arguments are not valid. |
Source code in zenml/service_connectors/service_connector.py
def validate_runtime_args(
self,
resource_type: Optional[str],
resource_id: Optional[str] = None,
require_resource_type: bool = False,
require_resource_id: bool = False,
**kwargs: Any,
) -> Tuple[Optional[str], Optional[str]]:
"""Validate the runtime arguments against the connector configuration.
Validate that the supplied runtime arguments are compatible with the
connector configuration and its specification. This includes validating
that the resource type and resource ID are compatible with the connector
configuration and its capabilities.
Args:
resource_type: The type of the resource supplied at runtime by the
connector's consumer. Must be the same as the resource type that
the connector is configured to access, unless the connector is
configured to access any resource type.
resource_id: The ID of the resource requested by the connector's
consumer. Can be different than the resource ID that the
connector is configured to access, e.g. if it is not in the
canonical form.
require_resource_type: Whether the resource type is required.
require_resource_id: Whether the resource ID is required.
kwargs: Additional runtime arguments.
Returns:
The validated resource type and resource ID.
Raises:
ValueError: If the runtime arguments are not valid.
"""
if (
self.resource_type
and resource_type
and (self.resource_type != resource_type)
):
raise ValueError(
f"the connector is configured to provide access to a "
f"'{self.resource_type}' resource type, but a different "
f"resource type was requested: '{resource_type}'."
)
resource_type = resource_type or self.resource_type
resource_id = resource_id or self.resource_id
if require_resource_type and not resource_type:
raise ValueError(
"the connector is configured to provide access to multiple "
"resource types. A resource type must be specified when "
"requesting access to a resource."
)
spec = self.get_type()
try:
# Get the resource specification corresponding to the
# connector configuration.
_, resource_spec = spec.find_resource_specifications(
self.auth_method,
resource_type,
)
except (KeyError, ValueError) as e:
raise ValueError(
f"connector configuration is not valid: {e}"
) from e
if not resource_type or not resource_spec:
if resource_id:
raise ValueError(
"the connector is configured to provide access to multiple "
"resource types, but only a resource name was specified. A "
"resource type must also be specified when "
"requesting access to a resource."
)
return resource_type, resource_id
# Validate and convert the resource ID to its canonical form.
# A default resource ID is returned for resource types that do not
# support instances, if no resource ID is specified.
resource_id = self._validate_resource_id(
resource_type=resource_type,
resource_id=resource_id,
)
if resource_id:
if self.resource_id and self.resource_id != resource_id:
raise ValueError(
f"the connector is configured to provide access to a "
f"single {resource_spec.name} resource with a "
f"resource name of '{self.resource_id}', but a "
f"different resource name was requested: "
f"'{resource_id}'."
)
else:
if not self.resource_id and require_resource_id:
raise ValueError(
f"the connector is configured to provide access to "
f"multiple {resource_spec.name} resources. A resource name "
"must be specified when requesting access to a resource."
)
return resource_type, resource_id
verify(self, resource_type=None, resource_id=None, list_resources=True)
Verify and optionally list all the resources that the connector can access.
This method uses the connector's configuration to verify that it can authenticate and access the indicated resource(s).
If list_resources is set, the list of resources that the connector can
access, scoped to the supplied resource type and resource ID is included
in the response, otherwise the connector only verifies that it can
globally authenticate and doesn't verify or return resource information
(i.e. the resource_ids fields in the response are empty).
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
resource_type |
Optional[str] |
The type of the resource to verify. If the connector instance is already configured with a resource type, this argument must be the same as the one configured if supplied. |
None |
resource_id |
Optional[str] |
The ID of a particular resource instance to check
whether the connector can access. If the connector instance is
already configured with a resource ID that is not the same or
equivalent to the one requested, a |
None |
list_resources |
bool |
Whether to list the resources that the connector can access. |
True |
Returns:
| Type | Description |
|---|---|
ServiceConnectorResourcesModel |
A list of resources that the connector can access. |
Exceptions:
| Type | Description |
|---|---|
ValueError |
If the arguments or the connector configuration are not valid. |
Source code in zenml/service_connectors/service_connector.py
def verify(
self,
resource_type: Optional[str] = None,
resource_id: Optional[str] = None,
list_resources: bool = True,
) -> ServiceConnectorResourcesModel:
"""Verify and optionally list all the resources that the connector can access.
This method uses the connector's configuration to verify that it can
authenticate and access the indicated resource(s).
If `list_resources` is set, the list of resources that the connector can
access, scoped to the supplied resource type and resource ID is included
in the response, otherwise the connector only verifies that it can
globally authenticate and doesn't verify or return resource information
(i.e. the `resource_ids` fields in the response are empty).
Args:
resource_type: The type of the resource to verify. If the connector
instance is already configured with a resource type, this
argument must be the same as the one configured if supplied.
resource_id: The ID of a particular resource instance to check
whether the connector can access. If the connector instance is
already configured with a resource ID that is not the same or
equivalent to the one requested, a `ValueError` exception is
raised.
list_resources: Whether to list the resources that the connector can
access.
Returns:
A list of resources that the connector can access.
Raises:
ValueError: If the arguments or the connector configuration are
not valid.
"""
spec = self.get_type()
resources = ServiceConnectorResourcesModel(
connector_type=spec,
id=self.id,
name=self.name,
)
name_msg = f" '{self.name}'" if self.name else ""
resource_types = self.supported_resource_types
if resource_type:
if resource_type not in resource_types:
raise ValueError(
f"connector{name_msg} does not support resource type: "
f"'{resource_type}'. Supported resource types are: "
f"{', '.join(resource_types)}"
)
resource_types = [resource_type]
# Pre-populate the list of resources with entries corresponding to the
# supported resource types and scoped to the supplied resource type
resources.resources = [
ServiceConnectorTypedResourcesModel(
resource_type=rt,
)
for rt in resource_types
]
if self.has_expired():
error = "the connector's authentication credentials have expired."
# Log the error in the resources object
resources.set_error(error)
return resources
verify_resource_types: List[Optional[str]] = []
verify_resource_id = None
if not list_resources and not resource_id:
# If we're not listing resources, we're only verifying that the
# connector can authenticate globally (i.e. without supplying a
# resource type or resource ID). This is the same as if no resource
# type or resource ID was supplied. The only exception is when the
# verification scope is already set to a single resource ID, in
# which case we still perform the verification on that resource ID.
verify_resource_types = [None]
verify_resource_id = None
else:
if len(resource_types) > 1:
# This forces the connector to verify that it can authenticate
# globally (i.e. without supplying a resource type or resource
# ID) before listing individual resources in the case of
# multi-type service connectors.
verify_resource_types = [None]
verify_resource_types.extend(resource_types)
if len(verify_resource_types) == 1:
verify_resource_id = resource_id
# Here we go through each resource type and attempt to verify and list
# the resources that the connector can access for that resource type.
# This list may start with a `None` resource type, which indicates that
# the connector should verify that it can authenticate globally.
for resource_type in verify_resource_types:
try:
resource_type, resource_id = self.validate_runtime_args(
resource_type=resource_type,
resource_id=verify_resource_id,
require_resource_type=False,
require_resource_id=False,
)
resource_ids = self._verify(
resource_type=resource_type,
resource_id=resource_id,
)
except ValueError as exc:
raise ValueError(
f"The connector configuration is incomplete or invalid: "
f"{exc}",
)
except AuthorizationException as exc:
error = f"connector{name_msg} authorization failure: {exc}"
# Log an exception if debug logging is enabled
if logger.isEnabledFor(logging.DEBUG):
logger.exception(error)
else:
logger.warning(error)
# Log the error in the resources object
resources.set_error(error, resource_type=resource_type)
if resource_type:
continue
else:
# We stop on a global failure
break
except Exception as exc:
error = (
f"connector{name_msg} verification failed with "
f"unexpected error: {exc}"
)
# Log an exception if debug logging is enabled
if logger.isEnabledFor(logging.DEBUG):
logger.exception(error)
else:
logger.warning(error)
error = (
"an unexpected error occurred while verifying the "
"connector."
)
# Log the error in the resources object
resources.set_error(error, resource_type=resource_type)
if resource_type:
continue
else:
# We stop on a global failure
break
if not resource_type:
# If a resource type is not provided as argument, we don't
# expect any resources to be listed
continue
resource_type_spec = spec.resource_type_dict[resource_type]
if resource_id:
# A single resource was requested, so we expect a single
# resource to be listed
if [resource_id] != resource_ids:
logger.error(
f"a different resource ID '{resource_ids}' was "
f"returned than the one requested: {resource_ids}. "
f"This is likely a bug in the {self.__class__} "
"connector implementation."
)
resources.set_resource_ids(resource_type, [resource_id])
elif not resource_ids:
# If no resources were listed, signal this as an error that the
# connector cannot access any resources.
error = (
f"connector{name_msg} didn't list any "
f"{resource_type_spec.name} resources. This is likely "
"caused by the connector credentials not being valid or "
"not having sufficient permissions to list or access "
"resources of this type. Please check the connector "
"configuration and its credentials and try again."
)
logger.debug(error)
resources.set_error(error, resource_type=resource_type)
else:
resources.set_resource_ids(resource_type, resource_ids)
return resources
ServiceConnectorMeta (ModelMetaclass)
Metaclass responsible for automatically registering ServiceConnector classes.
Source code in zenml/service_connectors/service_connector.py
class ServiceConnectorMeta(ModelMetaclass):
"""Metaclass responsible for automatically registering ServiceConnector classes."""
def __new__(
mcs, name: str, bases: Tuple[Type[Any], ...], dct: Dict[str, Any]
) -> "ServiceConnectorMeta":
"""Creates a new ServiceConnector class and registers it.
Args:
name: The name of the class.
bases: The base classes of the class.
dct: The dictionary of the class.
Returns:
The ServiceConnectorMeta class.
"""
cls = cast(
Type["ServiceConnector"], super().__new__(mcs, name, bases, dct)
)
# Skip the following validation and registration for the base class.
if name == "ServiceConnector":
return cls
else:
from zenml.service_connectors.service_connector_registry import (
service_connector_registry,
)
# Register the service connector.
service_connector_registry.register_service_connector_type(
cls.get_type()
)
return cls
__new__(mcs, name, bases, dct)
special
staticmethod
Creates a new ServiceConnector class and registers it.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
name |
str |
The name of the class. |
required |
bases |
Tuple[Type[Any], ...] |
The base classes of the class. |
required |
dct |
Dict[str, Any] |
The dictionary of the class. |
required |
Returns:
| Type | Description |
|---|---|
ServiceConnectorMeta |
The ServiceConnectorMeta class. |
Source code in zenml/service_connectors/service_connector.py
def __new__(
mcs, name: str, bases: Tuple[Type[Any], ...], dct: Dict[str, Any]
) -> "ServiceConnectorMeta":
"""Creates a new ServiceConnector class and registers it.
Args:
name: The name of the class.
bases: The base classes of the class.
dct: The dictionary of the class.
Returns:
The ServiceConnectorMeta class.
"""
cls = cast(
Type["ServiceConnector"], super().__new__(mcs, name, bases, dct)
)
# Skip the following validation and registration for the base class.
if name == "ServiceConnector":
return cls
else:
from zenml.service_connectors.service_connector_registry import (
service_connector_registry,
)
# Register the service connector.
service_connector_registry.register_service_connector_type(
cls.get_type()
)
return cls
service_connector_registry
Implementation of a service connector registry.
ServiceConnectorRegistry
Service connector registry.
Source code in zenml/service_connectors/service_connector_registry.py
class ServiceConnectorRegistry:
"""Service connector registry."""
def __init__(self) -> None:
"""Initialize the service connector registry."""
self.service_connector_types: Dict[str, ServiceConnectorTypeModel] = {}
self.initialized = False
self.lock = threading.RLock()
def register_service_connector_type(
self,
service_connector_type: ServiceConnectorTypeModel,
overwrite: bool = False,
) -> None:
"""Registers a service connector type.
Args:
service_connector_type: Service connector type.
overwrite: Whether to overwrite an existing service connector type.
"""
with self.lock:
if (
service_connector_type.connector_type
not in self.service_connector_types
or overwrite
):
self.service_connector_types[
service_connector_type.connector_type
] = service_connector_type
logger.debug(
"Registered service connector type "
f"{service_connector_type.connector_type}."
)
else:
logger.debug(
f"Found existing service connector for type "
f"{service_connector_type.connector_type}: Skipping "
"registration."
)
def get_service_connector_type(
self,
connector_type: str,
) -> ServiceConnectorTypeModel:
"""Get a service connector type by its connector type identifier.
Args:
connector_type: The service connector type identifier.
Returns:
A service connector type that was registered for the given
connector type identifier.
Raises:
KeyError: If no service connector was registered for the given type
identifier.
"""
self.register_builtin_service_connectors()
if connector_type not in self.service_connector_types:
raise KeyError(
f"Service connector type {connector_type} is not available. "
f"Please make sure the corresponding packages and/or ZenML "
f"integration are installed and try again."
)
return self.service_connector_types[connector_type].model_copy()
def __getitem__(self, key: str) -> ServiceConnectorTypeModel:
"""Get a service connector type by its connector type identifier.
Args:
key: The service connector type identifier.
Returns:
A service connector that was registered for the given service
connector type identifier.
"""
return self.get_service_connector_type(key)
def is_registered(self, connector_type: str) -> bool:
"""Returns if a service connector is registered for the given type identifier.
Args:
connector_type: The service connector type identifier.
Returns:
True if a service connector is registered for the given type
identifier, False otherwise.
"""
self.register_builtin_service_connectors()
return connector_type in self.service_connector_types
def list_service_connector_types(
self,
connector_type: Optional[str] = None,
resource_type: Optional[str] = None,
auth_method: Optional[str] = None,
) -> List[ServiceConnectorTypeModel]:
"""Find one or more service connector types that match the given criteria.
Args:
connector_type: Filter by service connector type identifier.
resource_type: Filter by a resource type that the connector can
be used to give access to.
auth_method: Filter by an authentication method that the connector
uses to authenticate with the resource provider.
Returns:
A list of service connector type models that match the given
criteria.
"""
self.register_builtin_service_connectors()
matches: List[ServiceConnectorTypeModel] = []
for service_connector_type in self.service_connector_types.values():
if (
(
connector_type is None
or connector_type == service_connector_type.connector_type
)
and (
resource_type is None
or resource_type
in service_connector_type.resource_type_dict
)
and (
auth_method is None
or auth_method in service_connector_type.auth_method_dict
)
):
matches.append(service_connector_type.model_copy())
return matches
def instantiate_connector(
self,
model: Union[
"ServiceConnectorRequest",
"ServiceConnectorResponse",
],
) -> "ServiceConnector":
"""Validate a service connector model and create an instance from it.
Args:
model: The service connector model to validate and instantiate.
Returns:
A service connector instance.
Raises:
NotImplementedError: If no service connector is registered for the
given type identifier.
ValueError: If the service connector model is not valid.
"""
try:
service_connector_type = self.get_service_connector_type(
model.type
)
except KeyError:
raise NotImplementedError(
f"Service connector type {model.type} is not available "
"locally. Please make sure the corresponding packages and/or "
"ZenML integration are installed and try again."
)
assert service_connector_type.connector_class is not None
try:
return service_connector_type.connector_class.from_model(model)
except ValueError as e:
raise ValueError(
f"The service connector configuration is not valid: {e}"
)
def register_builtin_service_connectors(self) -> None:
"""Registers the default built-in service connectors."""
# Only register built-in service connectors once
with self.lock:
if self.initialized:
return
self.initialized = True
try:
from zenml.integrations.aws.service_connectors.aws_service_connector import ( # noqa
AWSServiceConnector,
)
except ImportError as e:
logger.warning(f"Could not import AWS service connector: {e}.")
try:
from zenml.integrations.gcp.service_connectors.gcp_service_connector import ( # noqa
GCPServiceConnector,
)
except ImportError as e:
logger.warning(f"Could not import GCP service connector: {e}.")
try:
from zenml.integrations.azure.service_connectors.azure_service_connector import ( # noqa
AzureServiceConnector,
)
except ImportError as e:
logger.warning(
f"Could not import Azure service connector: {e}."
)
try:
from zenml.integrations.kubernetes.service_connectors.kubernetes_service_connector import ( # noqa
KubernetesServiceConnector,
)
except ImportError as e:
logger.warning(
f"Could not import Kubernetes service connector: {e}."
)
try:
from zenml.service_connectors.docker_service_connector import ( # noqa
DockerServiceConnector,
)
except ImportError as e:
logger.warning(
f"Could not import Docker service connector: {e}."
)
try:
from zenml.integrations.hyperai.service_connectors.hyperai_service_connector import ( # noqa
HyperAIServiceConnector,
)
except ImportError as e:
logger.warning(
f"Could not import HyperAI service connector: {e}."
)
__getitem__(self, key)
special
Get a service connector type by its connector type identifier.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
key |
str |
The service connector type identifier. |
required |
Returns:
| Type | Description |
|---|---|
ServiceConnectorTypeModel |
A service connector that was registered for the given service connector type identifier. |
Source code in zenml/service_connectors/service_connector_registry.py
def __getitem__(self, key: str) -> ServiceConnectorTypeModel:
"""Get a service connector type by its connector type identifier.
Args:
key: The service connector type identifier.
Returns:
A service connector that was registered for the given service
connector type identifier.
"""
return self.get_service_connector_type(key)
__init__(self)
special
Initialize the service connector registry.
Source code in zenml/service_connectors/service_connector_registry.py
def __init__(self) -> None:
"""Initialize the service connector registry."""
self.service_connector_types: Dict[str, ServiceConnectorTypeModel] = {}
self.initialized = False
self.lock = threading.RLock()
get_service_connector_type(self, connector_type)
Get a service connector type by its connector type identifier.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
connector_type |
str |
The service connector type identifier. |
required |
Returns:
| Type | Description |
|---|---|
ServiceConnectorTypeModel |
A service connector type that was registered for the given connector type identifier. |
Exceptions:
| Type | Description |
|---|---|
KeyError |
If no service connector was registered for the given type identifier. |
Source code in zenml/service_connectors/service_connector_registry.py
def get_service_connector_type(
self,
connector_type: str,
) -> ServiceConnectorTypeModel:
"""Get a service connector type by its connector type identifier.
Args:
connector_type: The service connector type identifier.
Returns:
A service connector type that was registered for the given
connector type identifier.
Raises:
KeyError: If no service connector was registered for the given type
identifier.
"""
self.register_builtin_service_connectors()
if connector_type not in self.service_connector_types:
raise KeyError(
f"Service connector type {connector_type} is not available. "
f"Please make sure the corresponding packages and/or ZenML "
f"integration are installed and try again."
)
return self.service_connector_types[connector_type].model_copy()
instantiate_connector(self, model)
Validate a service connector model and create an instance from it.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model |
Union[ServiceConnectorRequest, ServiceConnectorResponse] |
The service connector model to validate and instantiate. |
required |
Returns:
| Type | Description |
|---|---|
ServiceConnector |
A service connector instance. |
Exceptions:
| Type | Description |
|---|---|
NotImplementedError |
If no service connector is registered for the given type identifier. |
ValueError |
If the service connector model is not valid. |
Source code in zenml/service_connectors/service_connector_registry.py
def instantiate_connector(
self,
model: Union[
"ServiceConnectorRequest",
"ServiceConnectorResponse",
],
) -> "ServiceConnector":
"""Validate a service connector model and create an instance from it.
Args:
model: The service connector model to validate and instantiate.
Returns:
A service connector instance.
Raises:
NotImplementedError: If no service connector is registered for the
given type identifier.
ValueError: If the service connector model is not valid.
"""
try:
service_connector_type = self.get_service_connector_type(
model.type
)
except KeyError:
raise NotImplementedError(
f"Service connector type {model.type} is not available "
"locally. Please make sure the corresponding packages and/or "
"ZenML integration are installed and try again."
)
assert service_connector_type.connector_class is not None
try:
return service_connector_type.connector_class.from_model(model)
except ValueError as e:
raise ValueError(
f"The service connector configuration is not valid: {e}"
)
is_registered(self, connector_type)
Returns if a service connector is registered for the given type identifier.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
connector_type |
str |
The service connector type identifier. |
required |
Returns:
| Type | Description |
|---|---|
bool |
True if a service connector is registered for the given type identifier, False otherwise. |
Source code in zenml/service_connectors/service_connector_registry.py
def is_registered(self, connector_type: str) -> bool:
"""Returns if a service connector is registered for the given type identifier.
Args:
connector_type: The service connector type identifier.
Returns:
True if a service connector is registered for the given type
identifier, False otherwise.
"""
self.register_builtin_service_connectors()
return connector_type in self.service_connector_types
list_service_connector_types(self, connector_type=None, resource_type=None, auth_method=None)
Find one or more service connector types that match the given criteria.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
connector_type |
Optional[str] |
Filter by service connector type identifier. |
None |
resource_type |
Optional[str] |
Filter by a resource type that the connector can be used to give access to. |
None |
auth_method |
Optional[str] |
Filter by an authentication method that the connector uses to authenticate with the resource provider. |
None |
Returns:
| Type | Description |
|---|---|
List[zenml.models.v2.misc.service_connector_type.ServiceConnectorTypeModel] |
A list of service connector type models that match the given criteria. |
Source code in zenml/service_connectors/service_connector_registry.py
def list_service_connector_types(
self,
connector_type: Optional[str] = None,
resource_type: Optional[str] = None,
auth_method: Optional[str] = None,
) -> List[ServiceConnectorTypeModel]:
"""Find one or more service connector types that match the given criteria.
Args:
connector_type: Filter by service connector type identifier.
resource_type: Filter by a resource type that the connector can
be used to give access to.
auth_method: Filter by an authentication method that the connector
uses to authenticate with the resource provider.
Returns:
A list of service connector type models that match the given
criteria.
"""
self.register_builtin_service_connectors()
matches: List[ServiceConnectorTypeModel] = []
for service_connector_type in self.service_connector_types.values():
if (
(
connector_type is None
or connector_type == service_connector_type.connector_type
)
and (
resource_type is None
or resource_type
in service_connector_type.resource_type_dict
)
and (
auth_method is None
or auth_method in service_connector_type.auth_method_dict
)
):
matches.append(service_connector_type.model_copy())
return matches
register_builtin_service_connectors(self)
Registers the default built-in service connectors.
Source code in zenml/service_connectors/service_connector_registry.py
def register_builtin_service_connectors(self) -> None:
"""Registers the default built-in service connectors."""
# Only register built-in service connectors once
with self.lock:
if self.initialized:
return
self.initialized = True
try:
from zenml.integrations.aws.service_connectors.aws_service_connector import ( # noqa
AWSServiceConnector,
)
except ImportError as e:
logger.warning(f"Could not import AWS service connector: {e}.")
try:
from zenml.integrations.gcp.service_connectors.gcp_service_connector import ( # noqa
GCPServiceConnector,
)
except ImportError as e:
logger.warning(f"Could not import GCP service connector: {e}.")
try:
from zenml.integrations.azure.service_connectors.azure_service_connector import ( # noqa
AzureServiceConnector,
)
except ImportError as e:
logger.warning(
f"Could not import Azure service connector: {e}."
)
try:
from zenml.integrations.kubernetes.service_connectors.kubernetes_service_connector import ( # noqa
KubernetesServiceConnector,
)
except ImportError as e:
logger.warning(
f"Could not import Kubernetes service connector: {e}."
)
try:
from zenml.service_connectors.docker_service_connector import ( # noqa
DockerServiceConnector,
)
except ImportError as e:
logger.warning(
f"Could not import Docker service connector: {e}."
)
try:
from zenml.integrations.hyperai.service_connectors.hyperai_service_connector import ( # noqa
HyperAIServiceConnector,
)
except ImportError as e:
logger.warning(
f"Could not import HyperAI service connector: {e}."
)
register_service_connector_type(self, service_connector_type, overwrite=False)
Registers a service connector type.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
service_connector_type |
ServiceConnectorTypeModel |
Service connector type. |
required |
overwrite |
bool |
Whether to overwrite an existing service connector type. |
False |
Source code in zenml/service_connectors/service_connector_registry.py
def register_service_connector_type(
self,
service_connector_type: ServiceConnectorTypeModel,
overwrite: bool = False,
) -> None:
"""Registers a service connector type.
Args:
service_connector_type: Service connector type.
overwrite: Whether to overwrite an existing service connector type.
"""
with self.lock:
if (
service_connector_type.connector_type
not in self.service_connector_types
or overwrite
):
self.service_connector_types[
service_connector_type.connector_type
] = service_connector_type
logger.debug(
"Registered service connector type "
f"{service_connector_type.connector_type}."
)
else:
logger.debug(
f"Found existing service connector for type "
f"{service_connector_type.connector_type}: Skipping "
"registration."
)
service_connector_utils
Utility methods for Service Connectors.
get_resources_options_from_resource_model_for_full_stack(connector_details)
Get the resource options from the resource model for the full stack.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
connector_details |
Union[uuid.UUID, zenml.models.v2.misc.info_models.ServiceConnectorInfo] |
The service connector details (UUID or Info). |
required |
Returns:
| Type | Description |
|---|---|
ServiceConnectorResourcesInfo |
All available service connector resource options. |
Source code in zenml/service_connectors/service_connector_utils.py
def get_resources_options_from_resource_model_for_full_stack(
connector_details: Union[UUID, ServiceConnectorInfo],
) -> ServiceConnectorResourcesInfo:
"""Get the resource options from the resource model for the full stack.
Args:
connector_details: The service connector details (UUID or Info).
Returns:
All available service connector resource options.
"""
client = Client()
zen_store = client.zen_store
if isinstance(connector_details, UUID):
resource_model = zen_store.verify_service_connector(
connector_details,
list_resources=True,
)
else:
resource_model = zen_store.verify_service_connector_config(
service_connector=ServiceConnectorRequest(
user=client.active_user.id,
workspace=client.active_workspace.id,
name="fake",
connector_type=connector_details.type,
auth_method=connector_details.auth_method,
configuration=connector_details.configuration,
secrets={},
labels={},
),
list_resources=True,
)
resources = resource_model.resources
if isinstance(
resource_model.connector_type,
str,
):
connector_type = resource_model.connector_type
else:
connector_type = resource_model.connector_type.connector_type
artifact_stores: List[ResourcesInfo] = []
orchestrators: List[ResourcesInfo] = []
container_registries: List[ResourcesInfo] = []
if connector_type == "aws":
for each in resources:
if each.resource_ids:
if each.resource_type == "s3-bucket":
artifact_stores.append(
_prepare_resource_info(
connector_details=connector_details,
resource_ids=each.resource_ids,
stack_component_type=StackComponentType.ARTIFACT_STORE,
flavor="s3",
required_configuration={"path": "Path"},
use_resource_value_as_fixed_config=True,
flavor_display_name="S3 Bucket",
)
)
if each.resource_type == "aws-generic":
orchestrators.append(
_prepare_resource_info(
connector_details=connector_details,
resource_ids=each.resource_ids,
stack_component_type=StackComponentType.ORCHESTRATOR,
flavor="sagemaker",
required_configuration={
"execution_role": "execution role ARN"
},
flavor_display_name="AWS Sagemaker",
)
)
orchestrators.append(
_prepare_resource_info(
connector_details=connector_details,
resource_ids=each.resource_ids,
stack_component_type=StackComponentType.ORCHESTRATOR,
flavor="vm_aws",
required_configuration={"region": "region"},
use_resource_value_as_fixed_config=True,
flavor_display_name="Skypilot (EC2)",
)
)
if each.resource_type == "kubernetes-cluster":
orchestrators.append(
_prepare_resource_info(
connector_details=connector_details,
resource_ids=each.resource_ids,
stack_component_type=StackComponentType.ORCHESTRATOR,
flavor="kubernetes",
required_configuration={},
flavor_display_name="Kubernetes",
)
)
if each.resource_type == "docker-registry":
container_registries.append(
_prepare_resource_info(
connector_details=connector_details,
resource_ids=each.resource_ids,
stack_component_type=StackComponentType.CONTAINER_REGISTRY,
flavor="aws",
required_configuration={"uri": "URI"},
use_resource_value_as_fixed_config=True,
flavor_display_name="ECR",
)
)
elif connector_type == "gcp":
for each in resources:
if each.resource_ids:
if each.resource_type == "gcs-bucket":
artifact_stores.append(
_prepare_resource_info(
connector_details=connector_details,
resource_ids=each.resource_ids,
stack_component_type=StackComponentType.ARTIFACT_STORE,
flavor="gcp",
required_configuration={"path": "Path"},
use_resource_value_as_fixed_config=True,
flavor_display_name="GCS Bucket",
)
)
if each.resource_type == "gcp-generic":
orchestrators.append(
_prepare_resource_info(
connector_details=connector_details,
resource_ids=each.resource_ids,
stack_component_type=StackComponentType.ORCHESTRATOR,
flavor="vertex",
required_configuration={"location": "region name"},
flavor_display_name="Vertex AI",
)
)
orchestrators.append(
_prepare_resource_info(
connector_details=connector_details,
resource_ids=each.resource_ids,
stack_component_type=StackComponentType.ORCHESTRATOR,
flavor="vm_gcp",
required_configuration={"region": "region name"},
flavor_display_name="Skypilot (Compute)",
)
)
if each.resource_type == "kubernetes-cluster":
orchestrators.append(
_prepare_resource_info(
connector_details=connector_details,
resource_ids=each.resource_ids,
stack_component_type=StackComponentType.ORCHESTRATOR,
flavor="kubernetes",
required_configuration={},
flavor_display_name="Kubernetes",
)
)
if each.resource_type == "docker-registry":
container_registries.append(
_prepare_resource_info(
connector_details=connector_details,
resource_ids=each.resource_ids,
stack_component_type=StackComponentType.CONTAINER_REGISTRY,
flavor="gcp",
required_configuration={"uri": "URI"},
use_resource_value_as_fixed_config=True,
flavor_display_name="GCR",
)
)
elif connector_type == "azure":
for each in resources:
if each.resource_ids:
if each.resource_type == "blob-container":
artifact_stores.append(
_prepare_resource_info(
connector_details=connector_details,
resource_ids=each.resource_ids,
stack_component_type=StackComponentType.ARTIFACT_STORE,
flavor="azure",
required_configuration={"path": "Path"},
use_resource_value_as_fixed_config=True,
flavor_display_name="Blob container",
)
)
if each.resource_type == "azure-generic":
# No native orchestrator ATM
orchestrators.append(
_prepare_resource_info(
connector_details=connector_details,
resource_ids=each.resource_ids,
stack_component_type=StackComponentType.ORCHESTRATOR,
flavor="vm_azure",
required_configuration={"region": "region name"},
flavor_display_name="Skypilot (VM)",
)
)
orchestrators.append(
_prepare_resource_info(
connector_details=connector_details,
resource_ids=each.resource_ids,
stack_component_type=StackComponentType.ORCHESTRATOR,
flavor="azureml",
required_configuration={
"subscription_id": "subscription ID",
"resource_group": "resource group",
"workspace": "workspace",
},
flavor_display_name="AzureML",
)
)
if each.resource_type == "kubernetes-cluster":
orchestrators.append(
_prepare_resource_info(
connector_details=connector_details,
resource_ids=each.resource_ids,
stack_component_type=StackComponentType.ORCHESTRATOR,
flavor="kubernetes",
required_configuration={},
flavor_display_name="Kubernetes",
)
)
if each.resource_type == "docker-registry":
container_registries.append(
_prepare_resource_info(
connector_details=connector_details,
resource_ids=each.resource_ids,
stack_component_type=StackComponentType.CONTAINER_REGISTRY,
flavor="azure",
required_configuration={"uri": "URI"},
use_resource_value_as_fixed_config=True,
flavor_display_name="ACR",
)
)
_raise_specific_cloud_exception_if_needed(
cloud_provider=connector_type,
artifact_stores=artifact_stores,
orchestrators=orchestrators,
container_registries=container_registries,
)
return ServiceConnectorResourcesInfo(
connector_type=connector_type,
components_resources_info={
StackComponentType.ARTIFACT_STORE: artifact_stores,
StackComponentType.ORCHESTRATOR: orchestrators,
StackComponentType.CONTAINER_REGISTRY: container_registries,
},
)