Feast
zenml.integrations.feast
Initialization for Feast integration.
The Feast integration offers a way to connect to a Feast Feature Store. ZenML implements a dedicated stack component that you can access as part of your ZenML steps in the usual ways.
Attributes
FEAST = 'feast'
module-attribute
FEAST_FEATURE_STORE_FLAVOR = 'feast'
module-attribute
Classes
FeastIntegration
Bases: Integration
Definition of Feast integration for ZenML.
Functions
flavors() -> List[Type[Flavor]]
classmethod
Declare the stack component flavors for the Feast integration.
Returns:
Type | Description |
---|---|
List[Type[Flavor]]
|
List of stack component flavors for this integration. |
Source code in src/zenml/integrations/feast/__init__.py
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|
get_requirements(target_os: Optional[str] = None, python_version: Optional[str] = None) -> List[str]
classmethod
Method to get the requirements for the integration.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
target_os
|
Optional[str]
|
The target operating system to get the requirements for. |
None
|
python_version
|
Optional[str]
|
The Python version to use for the requirements. |
None
|
Returns:
Type | Description |
---|---|
List[str]
|
A list of requirements. |
Source code in src/zenml/integrations/feast/__init__.py
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|
Flavor
Class for ZenML Flavors.
Attributes
config_class: Type[StackComponentConfig]
abstractmethod
property
Returns StackComponentConfig
config class.
Returns:
Type | Description |
---|---|
Type[StackComponentConfig]
|
The config class. |
config_schema: Dict[str, Any]
property
The config schema for a flavor.
Returns:
Type | Description |
---|---|
Dict[str, Any]
|
The config schema. |
docs_url: Optional[str]
property
A url to point at docs explaining this flavor.
Returns:
Type | Description |
---|---|
Optional[str]
|
A flavor docs url. |
implementation_class: Type[StackComponent]
abstractmethod
property
Implementation class for this flavor.
Returns:
Type | Description |
---|---|
Type[StackComponent]
|
The implementation class for this flavor. |
logo_url: Optional[str]
property
A url to represent the flavor in the dashboard.
Returns:
Type | Description |
---|---|
Optional[str]
|
The flavor logo. |
name: str
abstractmethod
property
The flavor name.
Returns:
Type | Description |
---|---|
str
|
The flavor name. |
sdk_docs_url: Optional[str]
property
A url to point at SDK docs explaining this flavor.
Returns:
Type | Description |
---|---|
Optional[str]
|
A flavor SDK docs url. |
service_connector_requirements: Optional[ServiceConnectorRequirements]
property
Service connector resource requirements for service connectors.
Specifies resource requirements that are used to filter the available service connector types that are compatible with this flavor.
Returns:
Type | Description |
---|---|
Optional[ServiceConnectorRequirements]
|
Requirements for compatible service connectors, if a service |
Optional[ServiceConnectorRequirements]
|
connector is required for this flavor. |
type: StackComponentType
abstractmethod
property
Functions
from_model(flavor_model: FlavorResponse) -> Flavor
classmethod
Loads a flavor from a model.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
flavor_model
|
FlavorResponse
|
The model to load from. |
required |
Raises:
Type | Description |
---|---|
CustomFlavorImportError
|
If the custom flavor can't be imported. |
ImportError
|
If the flavor can't be imported. |
Returns:
Type | Description |
---|---|
Flavor
|
The loaded flavor. |
Source code in src/zenml/stack/flavor.py
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|
generate_default_docs_url() -> str
Generate the doc urls for all inbuilt and integration flavors.
Note that this method is not going to be useful for custom flavors, which do not have any docs in the main zenml docs.
Returns:
Type | Description |
---|---|
str
|
The complete url to the zenml documentation |
Source code in src/zenml/stack/flavor.py
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|
generate_default_sdk_docs_url() -> str
Generate SDK docs url for a flavor.
Returns:
Type | Description |
---|---|
str
|
The complete url to the zenml SDK docs |
Source code in src/zenml/stack/flavor.py
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|
to_model(integration: Optional[str] = None, is_custom: bool = True) -> FlavorRequest
Converts a flavor to a model.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
integration
|
Optional[str]
|
The integration to use for the model. |
None
|
is_custom
|
bool
|
Whether the flavor is a custom flavor. |
True
|
Returns:
Type | Description |
---|---|
FlavorRequest
|
The model. |
Source code in src/zenml/stack/flavor.py
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|
Integration
Base class for integration in ZenML.
Functions
activate() -> None
classmethod
Abstract method to activate the integration.
Source code in src/zenml/integrations/integration.py
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|
check_installation() -> bool
classmethod
Method to check whether the required packages are installed.
Returns:
Type | Description |
---|---|
bool
|
True if all required packages are installed, False otherwise. |
Source code in src/zenml/integrations/integration.py
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|
flavors() -> List[Type[Flavor]]
classmethod
Abstract method to declare new stack component flavors.
Returns:
Type | Description |
---|---|
List[Type[Flavor]]
|
A list of new stack component flavors. |
Source code in src/zenml/integrations/integration.py
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|
get_requirements(target_os: Optional[str] = None, python_version: Optional[str] = None) -> List[str]
classmethod
Method to get the requirements for the integration.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
target_os
|
Optional[str]
|
The target operating system to get the requirements for. |
None
|
python_version
|
Optional[str]
|
The Python version to use for the requirements. |
None
|
Returns:
Type | Description |
---|---|
List[str]
|
A list of requirements. |
Source code in src/zenml/integrations/integration.py
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|
get_uninstall_requirements(target_os: Optional[str] = None) -> List[str]
classmethod
Method to get the uninstall requirements for the integration.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
target_os
|
Optional[str]
|
The target operating system to get the requirements for. |
None
|
Returns:
Type | Description |
---|---|
List[str]
|
A list of requirements. |
Source code in src/zenml/integrations/integration.py
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|
plugin_flavors() -> List[Type[BasePluginFlavor]]
classmethod
Abstract method to declare new plugin flavors.
Returns:
Type | Description |
---|---|
List[Type[BasePluginFlavor]]
|
A list of new plugin flavors. |
Source code in src/zenml/integrations/integration.py
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|
Modules
feature_stores
Feast Feature Store integration for ZenML.
Feature stores allow data teams to serve data via an offline store and an online low-latency store where data is kept in sync between the two. It also offers a centralized registry where features (and feature schemas) are stored for use within a team or wider organization. Feature stores are a relatively recent addition to commonly-used machine learning stacks. Feast is a leading open-source feature store, first developed by Gojek in collaboration with Google.
Classes
FeastFeatureStore(name: str, id: UUID, config: StackComponentConfig, flavor: str, type: StackComponentType, user: Optional[UUID], created: datetime, updated: datetime, labels: Optional[Dict[str, Any]] = None, connector_requirements: Optional[ServiceConnectorRequirements] = None, connector: Optional[UUID] = None, connector_resource_id: Optional[str] = None, *args: Any, **kwargs: Any)
Bases: BaseFeatureStore
Class to interact with the Feast feature store.
Source code in src/zenml/stack/stack_component.py
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|
config: FeastFeatureStoreConfig
property
Returns the FeastFeatureStoreConfig
config.
Returns:
Type | Description |
---|---|
FeastFeatureStoreConfig
|
The configuration. |
get_data_sources() -> List[str]
Returns the data sources' names.
Raise
ConnectionError: If the online component (Redis) is not available.
Returns:
Type | Description |
---|---|
List[str]
|
The data sources' names. |
Source code in src/zenml/integrations/feast/feature_stores/feast_feature_store.py
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|
get_entities() -> List[str]
Returns the entity names.
Raise
ConnectionError: If the online component (Redis) is not available.
Returns:
Type | Description |
---|---|
List[str]
|
The entity names. |
Source code in src/zenml/integrations/feast/feature_stores/feast_feature_store.py
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|
get_feast_version() -> str
Returns the version of Feast used.
Raise
ConnectionError: If the online component (Redis) is not available.
Returns:
Type | Description |
---|---|
str
|
The version of Feast currently being used. |
Source code in src/zenml/integrations/feast/feature_stores/feast_feature_store.py
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|
get_feature_services() -> List[FeatureService]
Returns the feature services.
Raise
ConnectionError: If the online component (Redis) is not available.
Returns:
Type | Description |
---|---|
List[FeatureService]
|
The feature services. |
Source code in src/zenml/integrations/feast/feature_stores/feast_feature_store.py
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|
get_feature_views() -> List[str]
Returns the feature view names.
Raise
ConnectionError: If the online component (Redis) is not available.
Returns:
Type | Description |
---|---|
List[str]
|
The feature view names. |
Source code in src/zenml/integrations/feast/feature_stores/feast_feature_store.py
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|
get_historical_features(entity_df: Union[pd.DataFrame, str], features: Union[List[str], FeatureService], full_feature_names: bool = False) -> pd.DataFrame
Returns the historical features for training or batch scoring.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
entity_df
|
Union[DataFrame, str]
|
The entity DataFrame or entity name. |
required |
features
|
Union[List[str], FeatureService]
|
The features to retrieve or a FeatureService. |
required |
full_feature_names
|
bool
|
Whether to return the full feature names. |
False
|
Raise
ConnectionError: If the online component (Redis) is not available.
Returns:
Type | Description |
---|---|
DataFrame
|
The historical features as a Pandas DataFrame. |
Source code in src/zenml/integrations/feast/feature_stores/feast_feature_store.py
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|
get_online_features(entity_rows: List[Dict[str, Any]], features: Union[List[str], FeatureService], full_feature_names: bool = False) -> Dict[str, Any]
Returns the latest online feature data.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
entity_rows
|
List[Dict[str, Any]]
|
The entity rows to retrieve. |
required |
features
|
Union[List[str], FeatureService]
|
The features to retrieve or a FeatureService. |
required |
full_feature_names
|
bool
|
Whether to return the full feature names. |
False
|
Raise
ConnectionError: If the online component (Redis) is not available.
Returns:
Type | Description |
---|---|
Dict[str, Any]
|
The latest online feature data as a dictionary. |
Source code in src/zenml/integrations/feast/feature_stores/feast_feature_store.py
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|
get_project() -> str
Returns the project name.
Raise
ConnectionError: If the online component (Redis) is not available.
Returns:
Type | Description |
---|---|
str
|
The project name. |
Source code in src/zenml/integrations/feast/feature_stores/feast_feature_store.py
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|
get_registry() -> BaseRegistry
Returns the feature store registry.
Raise
ConnectionError: If the online component (Redis) is not available.
Returns:
Type | Description |
---|---|
BaseRegistry
|
The registry. |
Source code in src/zenml/integrations/feast/feature_stores/feast_feature_store.py
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|
Modules
feast_feature_store
Implementation of the Feast Feature Store for ZenML.
FeastFeatureStore(name: str, id: UUID, config: StackComponentConfig, flavor: str, type: StackComponentType, user: Optional[UUID], created: datetime, updated: datetime, labels: Optional[Dict[str, Any]] = None, connector_requirements: Optional[ServiceConnectorRequirements] = None, connector: Optional[UUID] = None, connector_resource_id: Optional[str] = None, *args: Any, **kwargs: Any)
Bases: BaseFeatureStore
Class to interact with the Feast feature store.
Source code in src/zenml/stack/stack_component.py
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|
config: FeastFeatureStoreConfig
property
Returns the FeastFeatureStoreConfig
config.
Returns:
Type | Description |
---|---|
FeastFeatureStoreConfig
|
The configuration. |
get_data_sources() -> List[str]
Returns the data sources' names.
Raise
ConnectionError: If the online component (Redis) is not available.
Returns:
Type | Description |
---|---|
List[str]
|
The data sources' names. |
Source code in src/zenml/integrations/feast/feature_stores/feast_feature_store.py
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|
get_entities() -> List[str]
Returns the entity names.
Raise
ConnectionError: If the online component (Redis) is not available.
Returns:
Type | Description |
---|---|
List[str]
|
The entity names. |
Source code in src/zenml/integrations/feast/feature_stores/feast_feature_store.py
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|
get_feast_version() -> str
Returns the version of Feast used.
Raise
ConnectionError: If the online component (Redis) is not available.
Returns:
Type | Description |
---|---|
str
|
The version of Feast currently being used. |
Source code in src/zenml/integrations/feast/feature_stores/feast_feature_store.py
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|
get_feature_services() -> List[FeatureService]
Returns the feature services.
Raise
ConnectionError: If the online component (Redis) is not available.
Returns:
Type | Description |
---|---|
List[FeatureService]
|
The feature services. |
Source code in src/zenml/integrations/feast/feature_stores/feast_feature_store.py
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|
get_feature_views() -> List[str]
Returns the feature view names.
Raise
ConnectionError: If the online component (Redis) is not available.
Returns:
Type | Description |
---|---|
List[str]
|
The feature view names. |
Source code in src/zenml/integrations/feast/feature_stores/feast_feature_store.py
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|
get_historical_features(entity_df: Union[pd.DataFrame, str], features: Union[List[str], FeatureService], full_feature_names: bool = False) -> pd.DataFrame
Returns the historical features for training or batch scoring.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
entity_df
|
Union[DataFrame, str]
|
The entity DataFrame or entity name. |
required |
features
|
Union[List[str], FeatureService]
|
The features to retrieve or a FeatureService. |
required |
full_feature_names
|
bool
|
Whether to return the full feature names. |
False
|
Raise
ConnectionError: If the online component (Redis) is not available.
Returns:
Type | Description |
---|---|
DataFrame
|
The historical features as a Pandas DataFrame. |
Source code in src/zenml/integrations/feast/feature_stores/feast_feature_store.py
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|
get_online_features(entity_rows: List[Dict[str, Any]], features: Union[List[str], FeatureService], full_feature_names: bool = False) -> Dict[str, Any]
Returns the latest online feature data.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
entity_rows
|
List[Dict[str, Any]]
|
The entity rows to retrieve. |
required |
features
|
Union[List[str], FeatureService]
|
The features to retrieve or a FeatureService. |
required |
full_feature_names
|
bool
|
Whether to return the full feature names. |
False
|
Raise
ConnectionError: If the online component (Redis) is not available.
Returns:
Type | Description |
---|---|
Dict[str, Any]
|
The latest online feature data as a dictionary. |
Source code in src/zenml/integrations/feast/feature_stores/feast_feature_store.py
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|
get_project() -> str
Returns the project name.
Raise
ConnectionError: If the online component (Redis) is not available.
Returns:
Type | Description |
---|---|
str
|
The project name. |
Source code in src/zenml/integrations/feast/feature_stores/feast_feature_store.py
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|
get_registry() -> BaseRegistry
Returns the feature store registry.
Raise
ConnectionError: If the online component (Redis) is not available.
Returns:
Type | Description |
---|---|
BaseRegistry
|
The registry. |
Source code in src/zenml/integrations/feast/feature_stores/feast_feature_store.py
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|
flavors
Feast integration flavors.
Classes
FeastFeatureStoreConfig(warn_about_plain_text_secrets: bool = False, **kwargs: Any)
Bases: BaseFeatureStoreConfig
Config for Feast feature store.
Source code in src/zenml/stack/stack_component.py
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|
is_local: bool
property
Checks if this stack component is running locally.
Returns:
Type | Description |
---|---|
bool
|
True if this config is for a local component, False otherwise. |
FeastFeatureStoreFlavor
Bases: BaseFeatureStoreFlavor
Feast Feature store flavor.
config_class: Type[FeastFeatureStoreConfig]
property
Returns FeastFeatureStoreConfig config class.
Returns:
Type | Description |
---|---|
Type[FeastFeatureStoreConfig]
|
The config class. |
docs_url: Optional[str]
property
A url to point at docs explaining this flavor.
Returns:
Type | Description |
---|---|
Optional[str]
|
A flavor docs url. |
implementation_class: Type[FeastFeatureStore]
property
Implementation class for this flavor.
Returns:
Type | Description |
---|---|
Type[FeastFeatureStore]
|
The implementation class. |
logo_url: str
property
A url to represent the flavor in the dashboard.
Returns:
Type | Description |
---|---|
str
|
The flavor logo. |
name: str
property
Name of the flavor.
Returns:
Type | Description |
---|---|
str
|
The name of the flavor. |
sdk_docs_url: Optional[str]
property
A url to point at SDK docs explaining this flavor.
Returns:
Type | Description |
---|---|
Optional[str]
|
A flavor SDK docs url. |
Modules
feast_feature_store_flavor
Feast feature store flavor.
FeastFeatureStoreConfig(warn_about_plain_text_secrets: bool = False, **kwargs: Any)
Bases: BaseFeatureStoreConfig
Config for Feast feature store.
Source code in src/zenml/stack/stack_component.py
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|
is_local: bool
property
Checks if this stack component is running locally.
Returns:
Type | Description |
---|---|
bool
|
True if this config is for a local component, False otherwise. |
FeastFeatureStoreFlavor
Bases: BaseFeatureStoreFlavor
Feast Feature store flavor.
config_class: Type[FeastFeatureStoreConfig]
property
Returns FeastFeatureStoreConfig config class.
Returns:
Type | Description |
---|---|
Type[FeastFeatureStoreConfig]
|
The config class. |
docs_url: Optional[str]
property
A url to point at docs explaining this flavor.
Returns:
Type | Description |
---|---|
Optional[str]
|
A flavor docs url. |
implementation_class: Type[FeastFeatureStore]
property
Implementation class for this flavor.
Returns:
Type | Description |
---|---|
Type[FeastFeatureStore]
|
The implementation class. |
logo_url: str
property
A url to represent the flavor in the dashboard.
Returns:
Type | Description |
---|---|
str
|
The flavor logo. |
name: str
property
Name of the flavor.
Returns:
Type | Description |
---|---|
str
|
The name of the flavor. |
sdk_docs_url: Optional[str]
property
A url to point at SDK docs explaining this flavor.
Returns:
Type | Description |
---|---|
Optional[str]
|
A flavor SDK docs url. |