Method __init__

sdk/python/feast/on_demand_feature_view.py:162–339

Creates an OnDemandFeatureView object. Args: name: The unique name of the on demand feature view. entities (optional): The list of names of entities that this feature view is associated with. schema: The list of features in the output of the on d

(  # noqa: C901
        self,
        *,
        name: str,
        entities: Optional[List[Entity]] = None,
        schema: Optional[List[Field]] = None,
        sources: Optional[List[OnDemandSourceType]] = None,
        input_schema: Optional[List[Field]] = None,
        udf: Optional[FunctionType] = None,
        udf_string: Optional[str] = "",
        feature_transformation: Optional[Transformation] = None,
        mode: str = "pandas",
        description: str = "",
        tags: Optional[dict[str, str]] = None,
        owner: str = "",
        org: str = "",
        write_to_online_store: bool = False,
        singleton: bool = False,
        track_metrics: bool = False,
        aggregations: Optional[List[Aggregation]] = None,
        version: str = "latest",
        enabled: bool = True,
    )

    _raw_feature_transformation_proto: Optional[Any] = None

    def __init__(  # noqa: C901
        self,
        *,
        name: str,
        entities: Optional[List[Entity]] = None,
        schema: Optional[List[Field]] = None,
        sources: Optional[List[OnDemandSourceType]] = None,
        input_schema: Optional[List[Field]] = None,
        udf: Optional[FunctionType] = None,
        udf_string: Optional[str] = "",
        feature_transformation: Optional[Transformation] = None,
        mode: str = "pandas",
        description: str = "",
        tags: Optional[dict[str, str]] = None,
        owner: str = "",
        org: str = "",
        write_to_online_store: bool = False,
        singleton: bool = False,
        track_metrics: bool = False,
        aggregations: Optional[List[Aggregation]] = None,
        version: str = "latest",
        enabled: bool = True,
    ):
        """
        Creates an OnDemandFeatureView object.

        Args:
            name: The unique name of the on demand feature view.
            entities (optional): The list of names of entities that this feature view is associated with.
            schema: The list of features in the output of the on demand feature view, after
                the transformation has been applied.
            sources: A map from input source names to the actual input sources, which may be
                feature views, or request data sources. These sources serve as inputs to the udf,
                which will refer to them by name.
            input_schema (optional): A list of Fields describing data that is accepted as input
                but not stored directly as features — e.g. aggregation columns, normalization
                parameters, thresholds, or other contextual values passed at request time.
                When provided, sources is not required — an internal RequestSource will be
                created automatically.
            udf: The user defined transformation function, which must take pandas
                dataframes as inputs.
            udf_string: The source code version of the udf (for diffing and displaying in Web UI)
            feature_transformation: The user defined transformation.
            mode: Mode of execution (e.g., Pandas or Python native)
            description (optional): A human-readable description.
            tags (optional): A dictionary of key-value pairs to store arbitrary metadata.
            owner (optional): The owner of the on demand feature view, typically the email
                of the primary maintainer.
            org (optional): The organizational unit that owns this feature view
                (e.g. "ads", "search").
            write_to_online_store (optional): A boolean that indicates whether to write the on demand feature view to
            the online store for faster retrieval.
            singleton (optional): A boolean that indicates whether the transformation is executed on a singleton
                (only applicable when mode="python").
            track_metrics (optional): Whether to emit Prometheus timing metrics
                (``feast_feature_server_transformation_duration_seconds``) for
                this ODFV.  Defaults to ``False``.  Set to ``True`` to opt in
                to per-ODFV transformation duration tracking when the server