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featurebyte.Catalog.list_feature_lists

list_feature_lists(
include_id: Union[bool, NoneType]=True,
primary_entity: Union[str, List[str], NoneType]=None,
entity: Union[str, NoneType]=None,
table: Union[str, NoneType]=None
) -> DataFrame

Description

Returns a DataFrame that contains various attributes of the registered feature lists. These attributes include the names of the feature lists, the number of features in each list, their status, whether they have been deployed in production, the percentage of production ready features of their default version, the tables used by the features, their related entities, and creation dates.

The resulting DataFrame can be filtered based on the primary entity of the feature lists or the tables utilized by the feature lists.

Parameters

  • include_id: Union[bool, NoneType]
    default: True
    Whether to include id in the list.

  • primary_entity: Union[str, List[str], NoneType]
    Specifies the primary entity or entities for filtering results. Retrieve feature lists with the specified primary entity name(s). If multiple entities are provided in a list, the filtered results will include feature lists that have primary entities matching any entity in this list.

  • entity: Union[str, NoneType]
    Specifies the entity name for filtering results. Retrieve feature lists containing features with the specified entity name as their primary entity.

  • table: Union[str, NoneType]
    Specifies the table name for filtering results. Retrieve feature lists associated with the specified table name.

Returns

  • DataFrame
    Table of feature lists.

Examples

>>> feature_lists = catalog.list_feature_lists()