featurebyte.Catalog.list_features

list_features(

include_id: Union[bool, NoneType]=True,

primary_entity: Union[str, List[str], NoneType]=None,

primary_table: Union[str, List[str], NoneType]=None

) -> DataFrame

Description

Generates a DataFrame that contains various attributes of the registered features, such as their names, types, corresponding tables, related entities, creation dates, and the state of readiness and online availability of their default version.

The returned DataFrame can be filtered by the primary entity or the primary table of the features in the catalog.

Parameters

• include_id: Union[bool, NoneType]
  default: True
  Whether to include id in the list
  
  
• primary_entity: Union[str, List[str], NoneType]
  Name of entity used to filter results. If multiple entities are provided, the filtered results will contain features that are associated with all the entities.
  
  
• primary_table: Union[str, List[str], NoneType]
  Name of table used to filter results. If multiple tables are provided, the filtered results will contain features that are associated with all the tables.
  
  

Returns

• DataFrame
  Table of features
  
  

Examples

List all features saved in the catalog.

>>> features = catalog.list_features()

List all features having grocerycustomer or frenchstate as primary entity.

>>> customer_or_state_features = catalog.list_features(
...   primary_entity = ["grocerycustomer", "frenchstate"]
... )