teradataml.store.feature_store.feature_store.FeatureStore.list_feature_catalogs = list_feature_catalogs(self) -> teradataml.dataframe.dataframe.DataFrame

DESCRIPTION:
    Lists all the feature catalogs.
 
PARAMETERS:
    None
 
RETURNS:
    teradataml DataFrame
 
RAISES:
    None
 
EXAMPLES:
    # Example 1: List all the feature catalogs in the repo 'vfs_v1'.
    >>> from teradataml import FeatureStore
 
    # Create FeatureStore for the repo 'vfs_v1' or use existing one.
    >>> fs = FeatureStore("vfs_v1")
    FeatureStore is ready to use.
 
    # Load the sales data.
    >>> load_example_data("dataframe", "sales")
    >>> df = DataFrame("sales")
 
    # Create a feature process.
    >>> from teradataml import FeatureProcess
    >>> fp = FeatureProcess(repo="vfs_v1",
    ...                     data_domain='sales',
    ...                     object=df,
    ...                     entity="accounts",
    ...                     features=["Jan", "Feb", "Mar", "Apr"])
    >>> fp.run()
    Process '5747082b-4acb-11f0-a2d7-f020ffe7fe09' started.
    Process '5747082b-4acb-11f0-a2d7-f020ffe7fe09' completed.
 
    # List all the feature catalogs in the repo 'vfs_v1'.
    >>> fs.list_feature_catalogs()
                data_domain  feature_id                                 table_name                     valid_start                      valid_end
    entity_name
    accounts          sales           2  FS_T_918e1cb4_c6bc_6d38_634d_7b9fe53e2a63  2025-06-16 16:02:49.481245+00:  9999-12-31 23:59:59.999999+00:
    accounts          sales      100001  FS_T_e84ff803_3d5c_4793_cd72_251c780fffe4  2025-06-16 16:02:49.481245+00:  9999-12-31 23:59:59.999999+00:
    accounts          sales           1  FS_T_918e1cb4_c6bc_6d38_634d_7b9fe53e2a63  2025-06-16 16:02:49.481245+00:  9999-12-31 23:59:59.999999+00:
    accounts          sales      200001  FS_T_918e1cb4_c6bc_6d38_634d_7b9fe53e2a63  2025-06-16 16:02:49.481245+00:  9999-12-31 23:59:59.999999+00: