teradataml.store.feature_store.feature_store.FeatureStore.list_feature_groups = list_feature_groups(self, archived=False) -> teradataml.dataframe.dataframe.DataFrame

DESCRIPTION:
    List all the FeatureGroups.
 
PARAMETERS:
    archived:
        Optional Argument.
        Specifies whether to list effective feature groups or archived feature groups.
        When set to False, effective feature groups in FeatureStore are listed,
        otherwise, archived feature groups are listed.
        Default Value: False
        Types: bool
 
RETURNS:
    teradataml DataFrame
 
RAISES:
    None
 
EXAMPLES:
    >>> from teradataml import FeatureGroup, FeatureStore, load_example_data
    # Create teradataml DataFrame.
    >>> load_example_data("dataframe", "admissions_train")
    >>> admissions=DataFrame("admissions_train")
 
    # Create FeatureStore for repo 'vfs_v1'.
    >>> fs = FeatureStore("vfs_v1")
    Repo vfs_v1 does not exist. Run FeatureStore.setup() to create the repo and setup FeatureStore.
    # Setup FeatureStore for this repository.
    >>> fs.setup()
    True
 
    # Create a FeatureGroup from DataFrame.
    >>> fg = FeatureGroup.from_DataFrame("admissions", df=admissions, entity_columns='id')
    # Apply FeatureGroup to FeatureStore.
    >>> fs.apply(fg)
    True
 
    # Example 1: List all the effective FeatureGroups in the repo 'vfs_v1'.
    >>> fs.list_feature_groups()
                           description data_source_name  entity_name               creation_time               modified_time
    name       data_domain                                                                                                  
    admissions ALICE              None       admissions   admissions  2025-07-28 03:30:04.115331                        None
 
    # Example 2: List all the archived FeatureGroups in the repo 'vfs_v1'.
    # Let's first archive the FeatureGroup.
    >>> fs.archive_feature_group("admissions")
    True
 
    # List archived FeatureGroups.
    >>> fs.list_feature_groups(archived=True)
             name data_domain description data_source_name entity_name               creation_time modified_time               archived_time
    0  admissions       ALICE        None       admissions  admissions  2025-07-28 03:30:04.115331          None  2025-07-28 03:31:04.550000
    >>>