list_feature_groups() | FeatureStore List Method | Teradata Package for Python - list_feature_groups() - Teradata Package for Python

Use the list_feature_groups() method to list all the feature groups.

Optional Parameter

archived

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

Example setup

>>> 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.

Set up 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'

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