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

Use the list_features() method to list all the features in the repository.

Optional Parameter

archived

Specifies whether to list effective features or archived features. When set to False, effective features in FeatureStore are listed, otherwise, archived features are listed.

Default value: False.

Example setup

>>> from teradataml import DataFrame, FeatureStore, load_example_data

Create teradataml DataFrame.

>>> load_example_data("dataframe", "sales")
>>> df = DataFrame("sales")

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 teradataml DataFrame.

>>> fg = FeatureGroup.from_DataFrame(name='sales',
...                                  entity_columns='accounts',
...                                  df=df,
...                                  timestamp_column='datetime')

Apply the FeatureGroup to FeatureStore.

>>> fs.apply(fg)

True

Example 1: List all the effective Features in the repo 'vfs_v1'

>>> fs.list_features()

                id column_name description  tags data_type feature_type  status               creation_time modified_time group_name
name data_domain                                                                                                                     
Apr  ALICE         4         Apr        None  None    BIGINT   CONTINUOUS  ACTIVE  2025-07-28 03:17:31.262501          None      sales
Jan  ALICE         2         Jan        None  None    BIGINT   CONTINUOUS  ACTIVE  2025-07-28 03:17:30.056273          None      sales
Mar  ALICE         3         Mar        None  None    BIGINT   CONTINUOUS  ACTIVE  2025-07-28 03:17:30.678060          None      sales
Feb  ALICE         1         Feb        None  None     FLOAT   CONTINUOUS  ACTIVE  2025-07-28 03:17:29.403242          None      sales

Example 2: List all the archived Features in the repo 'vfs_v1'

Feature can only be archived when it is not associated with any Group.

Remove Feature 'Feb' from FeatureGroup.

>>> fg.remove_feature(fs.get_feature('Feb'))

True

Apply the modified FeatureGroup to FeatureStore.

>>> fs.apply(fg)

True

Archive Feature 'Feb'.

>>> fs.archive_feature('Feb')

True

List all the archived Features in the repo 'vfs_v1'.

>>> fs.list_features(archived=True)

   id name data_domain column_name description  tags data_type feature_type  status               creation_time modified_time               archived_time group_name
0   1  Feb       ALICE         Feb        None  None     FLOAT   CONTINUOUS  ACTIVE  2025-07-28 03:17:29.403242          None  2025-07-28 03:19:58.950000      sales