Use the list_entities() method to list all the entities.
Optional Parameter
- archived
- Specifies whether to list effective entities or archived entities.
Default value: False
Example setup
>>> from teradataml import DataFrame, FeatureStore, load_example_data
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 teradataml DataFrame.
>>> load_example_data("dataframe", "sales")
>>> df = DataFrame("sales")
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 Entities in the repo 'vfs_v1'
>>> fs.list_entities()
description creation_time modified_time entity_column name data_domain sales ALICE None 2025-07-28 03:17:31.558796 2025-07-28 03:19:41.233953 accounts
Example 2: List all the archived Entities in the repo 'vfs_v1'
Entity cannot be archived if it is a part of FeatureGroup. First, create another Entity, and update FeatureGroup with other Entity. Then archive Entity 'sales'.
>>> entity = Entity('store_sales', columns=df.accounts)
Update new entity to FeatureGroup.
>>> fg.apply(entity)
True
Update FeatureGroup to FeatureStore. This will update Entity from 'sales' to 'store_sales' for FeatureGroup 'sales'.
>>> fs.apply(fg)
True
Archive Entity 'sales' since it is not part of any FeatureGroup.
>>> fs.archive_entity('sales')
Entity 'sales' is archived. True
List the archived entities.
>>> fs.list_entities(archived=True)
description creation_time modified_time entity_column name data_domain store_sales ALICE None 2025-07-28 03:23:40.322424 None accounts