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

Teradata® Package for Python User Guide

Deployment
VantageCloud
VantageCore
Edition
VMware
Enterprise
IntelliFlex
Product
Teradata Package for Python
Release Number
20.00
Publication Date
March 2025
Content Type
User Guide
Publication ID
B700-4006-200K
ft:locale
en-US
ft:lastEdition
2026-08-13
dita:mapPath
nvi1706202040305.ditamap
dita:ditavalPath
plt1683835213376.ditaval
ft:sourceId
dita
dita:id
rkb1531260709148
Product Category
Teradata Vantage

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