delete_feature_process() | FeatureStore Delete Method | Teradata Package for Python - delete_feature_process() - 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
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nvi1706202040305.ditamap
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plt1683835213376.ditaval
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dita:id
rkb1531260709148
Product Category
Teradata Vantage

Use the delete_feature_process() method to delete the archived feature process from feature store with the given process_id.

One feature can be ingested by multiple processes. If feature associated with process process_id is also ingested by other processes, the delete_feature_process() function only deletes the feature values associated with the process process_id. Else it deletes the feature values from the feature catalog. Look at FeatureCatalog.delete_features() for more details.

Required Parameter

process_id
Specifies the ID of the FeatureProcess to delete from repository.

Example setup

>>> load_example_data('dataframe', ['sales'])

Create a teradataml DataFrame.

>>> from teradataml import DataFrame, FeatureProcess, FeatureStore
>>> df = DataFrame("sales")

Create FeatureStore for repo 'repo'.

>>> fs = FeatureStore("repo", data_domain='sales')
Repo repo does not exist. Run FeatureStore.setup() to create the repo and setup FeatureStore.

Set up FeatureStore for this repository.

>>> fs.setup()
True

Run FeatureProcess to ingest features.

>>> from teradataml import FeatureProcess
>>> fp = FeatureProcess(repo='repo',
...                     data_domain='sales',
...                     object=df,
...                     entity='accounts',
...                     features=['Jan', 'Feb', 'Mar', 'Apr'])
>>> fp.run()
Process '2a014f2d-6b71-11f0-aeda-f020ffe7fe09' started.
Process '2a014f2d-6b71-11f0-aeda-f020ffe7fe09' completed.

List the available feature processes.

>>> fs.list_feature_processes()
                                     description data_domain       process_type data_source entity_id       feature_names feature_ids                     valid_start                       valid_end
process_id                                                                                                                                                                                          
2a014f2d-6b71-11f0-aeda-f020ffe7fe09                   sales  denormalized view     "sales"  accounts  Apr, Feb, Jan, Mar        None  2025-07-28 05:10:34.760000+00:  9999-12-31 23:59:59.999999+00:

Example 1: Archive the FeatureProcess with process_id '2a014f2d-6b71-11f0-aeda-f020ffe7fe09'

>>> fs.archive_feature_process("2a014f2d-6b71-11f0-aeda-f020ffe7fe09")
Feature 'Jan' is archived from table 'FS_T_a38baff6_821b_3bb7_0850_827fe5372e31'.
Feature 'Jan' is archived from metadata.
Feature 'Feb' is archived from table 'FS_T_6003dc24_375e_7fd6_46f0_eeb868305c4a'.
Feature 'Feb' is archived from metadata.
Feature 'Mar' is archived from table 'FS_T_a38baff6_821b_3bb7_0850_827fe5372e31'.
Feature 'Mar' is archived from metadata.
Feature 'Apr' is archived from table 'FS_T_a38baff6_821b_3bb7_0850_827fe5372e31'.
Feature 'Apr' is archived from metadata.
FeatureProcess with process id '2a014f2d-6b71-11f0-aeda-f020ffe7fe09' is archived.
True

Example 2: Delete the FeatureProcess with process_id '2a014f2d-6b71-11f0-aeda-f020ffe7fe09'

>>> fs.delete_feature_process('2a014f2d-6b71-11f0-aeda-f020ffe7fe09')
Feature 'Feb' deleted successfully from table 'FS_T_e84ff803_3d5c_4793_cd72_251c780fffe4'.
Feature 'Jan' deleted successfully from table 'FS_T_918e1cb4_c6bc_6d38_634d_7b9fe53e2a63'.
Feature 'Mar' deleted successfully from table 'FS_T_918e1cb4_c6bc_6d38_634d_7b9fe53e2a63'.
Feature 'Apr' deleted successfully from table 'FS_T_918e1cb4_c6bc_6d38_634d_7b9fe53e2a63'.
FeatureProcess with process_id '2a014f2d-6b71-11f0-aeda-f020ffe7fe09' is deleted.
True

List the available feature processes after delete.

>>> fs.list_feature_processes()
Empty DataFrame
Columns: [description, data_domain, process_type, data_source, entity_id, feature_names, feature_ids, valid_start, valid_end]
Index: []