Teradata Package for Python Function Reference | 20.00 - delete_feature_process - Teradata Package for Python - Look here for syntax, methods and examples for the functions included in the Teradata Package for Python.
Teradata® Package for Python Function Reference - 20.00
- Deployment
- VantageCloud
- VantageCore
- Edition
- VMware
- Enterprise
- IntelliFlex
- Product
- Teradata Package for Python
- Release Number
- 20.00.00.11
- Published
- August 2026
- ft:locale
- en-US
- ft:lastEdition
- 2026-08-13
- dita:id
- TeradataPython_FxRef_Enterprise_2000
- Product Category
- Teradata Vantage
- teradataml.store.feature_store.feature_store.FeatureStore.delete_feature_process = delete_feature_process(self, process_id)
- DESCRIPTION:
Deletes the archived feature process from feature store with the given process_id.
Notes:
* One feature can be ingested by multiple processes. If feature associated with
process "process_id" is also ingested by other processes, then "delete_feature_process()"
function only deletes the feature values associated with the process "process_id". Else
it deletes the feature from the feature catalog. Look at 'FeatureCatalog.delete_features()'
for more details.
PARAMETERS:
process_id:
Required Argument.
Specifies the ID of the FeatureProcess to delete from repository.
Types: str
RETURNS:
bool
RAISES:
TeradataMLException, TypeError, ValueError
EXAMPLES:
>>> 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.
# Setup 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 FeatureProcesses.
>>> 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: 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: 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 FeatureProcesses 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: []