delete_data_source() | FeatureStore Delete Method | Teradata Package for Python - delete_data_source() - Teradata Package for Python

Use the delete_data_source() method to remove the archived data source from the repository.

Required Parameter

data_source

Specifies either the name of the data source or object of the data source to remove from the repository.

Example setup

>>> from teradataml import DataFrame, DataSource, 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

Example: Delete the data source from the repository

Create a data source with source as teradataml DataFrame.

>>> ds = DataSource(name="sales_data", source=df)

Apply the data source to FeatureStore.

>>> fs.apply(ds)

True

Archive the data source.

>>> fs.archive_data_source("sales_data")

DataSource 'sales_data' is archived.
True

Delete the data source with the name "sales_data".

>>> fs.delete_data_source("sales_data")

DataSource 'sales_data' is deleted.
True

List the available data sources after delete.

>>> fs.list_data_sources()

Empty DataFrame
Columns: [description, timestamp_column, source, creation_time, modified_time]
Index: []