Teradata Package for Python Function Reference on VantageCloud Lake - delete_data_source - 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 on VantageCloud Lake
- Deployment
- VantageCloud
- Edition
- Lake
- Product
- Teradata Package for Python
- Release Number
- 20.00.00.03
- Published
- December 2024
- ft:locale
- en-US
- ft:lastEdition
- 2024-12-19
- dita:id
- TeradataPython_FxRef_Lake_2000
- Product Category
- Teradata Vantage
- teradataml.store.feature_store.feature_store.FeatureStore.delete_data_source = delete_data_source(self, data_source)
- DESCRIPTION:
Removes the archived DataSource from repository.
PARAMETERS:
data_source:
Required Argument.
Specifies either the name of DataSource or Object of DataSource
to remove from repository.
Types: str OR DataSource
RETURNS:
bool.
RAISES:
TeradataMLException, TypeError, ValueError
EXAMPLES:
>>> from teradataml import DataFrame, DataSource, FeatureStore, load_example_data
>>> load_example_data('dataframe', ['sales'])
# Create teradataml DataFrame.
>>> df = DataFrame("sales")
# Create DataSource with source as teradataml DataFrame.
>>> ds = DataSource(name="sales_data", source=df)
# # Create FeatureStore for repo 'vfs_v1'.
>>> fs = FeatureStore("vfs_v1")
# Apply the DataSource to FeatureStore.
>>> fs.apply(ds)
True
# Let's first archive the DataSource.
>>> fs.archive_data_source("sales_data")
DataSource 'sales_data' is archived.
True
# Delete DataSource with name "sales_data".
>>> fs.delete_data_source("sales_data")
DataSource 'sales_data' is deleted.
True
>>>