Teradata Package for Python Function Reference on VantageCloud Lake - archive_entity - 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.archive_entity = archive_entity(self, entity)
- DESCRIPTION:
Archives Entity from repository. Note that archived Entity
is not available for any further processing. Archived Entity can be
viewed using "list_archived_entities()" method.
PARAMETERS:
entity:
Required Argument.
Specifies either the name of Entity or Object of Entity
to remove from repository.
Types: str OR Entity
RETURNS:
bool.
RAISES:
TeradataMLException, TypeError, ValueError
EXAMPLES:
>>> from teradataml import DataFrame, Entity, FeatureStore
>>> load_example_data('dataframe', ['sales'])
# Create teradataml DataFrame.
>>> df = DataFrame("sales")
# Create Entity using teradataml DataFrame Column.
>>> entity = Entity(name="sales_data", columns=df.accounts)
# Create FeatureStore for repo 'staging_repo'.
>>> fs = FeatureStore("staging_repo")
# Apply the entity to FeatureStore.
>>> fs.apply(entity)
True
# List all the available entities.
>>> fs.list_entities()
description
name entity_column
sales_data accounts None
# Archive Entity with name "sales_data".
>>> fs.archive_entity(entity=entity.name)
Entity 'sales_data' is archived.
True
# List the entities after archive.
>>> fs.list_entities()
Empty DataFrame
Columns: [description]
Index: []