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: []