teradataml.store.feature_store.models.Dataset.id

DESCRIPTION:
    Returns the id of the Dataset.
 
PARAMETERS:
    None
 
RETURNS:
    str
 
RAISES:
    None
 
EXAMPLES:
    >>> from teradataml import load_example_data, FeatureStore
    >>> load_example_data('dataframe', 'sales')
    >>> df = DataFrame("sales")
    
    # Create a FeatureStore.
    >>> fs = FeatureStore(repo='vfs_v1', data_domain='sales')
    Repo vfs_v1 does not exist. Run FeatureStore.setup() to create the repo and setup FeatureStore.
    >>> fs.setup()
    True
 
    # Create a FeatureProcess and ingest features on existing repo 'vfs_v1'.
    >>> from teradataml import FeatureProcess
    >>> fp = FeatureProcess(repo="vfs_v1",
    ...                     data_domain='sales',
    ...                     object=df,
    ...                     entity="accounts",
    ...                     features=["Jan", "Feb", "Mar", "Apr"])
    >>> fp.run()
    Process 'eadf3787-4ad4-11f0-8afd-f020ffe7fe09' started.
    Process 'eadf3787-4ad4-11f0-8afd-f020ffe7fe09' completed.
 
    # Build dataset.
    >>> dc = DatasetCatalog(repo='vfs_v1', data_domain='sales')
    >>> dataset = dc.build_dataset(entity='accounts',
    ...                            selected_features = {
    ...                             'Jan': 'eadf3787-4ad4-11f0-8afd-f020ffe7fe09',
    ...                             'Feb': 'eadf3787-4ad4-11f0-8afd-f020ffe7fe09'},
    ...                            view_name='ds_jan_feb',
    ...                            description='Dataset with Jan and Feb features')
 
    # List available datasets.
    >>> dc.list_datasets()
                                         data_domain        name entity_name                        description                      valid_start                       valid_end
    id                                                                                                                                                                         
    abbde025-83b3-4cd8-bb72-57c40ba68f49       sales  ds_jan_feb    accounts  Dataset with Jan and Feb features   2025-06-12 12:06:15.572420+00:  9999-12-31 23:59:59.999999+00:
 
    # Use one of the dataset IDs to create Dataset object.
    >>> ds = Dataset(repo='vfs_v1',
    ...              id='abbde025-83b3-4cd8-bb72-57c40ba68f49',
    ...              data_domain='sales')
    
    # Example: Retrieve id.
    >>> ds.id
    'abbde025-83b3-4cd8-bb72-57c40ba68f49'