Use the lists_entities() method to list the available entities along with the associated dataset.
There are no parameters for this function.
Example setup
Upload features first to create a dataset.
>>> from teradataml import load_example_data, FeatureProcess
>>> load_example_data('dataframe', 'sales')
>>> df = DataFrame("sales")
Create a feature store.
>>> fs = FeatureStore(repo='vfs_v1', data_domain='sales')
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
Run FeatureProcess to ingest features.
>>> fp = FeatureProcess(repo='vfs_v1', data_domain='sales', object=df, entity='accounts', ... features=['Jan', 'Feb', 'Mar', 'Apr'])
Build a dataset.
>>> from teradataml import DatasetCatalog
>>> dc = DatasetCatalog(repo='vfs_v1', data_domain='sales')
>>> dataset = dc.build_dataset(entity='accounts',
... selected_features = {
... 'Jan': fp.process_id,
... 'Feb': fp.process_id},
... view_name='ds_jan_feb',
... description='Dataset with Jan and Feb features')
Example: List entities
>>> dc.list_entities()
data_domain name entity_name description id 201bb332-dcb3-4fe1-9a7d-d575b36c8790 sales ds_jan_feb accounts Dataset with Jan and Feb features