get_dataset_catalog() | FeatureStore Get Method | Teradata Package for Python - get_dataset_catalog() - Teradata Package for Python

Use the get_dataset_catalog() method to retrieve the DataCatalog based on the feature store's repo and data domain.

There are no parameters for this function.

Example setup

>>> from teradataml import FeatureStore

Example: Get the DataCatalog

Create FeatureStore for repo 'vfs_v1'.

>>> fs = FeatureStore('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

Load the sales data to the database.

>>> from teradataml import load_example_data
>>> load_example_data("dataframe", "sales")
>>> df = DataFrame("sales")

Create a feature process.

>>> from teradataml import FeatureProcess
>>> fp = FeatureProcess(repo="vfs_v1",
...                     data_domain='sales',
...                     object=df,
...                     entity="accounts",
...                     features=["Jan", "Feb", "Mar", "Apr"])
>>> fp.run()

Process '5747082b-4acb-11f0-a2d7-f020ffe7fe09' started.
Process '5747082b-4acb-11f0-a2d7-f020ffe7fe09' completed.
True

Get DatasetCatalog from FeatureStore.

>>> dc = fs.get_dataset_catalog()

Build the dataset using DatasetCatalog object.

>>> 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')

>>> dataset

     accounts    Jan    Feb
0    Blue Inc   50.0   90.0
1    Alpha Co  200.0  210.0
2   Jones LLC  150.0  200.0
3  Yellow Inc    NaN   90.0
4  Orange Inc    NaN  210.0
5     Red Inc  150.0  200.0