Example 5: Ingest feature values for a specific time using DataFrame as source - Teradata Package for Python

Teradata® Package for Python User Guide

Deployment
VantageCloud
VantageCore
Edition
VMware
Enterprise
IntelliFlex
Product
Teradata Package for Python
Release Number
20.00
Published
March 2025
ft:locale
en-US
ft:lastEdition
2025-12-05
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nvi1706202040305.ditamap
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plt1683835213376.ditaval
dita:id
rkb1531260709148
Product Category
Teradata Vantage

Example setup

>>> load_example_data('dataframe', ['sales'])
>>> df = DataFrame("sales")

Create a feature store.

>>> from teradataml import FeatureStore
>>> fs = FeatureStore("vfs_test", data_domain='sales')
Repo vfs_test does not exist. Run FeatureStore.setup() to create the repo and setup FeatureStore.
>>> fs.setup()
True

Create the FeatureProcess

>>> from datetime import datetime, timezone
>>> fp = FeatureProcess(repo="vfs_test",
...                     data_domain='sales',
...                     object=df,
...                     entity='accounts',
...                     features=['Jan', 'Feb'])

Ingest the features as of January 1, 2024

>>> fp.run(as_of='2024-01-01 00:00:00+00:00')
Process '2a5d5eee-738e-11f0-99c5-a30631e77953' started.
Process '2a5d5eee-738e-11f0-99c5-a30631e77953' completed.
True