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Azure Machine Learning Feature Store SDK

Project description

Azure Machine Learning Feature Store Python SDK

The azureml-featurestore package is the core SDK interface for Azure ML Feature Store. This SDK works along the azure-ai-ml SDK to provide the managed feature store experience.

Main features in the azureml-featurestore package

  • Develop feature set specification in Spark with the ability for feature transformation.
  • List and get feature sets defined in Azure ML Feature Store.
  • Generate and resolve feature retrieval specification.
  • Run offline feature retrieval with point-in-time join.

Getting started

You can install the package via pip install azureml-featurestore

To learn more about Azure ML managed feature store visit https://aka.ms/featurestore-get-started

Change Log

1.2.1 (2025.09.17)

  • Fix bugs

1.2.0 (2025.08.18)

  • Improve online featurestore

1.1.2 (2025.03.27)

  • Fix bugs

1.1.1 (2025.02.25)

  • Fix logging issue

1.1.0 (2024.03.12)

New Features:

  • [Public Preview] Support for DSL (Domain Specific Language) for feature definition. The DSL is a simplified way to define feature set transformations using a declarative syntax.
    • DSL feature set supports custom source
    • DSL feature set supports temporal join lookback, source delay and source lookback
    • DSL feature set supports load from materialized store
    • get_offline_features supports feature sets with different transformations(dsl, udf or none).

1.0.1 (2023.12.28)

  • Update dependencies

1.0.0 (2023.11.14)

  • [GA] Custom feature source: Custom feature source supports customized source process code script with a user defined dictionary as input.
  • [GA] International regions and sovereign cloud support.
  • [GA] Offline backfill materialization now replaces all data within a feature window instead of doing upsert based on timestamp.
  • [GA] Added bootstrap option for materialization, which enables materializing data from offline store into online store.
  • Re-enabling materialization in a feature set now invalidates all previously materialized data.
  • Feature set spec dump now accepts a file path or a folder path as dump target, and an overwrite option to control whether to override the target.
  • Various bug fixes

0.1.0b6 (2023.11.1)

  • Various bug fixes

0.1.0b5 (2023.10.4)

  • Various bug fixes

0.1.0b4 (2023.08.28)

New Features:

  • [Public preview] Added custom feature source. Custom feature source supports customized source process code script with a user defined dictionary as input.

  • [Public preview] Added csv feature source, deltatable feature source, mltable feature source, parquet feature source as new feature source experience. Previous feature source usage compatibility will be deprecated in 6 months.

  • Bug fixes

Breaking changes:

  • Moved init_online_lookup, shutdown_online_lookup and get_online_features out of FeatureStoreClient, and into the module as standalone functions.
  • get_online_features contract changed from accepting (for the observation_data argument) and returning pandas.DataFrame to accepting (as the observation_data argument) and returning pyarrow.Table.

Other changes:

  • Moved online feature store support into public preview.

0.1.0b3 (2023.07.10)

  • Various bug fixes

0.1.0b2 (2023.06.13)

New Features:

  • [Private preview] Added online store support. Online store supports materialization and online feature values retrieval from Redis cache for batch scoring.

  • Various bug fixes

0.1.0b1 (2023.05.15)

New Features:

Initial release.

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