Metadata-Version: 2.0
Name: azureml-featurestore
Version: 1.0.0
Summary: Azure Machine Learning Feature Store SDK
Home-page: https://aka.ms/featurestore-get-started
Author: Microsoft Corporation
Author-email: azuresdkengsysadmins@microsoft.com
License: MIT License
Keywords: AzureMachineLearning,azure,feature store
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: License :: OSI Approved :: MIT License
Requires-Python: <4.0,>=3.8
Description-Content-Type: text/markdown
Requires-Dist: azure-ai-ml<2.0.0,>=1.12.0
Requires-Dist: mltable<2.0.0,>=1.5.0
Requires-Dist: jinja2<4.0.0,>=3.1.2
Requires-Dist: marshmallow<4.0.0,>=3.18.0
Provides-Extra: online
Requires-Dist: azure-identity; extra == "online"
Requires-Dist: azure-mgmt-redis<15.0.0,>=14.1.0; extra == "online"
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Requires-Dist: pyarrow>=9.0.0; extra == "online"
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Requires-Dist: azure-ai-ml (<2.0.0,>=1.12.0)
Requires-Dist: mltable (<2.0.0,>=1.5.0)
Requires-Dist: jinja2 (<4.0.0,>=3.1.2)
Requires-Dist: marshmallow (<4.0.0,>=3.18.0)
Provides-Extra: online
Requires-Dist: azure-identity; extra == 'online'
Requires-Dist: azure-mgmt-redis (<15.0.0,>=14.1.0); extra == 'online'
Requires-Dist: pandas (>=1.5.3); extra == 'online'
Requires-Dist: pyarrow (>=9.0.0); extra == 'online'
Requires-Dist: redis (>=4.5.1); extra == 'online'
Requires-Dist: msgpack (<2.0.0,>=1.0.5); extra == 'online'

# 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

## 1.0.0 (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.
