Metadata-Version: 2.1
Name: shrike
Version: 1.0.0rc11
Summary: Python utilities for compliant Azure machine learning
Home-page: https://github.com/azure/shrike
Author: AML Data Science
Author-email: aml-ds@microsoft.com
License: MIT
Description: # Shrike: Compliant Azure ML Utilities
        
        [![CodeQL](https://github.com/Azure/shrike/actions/workflows/codeql-analysis.yml/badge.svg)](https://github.com/Azure/shrike/actions/workflows/codeql-analysis.yml)
        [![docs](https://github.com/Azure/shrike/actions/workflows/docs.yml/badge.svg)](https://github.com/Azure/shrike/actions/workflows/docs.yml)
        [![python](https://github.com/Azure/shrike/actions/workflows/python.yml/badge.svg)](https://github.com/Azure/shrike/actions/workflows/python.yml)
        [![Component Governance](https://dev.azure.com/msdata/Vienna/_apis/build/status/aml-ds/Azure.shrike%20Component%20Governance?branchName=main)](https://dev.azure.com/msdata/Vienna/_build/latest?definitionId=16088&branchName=main)
        [![ci-gate](https://dev.azure.com/msdata/Vienna/_apis/build/status/aml-ds/Azure.shrike%20ci-gate?branchName=main)](https://dev.azure.com/msdata/Vienna/_build/latest?definitionId=16115&branchName=main)
        [![Python versions](https://img.shields.io/badge/python-3.6+-blue.svg)](https://www.python.org/downloads/)
        [![code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
        [![codecov](https://codecov.io/gh/Azure/shrike/branch/main/graph/badge.svg?token=sSq0BKlfTu)](https://codecov.io/gh/Azure/shrike)
        [![PyPI - Downloads](https://img.shields.io/pypi/dm/shrike)](https://pypi.org/project/shrike/)
        [![PyPI version](https://badge.fury.io/py/shrike.svg)](https://badge.fury.io/py/shrike)
        [![license: MIT](https://img.shields.io/badge/License-MIT-purple.svg)](LICENSE)
        
        Compliant Machine Learning is the practice of training, validating and deploying
        machine learning models withou seeing the private data. It is needed in many
        enterprises to satsify the strict compliance and privacy guarantees that 
        they provide to their customers.
        
        The library `shrike` is a set of Python utilities for compliant machine
        learning, with a special emphasis on running pipeline in the platform of 
        [Azure Machine Learning](https://github.com/Azure/azureml-examples). This
        library mainly contains three components, that are
        
        -  `shrike.compliant_logging`: utlities for compliant logging and 
        exception handling;
        -  `shrike.pipeline`: helper code for manging, validating and submitting Azure
        Machine Learning pipelines based on 
        [azure-ml-component](https://aka.ms/azure-ml-component-reference);
        -  `shrike.build`: helper code for packaging, building, validating, signing and
        registering Azure Machine Learning components.
        
        ## Documentation
        For the full documentation of `shrike` with detailed examples and API reference, 
        please see the [docs page](http://azure.github.io/shrike).
        
        ## Installation
        
        The library `shrike` is publicly available in PyPi. There are three optional extra dependenciies - `pipeline`, `build` and `dev`, 
        among which  `pipeline` is for submitting Azure Machine Learning pipelines, `build` is for signing and registering components, 
        and `dev` is for the development environment of `shrike`.
        
        - If only the compliant-logging feature would be used, please pip install without any extras:
        ```pwsh
        pip install shrike
        ```
        - If it will be used for signing and registering components, please type with `[build]`:
        ```pwsh
        pip install shrike[build]
        ```
        - If it will be used for submitting Azure Machine Learning pipelines, please type with `[pipeline]`:
        ```pwsh
        pip install shrike[pipeline]
        ```
        - If you would like to contribute to the source code, please install with all the dependencies:
        ```pwsh
        pip install shrike[pipeline,build,dev]
        ```
        
        ## Migration from `aml-build-tooling`, `aml-ds-pipeline-contrib`, and `confidential-ml-utils`
        If you have been using "aml-build-tooling", "aml-ds-pipeline-contrib", and `confidential-ml-utils` libraries, please use the migration script ([migration.py](https://github.com/Azure/shrike/blob/main/migration.py)) to convert your repo or file and adopt the `shrike` package with one simple command:
        ```pwsh
        python migraton.py --input_path PATH/TO/YOUR/REPO/OR/FILE
        ```
        :warning: This command will update files **in-place**. Please make a copy of your repo/file if you do not want to do so.
        
        ## Need Support?
        When you have any feature requests or technical questions or find
        any bugs, please don't hesitate to file issues.
        
        - If you are Microsoft employees, please refer to the 
        [support page](https://aka.ms/aml/support) for details;
        - If you are outside Microsoft, feel free to send an email
        to [aml-ds@microsoft.com](mailto:aml-ds@microsoft.com). 
        
        
        ## Contributing
        
        This project welcomes contributions and suggestions. Most contributions require
        you to agree to a Contributor License Agreement (CLA) declaring that you have
        the right to, and actually do, grant us the rights to use your contribution.
        For details, visit https://cla.opensource.microsoft.com.
        
        When you submit a pull request, a CLA bot will automatically determine whether
        you need to provide a CLA and decorate the PR appropriately (e.g., status check,
        comment). Simply follow the instructions provided by the bot. You will only need
        to do this once across all repos using our CLA.
        
        This project has adopted the
        [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).
        For more information see the
        [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or
        contact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any
        additional questions or comments.
        
        
        ## Trademarks
        
        This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft 
        trademarks or logos is subject to and must follow 
        [Microsoft's Trademark & Brand Guidelines](https://www.microsoft.com/en-us/legal/intellectualproperty/trademarks/usage/general).
        Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship.
        Any use of third-party trademarks or logos are subject to those third-party's policies.
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Requires-Python: ~=3.6
Description-Content-Type: text/markdown
Provides-Extra: pipeline
Provides-Extra: build
Provides-Extra: dev
