Metadata-Version: 2.1
Name: shrike
Version: 1.0.0rc3
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)
        [![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.confidential_logging`: utlities for confidential logging and 
        exception handling;
        -  `shrike.pipeline`: helper code for manging, validating and submitting Azure
        Machine Learning pipelines based on 
        [azure-ml-component](https://componentsdk.z22.web.core.windows.net/index.html);
        -  `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
        To install via PyPi, please type:
        ```pwsh
        pip install shrike[pipeline,build]
        ```
        There are three optional extra dependenciies - `pipeline`, `build` and `dev`, 
        among which `dev` is for the development environment of shrike. 
        If only the confidential-logging feature would be used, please 
        just type without any extras:
        ```pwsh
        pip install shrike
        ```
        
        ## Need Support?
        When you have any feature requests or technical questions or find
        any bugs, please don't hesitate to contact the Azure ML Data Science
        Team.
        
        - 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: dev
Provides-Extra: build
Provides-Extra: pipeline
