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    "info": {
        "author": "Zofia Kochutek, \u0141ukasz Kleczaj, Marek Kochanowski",
        "author_email": "support@maisie.dev",
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            "Natural Language :: English",
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            "Programming Language :: Python",
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            "Programming Language :: Python :: 3.8",
            "Programming Language :: Python :: 3 :: Only",
            "Topic :: Communications :: File Sharing",
            "Topic :: Scientific/Engineering",
            "Topic :: Scientific/Engineering :: Artificial Intelligence",
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        "description": "Maisie - ML Models Management System\n####################################\n\n.. |RTFD_BADGE| image:: https://img.shields.io/readthedocs/maisie.svg\n    :alt: Read the Docs Badge\n\n.. |PyPI_Badge| image:: https://img.shields.io/pypi/v/Maisie.svg\n    :alt: PyPI Badge\n\n.. |AzureMaisie_Badge| image:: https://img.shields.io/azure-devops/build/maisie-dev/7e500d81-c7bf-42fc-87ca-e58e58dad4ee/1/master.svg\n    :alt: Azure DevOps Badge\n\n.. |AzureMaisieDev_Badge| image:: https://img.shields.io/azure-devops/build/maisie-dev/7e500d81-c7bf-42fc-87ca-e58e58dad4ee/1/develop.svg\n    :alt: Azure DevOps Badge\n\n.. |AzureSphinxTheme_Badge| image:: \n    https://img.shields.io/azure-devops/build/maisie-dev/7e500d81-c7bf-42fc-87ca-e58e58dad4ee/2.svg\n    :alt: Azure DevOps Badge\n\n.. |DockerHub_Badge| image:: https://img.shields.io/docker/pulls/maisiedev/maisie.svg\n    :alt: DockerHub Pulls Badge\n\n+------------------------------------------------------------------------------+--------------------------+\n| `Maisie (stable) <https://dev.azure.com/maisie/Maisie/_build>`_              | |AzureMaisie_Badge|      |\n+------------------------------------------------------------------------------+--------------------------+\n| `Maisie (development) <https://dev.azure.com/maisie/Maisie/_build>`_         | |AzureMaisieDev_Badge|   |\n+------------------------------------------------------------------------------+--------------------------+\n| `Maisie Sphinx Theme <https://github.com/maisie-dev/maisie-sphinx-theme>`_   | |AzureSphinxTheme_Badge| |\n+------------------------------------------------------------------------------+--------------------------+\n| `Documentation <https://docs.maisie.dev>`_                                   | |RTFD_BADGE|             |\n+------------------------------------------------------------------------------+--------------------------+\n| `PyPI <https://pypi.org/project/Maisie/>`_                                   | |PyPI_Badge|             |  \n+------------------------------------------------------------------------------+--------------------------+\n| `DockerHub <https://hub.docker.com/r/maisiedev/maisie>`_                     | |DockerHub_Badge|        |\n+------------------------------------------------------------------------------+--------------------------+\n\n.. contents:: \\\n\n.. section-numbering::\n\n\nFeatures\n========\n\nCould archiving, storing, managing and organizing machine learning models be done efficiently and with great focus on user experience? Sure, Maisie does just that. \n\nMaisie is a friendly, easy to use assistant that consists of:\n\n- Web Application written in React\n- Backend API written in Python, Flask\n- Client Application/Package written in Python and hosted on PyPI\n\nIt integrates seamlessly with your favorite tools and provides you with all the important data, such as:\n\n- Git revisions for all trained models, as well as information about source branches\n- Searchable, filterable hyperparameters, parameters and metrics\n- A single identifying dataset name, as well as an optional description\n- Permanent URLs for easy sharing and downloading of stored models\n\nInstalling\n==========\n\nYou can get the most current package from `PyPI <https://pypi.org/project/Maisie/>`_\n\n.. code-block:: bash\n\n    $ pip install Maisie\n\nUsing it in your training environment is fairly straightforward:\n\n.. code-block:: python\n\n    import maisie\n    from sklearn.externals import joblib\n\n    # Define your model here\n\n    model.fit(X, y)\n    model_filename = \"example_model.pkl\"\n    joblib.dump(model, model_filename)\n\n    # Define your metrics, fetch parameters and hyperparameters\n\n    models = maisie.Models()\n    models.upload(\n        name=\"My first uploaded model\",\n        filename=model_filename,\n        dataset_name=\"Singly Identifying Dataset Name\",\n        metrics={\"accuracy\": accuracy},\n        hyperparameters=hyperparameters,\n        parameters=parameters,\n    )\n\nDeploying\n=========\n\nUsing docker-compose\n--------------------\n\nThis repository provides a pre-configured ``docker-compose.yml`` file that contains sensible default options. \n\nBefore starting the containers, you should create a local ``.env`` file using the included ``.env.sample``.\n\nTo start up all services, run:\n\n.. code-block:: bash\n\n    $ docker-compose up\n\nTo stop your services, you can press Ctrl+C/Ctrl+D. If you started the services in the background using  ``docker-compose up -d``, the correct way to do this would be:\n\n.. code-block:: bash\n\n    $ docker-compose stop\n\nYou can learn more about Docker Compose by `clicking here <https://docs.docker.com/compose/>`_.\n\nFetching individual images\n--------------------------\n\nBoth frontend and backend images are automatically published to `Docker Hub <https://hub.docker.com>`_ as soon as new stable release is made available.\n\nLinks\n\n- `Frontend image on Docker Hub <https://hub.docker.com/r/kochanowski/maisie>`_\n- `Backend image on Docker Hub <https://hub.docker.com/r/kochanowski/maisie>`_\n- ...other services\n\nFor reference, you can look at the `sample Ansible playbook <#>`_ that deploys all containers to a specified host using the locally configured ``.env`` file.\n\nContributing\n============\n\nGetting started\n---------------\n\n1. Clone the repository from the ``develop`` branch\n\n.. code-block:: bash\n\n    $ git clone -b develop git@github.com:nokia-wroclaw/innovativeproject-ml-models-management.git\n\n2. Install `pre-commit <https://pre-commit.com/#install>`_\n\n3. Inside the project's root directory install all required githooks:\n\n.. code-block:: bash\n\n    $ pre-commit install\n\n4. To start all required services for local development, run:\n\n.. code-block:: bash\n\n    $ docker-compose up\n\n5. You're all set up!\n\nFixing existing issues\n----------------------\n\n1. Pick one of the `open issues <https://github.com/nokia-wroclaw/innovativeproject-ml-models-management/issues>`_ or `create a new one <https://github.com/nokia-wroclaw/innovativeproject-ml-models-management/issues/new>`_\n\n2. Create a new branch named ``issue-[number]-[short description]`` derived from the ``develop`` branch, for example\n\n.. code-block:: bash\n\n    $ git checkout -b issue-42-project-removal-permissions develop\n\n3. Make sure your implementation fixes the actual problem and is well tested. \n\nImplementing new features\n-------------------------\n\nWhen implementing new features, you should start by creating a new branch named ``feature-[short description]`` derived from the ``develop`` branch, for example\n\n.. code-block:: bash\n\n    $ git checkout -b feature-new-user-profile develop\n\n\nCommiting the changes\n---------------------\n\nTo run all tests and check whether all required pre-commit githooks are satisfied, run \n\n.. code-block:: bash\n\n    $ pre-commit run --all-files\n\nYour commit message should briefly summarize the changes (if possible) in plain English. To learn how to write a proper commit message, check out `this article <https://juffalow.com/other/write-good-git-commit-message>`_.\n\nWhen ready, create a new pull request compared with the ``develop`` branch set as a base branch.\n\nDocumentation\n=============\n\nFor the lastest stable release, the documentation can be seen at `docs.maisie.dev <https://docs.maisie.dev>`_.\n\n\n",
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