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            "License :: OSI Approved :: MIT License",
            "Natural Language :: English",
            "Programming Language :: Python :: 3",
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            "Topic :: Software Development :: Libraries :: Python Modules",
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        "description": "<h3 align=\"center\">\n  <img src=\"https://raw.githubusercontent.com/maxhumber/mummify/master/images/mummify.png\" width=\"200px\" alt=\"chart\">\n</h3>\n<p align=\"center\">\n  <a href=\"https://github.com/maxhumber/gazpacho/blob/master/setup.py\"><img alt=\"Dependencies\" src=\"https://img.shields.io/badge/dependencies-zero-blueviolet\"></a>\n  <a href=\"https://travis-ci.org/maxhumber/mummify\"><img alt=\"Travis\" src=\"https://img.shields.io/travis/maxhumber/mummify.svg\"></a>\n  <a href=\"https://pypi.python.org/pypi/mummify\"><img alt=\"PyPI\" src=\"https://img.shields.io/pypi/v/mummify.svg\"></a>\n  <a href=\"https://pepy.tech/project/mummify\"><img alt=\"Downloads\" src=\"https://pepy.tech/badge/mummify\"></a>  \n</p>\n\n#### About\n\nmummify makes model prototyping faster. The package automagically takes care of git and logging for your machine learning project so that you can focus on what's important.\n\n#### Functions\n\nmummify is one function and two command line tools:\n\n- `log` - to automatically log and commit model changes\n- `mummify history` - to view those changes\n- `mummify switch` - to go back to a different version of your model\n\n#### Usage\n\nmummify is simple to use. Just add `import mummify` at the top and `mummify.log(<string>)` at the bottom of your model:\n\n```python\nimport mummify\n\nfrom sklearn.datasets import load_wine\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.neighbors import KNeighborsClassifier\n\ndata = load_wine()\ny = data.target\nX = data.data\n\nX_train, X_test, y_train, y_test = train_test_split(\n    X, y, test_size=0.2, random_state=42)\n\nmodel = KNeighborsClassifier()\nmodel.fit(X_train, y_train)\naccuracy = model.score(X_test, y_test)\n\nmummify.log(f'Test accuracy: {accuracy:.3f}')\n```\n\nWhen you run your model (`python model.py`) for the first time mummify will create a protected `.mummify ` git folder and will start to log messages to a `mummify.log` file.\n\nWhen you make changes and run everything again:\n\n```python\n...\nmodel = LogisticRegression()\nmodel.fit(X_train, y_train)\naccuracy = model.score(X_test, y_test)\n\nmummify.log(f'Test accuracy: {accuracy:.3f}')\n```\n\nmummify will update the `mummify.log` file and save a snapshot of your working directory.\n\nTo view the history of your model, just run  `mummify history` from the command line:\n\n```sh\nmax$ mummify history\n\n*  HEAD mummify-3d15c7c2\n*  mummify-2d234a8a\n*  mummify-1fad5388\n*  mummify-root\n```\n\nAnd to go back to a previous snapshot of your model just grab the mummify id from the `mummify.log` file and run `mummify switch <id>` from the command line:\n\n```sh\nmax$ mummify switch mummify-2d234a8a\n```\n\nmummify will preserve all state history during and after a switch and keep the `mummify.log` file intact.\n\n#### Installation\n\n```sh\npip install mummify\n```\n\n#### Contribute\n\nFor feature requests or bug reports, please use [Github Issues](https://github.com/maxhumber/chart/issues)",
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