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        "author": "Katharine Jarmul",
        "author_email": "katharine@kjamistan.com",
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            "Development Status :: 2 - Pre-Alpha",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: BSD License",
            "Natural Language :: English",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.4",
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        "description": "========\ndatafuzz\n========\n\n\n.. image:: https://img.shields.io/pypi/v/datafuzz.svg\n        :target: https://pypi.python.org/pypi/datafuzz\n\n.. image:: https://img.shields.io/travis/kjam/datafuzz.svg\n        :target: https://travis-ci.org/kjam/datafuzz\n\n.. image:: https://readthedocs.org/projects/datafuzz/badge/?version=latest\n        :target: https://datafuzz.readthedocs.io/en/latest/?badge=latest\n        :alt: Documentation Status\n\n.. image:: https://pyup.io/repos/github/kjam/datafuzz/shield.svg\n     :target: https://pyup.io/repos/github/kjam/datafuzz/\n     :alt: Updates\n\n\nA data-science library built for testing cleaning, schema validation and model robustness. Datafuzz messes up your data so you can test things before they go wrong in production.\n\n* Free software: BSD license\n* Documentation: https://datafuzz.readthedocs.io.\n\n\nFeatures\n--------\n\n* Transform your data by adding noise to a subset of your rows\n* Duplicate data to test your duplication handling\n* Generate synthetic data for use in your testing suite\n* Insert random \"dumb\" fuzzing strategies to see how your tools cope with bad data\n* Seamlessly handle normal input and output types including CSVs, JSON, SQL, numpy and pandas\n\n\nInstallation\n------------\n\nInstall datafuzz by running::\n\n    $ pip install datafuzz\n\nRecommended use is with a proper Virtual Environment (learn more about `virtual environments <http://docs.python-guide.org/en/latest/dev/virtualenvs/>`).\n\nFor more details see :doc:`/installation`\n\nContribute\n----------\n\n- Issue Tracker: https://github.com/kjam/datafuzz/issues\n- Source Code: https://github.com/kjam/datafuzz\n\nSupport\n-------\n\nIf you are having issues, please let reach out via the Repository issues.\n\nLicense\n-------\n\nThe project is licensed under the BSD license.\n\nCredits\n---------\n\nThis package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.\n\n\n\n.. _Cookiecutter: https://github.com/audreyr/cookiecutter\n.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage\n\n\n\n=======\nHistory\n=======\n\n0.1.0 (2017-09-13)\n------------------\n\n* First release on PyPI.\n",
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