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        "author": "David Dotson",
        "author_email": "dotsdl@gmail.com",
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            "Development Status :: 4 - Beta",
            "Environment :: Console",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: BSD License",
            "Operating System :: POSIX",
            "Programming Language :: Python",
            "Topic :: Scientific/Engineering",
            "Topic :: Software Development :: Libraries :: Python Modules"
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        "description": "===========================================================\ndatreant: persistent, pythonic trees for heterogeneous data\n===========================================================\n\n|docs| |build| |cov|\n\nIn many fields of science, especially those analyzing experimental or\nsimulation data, there is often an existing ecosystem of specialized tools and \nfile formats which new tools must work around, for better or worse.\nFurthermore, centralized database solutions may be suboptimal for data\nstorage for a number of reasons, including insufficient hardware\ninfrastructure, variety and heterogeneity of raw data, the need for data\nportability, etc. This is particularly the case for fields centered around\nsimulation: simulation systems can vary widely in size, composition, rules,\nparamaters, and starting conditions. And with increases in computational power,\nit is often necessary to store intermediate results obtained from large amounts\nof simulation data so it can be accessed and explored interactively.\n\nThese problems make data management difficult, and serve as a barrier to\nanswering scientific questions. To make things easier, **datreant** is a Python\npackage that addresses the tedious and time-consuming logistics of intermediate\ndata storage and retrieval. It solves a boring problem, so we can focus on\ninteresting ones.\n\nFor more information on what **datreant** is and what it does, check out the\n`official documentation`_.\n\n.. _`official documentation`: http://datreant.readthedocs.org/\n\nGetting datreant\n================\nSee the `installation instructions`_ for installation details.\nThe package itself is pure Python.\n\nIf you want to work on the code, either for yourself or to contribute back to\nthe project, clone the repository to your local machine with::\n\n    git clone https://github.com/datreant/datreant.git\n\n.. _`installation instructions`: http://datreant.readthedocs.org/en/develop/install.html\n\nContributing\n============\nThis project is still under heavy development, and there are certainly rough\nedges and bugs. Issues and pull requests welcome! \n\nCheck out our `contributor's guide`_ to learn how to get started with\ncontributing back.\n\n.. _`contributor's guide`: http://datreant.readthedocs.org/en/develop/contributing.html\n\n.. |docs| image:: https://readthedocs.org/projects/datreant/badge/?version=develop\n    :alt: Documentation Status\n    :scale: 100%\n    :target: http://datreant.readthedocs.org/en/develop/?badge=develop\n\n.. |build| image:: https://travis-ci.org/datreant/datreant.svg?branch=develop\n    :alt: Build Status\n    :target: https://travis-ci.org/datreant/datreant\n\n.. |cov| image:: http://codecov.io/github/datreant/datreant/coverage.svg?branch=develop\n    :alt: Code Coverage\n    :scale: 100%\n    :target: http://codecov.io/github/datreant/datreant?branch=develop\n\n\n\n",
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