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    "info": {
        "author": "Abraham D. Flaxman",
        "author_email": "abie@uw.edu",
        "bugtrack_url": null,
        "classifiers": [
            "Intended Audience :: Developers",
            "Intended Audience :: Education",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)",
            "Natural Language :: English",
            "Operating System :: MacOS :: MacOS X",
            "Operating System :: Microsoft :: Windows",
            "Operating System :: POSIX",
            "Operating System :: POSIX :: BSD",
            "Operating System :: POSIX :: Linux",
            "Programming Language :: Python",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: Implementation :: CPython",
            "Topic :: Education",
            "Topic :: Scientific/Engineering",
            "Topic :: Scientific/Engineering :: Mathematics",
            "Topic :: Scientific/Engineering :: Medical Science Apps.",
            "Topic :: Software Development :: Libraries"
        ],
        "description": ".. image:: https://travis-ci.org/ihmeuw/dismod_mr.svg?branch=master\n    :target: https://travis-ci.org/ihmeuw/dismod_mr\n    :alt: Latest Version\n\n============\nIntroduction\n============\n\nThis project is the descriptive epidemiological meta-regression tool,\nDisMod-MR, which grew out of the Global Burden of Disease (GBD) Study\n2010.  DisMod-MR has been developed for the Institute of Health\nMetrics and Evaluation at the University of Washington from 2008-2013.\n\n.. contents::\n\nExamples\n--------\n\n`A motivating example: descriptive epidemiological meta-regression of Parkinson's Disease <http://nbviewer.ipython.org/github/ihmeuw/dismod_mr/blob/master/examples/pd_sim_data.ipynb>`_\n\n`All examples <http://nbviewer.ipython.org/github/ihmeuw/dismod_mr/tree/master/examples/>`_\n\nInstallation\n------------\n\nDismod MR requires PyMC2 which does not play nicely with normal Python\ninstallation tools.  Fortunately, ``conda`` has solved this issue for us.\nSo first you'll need to setup a conda environment\n(after `installing conda, if necessary <https://docs.conda.io/projects/conda/en/latest/user-guide/install/>`_)\nand install ``pymc``.  Then you can install ``dismod_mr`` using ``pip``.\n\n.. code-block:: sh\n\n   conda create --name=dismod_mr python=3.6 pymc\n   conda activate dismod_mr\n   pip install dismod_mr\n\nInstalling from source\n++++++++++++++++++++++\n\nIf you want to install ``dismod_mr`` locally in an editable mode, the\ninstructions are very similar.  We'll clone the repository and install it\nfrom a local directory instead of using ``pip`` to grab it from the Python\npackage index.\n\n.. code-block:: sh\n\n   conda create --name=dismod_mr python=3.6 pymc\n   conda activate dismod_mr\n   git clone git@github.com:ihmeuw/dismod_mr.git\n   cd dismod_mr\n   pip install -e .\n\nCoding Practices\n----------------\n\n* Write tests before code\n* Write equations before tests\n\n* Test quantitatively with simulation data\n* Test qualitatively with real data\n* Automate tests\n\n* Use a package instead of DIY\n* Test the package\n\n* Optimize code later\n* Optimize code for readability before speed\n\n* `.py` files should be short, less than 500 lines\n* Functions should be short, less than 25 lines",
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        "keywords": "",
        "license": "GNU GPLv3",
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        "name": "dismod-mr",
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