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        "author": "Cory Giles",
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        "description": "==========================================\nfmio - Fast stream I/O for numeric matrices\n==========================================\n\nIf you have ever piped large CSV or TSV numeric data between\nscripts, you might realize just how much time is taken parsing\nstrings rather than performing actual computations.\n\n``fmio`` is a simple compressed, binary format and Python library\nto read and write matrices -- defined as 2D numeric data with row\nand column names, analogous to pandas DataFrames that only accept\nnumeric data.\n\nInstallation\n============\n\nThe only dependencies are numpy and pandas.\n\n.. code-block:: bash\n    $ pip install fmio\n\nUsage\n=====\n\nFrom the command-line, you can serialize and deserialize fmio\nmatrices.\n\n.. code-block:: bash\n    \n    $ fmio < in.tsv > out.fmio\n    $ fmio -dc < out.fmio\n    <same as input>\n\nThe real purpose is to perform fast reads from within Python:\n\n``run.py``\n.. code-block:: python\n\n    import fmio, sys\n    with fmio.Reader(sys.stdin) as h:\n        for r in h:\n            print(r.name, r.sum())\n\n.. code-block:: bash\n    \n    $ python run.py < out.fmio\n\nWarnings\n========\n\nThe file format is in machine-native format. Although almost all\nmodern processors are \"little-endian\", these files may not be\ncompletely portable.\n\nThe library is still in development. The file format is mostly\nstable but still subject to change. Don't use this for long-term\ndata storage.\n\nLicense\n=======\n\nAGPLv3\n",
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