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        "author": "Gil Megidish, Vincenzo Di Massa and FutureLinkCorporation",
        "author_email": "gil@megidish.net & hawk.it@tiscali,it and devel@futurelinkcorporation.com",
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        "classifiers": [
            "Development Status :: 4 - Beta",
            "License :: OSI Approved :: GNU Lesser General Public License v2 or later (LGPLv2+)",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3.3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Topic :: Scientific/Engineering :: Artificial Intelligence"
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        "description": "======\nREADME\n======\n\n\nfann2\n=====\n\nPython bindings for Fast Artificial Neural Networks 2.2.0 (FANN >= 2.2.0). These\nare the original python bindings included with FANN 2.1.0 beta and updated to\ninclude support for python 2.6-3.6.\n\n\nDESCRIPTION\n===========\n\nThis is a python binding for Fast Artificial Neural Network Library (FANN >=\n2.2.0) that implements multi-layer artificial neural networks with support for\nboth fully-connected and sparsely-connected networks. It includes a framework\nfor easily handling training data sets. It is easy to use, versatile, well-\ndocumented, and fast.\n\nFANN 2.2.0 source\n-----------------\n\n- http://sourceforge.net/projects/fann/files/fann/2.2.0/FANN-2.2.0-Source.zip/download\n\n\nINSTALLATION\n============\n\nYou can install fann2 from pkgsrc or from pypi, using either pip or\neasy_install:\n\nwheels\n------\n\n    $ pip install ${wheel_file}\n\n\npypi\n----\n\n\n    $ pip install fann2\n    \n\nor\n\n\n    $ easy_install fann2\n\npkgsrc\n------\n\n\nSource installation\n...................\n\nGet and install pkgsrc. See `pkgsrc documentation\n<http://pkgsrc.org/#index4h1>`_. for platform-specific information.\n\ncd ${PKGSRCDIR}/devel/py-fann2\n\nbmake install\n\n\nFrom binaries\n.............\n\nGet and install pkgsrc. See `pkgsrc quickstart\n<http://pkgsrc.org/#index1h1>`_. for platform-specific information.\n\npkgin -y install py-fann2\n\nWindows considerations\n----------------------\n\nSource installation\n...................\n\n- Install Visual C++ Build Tools;\n- Install `FANN source code <https://github.com/libfann/fann>`_, using cmake;\n- Copy \"fanndouble.lib\" from FANN installed files to ${python_libs_directory} as \"doublefann.lib\";\n- Install swig for Windows (you will need to set an Enviroment Variable for \"swig.exe\");\n- Run > python setup.py install from PowerShell/Command Prompt.\n\nUSAGE\n=====\nJust \n\n\n    >> from fann2 import libfann \n\n\nand then create libfann.neural_net and libfann.training_data objects\n\n\n    >> ann = libfann.neural_net()\n    \n    >> train_data = libfann.training_data()\n\n\nLook at the examples in the FANN documentation and its C++ bindings for further\nreference.\n\n\nLICENSE\n=======\n\nAs with the original python bindings, this package is distributed under the\nterms of the GNU Lesser General Public License, Version 2.1. See LICENSE for\nfull terms and conditions.\n\n\nLINKS\n=====\n\n`fann2 on pypi\n<https://pypi.python.org/pypi/fann2>`_.\n\n`py-fann2 in pkgsrc\n<http://pkgsrc.se/devel/py-fann2>`_.\n\n`FANN\n<http://leenissen.dk/fann/>`_.\n\n`pkgsrc\n<http://pkgsrc.org/>`_.\n\n\nCONTACT\n=======\n\nSend us your patches and pull requests! We will release as often as these\nchanges are received and integrated. There's no reason to have countless\nbranches of this package. Consider this the official one and that it's being\nmaintained!\n\nThe pkgsrc package is maintained by us as well. We are active users of FANN and\nfann2. If you don't have or want a github account, send your patches for this\npackage or the pkgsrc version to pkgsrc@futurelinkcorporation.com.",
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