setup.py

from setuptools import setup, find_packages

setup(
    name='rasterfairy',

    # Versions should comply with PEP440.  For a discussion on single-sourcing
    # the version across setup.py and the project code, see
    # https://packaging.python.org/en/latest/single_source_version.html
    version='1.0.4',

    description='Transform a 2D point cloud into a regular raster',
    long_description="Transform any kind of 2D point cloud into a regular raster whilst trying to preserve the neighborhood relations that were present in the original cloud. A typical use case is if you have a similarity clustering of images and want to show the images in a regular table structure.",

    # The project's main homepage.
    url='https://github.com/quasimondo/RasterFairy',

    # Author details
    author='Mario Klingemann',
    author_email='quasimondo@gmail.com',

    # Choose your license
    license='GNU GPL v3',

    # See https://pypi.python.org/pypi?%3Aaction=list_classifiers
    classifiers=[
        # How mature is this project? Common values are
        #   3 - Alpha
        #   4 - Beta
        #   5 - Production/Stable
        'Development Status :: 3 - Alpha',

        # Indicate who your project is intended for
        'Intended Audience :: Developers',
        'Topic :: Software Development :: Build Tools',

        # Pick your license as you wish (should match "license" above)
        'License :: OSI Approved :: GNU GPL v3 License',

        # Specify the Python versions you support here. In particular, ensure
        # that you indicate whether you support Python 2, Python 3 or both.
        'Programming Language :: Python :: 2',
        'Programming Language :: Python :: 2.6',
        'Programming Language :: Python :: 2.7',
        'Programming Language :: Python :: 3',
        'Programming Language :: Python :: 3.3',
        'Programming Language :: Python :: 3.4',
        'Programming Language :: Python :: 3.5',
    ],

    # What does your project relate to?
    keywords='machine-learning raster assignment',

    # You can just specify the packages manually here if your project is
    # simple. Or you can use find_packages().
    packages=find_packages(exclude=['contrib', 'docs', 'tests', 'examples']),

    # Alternatively, if you want to distribute just a my_module.py, uncomment
    # this:
    #   py_modules=["my_module"],

    # List run-time dependencies here.  These will be installed by pip when
    # your project is installed. For an analysis of "install_requires" vs pip's
    # requirements files see:
    # https://packaging.python.org/en/latest/requirements.html
    install_requires=[
        'numpy >= 1.8.0',
        'scipy >= 0.13.0',
        'moviepy >= 0.2.3.5',
        'ipython',
    ],

    # List additional groups of dependencies here (e.g. development
    # dependencies). You can install these using the following syntax,
    # for example:
    # $ pip install -e .[dev,test]
    extras_require={
        'dev': ['check-manifest'],
        'test': ['coverage'],
    },

    # If there are data files included in your packages that need to be
    # installed, specify them here.  If using Python 2.6 or less, then these
    # have to be included in MANIFEST.in as well.
    package_data={
        # 'sample': ['package_data.dat'],
    },

    # Although 'package_data' is the preferred approach, in some case you may
    # need to place data files outside of your packages. See:
    # http://docs.python.org/3.4/distutils/setupscript.html#installing-additional-files # noqa
    # In this case, 'data_file' will be installed into '<sys.prefix>/my_data'
    data_files=[
        # ('my_data', ['data/data_file'])
    ],

    # To provide executable scripts, use entry points in preference to the
    # "scripts" keyword. Entry points provide cross-platform support and allow
    # pip to create the appropriate form of executable for the target platform.
    # entry_points={
    #    'console_scripts': [
    #        'sample=sample:main',
    #    ],
    # },
)