setup.py

from setuptools import setup, find_packages  # Always prefer setuptools over distutils
from codecs import open  # To use a consistent encoding
from os import path
import filterpy

here = path.abspath('..')


# Get the long description from the relevant file
with open(path.join(here, 'README.rst'), encoding='utf-8') as f:
    long_description = f.read()

setup(
    name='filterpy',

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

    description='Kalman filtering and optimal estimation library',
    long_description=long_description,

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

    # Author details
    author='Roger Labbe',
    author_email='[email protected]',

    # Choose your license
    license='MIT',

    # 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 :: 4 - Beta',

        # Indicate who your project is intended for
        'Intended Audience :: Developers',
        'Intended Audience :: Education',
        'Intended Audience :: Science/Research',
        'Topic :: Scientific/Engineering',
        'Topic :: Scientific/Engineering :: Mathematics',
        'Topic :: Scientific/Engineering :: Physics',
        'Topic :: Utilities',


        # Pick your license as you wish (should match "license" above)
        'License :: OSI Approved :: MIT 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 :: 3.2',
        'Programming Language :: Python :: 3.3',
        'Programming Language :: Python :: 3.4',
    ],

    # What does your project relate to?
    keywords='Kalman filters filtering optimal estimation tracking',

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

    # 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/technical.html#install-requires-vs-requirements-files
    install_requires=['numpy', 'scipy', 'matplotlib'],

    # 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={
        'filterpy': ['README.rst', 'changelog.txt', 'LICENSE.txt'],
    },

    # 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
    # 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',
    #    ],
    #},
)