setup.py

#!/usr/bin/env python
# -*- coding: utf-8 -*-

# Copyright (c) 2015 MaxPoint Interactive, Inc.
#
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without modification, are permitted provided that the
# following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following
#    disclaimer.
#
# 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following
#    disclaimer in the documentation and/or other materials provided with the distribution.
#
# 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products
#    derived from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES,
# INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF
# THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

try:
    from setuptools import setup
except ImportError:
    from distutils.core import setup


with open('README.rst') as readme_file:
    readme = readme_file.read()

with open('HISTORY.rst') as history_file:
    history = history_file.read().replace('.. :changelog:', '')

requirements = [
    "numpy", "scipy"
]

test_requirements = [
    "numpy", "scipy"
]

setup(
    name='bayes_logistic',
    version='0.2.0',
    description="Bayesian Logistic Regression using Laplace approximations to the posterior.",
    long_description=readme + '\n\n' + history,
    author="MaxPoint Interactive, Inc.",
    author_email='rob.haslinger@maxpoint.com',
    url='https://github.com/maxpoint/bayes_logistic',
    packages=[
        'bayes_logistic',
    ],
    package_dir={'bayes_logistic':
                 'bayes_logistic'},
    include_package_data=True,
    install_requires=requirements,
    license="BSD",
    zip_safe=False,
    keywords='bayes_logistic',
    classifiers=[
        'Development Status :: 4 - Beta',
        'Intended Audience :: Developers',
        'License :: OSI Approved :: BSD License',
        'Natural Language :: English',
        "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',
    ],
    test_suite='tests',
    tests_require=test_requirements
)