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setup.py
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setup.py
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"""A setuptools based setup module.
See:
https://packaging.python.org/en/latest/distributing.html
https://github.com/pypa/sampleproject
"""
# Always prefer setuptools over distutils
from setuptools import setup, find_packages
# To use a consistent encoding
from codecs import open
from os import path
here = path.abspath(path.dirname(__file__))
# Get the long description from the relevant file
with open(path.join(here, 'DESCRIPTION.rst'), encoding='utf-8') as f:
long_description = f.read()
setup(
name='nba_py',
# 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='0.1.1a2',
description='A python facing API for stats.nba.com',
long_description=long_description,
# The project's main homepage.
url='https://github.com/seemethere/nba_py',
# Author details
author='seemethere',
author_email='seemethere101@gmail.com',
# Choose your license
license='BSD 3-clause "New" or "Revised License"',
# 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',
'Intended Audience :: Science/Research',
# Pick your license as you wish (should match "license" above)
'License :: OSI Approved :: BSD 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 :: 2.7',
],
# What does your project relate to?
keywords='nba sports data-mining',
# 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*']),
# 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=['requests'],
# 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',
# ],
# },
)