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setup.py
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setup.py
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from setuptools import setup, find_packages # Always prefer setuptools over distutils
from codecs import open # To use a consistent encoding
from os import path
version = {}
here = path.abspath(path.dirname(__file__))
with open(path.join("pyConTextNLP","version.py")) as f0:
exec(f0.read(), version)
print(version)
# 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='pyConTextNLP',
# 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=version["__version__"],
description='A Python implementation of the ConText algorithm',
long_description=long_description,
# The project's main homepage.
url='https://github.com/chapmanbe/pyConTextNLP',
# Author details
author='Brian Chapman',
author_email='[email protected]',
# Choose your license
license='http://www.apache.org/licenses/LICENSE-2.0',
# 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 :: Students',
#'Topic :: Software Development :: Build Tools',
# Pick your license as you wish (should match "license" above)
#'License :: OSI Approved :: Apache2',
# 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 :: 3',
],
# What does your project relate to?
keywords='ConText NLP',
# 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',
'pyConText',
'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=['networkx', 'pyyaml'],
# 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={
},
# 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',
# ],
#},
)