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setup.py
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setup.py
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# Copyright (c) 2018
# Amy L. Olex, Virginia Commonwealth University
# alolex at vcu.edu
#
# Luke Maffey, Virginia Commonwealth University
# maffeyl at vcu.edu
#
# Nicholas Morton, Virginia Commonwealth University
# nmorton at vcu.edu
#
# Bridget T. McInnes, Virginia Commonwealth University
# btmcinnes at vcu.edu
#
# This file is part of Chrono
#
# Chrono is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 3
# of the License, or (at your option) any later version.
#
# Chrono is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with Chrono; if not, write to
#
# The Free Software Foundation, Inc.,
# 59 Temple Place - Suite 330,
# Boston, MA 02111-1307, USA.
## This was taken from https://github.com/pypa/sampleproject/blob/master/setup.py to get me started
# 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 README file
with open(path.join(here, 'README.md'), encoding='utf-8') as f:
long_description = f.read()
setup(
name='Chrono',
# 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='2.0.2',
description='Chrono is a hybrid rule-based and machine learning system that identifies temporal expressions in text and normalizes them into the Semantically Compositional Annotations for Temporal Expressions (SCATE) schema developed by Bethard and Parker. Chrono has emerged as the top performing system for SemEval 2018 Task 6: Parsing Time Normalizations.',
long_description=long_description,
# The project's main homepage.
url='https://github.com/AmyOlex/Chrono',
# Author details
author='Amy Olex, Luke Maffey, Nick Morton, and Bridget McInnes',
# Choose your license
license='GPLv3',
# 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 :: Science/Research',
'Topic :: Text Processing',
# Pick your license as you wish (should match "license" above)
'License :: OSI Approved :: GNU General Public License v3 (GPLv3)',
# 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 :: 3',
],
# What does your project relate to?
keywords='nlp temporal time-normalization semeval2018-Chrono',
# 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']),
# 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=['nltk', 'python-dateutil', 'numpy', 'sklearn', 'keras', 'tensorflow'],
# 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',
# ],
#},
)