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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 README file
#with open(path.join(here, 'README.md')) as f:
# long_description = f.read()
setup(
name='companysim',
version='0.2',
description='Package to find similarity between pairs of companies based\
on textual information',
# long_description=long_description,
# The project's main homepage.
url='https://github.com/conlamon/companysim',
author='Connor Lamon',
author_email='connor.lamon@gmail.com',
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 :: 3 - Alpha',
# Indicate who your project is intended for
'Intended Audience :: Developers',
'Topic :: Scientific/Engineering :: Information Analysis',
# 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 :: 3.6',
],
# What does your project relate to?
keywords='textualsimilarity NLP',
# You can just specify the packages manually here if your project is
# simple. Or you can use find_packages().
packages=['companysim'],
# 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=['numpy>=1.12.1',
'datasketch>=1.2.1',
'decorator>=4.0.11',
'pandas>=0.20.1',
'scipy>=0.19.0',
'python-dateutil>=2.6.0',
'pytz>=2017.2',
'setuptools>=18.1',
],
# 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',
# ],
#},
)