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setup.py
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setup.py
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import os.path as osp
from setuptools import find_packages, setup
def get_version():
# From: https://github.com/facebookresearch/iopath/blob/master/setup.py
# Author: Facebook Research
init_py_path = osp.join(osp.abspath(osp.dirname(__file__)), "greatx",
"version.py")
init_py = open(init_py_path, "r").readlines()
version_line = [
line.strip() for line in init_py if line.startswith("__version__")
][0]
version = version_line.split("=")[-1].strip().strip("'\"")
return version
VERSION = get_version()
url = 'https://github.com/EdisonLeeeee/GreatX'
install_requires = [
'tqdm',
'scipy',
'numpy',
'tabulate',
'pandas',
'termcolor',
'scikit_learn',
'matplotlib',
]
full_requires = [
'numba',
'pandas',
'matplotlib',
'networkx>=2.3',
# 'gensim>=3.8.0',
]
test_requires = [
'pytest',
'pytest-cov',
]
dev_requires = test_requires + [
'pre-commit',
]
setup(
name='greatx',
version=VERSION,
description='Graph reliability toolbox',
author='Jintang Li',
author_email='lijt55@mail2.sysu.edu.cn',
long_description=open("README.md", encoding="utf-8").read(),
long_description_content_type="text/markdown",
url=url,
download_url='{}/archive/{}.tar.gz'.format(url, VERSION),
keywords=[
'torch_geometric',
'pytorch',
'benchmark',
'geometric-adversarial-learning',
'graph-neural-networks',
],
python_requires='>=3.7',
license="MIT LICENSE",
install_requires=install_requires,
extras_require={
'full': full_requires,
'test': test_requires,
'dev': dev_requires,
},
packages=find_packages(exclude=("examples", "imgs", "benchmark", "test")),
classifiers=[
'Development Status :: 3 - Alpha',
"Intended Audience :: Science/Research",
"License :: OSI Approved :: MIT License",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
'Topic :: Scientific/Engineering',
'Topic :: Software Development :: Libraries',
"Operating System :: Microsoft :: Windows",
"Operating System :: Unix",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.7",
"Programming Language :: Python :: 3.8",
],
)