from setuptools import setup, find_packages

from os import path

import sys

from io import open

here = path.abspath(path.dirname(__file__))

sys.path.insert(0, path.join(here, 'ogb'))

from version import __version__

print('version')

print(__version__)

# Get the long description from the README file

with open(path.join(here, 'README.md'), encoding='utf-8') as f:

long_description = f.read()

package_data_list = ['ogb/graphproppred/master.csv', 'ogb/nodeproppred/master.csv', 'ogb/linkproppred/master.csv']

setup(name='ogb',

version=__version__,

description='Open Graph Benchmark',

url='https://github.com/snap-stanford/ogb',

author='OGB Team',

author_email='ogb@cs.stanford.edu',

keywords=['pytorch', 'graph machine learning', 'graph representation learning', 'graph neural networks'],

long_description=long_description,

long_description_content_type='text/markdown',

install_requires = [

'torch>=1.6.0',

'numpy>=1.16.0',

'tqdm>=4.29.0',

'scikit-learn>=0.20.0',

'pandas>=0.24.0',

'six>=1.12.0',

'urllib3>=1.24.0',

'outdated>=0.2.0',

'joblib>=1.3.2'

],

license='MIT',

packages=find_packages(exclude=['dataset', 'examples', 'docs']),

package_data={'ogb': package_data_list},

include_package_data=True,

classifiers=[

'Topic :: Scientific/Engineering :: Artificial Intelligence',

'Intended Audience :: Science/Research',

'Programming Language :: Python :: 3.6',

'Programming Language :: Python :: 3.7',

'License :: OSI Approved :: MIT License',

],

)