setup.py

from setuptools import setup, find_packages

setup(
    name='abcde',
    version='1.0.0',
    description='Approximating Betweenness Centrality with Drop Edge',
    author='Martin Mirakyan',
    author_email='mirakyanmartin@gmail.com',
    python_requires='>=3.6.9',
    url='https://github.com/MartinXPN/abcde',
    packages=find_packages(exclude=('tests',)),
    install_requires=[
        'torch>=1.7.0',
        'pytorch-lightning>=1.1.0',
        'torch-scatter',
        'torch-sparse',
        'torch-cluster',
        'torch-spline-conv',
        'torch-geometric>=1.6.3',
        'python-igraph>=0.8.3',
        'networkx>=2.5',
        'scipy>=1.5.0',
        'scikit-learn>=0.23.2',
        'numpy>=1.19.4',
        'pandas>=1.1.0',
        'tqdm>=4.54.1',
        'fire>=0.3.1',
        'aim>=2.1.4',
        'wandb>=0.10.17',
        'knockknock>=0.1.8.1',
    ],
    extras_require={
        'test': ['coverage', 'pytest', 'pytest-cov'],
    },
    include_package_data=True,
    license='MIT',
    classifiers=[
        # Full list of Trove classifiers: https://pypi.python.org/pypi?%3Aaction=list_classifiers
        'License :: OSI Approved :: MIT License',
        'Programming Language :: Python',
        'Programming Language :: Python :: 3 :: Only',
        'Programming Language :: Python :: 3',
        'Programming Language :: Python :: 3.6',
        'Programming Language :: Python :: 3.7',
        'Programming Language :: Python :: 3.8',
        'Programming Language :: Python :: 3.9',
        'Topic :: Scientific/Engineering :: Artificial Intelligence',
    ],
)