setup.py

from setuptools import setup, find_packages
from os import path
import sys

from io import open

extras = {
    'tcga': ['pandas~=0.24.0', 'academictorrents~=2.1.0', 'six~=1.11.0'],
}

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

sys.path.insert(0, path.join(here, 'torchmeta'))
from version import 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()

setup(
    name='torchmeta',
    version=VERSION,
    description='Dataloaders for meta-learning in Pytorch',
    long_description=long_description,
    long_description_content_type='text/markdown',
    license='MIT',
    author='Tristan Deleu',
    author_email='tristan.deleu@gmail.com',
    url='https://github.com/tristandeleu/pytorch-meta',
    keywords=['meta-learning', 'pytorch', 'few-shot', 'few-shot learning'],
    packages=find_packages(exclude=['data', 'contrib', 'docs', 'tests', 'examples']),
    install_requires=[
        'torch>=1.4.0,<1.7.0',
        'torchvision>=0.5.0,<0.8.0',
        'numpy>=1.14.0',
        'Pillow>=7.0.0',
        'h5py',
        'tqdm>=4.0.0',
        'requests',  # Required by Torchvision
        'ordered-set'
    ],
    extras_require=extras,
    package_data={'torchmeta': ['torchmeta/datasets/assets/*']},
    include_package_data=True,
    classifiers=[
        'Development Status :: 5 - Production/Stable',
        'Topic :: Scientific/Engineering :: Artificial Intelligence',
        'Intended Audience :: Science/Research',
        'Programming Language :: Python :: 3',
        'Programming Language :: Python :: 3.6',
        'Programming Language :: Python :: 3.7',
        'Programming Language :: Python :: 3.8',
        'License :: OSI Approved :: MIT License',
    ],
)