#!/usr/bin/env python import os from io import open # Always prefer setuptools over distutils from setuptools import setup, find_packages try: import builtins except ImportError: import __builtin__ as builtins # https://packaging.python.org/guides/single-sourcing-package-version/ # http://blog.ionelmc.ro/2014/05/25/python-packaging/ PATH_ROOT = os.path.dirname(__file__) builtins.__LIGHTNING_SETUP__ = True import pytorch_lightning # noqa: E402 def load_requirements(path_dir=PATH_ROOT, comment_char='#'): with open(os.path.join(path_dir, 'requirements', 'base.txt'), 'r') as file: lines = [ln.strip() for ln in file.readlines()] reqs = [] for ln in lines: # filer all comments if comment_char in ln: ln = ln[:ln.index(comment_char)] if ln: # if requirement is not empty reqs.append(ln) return reqs def load_long_description(): # https://github.com/PyTorchLightning/pytorch-lightning/raw/master/docs/source/_images/lightning_module/pt_to_pl.png url = os.path.join(pytorch_lightning.__homepage__, 'raw', pytorch_lightning.__version__, 'docs') text = open('README.md', encoding='utf-8').read() # replace relative repository path to absolute link to the release text = text.replace('](docs', f']({url}') # SVG images are not readable on PyPI, so replace them with PNG text = text.replace('.svg', '.png') return text # https://packaging.python.org/discussions/install-requires-vs-requirements / # keep the meta-data here for simplicity in reading this file... it's not obvious # what happens and to non-engineers they won't know to look in init ... # the goal of the project is simplicity for researchers, don't want to add too much # engineer specific practices setup( name='pytorch-lightning', version=pytorch_lightning.__version__, description=pytorch_lightning.__docs__, author=pytorch_lightning.__author__, author_email=pytorch_lightning.__author_email__, url=pytorch_lightning.__homepage__, download_url='https://github.com/PyTorchLightning/pytorch-lightning', license=pytorch_lightning.__license__, packages=find_packages(exclude=['tests', 'tests/*', 'benchmarks']), long_description=load_long_description(), long_description_content_type='text/markdown', include_package_data=True, zip_safe=False, keywords=['deep learning', 'pytorch', 'AI'], python_requires='>=3.6', setup_requires=[], install_requires=load_requirements(PATH_ROOT), project_urls={ "Bug Tracker": "https://github.com/PyTorchLightning/pytorch-lightning/issues", "Documentation": "https://pytorch-lightning.rtfd.io/en/latest/", "Source Code": "https://github.com/PyTorchLightning/pytorch-lightning", }, classifiers=[ 'Environment :: Console', 'Natural Language :: English', # How mature is this project? Common values are # 3 - Alpha, 4 - Beta, 5 - Production/Stable 'Development Status :: 4 - Beta', # Indicate who your project is intended for 'Intended Audience :: Developers', 'Topic :: Scientific/Engineering :: Artificial Intelligence', 'Topic :: Scientific/Engineering :: Image Recognition', 'Topic :: Scientific/Engineering :: Information Analysis', # Pick your license as you wish 'License :: OSI Approved :: BSD License', 'Operating System :: OS Independent', # 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', 'Programming Language :: Python :: 3.6', 'Programming Language :: Python :: 3.7', 'Programming Language :: Python :: 3.8', ], )