setup.py

#!/usr/bin/env python3
import re
from io import open
from os import path

from setuptools import find_packages, setup

# Dependencies for core API and examples. If updating this, you may need to update docs/requirements.txt too.
# Not all have a min-version specified, which is not uncommon. Specify when known or necessary (e.g. errors).
# Install PyTorch from the official website to match the hardware.
# To work on graphs, install torch-geometric following the official instructions (e.g. below):
# python -m pip install torch-cluster torch-scatter torch-sparse torch-spline
requirements = [
    "ipykernel",
    "ipython",
    "matplotlib",
    "numpy>=1.18.0",
    "Pillow",
    "PyTDC",
    "pydicom",
    "pandas",
    "pytorch-lightning>=1.3.0",
    "pytorch-memlab",
    "scikit-image>=0.16.2",
    "scikit-learn>=0.23.2",
    "scipy>=1.5.4",
    "tensorly>=0.5.1",
    "torch>=1.7.0",
    "torchsummary>=1.5.0",
    "torchvision",  # >=0.8.1
    "yacs>=0.1.7",
]

# Additional dependencies for development
dev_requirements = [
    "black==19.10b0",
    "coverage",
    "flake8",
    "flake8-print",
    "ipywidgets",
    "isort",
    "m2r",
    "mypy",
    "nbmake>=0.8",
    "nbsphinx",
    "nbsphinx-link",
    "nbval",
    "pre-commit",
    "pytest",
    "pytest-cov",
    "recommonmark",
    "sphinx",
    "sphinx-rtd-theme",
]


# Get version
def read(*names, **kwargs):
    with open(path.join(path.dirname(__file__), *names), encoding=kwargs.get("encoding", "utf8")) as fp:
        return fp.read()


def find_version(*file_paths):
    version_file = read(*file_paths)
    version_match = re.search(r"^__version__ = ['\"]([^'\"]*)['\"]", version_file, re.M)
    if version_match:
        return version_match.group(1)
    raise RuntimeError("Unable to find version string.")


readme = open("README.md").read()
version = find_version("kale", "__init__.py")


# Run the setup
setup(
    name="pykale",
    version=version,
    description="Knowledge-aware machine learning from multiple sources in Python",
    long_description=readme,
    long_description_content_type="text/markdown",
    author="The PyKale team",
    url="https://github.com/pykale/pykale",
    author_email="pykale-group@sheffield.ac.uk",
    project_urls={
        "Bug Tracker": "https://github.com/pykale/pykale/issues",
        "Documentation": "https://pykale.readthedocs.io",
        "Source": "https://github.com/pykale/pykale",
    },
    packages=find_packages(exclude=("docs", "examples", "tests")),
    python_requires=">=3.6",
    install_requires=requirements,
    extras_require={"dev": dev_requirements},
    setup_requires=["setuptools>=38.6.0"],
    license="MIT",
    keywords="machine learning, pytorch, deep learning, multimodal learning, transfer learning",
    classifiers=[
        "Intended Audience :: Developers",
        "Intended Audience :: Education",
        "Intended Audience :: Healthcare Industry",
        "Intended Audience :: Science/Research",
        "License :: OSI Approved :: MIT License",
        "Operating System :: OS Independent",
        "Programming Language :: Python :: 3",
        "Topic :: Scientific/Engineering :: Artificial Intelligence",
        "Topic :: Scientific/Engineering :: Medical Science Apps.",
        "Topic :: Software Development :: Libraries",
        "Natural Language :: English",
    ],
)