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setup.py
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setup.py
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from setuptools import setup, find_packages
from codecs import open
from os import path
def read(filename):
"""
Read a file relative to setup.py location.
"""
here = path.dirname(path.abspath(__file__))
with open(path.join(here, filename)) as fd:
return fd.read()
def find_version(filename):
"""
Find package version in file.
"""
import re
content = read(filename)
version_match = re.search(r"^__version__ = ['\"]([^'\"]*)['\"]", content, re.M)
if version_match:
return version_match.group(1)
raise RuntimeError("Unable to find version string.")
here = path.abspath(path.dirname(__file__))
with open(path.join(here, "README.md"), encoding="utf8") as f:
readme = f.read()
setup(
name="cogdl",
version=find_version("cogdl/__init__.py"),
description="An Extensive Research Toolkit for Deep Learning on Graphs",
long_description=readme,
long_description_content_type="text/markdown",
url="https://github.com/THUDM/cogdl",
license="MIT",
classifiers=[
# How mature is this project? Common values are
# 3 - Alpha
# 4 - Beta
# 5 - Production/Stable
"Development Status :: 3 - Alpha",
# Indicate who your project is intended for
"Intended Audience :: Science/Research",
"Intended Audience :: Developers",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
# Pick your license as you wish (should match "license" above)
"License :: OSI Approved :: MIT License",
# 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",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
],
# What does your project relate to?
keywords="network embedding, graph representation learning, graph neural networks",
# You can just specify the packages manually here if your project is
# simple. Or you can use find_packages().
packages=find_packages(exclude=["tests", "tests.*", "examples", "examples.*"]),
include_package_data=True,
# Alternatively, if you want to distribute just a my_module.py, uncomment
# this:
# py_modules=["my_module"],
# List run-time dependencies here. These will be installed by pip when
# your project is installed. For an analysis of "install_requires" vs pip's
# requirements files see:
# https://packaging.python.org/en/latest/requirements.html
install_requires=[
"torch",
"importlib-metadata<5.0",
"networkx",
"matplotlib",
"tqdm",
"numpy>=1.21",
"scipy",
"gensim>=4.0",
"grave",
"scikit_learn",
"tabulate",
"optuna==2.4.0",
"ogb",
"pre-commit",
"flake8",
"numba",
"ninja",
"transformers",
"sentencepiece",
],
# List additional groups of dependencies here (e.g. development
# dependencies). You can install these using the following syntax,
# for example:
# $ pip install -e .[dev,test]
extra_require={
"test": [
"pytest",
]
}
# If there are data files included in your packages that need to be
# installed, specify them here. If using Python 2.6 or less, then these
# have to be included in MANIFEST.in as well.
# package_data={
# 'sample': ['package_data.dat'],
# },
# Although 'package_data' is the preferred approach, in some case you may
# need to place data files outside of your packages. See:
# http://docs.python.org/3.4/distutils/setupscript.html#installing-additional-files
# In this case, 'data_file' will be installed into '<sys.prefix>/my_data'
# data_files=[('my_data', ['data/data_file'])],
# To provide executable scripts, use entry points in preference to the
# "scripts" keyword. Entry points provide cross-platform support and allow
# pip to create the appropriate form of executable for the target platform.
# entry_points={
# 'console_scripts': [
# 'sample=sample:main',
# ],
# },
)