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setup.py
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from setuptools import setup
exec(compile(open('SemiBin/semibin_version.py').read(),
'SemiBin/semibin_version.py', 'exec'))
long_description = open('README.md', encoding='utf-8').read()
setup(name='SemiBin',
version=__version__,
python_requires='>=3.7',
description='Metagenomic binning with siamese neural networks',
long_description = long_description,
long_description_content_type = 'text/markdown',
classifiers=[
'Development Status :: 5 - Production/Stable',
'Intended Audience :: Science/Research',
'Topic :: Scientific/Engineering :: Bio-Informatics',
'Topic :: Scientific/Engineering :: Artificial Intelligence',
'License :: OSI Approved :: MIT License',
'Programming Language :: Python :: 3.7',
'Programming Language :: Python :: 3.8',
'Programming Language :: Python :: 3.9',
'Programming Language :: Python :: 3.10',
'Programming Language :: Python :: 3.11',
'Programming Language :: Python :: 3.12',
],
url='https://github.com/BigDataBiology/SemiBin',
author='Shaojun Pan and Luis Pedro Coelho',
author_email='[email protected]',
license='MIT',
packages = ['SemiBin'],
install_requires=[
'numpy',
'tqdm',
'pyyaml',
'torch',
'python-igraph',
'pandas',
'scikit-learn',
'requests',
'numexpr',
],
package_data={
'SemiBin': ['*.hmm', 'models/*.pt']},
zip_safe=False,
entry_points={
'console_scripts': ['SemiBin=SemiBin.main:main_no_version',
'SemiBin2=SemiBin.main:main2',
'SemiBin1=SemiBin.main:main1',
],
}
)