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setup.py
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setup.py
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import io
import re
import setuptools
with open('mgktools/__init__.py') as fd:
__version__ = re.search("__version__ = '(.*)'", fd.read()).group(1)
def read(*filenames, **kwargs):
encoding = kwargs.get('encoding', 'utf-8')
sep = kwargs.get('sep', '\n')
buf = []
for filename in filenames:
with io.open(filename, encoding=encoding) as f:
buf.append(f.read())
return sep.join(buf)
long_description = read('README.md')
setuptools.setup(
name='mgktools',
version=__version__,
python_requires='>=3.10',
install_requires=[
'scikit-learn>=0.24.1',
'tqdm>=4.62.0',
'hyperopt>=0.2.5',
'optuna>=3.6.0',
'scipy>=1.6.2',
'mendeleev>=0.7',
'rxntools>=0.0.2',
'pycuda>=2022.1',
'rdkit>=2022.9.2',
'deepchem==2.7.2.dev20231207083329',
'typed-argument-parser',
'ipython',
],
entry_points={
'console_scripts': [
'mgk_read_data=mgktools.exe.run:mgk_read_data',
'mgk_kernel_calc=mgktools.exe.run:mgk_kernel_calc',
'mgk_model_evaluate=mgktools.exe.run:mgk_model_evaluate',
'mgk_hyperopt=mgktools.exe.run:mgk_hyperopt',
'mgk_hyperopt_multi_datasets=mgktools.exe.run:mgk_hyperopt_multi_datasets',
'mgk_optuna=mgktools.exe.run:mgk_optuna',
'mgk_optuna_multi_datasets=mgktools.exe.run:mgk_optuna_multi_datasets',
]
},
author='Yan Xiang',
author_email='1993.xiangyan@gmail.com',
description='Marginalized graph kernel library for molecular property prediction',
long_description=long_description,
url='https://github.com/xiangyan93/mgktools',
packages=setuptools.find_namespace_packages(include=['mgktools', 'mgktools.*']),
classifiers=[
'Programming Language :: Python',
'License :: OSI Approved :: MIT License',
'Operating System :: OS Independent',
],
include_package_data=True,
package_data={'': ['hyperparameters/configs/*.json']}
)