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setup.py
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setup.py
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from os import path
import setuptools
path_to_repo = path.abspath(path.dirname(__file__))
with open(path.join(path_to_repo, 'readme.md'), encoding='utf-8') as f:
long_description = f.read()
required_pypi = [
'matplotlib',
'mlxtend>=0.18.0', # some lower version are missing fpgrowth
'numpy',
'pandas',
'requests', # used in c4.5
'scipy',
'scikit-learn', # 0.23+ only works on py3.6+
'tqdm', # used in BART
"cvxpy"
]
extra_deps = [
'cvxpy', # optionally requires cvxpy for slim
'corels', # optionally requires corels for optimalrulelistclassifier
'gosdt-deprecated', # optionally requires gosdt for optimaltreeclassifier
'irf', # optionally require irf for iterativeRandomForestClassifier
]
setuptools.setup(
name="imodels",
version="1.3.17",
author="Chandan Singh, Keyan Nasseri, Matthew Epland, Yan Shuo Tan, Omer Ronen, Tiffany Tang, Abhineet Agarwal, Theo Saarinen, Bin Yu, and others",
author_email="[email protected]",
description="Implementations of various interpretable models",
long_description=long_description,
long_description_content_type="text/markdown",
url="https://github.com/csinva/imodels",
packages=setuptools.find_packages(
exclude=['tests', 'tests.*', '*.test.*']
),
install_requires=required_pypi,
extras_require={
'dev': [
'dvu',
'gdown',
# 'irf',
'jupyter',
'jupytext',
'matplotlib',
# 'pdoc3', # for building docs
'pytest',
'pytest-cov',
# 'seaborn', # in bartpy.diagnostics.features
'slurmpy',
# 'statsmodels', # in bartpy.diagnostics.diagnostics
# 'torch', # for neural-net-integrated models
'tqdm',
'pmlb',
]
},
python_requires='>=3.6',
classifiers=[
"Programming Language :: Python :: 3",
"License :: OSI Approved :: MIT License",
"Operating System :: OS Independent",
],
)