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setup.py
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setup.py
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#!/usr/bin/env python
from os.path import join
from setuptools import setup, find_packages
MODULE_NAME = 'fklearn' # package name used to install via pip (as shown in `pip freeze` or `conda list`)
MODULE_NAME_IMPORT = 'fklearn' # this is how this module is imported in Python (name of the folder inside `src`)
REPO_NAME = 'fklearn' # repository name
def requirements_from_pip(filename='requirements.txt'):
with open(filename, 'r') as pip:
return [l.strip() for l in pip if not l.startswith('#') and l.strip()]
core_deps = requirements_from_pip()
demos_deps = requirements_from_pip("requirements_demos.txt")
test_deps = requirements_from_pip("requirements_test.txt")
tools_deps = requirements_from_pip("requirements_tools.txt")
lgbm_deps = requirements_from_pip("requirements_lgbm.txt")
xgboost_deps = requirements_from_pip("requirements_xgboost.txt")
catboost_deps = requirements_from_pip("requirements_catboost.txt")
all_models_deps = lgbm_deps + xgboost_deps + catboost_deps
all_deps = all_models_deps + tools_deps
devel_deps = test_deps + all_deps
with open("README.md", "r") as fh:
long_description = fh.read()
setup(name=MODULE_NAME,
description="Functional machine learning",
long_description=long_description,
long_description_content_type="text/markdown",
url='https://github.com/nubank/{:s}'.format(REPO_NAME),
python_requires='>=3.8,<3.12',
author="Nubank",
package_dir={'': 'src'},
packages=find_packages('src'),
version=(open(join('src', MODULE_NAME, 'resources', 'VERSION'))
.read().strip()),
install_requires=core_deps,
extras_require={"test_deps": test_deps,
"lgbm": lgbm_deps,
"xgboost": xgboost_deps,
"catboost": catboost_deps,
"tools": tools_deps,
"devel": devel_deps,
"all_models": all_models_deps,
"all": all_deps},
include_package_data=True,
zip_safe=False,
classifiers=[
'Programming Language :: Python :: 3.8',
'Programming Language :: Python :: 3.9',
'Programming Language :: Python :: 3.10',
'Programming Language :: Python :: 3.11',
])