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setup.py
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from setuptools import setup
setup(
name='boxsers',
url='https://github.com/ALebrun-108/BoxSERS',
author='Alexis Lebrun',
author_email='[email protected]',
# dependencies
install_requires=['numpy', 'pandas', 'matplotlib', 'seaborn', 'scipy', 'scikit-learn', 'tensorflow',
'tables', 'scikit-image'],
python_requires='>=3.6',
# *strongly* suggested for sharing
version='1.5.2',
# The license can be anything you like
license='MIT',
description='Python package that provides a full range of functionality to process and analyze vibrational'
' spectra (Raman, SERS, FTIR, etc.).',
# We will also need a readme eventually (there will be a warning)
long_description=open('README_pypi.md').read(),
long_description_content_type="text/markdown",
classifiers=[
"Programming Language :: Python :: 3",
"License :: OSI Approved :: MIT License",
"Operating System :: OS Independent",
],
packages=["boxsers", "boxsers.machine_learning"],
)