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setup.py
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import os
from setuptools import setup, find_packages
NAME = "occamypy"
DESCRIPTION = "OccamyPy. An object-oriented optimization library for small- and large-scale problems."
URL = "https://github.com/fpicetti/occamypy"
AUTHOR = "Ettore Biondi, Guillame Barnier, Robert Clapp, Francesco Picetti, Stuart Farris"
REQUIRES_PYTHON = ">=3.6.0"
PROJECT_ROOT = os.path.abspath(os.path.dirname(__file__))
def load_readme():
readme_path = os.path.join(PROJECT_ROOT, "README.md")
with open(readme_path, encoding="utf-8") as f:
return f"\n{f.read()}"
def load_version():
context = {}
with open(os.path.join(PROJECT_ROOT, "occamypy", "__version__.py")) as f:
exec(f.read(), context)
return context["__version__"]
setup(name='occamypy',
version=load_version(),
url="https://github.com/fpicetti/occamypy",
description='An Object-Oriented Optimization Framework for Large-Scale Inverse Problems',
long_description=load_readme(),
long_description_content_type='text/markdown',
keywords=['algebra', 'inverse problems', 'large-scale optimization'],
classifiers=[
'Development Status :: 4 - Beta',
'Intended Audience :: Developers',
'Intended Audience :: Science/Research',
'Natural Language :: English',
'Programming Language :: Python :: 3.6',
'Programming Language :: Python :: 3.7',
'Programming Language :: Python :: 3.8',
'Topic :: Scientific/Engineering :: Mathematics',
'Operating System :: Unix'
],
author=AUTHOR,
author_email=EMAIL,
install_requires=['numpy',
'scipy',
'numba',
'torch>=1.7.0',
'dask',
'dask-jobqueue',
'dask-kubernetes',
'matplotlib',
'gputil',
'imageio',
],
packages=find_packages(),
zip_safe=True)