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setup.py
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from setuptools import setup, find_packages
import codecs
import os.path
here = os.path.abspath(os.path.dirname(__file__))
def read(rel_path):
with codecs.open(os.path.join(here, rel_path), 'r') as fp:
return fp.read()
def get_version(rel_path):
for line in read(rel_path).splitlines():
if line.startswith('__version__'):
delim = '"' if '"' in line else "'"
return line.split(delim)[1]
else:
raise RuntimeError("Unable to find version string.")
DISTNAME = 'scikit-qlearn'
DESCRIPTION = 'A set of python modules for quantum enhanced machine learning algorithms'
MAINTAINER = 'Daniel Mohedano'
MAINTAINER_EMAIL = 'danimohedano1998@gmail.com'
URL = 'https://github.com/danmohedano/scikit-qlearn'
LICENSE = 'MIT'
DOWNLOAD_URL = URL
PACKAGE_NAME = 'skqlearn'
LONG_DESCRIPTION = read('README.rst')
# Arguments marked as "Required" below must be included for upload to PyPI.
# Fields marked as "Optional" may be commented out.
if __name__ == '__main__':
setup(
name=DISTNAME, # Required
version=get_version(os.path.join(PACKAGE_NAME, '_version.py')), # Required
description=DESCRIPTION, # Optional
long_description=LONG_DESCRIPTION, # Optional
long_description_content_type='text/x-rst', # Optional (see note above)
url=URL, # Optional
author=MAINTAINER, # Optional
author_email=MAINTAINER_EMAIL, # Optional
classifiers=[ # Optional
'Development Status :: 5 - Production/Stable',
'Intended Audience :: Developers',
'Intended Audience :: Science/Research',
'Topic :: Scientific/Engineering',
'License :: OSI Approved :: BSD License',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 3.7',
'Programming Language :: Python :: 3.8',
'Programming Language :: Python :: 3.9',
"Programming Language :: Python :: 3.10",
'Programming Language :: Python :: 3 :: Only',
],
keywords='quantum, machine learning, ai', # Optional
packages=find_packages(), # Required
python_requires='>=3.7, <4',
install_requires=['qiskit',
'numpy',
'pytest',
'matplotlib'], # Optional
project_urls={
'Documentation': 'https://danmohedano.github.io/scikit-qlearn/',
'Source': URL,
}
)