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setup.py
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setup.py
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import os
import platform
from setuptools import setup, find_packages
from kameris import __version__
from kameris.utils.platform_utils import platform_name
try:
from wheel.bdist_wheel import bdist_wheel as _bdist_wheel
class bdist_wheel(_bdist_wheel):
def finalize_options(self):
_bdist_wheel.finalize_options(self)
self.root_is_pure = False
def get_tag(self):
if platform.system() == 'Windows':
platform_tag = 'win_amd64'
elif platform.system() == 'Linux':
platform_tag = 'manylinux1_x86_64'
elif platform.system() == 'Darwin':
platform_tag = 'macosx_10_6_intel'
return 'py2.py3', 'none', platform_tag
except ImportError:
bdist_wheel = None
with open(os.path.join(os.path.dirname(__file__), 'README.md')) as readme:
long_description = readme.read()
setup(
name='kameris',
version=__version__,
description=('A fast, user-friendly analysis and evaluation pipeline '
'for some DNA sequence classification tasks.'),
long_description=long_description,
long_description_content_type='text/markdown',
url='https://github.com/stephensolis/kameris/',
classifiers=[
'Development Status :: 4 - Beta',
'License :: OSI Approved :: MIT License',
'Programming Language :: Python :: 2',
'Programming Language :: Python :: 2.7',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 3.4',
'Programming Language :: Python :: 3.5',
'Programming Language :: Python :: 3.6',
'Programming Language :: Python :: 3.7',
'Topic :: Scientific/Engineering :: Artificial Intelligence',
'Topic :: Scientific/Engineering :: Bio-Informatics'
],
author='Stephen',
author_email='[email protected]',
license='MIT',
packages=find_packages(),
package_data={
'kameris': [
'schemas/*',
'scripts/make_plots.wls',
'scripts/generation_cgr_' + platform_name() + '_*',
'scripts/generation_dists_' + platform_name() + '_*'
]
},
entry_points={
'console_scripts': [
'kameris = kameris.__main__:main'
]
},
install_requires=[
'appdirs',
'backports.tempfile',
'jsonschema',
'kameris-formats',
'numpy',
'requests>=2.18.0',
'ruamel.yaml',
'psutil',
# it's necessary to freeze scikit-learn since models are neither
# forward nor backward-compatible
# kameris classify will warn if the current scikit-learn
# version doesn't match the version at train time
'scikit-learn==0.19.1',
'scipy',
'six',
'stopit',
'tabulate',
'tqdm',
'watchtower',
'x86cpu'
],
cmdclass={
'bdist_wheel': bdist_wheel
}
)