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setup.py
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from setuptools import setup
import codecs
import os.path
def read(rel_path):
here = os.path.abspath(os.path.dirname(__file__))
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.")
with open('README.md') as readme:
long_description = readme.read()
PACKAGES=['packman',
'packman.molecule',
'packman.anm',
'packman.gnm',
'packman.apps',
'packman.bin',
'packman.constants',
'packman.utilities',
'packman.entropy',
'packman.geometry',
'packman.tests',
'packman.tests.anm',
'packman.tests.data',
'packman.tests.entropy',
'packman.tests.molecule'
]
PACKAGE_DATA = {'packman.bin': ['logo.ico'],
'packman.tests' : ['data/*.hng','data/*.pdb','data/*.cif']
}
SCRIPTS=['packman=packman.bin.PACKMAN:main']
setup(name='py-packman',
version = get_version('packman/__init__.py'),
description = 'A software package for molecular PACKing and Motion ANalysis (PACKMAN)',
url = 'https://github.com/Pranavkhade/PACKMAN',
author = 'Pranav Khade',
author_email = '[email protected]',
license = 'MIT',
packages = PACKAGES,
package_data = PACKAGE_DATA,
long_description = long_description,
long_description_content_type = 'text/markdown',
keywords = ('protein, dynamics, protein packing, protein domain, protein hinge'),
classifiers = [
'Intended Audience :: Education',
'Intended Audience :: Science/Research',
'License :: OSI Approved :: MIT License',
'Operating System :: MacOS',
'Operating System :: Microsoft :: Windows',
'Operating System :: POSIX',
'Programming Language :: Python',
'Programming Language :: Python :: 2',
'Programming Language :: Python :: 3',
'Topic :: Scientific/Engineering :: Bio-Informatics',
'Topic :: Scientific/Engineering :: Chemistry',
'Topic :: Scientific/Engineering :: Mathematics'
],
entry_points = {
'console_scripts': SCRIPTS,
},
install_requires = ['numpy', 'scipy', 'networkx', 'mlxtend', 'scikit-learn'],
)