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setup.py
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setup.py
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#! /usr/bin/env python
#
# Copyright (C) 2007-2009 Cournapeau David <[email protected]>
# 2010 Fabian Pedregosa <[email protected]>
# 2014 Gael Varoquaux
# 2014 Sergei Lebedev <[email protected]>
"""Hidden Markov Models in Python with scikit-learn like API"""
import sys
from setuptools import setup, Extension
from Cython.Distutils import build_ext
DISTNAME = "hmmlearn"
DESCRIPTION = __doc__
LONG_DESCRIPTION = open("README.rst").read()
MAINTAINER = "Sergei Lebedev"
MAINTAINER_EMAIL = "[email protected]"
LICENSE = "new BSD"
CLASSIFIERS = [
"Development Status :: 3 - Alpha",
"License :: OSI Approved",
"Intended Audience :: Developers",
"Intended Audience :: Science/Research",
"Topic :: Software Development",
"Topic :: Scientific/Engineering",
"Programming Language :: Cython",
"Programming Language :: Python",
"Programming Language :: Python :: 2",
"Programming Language :: Python :: 2.6",
"Programming Language :: Python :: 2.7",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.3",
"Programming Language :: Python :: 3.4",
]
import hmmlearn
VERSION = hmmlearn.__version__
setup_options = dict(
name="hmmlearn",
version=VERSION,
description=DESCRIPTION,
long_description=LONG_DESCRIPTION,
maintainer=MAINTAINER,
maintainer_email=MAINTAINER_EMAIL,
license=LICENSE,
url="https://github.com/hmmlearn/hmmlearn",
packages=["hmmlearn", "hmmlearn.utils"],
classifiers=CLASSIFIERS,
cmdclass={"build_ext": build_ext},
ext_modules=[
Extension("hmmlearn._hmmc", ["hmmlearn/_hmmc.pyx"])
],
requires=["sklearn"],
install_requires=["Cython"]
)
# For these actions, NumPy is not required. We want them to succeed without,
# for example when pip is used to install seqlearn without NumPy present.
NO_NUMPY_ACTIONS = ('--help-commands', 'egg_info', '--version', 'clean')
if not ('--help' in sys.argv[1:]
or len(sys.argv) > 1 and sys.argv[1] in NO_NUMPY_ACTIONS):
import numpy as np
setup_options['include_dirs'] = [np.get_include()]
setup(**setup_options)