https://github.com/pymc-devs/pymc3
Tip revision: 90a3fbf266ef0aac92326ecf95fe60e992b9ad46 authored by Chris Fonnesbeck on 06 September 2016, 19:12:49 UTC
Incremented version to 3.0.rc1 (#1334)
Incremented version to 3.0.rc1 (#1334)
Tip revision: 90a3fbf
setup.py
#!/usr/bin/env python
from setuptools import setup
import sys
DISTNAME = 'pymc3'
DESCRIPTION = "PyMC3"
LONG_DESCRIPTION = """Bayesian estimation, particularly using Markov chain Monte Carlo (MCMC), is an increasingly relevant approach to statistical estimation. However, few statistical software packages implement MCMC samplers, and they are non-trivial to code by hand. ``pymc3`` is a python package that implements the Metropolis-Hastings algorithm as a python class, and is extremely flexible and applicable to a large suite of problems. ``pymc3`` includes methods for summarizing output, plotting, goodness-of-fit and convergence diagnostics."""
MAINTAINER = 'Thomas Wiecki'
MAINTAINER_EMAIL = 'thomas.wiecki@gmail.com'
AUTHOR = 'John Salvatier and Christopher Fonnesbeck'
AUTHOR_EMAIL = 'chris.fonnesbeck@vanderbilt.edu'
URL = "http://github.com/pymc-devs/pymc"
LICENSE = "Apache License, Version 2.0"
VERSION = "3.0.rc1"
classifiers = ['Development Status :: 5 - Production/Stable',
'Programming Language :: Python',
'Programming Language :: Python :: 2',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 2.7',
'Programming Language :: Python :: 3.4',
'Programming Language :: Python :: 3.5',
'License :: OSI Approved :: Apache Software License',
'Intended Audience :: Science/Research',
'Topic :: Scientific/Engineering',
'Topic :: Scientific/Engineering :: Mathematics',
'Operating System :: OS Independent']
with open('requirements.txt') as f:
install_reqs = f.read().splitlines()
if sys.version_info < (3, 4):
install_reqs.append('enum34')
test_reqs = ['nose']
if sys.version_info[0] == 2: # py3 has mock in stdlib
test_reqs.append('mock')
if __name__ == "__main__":
setup(name=DISTNAME,
version=VERSION,
maintainer=MAINTAINER,
maintainer_email=MAINTAINER_EMAIL,
description=DESCRIPTION,
license=LICENSE,
url=URL,
long_description=LONG_DESCRIPTION,
packages=['pymc3', 'pymc3.distributions',
'pymc3.step_methods', 'pymc3.tuning',
'pymc3.tests', 'pymc3.glm', 'pymc3.examples',
'pymc3.backends', 'pymc3.variational'],
package_data = {'pymc3.examples': ['data/*.*']},
classifiers=classifiers,
install_requires=install_reqs,
tests_require=test_reqs,
test_suite='nose.collector')