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setup.py
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setup.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Copyright (c) 2013 Spotify AB
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may not
# use this file except in compliance with the License. You may obtain a copy of
# the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations under
# the License.
from setuptools import setup, Extension
import codecs
import os
import sys
readme_note = """\
.. note::
For the latest source, discussion, etc, please visit the
`GitHub repository <https://github.com/spotify/annoy>`_\n\n
.. image:: https://img.shields.io/github/stars/spotify/annoy.svg
:target: https://github.com/spotify/annoy
"""
with codecs.open('README.rst', encoding='utf-8') as fobj:
long_description = readme_note + fobj.read()
if os.environ.get('TRAVIS') == 'true':
# Resolving some annoying issue
travis_extra_compile_args = ['-mno-avx']
else:
travis_extra_compile_args = []
# Not all CPUs have march as a tuning parameter
import platform
cputune = ['-march=native',]
if platform.machine() == "ppc64le":
cputune = ['-mcpu=native',]
if os.name != 'nt':
compile_args = ['-O3', '-ffast-math', '-fno-associative-math']
else:
compile_args = []
cputune = []
setup(name='annoy',
version='1.9.5',
description='Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk.',
packages=['annoy'],
ext_modules=[
Extension(
'annoy.annoylib', ['src/annoymodule.cc'],
depends=['src/annoylib.h', 'src/kissrandom.h', 'src/mman.h'],
extra_compile_args=compile_args + cputune + travis_extra_compile_args
)
],
long_description=long_description,
author='Erik Bernhardsson',
author_email='[email protected]',
url='https://github.com/spotify/annoy',
license='Apache License 2.0',
classifiers=[
'Development Status :: 5 - Production/Stable',
'Programming Language :: Python',
'Programming Language :: Python :: 2.6',
'Programming Language :: Python :: 2.7',
'Programming Language :: Python :: 3.3',
'Programming Language :: Python :: 3.4',
'Programming Language :: Python :: 3.5',
],
keywords='nns, approximate nearest neighbor search',
setup_requires=['nose>=1.0']
)