[url=http://psyco.sourceforge.net/]http://psyco.sourceforge.net/[/url]
[url=https://bitbucket.org/pypy/pypy/downloads/pypy-1.8-win32.zip]https://bitbucket.org/pypy/pypy/downloads/pypy-1.8-win32.zip[/url]， 然后解压到相关的目录，并将解压后的路径添加到环境变量 path 中即可。在命令行运行 pypy，如果出现如下错误："没有找到 MSVCR100.dll, 因此这个应用程序未能启动，重新安装应用程序可能会修复此问题"，则还需要在微软的官网上下载 VS 2010 runtime libraries 解决该问题。具体地址为 [url=http://www.microsoft.com/download/en/details.aspx?displaylang=en&id=5555]http://www.microsoft.com/download/en/details.aspx?displaylang=en&id=5555[/url]
安装成功后在命令行里运行 pypy，输出结果如下：
C:\Documents and Settings\Administrator>pypy
Python 2.7.2 (0e28b379d8b3, Feb 09 2012, 18:31:47)
[PyPy 1.8.0 with MSC v.1500 32 bit] on win32
Type "help", "copyright", "credits" or "license" for more information.
And now for something completely different: ``PyPy is vast, and contains
multitudes''
>>>>
以清单 5 的循环为例子，使用 python 和 pypy 分别运行，得到的运行结果分别如下：
C:\Documents and Settings\Administrator\ 桌面 \doc\python>pypy loop.py
total run time:
8.42199993134
C:\Documents and Settings\Administrator\ 桌面 \doc\python>python loop.py
total run time:
106.391000032
可见使用 pypy 来编译和运行程序，其效率大大的提高。
Cython
Cython 是用 python 实现的一种语言，可以用来写 python 扩展，用它写出来的库都可以通过 import 来载入，性能上比 python 的快。cython 里可以载入 python 扩展 ( 比如 import math)，也可以载入 c 的库的头文件 ( 比如 :cdef extern from "math.h")，另外也可以用它来写 python 代码。将关键部分重写成 C 扩展模块
[b]Linux Cpython 的安装：
[/b]第一步：下载
[root@v5254085f259 cpython]# wget -N http://cython.org/release/Cython-0.15.1.zip
--2012-04-16 22:08:35-- http://cython.org/release/Cython-0.15.1.zip
Resolving cython.org... 128.208.160.197
Connecting to cython.org|128.208.160.197|:80... connected.
HTTP request sent, awaiting response... 200 OK
Length: 2200299 (2.1M) [application/zip]
Saving to: `Cython-0.15.1.zip'
100%[======================================>] 2,200,299 1.96M/s in 1.1s
2012-04-16 22:08:37 (1.96 MB/s) - `Cython-0.15.1.zip' saved [2200299/2200299]
第二步：解压
[root@v5254085f259 cpython]# unzip -o Cython-0.15.1.zip
第三步：安装
python setup.py install
安装完成后直接输入 cython，如果出现如下内容则表明安装成功。
[root@v5254085f259 Cython-0.15.1]# cython
Cython (http://cython.org) is a compiler for code written in the
Cython language. Cython is based on Pyrex by Greg Ewing.
Usage: cython [options] sourcefile.{pyx,py} ...
Options:
-V, --version Display version number of cython compiler
-l, --create-listing Write error messages to a listing file
-I, --include-dir Search for include files in named directory
(multiple include directories are allowed).
-o, --output-file Specify name of generated C file
-t, --timestamps Only compile newer source files
-f, --force Compile all source files (overrides implied -t)
-q, --quiet Don't print module names in recursive mode
-v, --verbose Be verbose, print file names on multiple compil ation
-p, --embed-positions If specified, the positions in Cython files of each
function definition is embedded in its docstring.
--cleanup
Release interned objects on python exit, for memory debugging.
Level indicates aggressiveness, default 0 releases nothing.
-w, --working
Sets the working directory for Cython (the directory modules are searched from)
--gdb Output debug information for cygdb
-D, --no-docstrings
Strip docstrings from the compiled module.
-a, --annotate
Produce a colorized HTML version of the source.
--line-directives
Produce #line directives pointing to the .pyx source
--cplus
Output a C++ rather than C file.
--embed[=]
Generate a main() function that embeds the Python interpreter.
-2 Compile based on Python-2 syntax and code seman tics.
-3 Compile based on Python-3 syntax and code seman tics.
--fast-fail Abort the compilation on the first error
--warning-error, -Werror Make all warnings into errors
--warning-extra, -Wextra Enable extra warnings
-X, --directive =
[,
其他平台上的安装可以参考文档：http://docs.cython.org/src/quickstart/install.html
Cython 代码与 python 不同，必须先编译，编译一般需要经过两个阶段，将 pyx 文件编译为 .c 文件，再将 .c 文件编译为 .so 文件。编译有多种方法：
•通过命令行编译：
假设有如下测试代码，使用命令行编译为 .c 文件。
def sum(int a,int b):
print a+b
[root@v5254085f259 test]# cython sum.pyx
[root@v5254085f259 test]# ls
total 76
4 drwxr-xr-x 2 root root 4096 Apr 17 02:45 .
4 drwxr-xr-x 4 root root 4096 Apr 16 22:20 ..
4 -rw-r--r-- 1 root root 35 Apr 17 02:45 1
60 -rw-r--r-- 1 root root 55169 Apr 17 02:45 sum.c
4 -rw-r--r-- 1 root root 35 Apr 17 02:45 sum.pyx
在 linux 上利用 gcc 编译为 .so 文件：
[root@v5254085f259 test]# gcc -shared -pthread -fPIC -fwrapv -O2
-Wall -fno-strict-aliasing -I/usr/include/python2.4 -o sum.so sum.c
[root@v5254085f259 test]# ls
total 96
4 drwxr-xr-x 2 root root 4096 Apr 17 02:47 .
4 drwxr-xr-x 4 root root 4096 Apr 16 22:20 ..
4 -rw-r--r-- 1 root root 35 Apr 17 02:45 1
60 -rw-r--r-- 1 root root 55169 Apr 17 02:45 sum.c
4 -rw-r--r-- 1 root root 35 Apr 17 02:45 sum.pyx
20 -rwxr-xr-x 1 root root 20307 Apr 17 02:47 sum.so
•使用 distutils 编译
建立一个 setup.py 的脚本：
from distutils.core import setup
from distutils.extension import Extension
from Cython.Distutils import build_ext
ext_modules = [Extension("sum", ["sum.pyx"])]
setup(
name = 'sum app',
cmdclass = {'build_ext': build_ext},
ext_modules = ext_modules
)
[root@v5254085f259 test]# python setup.py build_ext --inplace
running build_ext
cythoning sum.pyx to sum.c
building 'sum' extension
gcc -pthread -fno-strict-aliasing -fPIC -g -O2 -DNDEBUG -g -fwrapv -O3
-Wall -Wstrict-prototypes -fPIC -I/opt/ActivePython-2.7/include/python2.7
-c sum.c -o build/temp.linux-x86_64-2.7/sum.o
gcc -pthread -shared build/temp.linux-x86_64-2.7/sum.o
-o /root/cpython/test/sum.so
编译完成之后可以导入到 python 中使用：
[root@v5254085f259 test]# python
ActivePython 2.7.2.5 (ActiveState Software Inc.) based on
Python 2.7.2 (default, Jun 24 2011, 11:24:26)
[GCC 4.0.2 20051125 (Red Hat 4.0.2-8)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import pyximport; pyximport.install()
>>> import sum
>>> sum.sum(1,3)
下面来进行一个简单的性能比较：
清单 9. Cython 测试代码
from time import time
def test(int n):
cdef int a =0
cdef int i
for i in xrange(n):
a+= i
return a
t = time()
test(10000000)
print "total run time:"
print time()-t
测试结果：
[GCC 4.0.2 20051125 (Red Hat 4.0.2-8)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import pyximport; pyximport.install()
>>> import ctest
total run time:
0.00714015960693
清单 10. Python 测试代码
from time import time
def test(n):
a =0;
for i in xrange(n):
a+= i
return a
t = time()
test(10000000)
print "total run time:"
print time()-t
[root@v5254085f259 test]# python test.py
total run time:
0.971596002579
从上述对比可以看到使用 Cython 的速度提高了将近 100 多倍。
总结
本文初步探讨了 python 常见的性能优化技巧以及如何借助工具来定位和分析程序的性能瓶颈，并提供了相关可以进行性能优化的工具或语言，希望能够更相关人员一些参考。
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