Python调用C模块以及性能分析
cellyhu
8年前
<h3>1.c,ctypes和python的数据类型的对应关系</h3> <p>ctypes type ctype Python type</p> <p>c_char char 1-character string</p> <p>c_wchar wchar_t 1-character unicode string</p> <p>c_byte char int/long</p> <p>c_ubyte unsigned char int/long</p> <p>c_short short int/long</p> <p>c_ushort unsigned short int/long</p> <p>c_int int int/long</p> <p>c_uint unsigned int int/long</p> <p>c_long long int/long</p> <p>c_ulong unsigned long int/long</p> <p>c_longlong __int64 or long long int/long</p> <p>c_ulonglong unsigned __int64 or unsigned long long int/long</p> <p>c_float float float</p> <p>c_double double float</p> <p>c_char_p char * (NUL terminated) string or None</p> <p>c_wchar_p wchar_t * (NUL terminated) unicode or None</p> <p>c_void_p void * int/long or None</p> <h3>2.操作int</h3> <pre> <code class="language-python">>>> fromctypesimport * >>> c=c_int(34) >>> c c_int(34) >>> c.value 34 >>> c.value=343 >>> c.value 343 </code></pre> <h3>3.操作字符串</h3> <pre> <code class="language-python">>>> p=create_string_buffer(10) >>> p.raw '\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00' >>> p.value='fefefe' >>> p.raw 'fefefe\x00\x00\x00\x00' >>> p.value='fefeeeeeeeeeeeeeeeeeeeeeee' #字符串太长,报错 Traceback (mostrecentcalllast): File "<stdin>", line 1, in <module> ValueError: string toolong </code></pre> <h3>4.操作指针</h3> <pre> <code class="language-python">>>> i=c_int(999) >>> pi=pointer(i) >>> pi <__main__.LP_c_intobject at 0x7f7be1983b00> >>> pi.value Traceback (mostrecentcalllast): File "<stdin>", line 1, in <module> AttributeError: 'LP_c_int' object hasnoattribute 'value' >>> pi.contents c_int(999) >>> pi.contents=c_long(34343) >>> pi.contents c_int(34343) </code></pre> <ul> <li>通过pointer获取一个值的指针</li> <li>通过contents获取一个指针的值</li> </ul> <h3>5.c的结构体</h3> <pre> <code class="language-python">#定义一个c的structure,包含两个成员变量x和y >>> class POINT(Structure): ... _fields_=[('x',c_int),('y',c_int)] ... >>> point=POINT(2,4) >>> point <__main__.POINTobject at 0x7f7be1983b90> >>> point.x,point.y (2, 4) >>> porint=POINT(y=2) >>> porint <__main__.POINTobject at 0x7f7be1983cb0> >>> point=POINT(y=2) >>> point.x,point.y (0, 2) 定义一个类型为POINT的数组 >>> POINT_ARRAY=POINT*3 >>> pa=POINT_ARRAY(POINT(2,3),POINT(2,4),POINT(2,5)) >>> for i in pa:print pa.y ... Traceback (mostrecentcalllast): File "<stdin>", line 1, in <module> AttributeError: 'POINT_Array_3' object hasnoattribute 'y' >>> for i in pa:print i.y ... 3 4 5 </code></pre> <h3>6.访问so文件</h3> <p>1.创建一个c文件</p> <pre> <code class="language-python">#include <stdio.h> int hello_world(){ printf("Hello World\n"); return 0; } int main(){ hello_world(); return 0; } </code></pre> <p>2.编译成动态链接库</p> <pre> <code class="language-python">gcchello_world.c -fPIC -shared -o hello_world.so </code></pre> <p>3.python中调用库中的函数</p> <pre> <code class="language-python">fromctypesimportcdll c_lib=cdll.LoadLibrary('./hello_world.so') c_lib.hello_world() </code></pre> <h2>二.测试c的性能和python的差别</h2> <p>sum.c</p> <p>#include</p> <pre> <code class="language-python">int sum(int num){ long sum=0; int i =0; for( i=1;i<=num;i++){ sum=sum+i; }; return sum; } int main(){ printf("%d",sum(10)); return 0; } </code></pre> <ul> <li>测试方案:计算1-100的和</li> <li>测试次数:100万次 <h3>1. 直接用c来执行,通linux 的time命令来记录执行的用时</h3> <p>sum.c:</p> <pre> <code class="language-python">#include <stdio.h> int sum(int num){ long sum=0; int i =0; for( i=1;i<=num;i++){ sum=sum+i; }; return sum; } int main(){ int i ; for (i=0;i<1000000;i++){ sum(100); } return 0; </code></pre> <p>测试结果的例子:</p> <p>real 1.16</p> <p>user 1.13</p> <p>sys 0.01</p> </li> </ul> <h3>2.通过Python调用so文件和python的测试结果</h3> <p>sum_test.py:</p> <pre> <code class="language-python">defsum_python(num): s = 0 for i in xrange(1,num+1): s += i return s fromctypesimportcdll c_lib = cdll.LoadLibrary('./sum.so') defsum_c(num): return c_lib.sum(num) deftest(num): importtimeit t1 = timeit.Timer('c_lib.sum(%d)' % num, 'from __main__ import c_lib') t2 = timeit.Timer('sum_python(%d)' % num, 'from __main__ import sum_python') print 'c', t1.timeit(number=1000000) print 'python', t2.timeit(number=1000000) if __name__ == '__main__': test(100) </code></pre> <p>测试结果的例子</p> <pre> <code class="language-python">c 1.02756714821 python 7.90672802925 </code></pre> <h3>3.测试erlang的测试结果</h3> <p>刚刚学了erlang,那就一起测试一下erlang的运算性能</p> <p>sum.erl:</p> <pre> <code class="language-python">-module(sum). -export([sum/2,sum_test/2]). sum(0,Sum) -> Sum; sum(Num,Sum) -> sum(Num-1,Sum+Num). sum_test(Num,0) -> 0; sum_test(Num,Times) -> sum(Num,0), sum_test(Num,Times-1). </code></pre> <p>调用:</p> <pre> <code class="language-python">timer:tc(sum,sum_test,[100,1000000]). </code></pre> <p>测试结果的例子:</p> <pre> <code class="language-python">{2418486,0} </code></pre> <h3>4.测试结果</h3> <p>用上面的测试方法,进行10次测试,去除最大值和最小值,再计算平均值,得出:</p> <table> <thead> <tr> <th>Python调用c</th> <th>原生的c</th> <th>Python</th> <th>erlang</th> </tr> </thead> <tbody> <tr> <td>0.95</td> <td>0.48</td> <td>8.47</td> <td>2.43</td> </tr> </tbody> </table> <p>单位:秒</p> <ul> <li>求和的运行,使用的内存比较小,但是占用CPU资源比较多。</li> <li>原生的C是最快的,Python调用c会稍微慢一点,原因是计算100的和的操作是在c里面做的,而执行100万次的逻辑是在python做的</li> <li>erlang的性能虽然比c稍慢,但是也是不错的,</li> <li>Python的运行效率惨不忍睹。。。</li> </ul> <p> </p> <p>来自:http://python.jobbole.com/87044/</p> <p> </p>