Python速度很快（是：Python的速度有多快） [英] Python is darn fast (was: How fast is Python)
问题描述
几个星期前我发布了这个帖子（还记得C Sharp的帖子吗？）但是在大量的帖子中没有注意到它是b / b
，所以让我重试一下。在这里，我获得了Python +
Psyco的速度是优化C的两倍，所以我想现在如果我的旧笔记本电脑上有什么东西是错误的，那么任何人都可以重现我的结果。
这是我用于调用错误函数一百万次的数字
（Python 2.3，Psyco 1.0，Red Hat Linux 7.3，Pentium II 366 MHz）：
$时间p23 erf.py
实际0m0.614s
用户0m0.551s
sys 0m0。 029s
这是优化C的两倍：
$ gcc erf.c -lm -o3
$ time ./a.out
real 0m1.125s
用户0m1.086s
sys 0m0.006s
以下是纯Python的情况
$ time p23 erf.jy
real 0m25.761s
用户0m25.012s
系统0m0.049s
，只是为了好玩，这里是Jython性能：
$ time jython erf.jy
real 0m42.979s
用户0m41.430s
sys 0m0.361s
源代码如下（复制自Alex Martelli的帖子）：
- -------------------------------------------------- -------------------
$ cat erf.py
导入数学
导入psyco
psyco.full（）
def erfc（x）：
exp = math.exp
p = 0.3275911
a1 = 0.254829592
a2 = -0.284496736
a3 = 1.421413741
a4 = -1.453152027
a5 = 1.061405429
t = 1.0 /（1.0 + p * x）
erfcx =（（a1 +（a2 +（a3 +
（a4 + a5 * t）* t）* t）* t）* t）* exp（-x * x）
返回erfcx
def main（）：
erg = 0.0
for i在xrange（1000000）：
erg + = erfc（0.456）
if __name__ ==''__ main__''：
main（）
---------------------------------- ----------------------------------------
＃py thon / jython版本=相同没有import psyco; psyco.full（）"
------------------------------- -------------------------------------------
$ cat erf.c
#include< stdio.h>
#include< math.h>
双倍erfc（双x）
{
双倍p，a1，a2，a3，a4，a5;
双t ，erfcx;
p = 0.3275911;
a1 = 0.254829592;
a2 = -0.284496736;
a3 = 1.421413741;
a4 = -1.453152027;
a5 = 1.061405429;
t = 1.0 /（1.0 + p * x）;
erfcx =（（a1 +（a2 +（a3 +
（a4 + a5 * t）* t）* t）* t）* t） * exp（-x * x）;
返回erfcx;
}
int main（）
{
double erg = 0.0;
int i;
for（i = 0; i< 1000000; i ++）
{
erg = erg + erfc（0.456）;
}
返回0;
}
Michele Simionato，博士。
Mi ************** @ libero.it
http://www.phyast.pitt.edu/~micheles
---目前正在找工作---
I posted this few weeks ago (remember the C Sharp thread?) but it went
unnoticed on the large mass of posts, so let me retry. Here I get Python+
Psyco twice as fast as optimized C, so I would like to now if something
is wrong on my old laptop and if anybody can reproduce my results.
Here are I my numbers for calling the error function a million times
(Python 2.3, Psyco 1.0, Red Hat Linux 7.3, Pentium II 366 MHz):
$ time p23 erf.py
real 0m0.614s
user 0m0.551s
sys 0m0.029s
This is twice as fast as optimized C:
$ gcc erf.c -lm -o3
$ time ./a.out
real 0m1.125s
user 0m1.086s
sys 0m0.006s
Here is the situation for pure Python
$time p23 erf.jy
real 0m25.761s
user 0m25.012s
sys 0m0.049s
and, just for fun, here is Jython performance:
$ time jython erf.jy
real 0m42.979s
user 0m41.430s
sys 0m0.361s
The source code follows (copied from Alex Martelli''s post):
----------------------------------------------------------------------
$ cat erf.py
import math
import psyco
psyco.full()
def erfc(x):
exp = math.exp
p = 0.3275911
a1 = 0.254829592
a2 = -0.284496736
a3 = 1.421413741
a4 = -1.453152027
a5 = 1.061405429
t = 1.0 / (1.0 + p*x)
erfcx = ( (a1 + (a2 + (a3 +
(a4 + a5*t)*t)*t)*t)*t ) * exp(-x*x)
return erfcx
def main():
erg = 0.0
for i in xrange(1000000):
erg += erfc(0.456)
if __name__ == ''__main__'':
main()
--------------------------------------------------------------------------
# python/jython version = same without "import psyco; psyco.full()"
--------------------------------------------------------------------------
$cat erf.c
#include <stdio.h>
#include <math.h>
double erfc( double x )
{
double p, a1, a2, a3, a4, a5;
double t, erfcx;
p = 0.3275911;
a1 = 0.254829592;
a2 = -0.284496736;
a3 = 1.421413741;
a4 = -1.453152027;
a5 = 1.061405429;
t = 1.0 / (1.0 + p*x);
erfcx = ( (a1 + (a2 + (a3 +
(a4 + a5*t)*t)*t)*t)*t ) * exp(-x*x);
return erfcx;
}
int main()
{
double erg=0.0;
int i;
for(i=0; i<1000000; i++)
{
erg = erg + erfc(0.456);
}
return 0;
}
Michele Simionato, Ph. D.
Mi**************@libero.it
http://www.phyast.pitt.edu/~micheles
--- Currently looking for a job ---
推荐答案
时间p23 erf.py
实际0m0 .614s
用户0m0.551s
sys 0m0.029s
这是优化C的两倍：
time p23 erf.py
real 0m0.614s
user 0m0.551s
sys 0m0.029s
This is twice as fast as optimized C:
gcc erf.c -lm -o3
gcc erf.c -lm -o3
time ./a.out
real 0m1.125s
用户0m1.086s
sys 0m0.006s
以下是纯Python的情况
time ./a.out
real 0m1.125s
user 0m1.086s
sys 0m0.006s
Here is the situation for pure Python
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