python知识点(一)：python检测代码效率常用方法

来源：互联网发布：数据可视化培训编辑：程序博客网时间：2024/06/05 08:44

工作中对大数据需要进行处理，发现某个2重循环运行效率很低，搜集试验了2种比较简单方便检测代码效率的方法如下

1）装饰器来测量函数的执行时间

2）利用库函数cProfile

样例如下：

#coding:utf-8import timefrom functools import wrapsimport cProfiledef fn_timer(function):    @wraps(function)    def function_timer(*args, **kwargs):        t0 = time.time()        result = function(*args, **kwargs)        t1 = time.time()        print ("Total time running %s: %s seconds" %                (function.func_name, str(t1-t0))                )        return result    return function_timer@fn_timerdef string_match1(a, b, n):    for i in range(n):        if a is b:            c = 'true'        else:            c = 'false'@fn_timerdef string_match2(a, b, n):    for i in range(n):        if a == b:            c = 'true'        else:            c = 'false'@fn_timerdef string_match3(a, b, n):    for i in range(n):        if cmp(a, b):            c = 'true'        else:            c = 'false'def string_match4(a, b, n):    for i in range(n):        if a is b:            c = 'true'        else:            c = 'false'def string_match5(a, b, n):    for i in range(n):        if a == b:            c = 'true'        else:            c = 'false'def string_match6(a, b, n):    for i in range(n):        if cmp(a, b):            c = 'true'        else:            c = 'false'  if __name__ == "__main__":    n = 10000000    a = 'abcdef'    b = 'bcdefg'    string_match1(a, b, n)    string_match2(a, b, n)    string_match3(a, b, n)    cProfile.run('string_match4(a, b, n)')    cProfile.run('string_match5(a, b, n)')    cProfile.run('string_match6(a, b, n)')

运行上述代码后结果为：

Total time running string_match1: 0.505000114441 seconds
Total time running string_match2: 0.487000226974 seconds
Total time running string_match3: 1.15999984741 seconds

4 function calls in 0.444 seconds

Ordered by: standard name
ncalls tottime percall cumtime percall filename:lineno(function)
1 0.000 0.000 0.444 0.444 <string>:1(<module>)
1 0.368 0.368 0.444 0.444 test1.py:43(string_match4)
1 0.000 0.000 0.000 0.000 {method 'disable' of '_lsprof.Profiler' objects}
1 0.075 0.075 0.075 0.075 {range}

4 function calls in 0.481 seconds
Ordered by: standard name
ncalls tottime percall cumtime percall filename:lineno(function)
1 0.000 0.000 0.481 0.481 <string>:1(<module>)
1 0.422 0.422 0.481 0.481 test1.py:49(string_match5)
1 0.000 0.000 0.000 0.000 {method 'disable' of '_lsprof.Profiler' objects}
1 0.059 0.059 0.059 0.059 {range}

10000004 function calls in 1.816 seconds
Ordered by: standard name
ncalls tottime percall cumtime percall filename:lineno(function)
1 0.000 0.000 1.816 1.816 <string>:1(<module>)
1 1.166 1.166 1.816 1.816 test1.py:56(string_match6)
10000000 0.585 0.000 0.585 0.000 {cmp}
1 0.000 0.000 0.000 0.000 {method 'disable' of '_lsprof.Profiler' objects}
1 0.065 0.065 0.065 0.065 {range}

结论：

1）3种简单的字符串比较方法中，a is b 最快，使用cmp()函数变慢很多，所以在项目中只需修改一行代码，可以让执行时间缩短至1/3左右

2）使用cProfile来查看运行效率，可以检查内部每个子函数的效率，方便在大型程序中排查问题

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