使用“时间”模块测量经过时间

start_time = time.time()# your preelapsed_time = time.time() - start_time

您还可以编写简单的装饰器来简化各种功能的执行时间的度量：

import timefrom functools import wrapsPROF_DATA = {}def profile(fn):    @wraps(fn)    def with_profiling(*args, **kwargs):        start_time = time.time()        ret = fn(*args, **kwargs)        elapsed_time = time.time() - start_time        if fn.__name__ not in PROF_data: PROF_DATA[fn.__name__] = [0, []]        PROF_DATA[fn.__name__][0] += 1        PROF_DATA[fn.__name__][1].append(elapsed_time)        return ret    return with_profilingdef print_prof_data():    for fname, data in PROF_DATA.items():        max_time = max(data[1])        avg_time = sum(data[1]) / len(data[1])        print "Function %s called %d times. " % (fname, data[0]),        print 'Execution time max: %.3f, average: %.3f' % (max_time, avg_time)def clear_prof_data():    global PROF_DATA    PROF_DATA = {}

用法：

@profiledef your_function(...):    ...

您可以同时分析多个功能。然后要打印测量值，只需调用print_prof_data（）：