The time-consuming method of running statistical functions in Python

This article illustrates the time-consuming method of running statistical functions in Python. Share to everyone for your reference. The implementation methods are as follows:

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Import Time Def time_me (FN): def _wrapper (*args, **kwargs): start = Time.clock () fn (*args, **kwargs) print '%s cost%s sec Ond "% (fn.__name__, Time.clock ()-start) return _wrapper #这个装饰器可以在方便地统计函数运行的耗时. #用来分析脚本的性能是最好不过了. #这样用: @time_me def test (x, y): Time.sleep (0.1) @time_me def test2 (x): Time.sleep (0.2) test (1, 2) test2 (2) #输出: #test cost 0.1001529524 second #test2 cost 0.199968431742 second

Another, more advanced version is:

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Import time Import Functools def time_me (info= "used"): Def _time_me (FN): @functools. Wraps (FN) def _wrapper (*args, **kwarg s): start = Time.clock () fn (*args, **kwargs) print "%s%s"% (fn.__name__, info, Time.clock ()-start), "second" return _ Wrapper return _time_me @time_me () def test (x, y): Time.sleep (0.1) @time_me (' cost ') def test2 (x): Time.sleep (0.2) test (1, 2) test2 (2)

I hope this article will help you with your Python programming.