准确测量python函数所需的时间 [英] accurately measure time python function takes

问题描述

我需要测量程序某些部分所花费的时间(不是用于调试，而是作为输出中的功能).准确性很重要，因为总时间将不到一秒钟.

I need to measure the time certain parts of my program take (not for debugging but as a feature in the output). Accuracy is important because the total time will be a fraction of a second.

当我遇到时间，它声称​​避免了一些用于测量执行时间的常见陷阱.不幸的是，它有一个糟糕的接口，需要一个字符串作为输入，然后才是eval的.

I was going to use the time module when I came across timeit, which claims to avoid a number of common traps for measuring execution times. Unfortunately it has an awful interface, taking a string as input which it then eval's.

那么，我需要使用此模块来准确地测量时间还是时间足够?它指的是什么陷阱?

So, do I need to use this module to measure time accurately, or will time suffice? And what are the pitfalls it refers to?

谢谢

推荐答案

根据Python 文档，它与不同操作系统中时间函数的准确性有关:

According to the Python documentation, it has to do with the accuracy of the time function in different operating systems:

默认计时器功能是平台 依赖.在Windows上，time.clock() 具有微秒级的粒度，但 time.time()的粒度为1/60 一秒;在Unix上，time.clock()具有 1/100秒的粒度和 time.time()更精确.在 任何一个平台，默认计时器 功能测量挂钟时间，而不是 CPU时间.这意味着其他 在同一台计算机上运行的进程 可能会干扰时间...在Unix上，您可以 使用time.clock()来测量CPU时间.

The default timer function is platform dependent. On Windows, time.clock() has microsecond granularity but time.time()‘s granularity is 1/60th of a second; on Unix, time.clock() has 1/100th of a second granularity and time.time() is much more precise. On either platform, the default timer functions measure wall clock time, not the CPU time. This means that other processes running on the same computer may interfere with the timing ... On Unix, you can use time.clock() to measure CPU time.

直接从timeit.py的代码中提取:

if sys.platform == "win32":
    # On Windows, the best timer is time.clock()
    default_timer = time.clock
else:
    # On most other platforms the best timer is time.time()
    default_timer = time.time

此外，它直接为您设置运行时代码.如果使用time，则必须自己执行.当然，这为您节省了时间

In addition, it deals directly with setting up the runtime code for you. If you use time you have to do it yourself. This, of course saves you time

Timeit的设置:

Timeit's setup:

def inner(_it, _timer):
    #Your setup code
    %(setup)s
    _t0 = _timer()
    for _i in _it:
        #The code you want to time
        %(stmt)s
    _t1 = _timer()
    return _t1 - _t0

Python 3:

从Python 3.3开始，您可以使用 time.perf_counter() (系统范围内的时间)或 time.process_time() (进程计时)，就像您以前使用time.clock()的方式一样:

Python 3:

Since Python 3.3 you can use time.perf_counter() (system-wide timing) or time.process_time() (process-wide timing), just the way you used to use time.clock():

from time import process_time

t = process_time()
#do some stuff
elapsed_time = process_time() - t

新功能process_time将不包括睡眠时间.

The new function process_time will not include time elapsed during sleep.

从Python 3.7开始，您还可以使用 process_time_ns() 类似于process_time()，但返回时间以纳秒为单位.

Since Python 3.7 you can also use process_time_ns() which is similar to process_time()but returns time in nanoseconds.

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