python中的timeit模块无法识别numpy模块 [英] timeit module in python does not recognize numpy module

问题描述

我想测试2个相同列表之间的处理时间，特别是对于普通列表和numpy列表.我的代码是

I want to test the processing time between 2 identical lists, specifically for a normal list and a numpy list. My code is

import timeit
import numpy as np

t = timeit.Timer("range(1000)")
print t.timeit()

u = timeit.Timer("np.arange(1000)")
print u.timeit()

对于t的计算很好，但是对于u的NameError:列出了未定义的全局名称'np'.

Calculation for t is fine, but for u NameError: global name 'np' is not defined is listed.

我应该如何编码以获得处理时间?

How should I code it to get the processing time?

推荐答案

timeit.Timer 类可以以两种不同的方式使用.

The timeit.Timer class can be used in two different ways.

它可以采用源代码进行编译执行-在这种情况下，该代码在仅运行setup代码的全新环境中执行，或者可以采用可调用的形式，在这种情况下，可调用的只是被调用(在您当前的环境中，与其他任何可调用对象一样).

It can either take source code to be compiled an executed—in which case, the code is executed in a fresh environment where only the setup code has been run, or it can take a callable, in which case the callable is just called (in your current environment, like any other callable).

因此，您有两个选择:

u = timeit.Timer("np.arange(1000)", setup='import numpy as np')

…或…

u = timeit.Timer(lambda: np.arange(1000))

在第一种情况下，您恰好完成了import numpy as np的事实是无关紧要的；它对编译和执行np.arange(1000)的环境没有影响(因此必须将其包含在setup=...位中).

In the first case, the fact that you happen to have done an import numpy as np is irrelevant; it has no effect on the environment in which np.arange(1000) is compiled and executed (and thus you must include it in the setup=... bit).

在第二种情况下，您已经完成了import numpy as np显然是 的事实-它会影响您的代码(包括lambda: np.arange(1000))得到评估的环境.

In the second case, the fact that you've done an import numpy as np obviously is relevant—it affects the environment in which your code, including the lambda: np.arange(1000), gets evaluated.

这篇关于python中的timeit模块无法识别numpy模块的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！