Python循环比Excel VBA慢？

我在excel(VBA)和python执行简单循环之间进行了一些测试.代码如下.令我惊讶的是,vba明显快于python.快了近6倍.我认为,由于python在命令行中运行,因此性能会更好.你们对此有何评论？

Python

import time
import ctypes  # An included library with Python install.
start_time = time.time()

for x in range(0, 1000000):
    print x

x = ("--- %s seconds ---" % (time.time() - start_time))
ctypes.windll.user32.MessageBoxA(0, x, "Your title", 1)

Excel(VBA)

Sub looptest()

Dim MyTimer As Double

MyTimer = Timer

Dim rng As Range, cell As Range
Set rng = Range("A1:A1000000")

x = 1
For Each cell In rng

    cell.Value = x
    x = x + 1
Next cell


MsgBox Timer - MyTimer
End Sub

解决方法:

你的两个代码示例没有做同样的事情.在Python代码中,内部循环必须：

>询问范围内的下一个数字(0,1000000).
>显示它.

在VBA代码中,Excel必须：

>请求Range中的下一个单元格(“A1：A1000000”)(与Python范围无关).
>设置cell.Value属性.
>运行各种代码Excel只要更改单元格就会执行.
>检查是否需要重新计算任何公式.
>显示它.
>递增x.

让我们重写一下,让Python和VBA循环做同样的事情,尽可能接近：

Python

import time
import ctypes
start_time = time.time()

x = 0
while x <= 1000000:
    x = x + 1

x = ("--- %s seconds ---" % (time.time() - start_time))
ctypes.windll.user32.MessageBoxA(0, x, "Your title", 1)

VBA

Declare Function QueryPerformanceCounter Lib "kernel32" (t As Currency) As Boolean
Declare Function QueryPerformanceFrequency Lib "kernel32" (t As Currency) As Boolean

Sub looptest()
    Dim StartTime As Currency
    QueryPerformanceCounter StartTime

    x = 0
    Do While x <= 1000000
        x = x + 1
    Loop

    Dim EndTime As Currency
    QueryPerformanceCounter EndTime
    Dim Frequency As Currency
    QueryPerformanceFrequency Frequency

    MsgBox Format$((EndTime - StartTime) / Frequency, "0.000")
End Sub

在我的计算机上,Python需要大约96毫秒,而VBA 33毫秒 – VBA的执行速度要快三倍.如果你投入Dim x As Long,它的速度会提高六倍.

为什么？那么,让我们来看看每个如何运行. Python在内部将.py文件编译为.pyc,并在Python VM下运行它. Another answer describes the Python case in detail. Excel将VBA编译为MS P-Code,并在Visual Basic VM下运行它.

此时,python.exe是命令行并且Excel是GUI并不重要. VM运行您的代码,它在您的计算机内部生活得更深一些.性能取决于已编译代码中的特定指令,以及VM运行这些指令的效率.在这种情况下,VB VM运行其P-Code的速度比Python VM运行其.pyc的速度快.

标签：python,excel,excel-vba,vba
来源： https://codeday.me/bug/20190716/1476321.html