Python：巨大幂运算陷入困境，但不会引发错误 [英] Python: Huge Exponentiation Gets STUCK, but DOESN'T Raise An Error

问题描述

我在Win10 x64上使用Python 3.6。

I am using Python 3.6 on Win10 x64.

print(10**10**10**10)

这不是引发错误吗？当我运行此程序时，它什么也不会打印，但不会出现任何错误。没有OverflowError，没有MemoryError，什么也没有。现在已经运行了大约10分钟。我认为，它正在忙于计算？我怎么知道实际发生了什么？

Shouldn't this raise an Error? When I run this, it just doesn't print anything, but no error is raised. No OverflowError, no MemoryError, nothing. It has been running for like 10 minutes now. I assume, it is busy calculating? How can I find out, what is actually happening?

它还没有完成脚本。（即PyCharm没有显示退出代码0）为什么

It's not finishing the script. (i.e. PyCharm is not printing exit code 0) Why is that?

更普遍的是：

如果我遇到这种情况，该如何处理不知道预先涉及的计算量吗？我想避免脚本像永远那样卡住，而不会给我任何类型的错误。

How do I catch a situation like this, if I don't know the magnitude of the calculations involved in advance? I want to stop the script from getting stuck like this "forever" without giving me any sort of error to work with.

。

解决方案：

如以下Arthur Spoon所指出的，<$使用整数时，不会引发c $ c> OverflowError 。如果您想捕获太大而无法在合理的时间内进行计算错误，则在这些情况下仅显式使用浮点数是最容易的。

As pointed out by Arthur Spoon below, the OverflowError is not raised when working with integers. If you want to be able to catch a "too large to compute in reasonable time"-error, it's easiest to just explicitly work only with floats in these circumstances.

至少这对幂运算有效，因为 print（10 ** 10 ** 10.0）已经抛出了 OverflowError 。

At least this works with exponentiation since print(10**10**10.0) already throws the OverflowError.

另一种选择是使用 signal 之类的东西来限制执行时间那段脚本。

The other option would be using something like the signal to limit the execution time of that piece of your script.

推荐答案

答案在 OverflowError ：

异常OverflowError

exception OverflowError

在算术运算的结果太大而无法表示时引发。对于整数而言，这种情况不会发生（宁可引发MemoryError而不是放弃）。

Raised when the result of an arithmetic operation is too large to be represented. This cannot occur for integers (which would rather raise MemoryError than give up).

因此，解决方案是，我猜想：与浮动数字。但是，文档的其余部分也说明了大多数浮点运算也未得到检查的事实……我知道一个事实，即太大的 exp（x）会引发 OverflowError 。

So the solution is, I guess: explicitly work with float numbers. However the rest of the documentation says something about most floating point operations not being checked either... I know for a fact that a too big exp(x) will raise an OverflowError.

编辑：为您解决该问题的解决方案可能是根据您自己引发Exception python执行一些您感兴趣的代码所花费的时间。我不是这样做的专家，但是您有几种可能的方式来做到这一点此处。

a solution to deal with that problem for you would probably be to raise an Exception yourself depending on the time it takes python to execute a bit of code you're interested in. I'm no expert in doing that, but you have a few possible ways of doing that here.

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