问题描述
我想关闭ZeroDivisionError。我想要0./0。只要给NaN，
，输出时，只需打印''NaN''。我注意到fpconst有所需的
常量。我不想显着减慢浮点数学，所以我
不想只是捕获异常。
如果我使用C关闭硬件信号的代码，会阻止python从
检测到异常，或者是python检查它的分母是否为b
拥有（希望不是，这将浪费周期。
I''d like to turn off ZeroDivisionError. I''d like 0./0. to just give NaN,
and when output, just print ''NaN''. I notice fpconst has the required
constants. I don''t want to significantly slow floating point math, so I
don''t want to just trap the exception.
If I use C code to turn off the hardware signal, will that stop python from
detecting the exception, or is python checking for 0 denominator on it''s
own (hope not, that would waste cycles).
推荐答案
是的，Python确实对零分母进行了明确的检查。这里是
摘自于Objects / floatobject.c中的floatdiv.c：
if（b == 0.0）{
PyErr_SetString（PyExc_ZeroDivisionError，float division）;
返回NULL;
}
这可能是在进行浮动分割时，只有理智的方式来处理
平台行为的差异。
Yes, Python does do an explicit check for a zero denominator. Here''s
an excerpt from floatdiv.c in Objects/floatobject.c:
if (b == 0.0) {
PyErr_SetString(PyExc_ZeroDivisionError, "float division");
return NULL;
}
This is probably the only sane way to deal with differences in
platform behaviour when doing float divisions.
是的，Python确实对零分母进行了明确的检查。这里是
摘自于Objects / floatobject.c中的floatdiv.c：
if（b == 0.0）{
PyErr_SetString（PyExc_ZeroDivisionError，float division）;
返回NULL;
}
这可能是在做浮动分割时，只有理智的方式来处理
平台行为的差异。
Yes, Python does do an explicit check for a zero denominator. Here''s
an excerpt from floatdiv.c in Objects/floatobject.c:
if (b == 0.0) {
PyErr_SetString(PyExc_ZeroDivisionError, "float division");
return NULL;
}
This is probably the only sane way to deal with differences in
platform behaviour when doing float divisions.
你确定吗？
很可能是1 /（尽可能小的数字）>（最大的
可能的数字）。因此，除了陷阱之外，我还会捕获任何错误。
明显的零分区。
Are you sure?
It could very well be that 1/(smallest possible number)>(greatest
possible number). So I would also trap any errors besides trapping for
the obvious zero division.
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