[issue43475] Worst-case behaviour of hash collision with float NaN

[Mark Dickinson]

Mark Dickinson <dickinsm at gmail.com> added the comment:

Hmm. On second thoughts, the proposed solution wouldn't actually *help* with the situation I gave: the elements (lazily) realised from the NumPy array are highly likely to all end up with the same address in RAM. :-(

>>> x = np.full(10, np.nan)
>>> for v in x:
...     print(id(v))
...     del v
... 
4601757008
4601757008
4601757008
4601757008
4601757008
4601757008
4601757008
4601757008
4601757008
4601757008

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Python tracker <report at bugs.python.org>
<https://bugs.python.org/issue43475>
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