Raymond Hettinger <raymond.hettin...@gmail.com> added the comment:
> If one wants to have all NaNs in one equivalency class > (e.g. if used as a key-value for example in pandas) it > is almost impossible to do so in a consistent way > without taking a performance hit. ISTM the performance of the equivalent class case is far less important than the one we were trying to solve. Given a choice we should prefer helping normal unadorned instances rather than giving preference to a subclass that redefines the usual behaviors. In CPython, it is a fact of life that overriding builtin behaviors with pure python code always incurs a performance hit. Also, in your example, the subclass isn't technically correct because it relies on a non-guaranteed implementation details. It likely isn't even the fastest approach. The only guaranteed behaviors are that math.isnan(x) reliably detects a NaN and that x!=x when x is a NaN. Those are the only assured tools in the uphill battle to fight the weird intrinsic nature of NaNs. So one possible solution is to replace all the NaNs with a canonical placeholder value that doesn't have undesired properties: {None if isnan(x) else x for x in arr} That relies on guaranteed behaviors and is reasonably fast. IMO that beats trying to reprogram float('NaN') to behave the opposite of how it was designed. ---------- _______________________________________ Python tracker <rep...@bugs.python.org> <https://bugs.python.org/issue43475> _______________________________________ _______________________________________________ Python-bugs-list mailing list Unsubscribe: https://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com