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Author tim.peters mark.dickinson, njs, rhettinger, serhiy.storchaka, tim.peters 2019-08-12.00:40:40 -1.0 Yes <1565570440.61.0.139863913831.issue37807@roundup.psfhosted.org>
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```I agree:  we "shouldn't have" documented anything about hash codes beyond the invariants needed to guarantee they work for their intended purpose, chiefly that x == y implies hash(x) == hash(y).

Which leads to your other question ;-)  That invariant is tricky to maintain across a pile of distinct but comparable numeric types!  Whatever we return for an int needs also to be what's returned for a float that happens to have the same value, and whatever we return for a float needs also to be what's returned for a fraction.Fraction with the same value, and so on.

So Python uses a single numeric hashing algorithm defined on mathematical rationals, described here:

https://docs.python.org/3.8/library/stdtypes.html#hashing-of-numeric-types

Presumably that's documented so that people defining their own numeric types have a clue about how to implement compatible hash codes.

Anyway, that algorithm uses a large fixed prime P (different on 32- and 64-bit boxes), and uses operations modulo P.  That's why the full bit width isn't used.  And not just any prime P, it picks one for which computing the remainder mod P is especially efficient.  2**61 - 1 is as good as it gets on 64 bit boxes.

I didn't pick this algorithm (I suspect Mark did), but I certainly approve of it.  It's clever and general enough to apply to any plausible subset-of-real numeric type short of the constructive reals (where equality isn't even theoretically decidable, so "x == y implies ..." can't get off the ground ;-) ).```
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Date User Action Args
2019-08-12 00:40:40tim.peterssetrecipients: + tim.peters, rhettinger, mark.dickinson, njs, serhiy.storchaka