On 13 February 2018 at 02:14, David Mertz <me...@gnosis.cx> wrote:
> NumPy np.bool_ is specifically not a subclass of any np.int_.  If it we're,
> there would be an ambiguity between indexing with a Boolean array and an
> array of ints. Both are meaningful, but they mean different things (mask vs
> collection of indices).
> Do we have other examples a Python ABC that exists to accommodate something
> outside the standard library or builtins? Even if not, NumPy is special...
> the actual syntax for '@' exists primarily for that library!

collections.abc.Sequence and collections.abc.Mapping come to mind -
the standard library doesn't tend to distinguish between different
kinds of subscriptable objects, but it's a distinction some third
party libraries and tools want to be able to make reliably.

The other comparison that comes to mind would be the distinction
between "__int__" ("can be coerced to an integer, but may lose
information in the process") and "__index__" ("can be losslessly
converted to and from a builtin integer").

Right now, we only define boolean coercion via "__bool__" - there's no
mechanism to say "this *is* a boolean value that can be losslessly
converted to and from the builtin boolean constants". That isn't a
distinction the standard library makes, but it sounds like it's one
that NumPy cares about (and NumPy was also the main driver for
introducing __index__).


Nick Coghlan   |   ncogh...@gmail.com   |   Brisbane, Australia
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