[Numpy-discussion] NEP: Dispatch Mechanism for NumPy’s high level API (original) (raw)

Stephan Hoyer shoyer at gmail.com
Tue Jun 5 14:49:00 EDT 2018

On Mon, Jun 4, 2018 at 7:35 AM Marten van Kerkwijk < m.h.vankerkwijk at gmail.com> wrote:

Hi Stephan,

Another potential consideration in favor of NotImplementedButCoercible is for subclassing: we could use it to write the default implementations of ndarray.arrayufunc and ndarray.arrayfunction, e.g.,

class ndarray: def arrayufunc(self, *args, **kwargs): return NotIImplementedButCoercible def arrayfunction(self, *args, **kwargs): return NotIImplementedButCoercible I think (not 100% sure yet) this would result in exactly equivalent behavior to what ndarray.arrayufunc currently does: http://www.numpy.org/neps/nep-0013-ufunc-overrides.html#subclass-hierarchies As written would not work for ndarray subclasses, because the subclass will generically change itself before calling super. At least for Quantity, say if I add two quantities, the quantities will both be converted to arrays (with one scaled so that the units match) and then the super call is done with those modified arrays. This expects that the super call will actually return a result (which it now can because all inputs are arrays).

Thanks for clarifying. This is definitely trickier than I had thought.

If Quantity.array_ufunc implemented overrides by calling the public ufunc method again (instead of calling super), then it would still work fine with this change. But of course, in that case you would not need ndarray.array_ufunc defined at all.

I will say that personally, I find the complexity of the current ndarray.array_ufunc implementation a little inelegant, and I would welcome simplifying it. But I also try to avoid implementation inheritance entirely [2], for exactly the same reasons why refactoring ndarray.array_ufunc here would be difficult (inheritance is fragile). So I would be happy to defer to your judgment, as someone who actually uses subclassing.

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