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

Hameer Abbasi einstein.edison at gmail.com
Mon Jun 4 00:47:15 EDT 2018

Mixed return values of NotImplementedButCoercible and NotImplemented would still result in TypeError, and there would be no second chances for overloads.

I would like to differ with you here: It can be quite useful to have second chances for overloads. Think np.func(list, custom_array)): If second rounds did not exist, custom_array would need to have a list of coercible types (which is not nice IMO).

It can also help in cases where performance/feature degradation isn’t an issue, so coercing all arguments that returned NotImplementedButCoercible would allow __array_function__ to succeed where it wouldn’t normally. I mean, that’s one of the major uses of this sentinel right?

If done in a for loop, it wouldn’t even slow down the nominal cases. It would have the adverse effect of not allowing for a default implementation to be as simple as you stated, though.

One thing we could do is manually (inside __array_function__) coerce anything that didn’t implement __array_function__, and that’s acceptable to me too. -------------- next part -------------- An HTML attachment was scrubbed... URL: <http://mail.python.org/pipermail/numpy-discussion/attachments/20180603/e292b4ef/attachment-0001.html>

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