[Numpy-discussion] NEP 30 - Duck Typing for NumPy Arrays - Implementation

[Peter Andreas Entschev]

What would be the use case for a duck-array to implement __array__ and
return a NumPy array? Unless I'm missing something, this seems
redundant and one should just use array/asarray functions then. This
would also prevent error-handling, what if the developer intentionally
wants a NumPy-like array (e.g., the original array passed to the
duckarray function) or an exception (instead of coercing to a NumPy
array)?

On Mon, Sep 16, 2019 at 9:25 PM Chris Barker <chris.barker at noaa.gov> wrote:
>
>
>
> On Mon, Aug 12, 2019 at 4:02 AM Peter Andreas Entschev <peter at entschev.com> wrote:
>>
>> Apologies for the late reply. I've opened a new PR
>> https://github.com/numpy/numpy/pull/14257 with the changes requested
>
>
> thanks!
>
> I've written a small PR on your PR:
>
> https://github.com/pentschev/numpy/pull/1
>
> Essentially, other than typos and copy editing, I'm suggesting that a duck-array could choose to implement __array__ if it so chooses -- it should, of course, return an actual numpy array.
>
> I think this could be useful, as much code does require an actual numpy array, and only that class itself knows how best to convert to one.
>
> -CHB
>
> --
>
> Christopher Barker, Ph.D.
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