[Numpy-discussion] Keep __array_function__ unexposed by default for 1.17?

Ralf Gommers ralf.gommers at gmail.com
Thu May 23 05:41:39 EDT 2019


On Thu, May 23, 2019 at 3:02 AM Marten van Kerkwijk <
m.h.vankerkwijk at gmail.com> wrote:

>
> If we want to keep an "off" switch we might want to add some sort of API
>> for exposing whether NumPy is using __array_function__ or not. Maybe
>> numpy.__experimental_array_function_enabled__ = True, so you can just test
>> `hasattr(numpy, '__experimental_array_function_enabled__')`? This is
>> assuming that we are OK with adding an underscore attribute to NumPy's
>> namespace semi-indefinitely.
>>
>
I don't think we want to add or document anything publicly. That only adds
to the configuration problem, and indeed makes it harder to rely on the
issue. All I was suggested was keeping some (private) safety switch in the
code base for a while in case of real issues as a workaround.



> Might this be overthinking it? I might use this myself on supercomputer
> runs were I know that I'm using arrays only. Though one should not
> extrapolate from oneself!
>
> That said, it is not difficult as is. For instance, we could explain in
> the docs that one can tell from:
> ```
> enabled = hasattr(np.core, 'overrides') and
> np.core.overrides.ENABLE_ARRAY_FUNCTION
>
```
> One could even allow for eventual removal by explaining it should be,
> ```
> enabled = hasattr(np.core, 'overrides') and getattr(np.core.overrides,
> 'ENABLE_ARRAY_FUNCTION', True)
> ```
> (If I understand correctly, one cannot tell from the presence of
> `ndarray.__array_function__`, correct?)
>

I think a hasattr check for __array_function__ is right.

Ralf


> -- Marten
>
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