Hi everyone,
> On 23. Aug 2018, at 17:35, Stephan Hoyer <sho...@gmail.com> wrote:
>
>> On Tue, Aug 21, 2018 at 6:57 PM Nathaniel Smith <n...@pobox.com> wrote:
>> I mean, the idea of the envvar is to be a temporary measure enable
>> devs to experiment with a provisional feature, while being awkward
>> enough that people don't build lots of stuff assuming its there. It
>> doesn't have to 100% supported in every environment.
>
> My understanding of the idea of the envvar is to obtain informed consent from
> NumPy users, e.g., "I understand that this is a unsupported experimental
> feature that may be removed in the future without warning."
>
> It's pretty important for me personally that's it's possible to use this in a
> flexible set of environments, and in particular to have something that works
> in my preferred notebook environment. How else are we going to test this?
>
> Every limitation that we put into the experimental version of this feature
> decreases the likelihood that it gets used enough to know if it's even a
> viable solution. If it's too awkward, nobody's even going to bother testing
> it, and this whole effort will fall flat on its face.
>
>> > I'm in complete agreement that only authors of end-user applications should
>> > invoke this option, but just because something is technically possible
>> > doesn't mean that people will actually do it or that we need to support
>> > that
>> > use case :).
>>
>> I didn't say "authors of end-user applications", I said "end-users" :-).
>
> These are mostly the same for NumPy, but I do disagree with you here.
> Ultimately we have to trust application developers to make the right choices
> for their tools. If they are willing to accept that maintenance burden of
> either (1) potentially being stuck on NumPy 1.16 forever or (2) needing to
> rewrite their code, that's their tradeoff to make. It's a little preposterous
> to force this decision onto end-users, who may not even know a tool is
> written in NumPy.
>
>> That said, I dunno. My intuition is that if we have a function call
>> like this then libraries that define __array_function__ will merrily
>> call it in their package __init__ and it accomplishes nothing, but
>> maybe I'm being too cynical and untrusting.
>
> People can do lots of dumb things in Python (e.g., monkeypatching) -- the
> language doesn't stop them. Fortunately this mostly isn't a problem.
I might add that most duck array authors are highly unlikely to be newcomers to
the Python space. We should just put a big warning there while enabling and
that’ll be enough to scare away most devs from doing it by default.
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Best Regards,
Hameer Abbasi
Sent from my iPhone
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