[Numpy-discussion] Experimental `like=` attribute for array creation functions

[Ralf Gommers]

Thanks for raising these concerns Ilhan and Juan, and for answering Peter.
Let me give my perspective as well.

To start with, this is not specifically about Peter's NEP and PR. NEP 35
simply follows the pattern set by previous PRs, and given its tight scope
is less difficult to understand than other NEPs on such technical topics.
Peter has done a lot of things right, and is close to the finish line.


On Thu, Aug 13, 2020 at 12:02 PM Peter Andreas Entschev <peter at entschev.com>
wrote:

>
> > I think, arriving to an agreement would be much faster if there is an
> executive summary of who this is intended for and what the regular usage
> is. Because with no offense, all I see is "dispatch", "_array_function_"
> and a lot of technical details of which I am absolutely ignorant.
>
> This is what I intended to do in the Usage Guidance [2] section. Could
> you elaborate on what more information you'd want to see there? Or is
> it just a matter of reorganizing the NEP a bit to try and summarize
> such things right at the top?
>

We adapted the NEP template [6] several times last year to try and improve
this. And specified in there as well that NEP content set to the mailing
list should only contain the sections: Abstract, Motivation and Scope,
Usage and Impact, and Backwards compatibility. This to ensure we fully
understand the "why" and "what" before the "how". Unfortunately that
template and procedure hasn't been exercised much yet, only in NEP 38 [7]
and partially in NEP 41 [8].

If we have long-time maintainers of SciPy (Ilhan and myself), scikit-image
(Juan) and CuPy (Leo, on the PR review) all saying they don't understand
the goals, relevance, target audience, or how they're supposed to use a new
feature, that indicates that the people doing the writing and having the
discussion are doing something wrong at a very fundamental level.

At this point I'm pretty disappointed in and tired of how we write and
discuss NEPs on technical topics like dispatching, dtypes and the like.
People literally refuse to write down concrete motivations, goals and
non-goals, code that's problematic now and will be better/working post-NEP
and usage examples before launching into extensive discussion of the gory
details of the internals. I'm not sure what to do about it. Completely
separate API and behavior proposals from implementation proposals? Make
separate "API" and "internals" teams with the likes of Juan, Ilhan and Leo
on the API team which then needs to approve every API change in new NEPs?
Offer to co-write NEPs if someone is willing but doesn't understand how to
go about it? Keep the current structure/process but veto further approvals
until NEP authors get it right?

I want to make an exception for merging the current NEP, for which the plan
is to merge it as experimental to try in downstream PRs and get more
experience. That does mean that master will be in an unreleasable state by
the way, which is unusual and it'd be nice to get Chuck's explicit OK for
that. But after that, I think we need a change here. I would like to hear
what everyone thinks is the shape that change should take - any of my above
suggestions, or something else?



> > Finally as a minor point, I know we are mostly (ex-)academics but this
> necessity of formal language on NEPs is self-imposed (probably PEPs are to
> blame) and not quite helping. It can be a bit more descriptive in my
> external opinion.
>
> TBH, I don't really know how to solve that point, so if you have any
> specific suggestions, that's certainly welcome. I understand the
> frustration for a reader trying to understand all the details, with
> many being only described in NEP-18 [3], but we also strive to avoid
> rewriting things that are written elsewhere, which would also
> overburden those who are aware of what's being discussed.
>
>
> > I also share Ilhan’s concern (and I mentioned this in a previous NEP
> discussion) that NEPs are getting pretty inaccessible. In a sense these are
> difficult topics and readers should be expected to have *some* familiarity
> with the topics being discussed, but perhaps more effort should be put into
> the context/motivation/background of a NEP before accepting it. One way to
> ensure this might be to require a final proofreading step by someone who
> has not been involved at all in the discussions, like peer review does for
> papers.
>

Some variant of this proposal would be my preference.

Cheers,
Ralf


> [1] https://github.com/numpy/numpy/issues/14441#issuecomment-529969572
> [2]
> https://numpy.org/neps/nep-0035-array-creation-dispatch-with-array-function.html#usage-guidance
> [3] https://numpy.org/neps/nep-0018-array-function-protocol.html
> [4] https://numpy.org/neps/nep-0000.html#nep-workflow
> [5]
> https://mail.python.org/pipermail/numpy-discussion/2019-October/080176.html


[6] https://github.com/numpy/numpy/blob/master/doc/neps/nep-template.rst
[7]
https://github.com/numpy/numpy/blob/master/doc/neps/nep-0038-SIMD-optimizations.rst
[8]
https://github.com/numpy/numpy/blob/master/doc/neps/nep-0041-improved-dtype-support.rst



>
>
> On Thu, Aug 13, 2020 at 3:44 AM Juan Nunez-Iglesias <jni at fastmail.com>
> wrote:
> >
> > I’ve generally been on the “let the NumPy devs worry about it” side of
> things, but I do agree with Ilhan that `like=` is confusing and `typeof=`
> would be a much more appropriate name for that parameter.
> >
> > I do think library writers are NumPy users and so I wouldn’t really make
> that distinction, though. Users writing their own analysis code could very
> well be interested in writing code using numpy functions that will
> transparently work when the input is a CuPy array or whatever.
> >
> > I also share Ilhan’s concern (and I mentioned this in a previous NEP
> discussion) that NEPs are getting pretty inaccessible. In a sense these are
> difficult topics and readers should be expected to have *some* familiarity
> with the topics being discussed, but perhaps more effort should be put into
> the context/motivation/background of a NEP before accepting it. One way to
> ensure this might be to require a final proofreading step by someone who
> has not been involved at all in the discussions, like peer review does for
> papers.
> >
> > Food for thought.
> >
> > Juan.
> >
> > On 13 Aug 2020, at 9:24 am, Ilhan Polat <ilhanpolat at gmail.com> wrote:
> >
> > For what is worth, as a potential consumer in SciPy, it really doesn't
> say anything (both in NEP and the PR) about how the regular users of NumPy
> will benefit from this. If only and only 3rd parties are going to benefit
> from it, I am not sure adding a new keyword to an already confusing
> function is the right thing to do.
> >
> > Let me clarify,
> >
> > - This is already a very (I mean extremely very) easy keyword name to
> confuse with ones_like, zeros_like and by its nature any other
> interpretation. It is not signalling anything about the functionality that
> is being discussed. I would seriously consider reserving such obvious names
> for really obvious tasks. Because you would also expect the shape and ndim
> would be mimicked by the "like"d argument but it turns out it is acting
> more like "typeof=" and not "like=" at all. Because if we follow the
> semantics it reads as "make your argument asarray like the other thing" but
> it is actually doing, "make your argument an array with the other thing's
> type" which might not be an array after all.
> >
> > - Again, if this is meant for downstream libraries (because that's what
> I got out of the PR discussion, cupy, dask, and JAX were the only examples
> I could read) then hiding it in another function and writing with capital
> letters "this is not meant for numpy users" would be a much more convenient
> way to separate the target audience and regular users.
> numpy.astypedarray([[some data], [...]], type_of=x) or whatever else it may
> be would be quite clean and to the point with no ambiguous keywords.
> >
> > I think, arriving to an agreement would be much faster if there is an
> executive summary of who this is intended for and what the regular usage
> is. Because with no offense, all I see is "dispatch", "_array_function_"
> and a lot of technical details of which I am absolutely ignorant.
> >
> > Finally as a minor point, I know we are mostly (ex-)academics but this
> necessity of formal language on NEPs is self-imposed (probably PEPs are to
> blame) and not quite helping. It can be a bit more descriptive in my
> external opinion.
>
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