[Numpy-discussion] How to Capitalize numpy?

Mon Sep 16 15:09:19 EDT 2019

Trivial note:

On the subject of naming things (spelling things??) -- should it be:

numpy
or
Numpy
or
NumPy
?

All three are in the draft NEP 30 ( mostly "NumPy", I noticed this when
reading/copy editing the NEP) . Is there an "official" capitalization?

My preference, would be to use "numpy", and where practicable, use a
"computer" font -- i.e. ``numpy`` in RST.

But if there is consensus already for anything else, that's fine, I'd just
like to know what it is.

-CHB

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
> on clarifying the text. After reading the detailed description, I've
> decided to add a subsection "Scope" to clarify the scope where NEP-30
> would be useful. I think the inclusion of this new subsection
> complements the "Detail description" forming a complete text w.r.t.
> motivation of the NEP, but feel free to point out disagreements with
> my suggestion. I've also added a new section "Usage" pointing out how
> one would use duck array in replacement to np.asarray where relevant.
>
> Regarding the naming discussion, I must say I like the idea of keeping
> the __array_ prefix, but it seems like that is going to be difficult
> given that none of the existing ideas so far play very nicely with
> that. So if the general consensus is to go with __numpy_like__, I
> would also update the NEP to reflect that changes. FWIW, I
> particularly neither like nor dislike __numpy_like__, but I don't have
> any better suggestions than that or keeping the current naming.
>
> Best,
> Peter
>
> On Thu, Aug 8, 2019 at 3:40 AM Stephan Hoyer <shoyer at gmail.com> wrote:
> >
> >
> >
> > On Wed, Aug 7, 2019 at 6:18 PM Charles R Harris <
> charlesr.harris at gmail.com> wrote:
> >>
> >>
> >>
> >> On Wed, Aug 7, 2019 at 7:10 PM Stephan Hoyer <shoyer at gmail.com> wrote:
> >>>
> >>> On Wed, Aug 7, 2019 at 5:11 PM Ralf Gommers <ralf.gommers at gmail.com>
> wrote:
> >>>>
> >>>>
> >>>> On Mon, Aug 5, 2019 at 6:18 PM Stephan Hoyer <shoyer at gmail.com>
> wrote:
> >>>>>
> >>>>> On Mon, Aug 5, 2019 at 2:48 PM Ralf Gommers <ralf.gommers at gmail.com>
> wrote:
> >>>>>
> >>>>>>
> >>>>>> The NEP currently does not say who this is meant for. Would you
> expect libraries like SciPy to adopt it for example?
> >>>>>>
> >>>>>> The NEP also (understandably) punts on the question of when
> something is a valid duck array. If you want this to be widely used, that
> will need an answer or at least some rough guidance though. For example, we
> would expect a duck array to have a mean() method, but probably not a ptp()
> method. A library author who wants to use np.duckarray() needs to know,
> because she can't test with all existing and future duck array
> implementations.
> >>>>>
> >>>>>
> >>>>> I think this is covered in NEP-22 already.
> >>>>
> >>>>
> >>>> It's not really. We discussed this briefly in the community call
> today, Peter said he will try to add some text.
> >>>>
> >>>> We should not add new functions to NumPy without indicating who is
> supposed to use this, and what need it fills / problem it solves. It seems
> pretty clear to me that it's mostly aimed at library authors rather than
> end users. And also that mature libraries like SciPy may not immediately
> adopt it, because it's too fuzzy - so it's new libraries first, mature
> libraries after the dust has settled a bit (I think).
> >>>
> >>>
> >>> I totally agree -- we definitely should clarify this in the docstring
> and elsewhere in the docs. An example in the new doc page on "Writing
> custom array containers" (
> https://numpy.org/devdocs/user/basics.dispatch.html) would also probably
> be appropriate.
> >>>
> >>>>>
> >>>>> As discussed there, I don't think NumPy is in a good position to
> pronounce decisive APIs at this time. I would welcome efforts to try, but I
> don't think that's essential for now.
> >>>>
> >>>>
> >>>> There's no need to pronounce a decisive API that fully covers duck
> array. Note that RNumPy is an attempt in that direction (not a full one,
> but way better than nothing). In the NEP/docs, at least saying something
> along the lines of "if you implement this, we recommend the following
> strategy: check if a function is present in Dask, CuPy and Sparse. If so,
> it's reasonable to expect any duck array to work here. If not, we suggest
> you indicate in your docstring what kinds of duck arrays are accepted, or
> what properties they need to have". That's a spec by implementation, which
> is less than ideal but better than saying nothing.
> >>>
> >>>
> >>> OK, I agree here as well -- some guidance is better than nothing.
> >>>
> >>> Two other minor notes on this NEP, concerning naming:
> >>> 1. We should have a brief note on why we settled on the name "duck
> array". Namely, as discussed in NEP-22, we don't love the "duck" jargon,
> but we couldn't come up with anything better since NumPy already uses
> "array like" and "any array" for different purposes.
> >>> 2. The protocol should use *something* more clearly namespaced as
> NumPy specific than __duckarray__. All the other special protocols NumPy
> defines start with "__array_". That suggests either __array_duckarray__
> (sounds a little redundant) or __numpy_duckarray__ (which I like the look
> of, but is a different from the existing protocols).
> >>>
> >>
> >> `__numpy_like__` ?
> >
> >
> >
> > This could work, but I think we would also want to rename the NumPy
> function itself to either np.like or np.numpy_like. The later is a little
> redundant but definitely more self-descriptive than "duck array".
> >
> >>
> >> Chuck
> >> _______________________________________________
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> >
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