[Numpy-discussion] How to Capitalize numpy?

Joe Harrington jh at physics.ucf.edu
Mon Sep 16 17:32:33 EDT 2019


Here are my thoughts on textual capitalization (at first, I thought you 
wanted to raise money!):

We all agree that in code, it is "numpy".  If you don't use that, it 
throws an error.  If, in text, we keep "numpy" with a forced lower-case 
letter at the start, it is just one more oddball to remember.  It is 
even weirder in titles and the beginnings of sentences.  I'd strongly 
like not to be weird that way.  A few packages are, it's annoying, and 
it doesn't much earn them any goodwill. The default among people who are 
not "in the know" will be to do what they're used to.  Let's give them 
what they're used to, a proper noun with initial (at least) capital.

Likewise, I object to preferring a particular font.  What fonts to use 
for the names of things like software packages is a decision for 
publications to make.  A journal or manual might make fine distinctions 
and demand several different, specific fonts, while a popular 
publication might prefer not to do that.  Leave the typesetting to the 
editors of the publications.  We can certainly adopt a standard for our 
publications (docs, web pages, etc.), but we should state explicitly 
that others can do as they like.

It's not an acronym, so that leaves the options of "Numpy" and "NumPy".  
It would be great, easy to remember, consistent for others, etc., if 
NumPy and SciPy were capitalized the same way and were pronounced the 
same (I still occasionally hear "numpee"). So, I would favor "NumPy" to 
go along with "SciPy", and let the context choose the font.

--jh--


On 9/16/19 9:09 PM, Chris Barker <chris.barker at noaa.gov> wrote:





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 <mailto: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
    <mailto:shoyer at gmail.com>> wrote:
     >
     >
     >
     > On Wed, Aug 7, 2019 at 6:18 PM Charles R Harris
    <charlesr.harris at gmail.com <mailto:charlesr.harris at gmail.com>> wrote:
     >>
     >>
     >>
     >> On Wed, Aug 7, 2019 at 7:10 PM Stephan Hoyer <shoyer at gmail.com
    <mailto:shoyer at gmail.com>> wrote:
     >>>
     >>> On Wed, Aug 7, 2019 at 5:11 PM Ralf Gommers
    <ralf.gommers at gmail.com <mailto:ralf.gommers at gmail.com>> wrote:
     >>>>
     >>>>
     >>>> On Mon, Aug 5, 2019 at 6:18 PM Stephan Hoyer <shoyer at gmail.com
    <mailto:shoyer at gmail.com>> wrote:
     >>>>>
     >>>>> On Mon, Aug 5, 2019 at 2:48 PM Ralf Gommers
    <ralf.gommers at gmail.com <mailto: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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