[Python-ideas] Vectorization [was Re: Add list.join() please]

[Adrien Ricocotam]

I think the actual proposal is having a new type of list (ie : vectors)
that works like numpy but for any data.
Instead of a list where the user has to be sure all the data is the same
type, vectors makes him-er sure it's full of the same data than can me
processed using a particular function (as s-he would do with map).

I think the syntax proposed is not cool, it's kinda unique in python and
doesn't feel pythonic to me. A thing I thought about but I'm not satisfy is
using the new matrix-multiplication operator:

    my_string_vector @ str.lower

    def compute_grad(a_student):
        return "you bad"
    my_student_vector @ compute_grad

But it's a bit confusing to me.

Le ven. 1 févr. 2019 à 17:04, Kirill Balunov <kirillbalunov at gmail.com> a
écrit :

>
>
> пт, 1 февр. 2019 г. в 02:24, Steven D'Aprano <steve at pearwood.info>:
>
>> On Thu, Jan 31, 2019 at 09:51:20AM -0800, Chris Barker via Python-ideas
>> wrote:
>>
>> > I do a lot of numerical programming, and used to use MATLAB and now
>> numpy a
>> > lot. So I am very used to "vectorization" -- i.e. having operations that
>> > work on a whole collection of items at once.
>> [...]
>> > You can imagine that for more complex expressions the "vectorized"
>> approach
>> > can make for much clearer and easier to parse code. Also much faster,
>> which
>> > is what is usually talked about, but I think the readability is the
>> bigger
>> > deal.
>>
>> Julia has special "dot" vectorize operator that looks like this:
>>
>>      L .+ 1   # adds 1 to each item in L
>>
>>      func.(L)   # calls f on each item in L
>>
>> https://julialang.org/blog/2017/01/moredots
>>
>> The beauty of this is that you can apply it to any function or operator
>> and the compiler will automatically vectorize it. The function doesn't
>> have to be written to specifically support vectorization.
>>
>>
> IMO, the beauty of vector type is that it contains homogeneous data.
> Therefore, it allows you to ensure that the method is present for each
> element in the vector. The first given example is what numpy is all about
> and without some guarantee that L consists of homogeneous data it hardly
> make sense. The second one is just `map`. So I can't catch what you are
> proposing:
>
> 1. To make an operator form of `map`.
> 2. To pull numpy into stdlib.
> 3. Or something else, which is not obvious to me from the examples given.
>
> With kind regards,
> -gdg
>
>
>>
>> > So what does this have to do with the topic at hand?
>> >
>> > I know that when I'm used to working with numpy and then need to do some
>> > string processing or some such, I find myself missing this
>> "vectorization"
>> > -- if I want to do the same operation on a whole bunch of strings, why
>> do I
>> > need to write a loop or comprehension or map? that is:
>> >
>> > [s.lower() for s in a_list_of_strings]
>> >
>> > rather than:
>> >
>> > a_list_of_strings.lower()
>>
>> Using Julia syntax, that might become a_list_of_strings..lower(). If you
>> don't like the double dot, perhaps str.lower.(a_list_of_strings) would
>> be less ugly.
>>
>>
>>
>> --
>> Steven
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