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

[Adrien Ricocotam]

That's tough. I'd say conver the vector to a list.

But :
my_vector.list()

Would apply list on each element of the vector.

Globally, I'd say if the vector is used as an argument, it's a usual
iterable, if you use a member function (or any other notation like @ or ..
or whatever) it's like map.

Note that it's just my opinion.

Le sam. 2 févr. 2019 à 19:46, MRAB <python at mrabarnett.plus.com> a écrit :

> On 2019-02-02 17:31, Adrien Ricocotam wrote:
>  > I personally would the first option to be the case. But then vectors
> shouldn't be list-like but more generator like.
>  >
> OK, here's another one: if you use 'list(...)' on a vector, does it
> apply to the vector itself or its members?
>
>  >>> list(my_strings)
>
> You might be wanting to convert a vector into a list:
>
> ['one', 'two', 'three']
>
> or convert each of its members onto lists:
>
> Vector([['one'], ['two'], ['three']])
>
>  > Le sam. 2 févr. 2019 à 19:26, MRAB <python at mrabarnett.plus.com> a
> écrit :
>  >
>  >     On 2019-02-02 09:22, Kirill Balunov wrote:
>  >     >
>  >     >
>  >     > сб, 2 февр. 2019 г. в 07:33, Steven D'Aprano <steve at pearwood.info
>  >     > <mailto:steve at pearwood.info>>:
>  >     >
>  >     >
>  >     >     I didn't say anything about a vector type.
>  >     >
>  >     >
>  >     > I agree  you did not say. But since you started a new thread
> from the
>  >     > one where the vector type was a little discussed, it seemed to
> me  that
>  >     > it is appropriate to mention it here. Sorry about that.
>  >     >
>  >     >      > 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.
>  >     >
>  >     >     Of course it makes sense. Even numpy supports inhomogeneous
> data:
>  >     >
>  >     >     py> a = np.array([1, 'spam'])
>  >     >     py> a
>  >     >     array(['1', 'spam'],
>  >     >            dtype='|S4')
>  >     >
>  >     >
>  >     > Yes, numpy, at some degree, supports heterogeneous arrays. But
> not in
>  >     > the way you brought it. Your example just shows homogeneous
> array of
>  >     > type `'|S4'`. In the same way as `np.array([1, 1.234])` will be
>  >     > homogeneous. Of course you can say -  np.array([1, 'spam'],
>  >     > dtype='object'), but in this case it will also be homogeneous
> array, but
>  >     > of type `object`.
>  >     >
>  >     >     Inhomogeneous data may rule out some optimizations, but
> that hardly
>  >     >     means that it "doesn't make sense" to use it.
>  >     >
>  >     >
>  >     > I did not say that it  "doesn't make sense". I only said that
> you should
>  >     > be lucky to call `..method()` on collections of heterogeneous
> data. And
>  >     > therefore, usually this kind of operations imply that you are
> working
>  >     > with a "homogeneous data". Unfortunately, built-in containers
> cannot
>  >     > provide such a guarantee without self-checking. Therefore, in
> my opinion
>  >     > that at the moment such an operator is not needed.
>  >     >
>  >     Here's a question: when you use a subscript on a vector, does it
> apply
>  >     to the vector itself, or its members?
>  >
>  >     For example, given:
>  >
>  >      >>> my_strings = Vector(['one', 'two', 'three'])
>  >
>  >     what is:
>  >
>  >      >>> my_strings[1 : ]
>  >
>  >     ?
>  >
>  >     Is it:
>  >
>  >     Vector(['ne', 'wo', 'hree'])
>  >
>  >     or:
>  >
>  >     Vector(['two', 'three'])
>  >
>  >     ?
>
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