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@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@pearwood.info
 >     > <mailto:steve@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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