Alexander Belopolsky wrote:
> Travis Oliphant <oliphant.travis <at> ieee.org> writes:
>
>
>>>>b = buffer(array('d', [1,2,3]))
>
>
> there is not much that I can do with b. For example, if I want to pass it to
> numpy, I will have to provide the type and shape information myself:
>
>
>>>>numpy.ndarray(shape=(3,), dtype=float, buffer=b)
>
> array([ 1., 2., 3.])
>
> With the extended buffer protocol, I should be able to do
>
>
>>>>numpy.array(b)
or just
numpy.array(array.array('d',[1,2,3]))
and leave-out the buffer object all together.
>
>
> So let's start by solving this problem and limit it to data that can be found
> in a standard library array. This way we can postpone the discussion of
> shapes,
> strides and nested structs.
Don't lump those ideas together. Shapes and strides are necessary for
N-dimensional array's (it's essentially what *defines* the N-dimensional
array). I really don't want to sacrifice those in the extended buffer
protocol. If you want to separate them into different functions then
that is a possibility.
>
> If we manage to agree on the standard way to pass primitive type information,
> it will be a big achievement and immediately useful because simple arrays are
> already in the standard library.
>
We could start there, I suppose. Especially if it helps us all get on
the same page. But, we already see the applications beyond this simple
case so I would like to have at least an "eye" for the more difficult
case which we already have a working solution for in the "array interface"
-Travis
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