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