On Sun, Oct 10, 2021 at 7:25 AM Facundo Batista <facundobatista@gmail.com> wrote:
Hello everyone!

I need to pack a long list of numbers into shared memory, so I thought
about using `struct.pack_into`.

Its signature is

    struct.pack_into(format, buffer, offset, v1, v2, ...)

I have a long list of nums (several millions), ended up doing the following:

    struct.pack_into(f'{len(nums)}Q', buf, 0, *nums)

However, passing all nums as `*args` is very inefficient [0]. So I
started wondering why we don't have something like:

    struct.pack_into(format, buffer, offset, values=values)

which would receive the list of values directly.

Is that because my particular case is very uncommon? Or maybe we *do*
want this but we don't have it yet? Or do we already have a better way
of doing this?

Thanks!

[0] https://linkode.org/#95ZZtVCIVtBbx72dURK7a4

My first reaction on seeing things like this is "Why not use a numpy.array?"

Does what you have really need to be a long list?  If so, that's already a huge amount of Python object storage as it is. Is it possible for your application to have kept that in a numpy array for the entirety of the data lifetime?  https://numpy.org/doc/stable/reference/routines.array-creation.html

I'm not saying the stdlib shouldn't have a better way to do this by not abusing *args as an API, just that other libraries solve the larger problem of data-memory-inefficiency in their own way already.

(neat tricks from others regarding stdlib array, shm, & memoryview even if... not ideal)

-gps