On Mon, Nov 6, 2017 at 4:28 PM, Stephan Hoyer <shoyer@gmail.com> wrote:

What's needed, though, is not just a single ABC. Some thought and design needs to go into segmenting the ndarray API to declare certain behaviors, just like was done for collections:

You don't just have a single ABC declaring a collection, but rather "I am a mapping" or "I am a mutable sequence". It's more of a pain for developers to properly specify things, but this is not a bad thing to actually give code some thought. 

I agree, it would be nice to nail down a hierarchy of duck-arrays, if possible. Although, there are quite a few options, so I don't know how doable this is.

Exactly -- there are an exponential amount of options...
Well, to get the ball rolling a bit, the key thing that matplotlib needs to know is if `shape`, `reshape`, 'size', broadcasting, and logical indexing is respected. So, I see three possible abc's here: one for attribute access (things like `shape` and `size`) and another for shape manipulations (broadcasting and reshape, and assignment to .shape).

I think we're going to get into an string of ABCs:


etc, etc.....
And then a third abc for indexing support, although, I am not sure how that could get implemented...

This is the really tricky one -- all ABCs really check is the existence of methods -- making sure they behave the same way is up to the developer of the ducktype.

which is K, but will require discipline.

But indexing, specifically fancy indexing, is another matter -- I'm not sure if there even a way with an ABC to check for what types of indexing are support, but we'd still have the problem with whether the semantics are the same!

For example, I work with netcdf variable objects, which are partly duck-typed as ndarrays, but I think n-dimensional fancy indexing works differently... how in the world do you detect that with an ABC???

For the shapes and reshaping, I wrote an ShapedLikeNDArray mixin/ABC
for astropy, which may be a useful starting point as it also provides
a way to implement the methods ndarray uses to reshape and get
elements: see https://github.com/astropy/astropy/blob/master/astropy/utils/misc.py#L863

Sounds like a good starting point for discussion.



Christopher Barker, Ph.D.

Emergency Response Division
NOAA/NOS/OR&R            (206) 526-6959   voice
7600 Sand Point Way NE   (206) 526-6329   fax
Seattle, WA  98115       (206) 526-6317   main reception