[jofer]

It actually doesn't, as far as I know :) It does get close, though. I should give it a deeper look than I have previously, though.

"array-like" has real meaning in the python world and lots of things operate in that world. A very common need in libraries is indicating that things expect something that's either a numpy array or a subclass of one or something that's _convertible_ into a numpy array. That last part is key. E.g. nested lists. Or something with the __array__ interface.

In addition to dimensionality that part doesn't translate well.

And regardless, if the type representation is not standardized across multiple libraries (i.e. in core numpy), there's little value to it.

[dwohnitmok]

Does it not?

E.g. `UInt8[ArrayLike, "... a b"]` means "an array-like of uint8s that has at least two dimensions". You are opting into jaxtyping's definition of an "array-like", but even though the general concept as you point out is wide spread, there isn't really a single agreed upon formal definition of array-like.

Alternatively, even more loosely as anything that is vaguely container-shaped, `UInt8[Any, "... a b"]`.

[jofer]

Ah, fair enough! I think I misread some things around the library initially awhile back and have been making incorrect assumptions about it for awhile!

[nerdponx]

I wonder if we should standardize on __array__ like how Iterable is standardized on the presence of __iter__, which can just return self if the Iterable is already an Iterator.