Just to speak for myself, I don't think the precise choice matters very much. There are arguments for consistency both ways.

I agree with this. In the absence of strong theoretical considerations I'd fall back to a practical one-we can make ndarray generic over dtype _right now_, while for shape we will need to wait 1+ years for the variadic type variable PEP to settle etc. To me that suggests: - Do ndarray[DType] now - When the shape stuff is ready, do ndarray[DType, ShapeStuff] (or however ShapeStuff ends up being spelled) - Write a mypy plugin that rewrites ndarray[DType] to ndarray[DType, AnyShape] (or whatever) for backwards compatibility On Thu, Oct 29, 2020 at 1:37 PM Stephan Hoyer wrote:

On Wed, Oct 28, 2020 at 2:44 PM bas van beek wrote:

...

Hey all,

With the recent merging of numpy/numpy#16759 we’re at the point where `ndarray` can be made generic w.r.t. its dtype and shape.

An open question which yet remains is to order in which these two parameters should appear (numpy/numpy#16547):

· `ndarray[Dtype, Shape]`

· `ndarray[Shape, Dtype]`

Hi Bas,

Thanks for driving this forward!

Just to speak for myself, I don't think the precise choice matters very much. There are arguments for consistency both ways. In the end Dtype and Shape are different enough that I doubt it will be a point of confusion.

Also, I would guess many users will define their own type aliases, so can write something more succinct like Float64[shape] rather than ndarray[float64, shape]. We might even consider including some of these in numpy.typing.

Cheers, Stephan

...

There has been a some discussion about this question in issue 16547, but a consensus has not yet to be reached.

Most people seem to slightly preferring one option over the other.

Are there any further thoughts on this subject?

Regards,

Bas van Beek

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