Ndarray static typing: Order of generic types
Hey all, With the recent merging of numpy/numpy#16759<https://github.com/numpy/numpy/pull/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<https://github.com/numpy/numpy/issues/16547>): * `ndarray[Dtype, Shape]` * `ndarray[Shape, Dtype]` 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
On Wed, Oct 28, 2020 at 2:44 PM bas van beek <bas.vanbeek@hotmail.com> wrote:
Hey all,
With the recent merging of numpy/numpy#16759 <https://github.com/numpy/numpy/pull/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 <https://github.com/numpy/numpy/issues/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
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
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 <shoyer@gmail.com> wrote:
On Wed, Oct 28, 2020 at 2:44 PM bas van beek <bas.vanbeek@hotmail.com> 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
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
participants (3)
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bas van beek -
Joshua Wilson -
Stephan Hoyer