TYP: apply_along_axis shape-typing and improved dtypes - #32676
Merged
charris merged 1 commit intoSep 17, 2026
Merged
Conversation
Member
|
Thanks Joren. I have a question, it there a way to distinguish between returning a view vs a new array? |
Member
Author
There isn't; both the view and the original are nominal |
Member
|
Just curious, mainly because it affects data flow in a program. Overall, I'm wondering how much typing tells you about the structure of NumPy itself. If you handed over all the type files, what could an AI pull out of them. |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
2 participants
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
np.apply_along_axisnow returns exact shape-types in the 0-2d cases based on the combination offunc1dreturn type and thearrshape-type. Exact dtypes are now also returned whenfunc1dreturns python builtin scalars (bool/int/float/complex).Pair programmed with AI.