8000 ENH: add type stubs from numpy-stubs by person142 · Pull Request #16515 · numpy/numpy · GitHub
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ENH: add type stubs from numpy-stubs #16515

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Merged
merged 8 commits into from
Jun 9, 2020
Merged

ENH: add type stubs from numpy-stubs #16515

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11b95d1
ENH: add type stubs from numpy-stubs
person142 Jun 6, 2020
3fee17a
MAINT: move typing tests cases into a subdirectory of numpy/tests
person142 Jun 7, 2020
744512d
MAINT: merge typing requirements into test requirements
person142 Jun 7, 2020
8362a36
MAINT: modify mypy error line parsing to work on windows
person142 Jun 7, 2020
7c0d99d
DOC: Add a release note about types being added
person142 Jun 7, 2020
f09b27d
MAINT: avoid divide by zero in typing test causing aarch64 tests to fail
person142 Jun 8, 2020
4b5f00e
MAINT: only run typing tests on python > 3.6 and < 3.9
person142 Jun 8, 2020
2e238e4
MAINT: avoid more division by zero in typing test causing aarch64 to …
person142 Jun 8, 2020
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8 changes: 8 additions & 0 deletions doc/release/upcoming_changes/16515.improvement.rst
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NumPy is now typed
------------------
Type annotations have been added for large parts of NumPy. There is
also a new `numpy.typing` module that contains useful types for
end-users. The currently available types are

- ``ArrayLike``: for objects that can be coerced to an array
- ``DtypeLike``: for objects that can be coerced to a dtype
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@person142, sorry for being late to the party. Should we make this DTypeLike with a capital T? I have been using DType for the dtype classes (I guess as a short form of the camel-case DataType. I am happy to use this one as well, would be good to keep it in sync).

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That is, unless this actually includes concrete instances, such as strings of specific length. In that case it may actually be better to use different spellings. I would have to review the discussion on that...

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Hm @seberg could you open an issue? I think “DtypeLike” was originally “things that can be passed into np.dtype“, and with the dtype changes we should think carefully about what makes sense...

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