API: Add Array API setops [Array API] #25088
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numpy/lib/_arraysetops_impl.py
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| UniqueAllResult.__module__ = "numpy" | ||
| UniqueCountsResult.__module__ = "numpy" | ||
| UniqueInverseResult.__module__ = "numpy" |
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I don't believe these named tuples are actually available in the main namespace (as __module__ now claims), no? This could potentially cause issue I imagine with anything relying on __module__ + __name__ for retrieving an object, e.g. does pickling even work now?
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Good point - @rgommers Do you think that namedtuple classes of return objects for setops should be present in the main namespace? Now when I think about it they shouldn't and I would leave __module__ as numpy.lib._arraysetops.
We had similar discussion for index tricks, e.g. np.r_ which is <numpy.lib._index_tricks_impl.RClass at 0x102fd6b20>. RClass return class is in a private module only.
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I don't think those should be public. But yes, pickling should work, and adding a test to confirm that would be useful. So __module__ should just not be set, then it should be automatically correct.
numpy/lib/_arraysetops_impl.pyi
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| @overload | ||
| def unique_all( | ||
| x: _ArrayLike[_SCT], / | ||
| ) -> tuple[NDArray[_SCT], NDArray[intp], NDArray[intp], NDArray[intp]]: ... |
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The return these here should be named tuples as well, just as is the case during runtime. It's a bit annoying, but that does mean the named tuples definitions will have to be repeated here in the .pyi file:
# NOTE: still needs a `from typing import Generic` statement
class UniqueAllResult(NamedTuple, Generic[_SCT]):
values: NDArray[_SCT]
indices: NDArray[intp]
inverse_indices: NDArray[intp]
counts: NDArray[intp]
class UniqueCountsResult(NamedTuple, Generic[_SCT]):
values: NDArray[_SCT]
counts: NDArray[intp]
class UniqueInverseResult(NamedTuple, Generic[_SCT]):
values: NDArray
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[_SCT]
inverse_indices: NDArray[intp]There was a problem hiding this comment.
Sure! I added these classes to typing.
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Looks good to me; In it goes. Thanks @mtsokol! |
Hi @rgommers @ngoldbaum,
This PR introduces Array API set functions. Their implementations mostly required setting
np.uniqueflags correctly.Tracking issue: #25076