DEP: Futurewarn on requiring __len__ on array-likes#17973
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I had this wrong first. Thought I can drop through to handle the scalar with the last fall-back path. This does not work, because it would break the current usage where we ignore everything from the __array__ protocol except the dtype. (The last fall-back forces object dtype.)
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This fixes issue numpygh-17965. The slightly annoying thing is that there is no simple way to opt-in to the new behaviour and the old behaviour is a bit quirky to begin with (honoring the dtype, but not the shape).
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Thanks Sebastian. |
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Starting from, NumPy 1.20 behaves differently when instantiating arrays from array-like objects. NumPy used to be agnostic about the type of the object inside the list (MX in our case), but now it actually tries to interpret it as an array if it can. In this particular case, we deliberately _did not_ want this behavior. We use the work-around described in [0] to get the old behavior back. For more details, see: [0] https://numpy.org/devdocs/release/1.20.0-notes.html under "ArrayLike objects which do not define __len__ and __getitem__" or [1] numpy/numpy#17973
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Starting from, NumPy 1.20 behaves differently when instantiating arrays from array-like objects. NumPy used to be agnostic about the type of the object inside the list (MX in our case), but now it actually tries to interpret it as an array if it can. In this particular case, we deliberately _did not_ want this behavior. We use something akin to the work-around described in [0] to get the old behavior back. For more details, see: [0] https://numpy.org/devdocs/release/1.20.0-notes.html under "ArrayLike objects which do not define __len__ and __getitem__" or [1] numpy/numpy#17973
jackvreeken
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Feb 15, 2021
Starting from, NumPy 1.20 behaves differently when instantiating arrays from array-like objects. NumPy used to be agnostic about the type of the object inside the list (MX in our case), but now it actually tries to interpret it as an array if it can. In this particular case, we deliberately _did not_ want this behavior. We use something akin to the work-around described in [0] to get the old behavior back. For more details, see: [0] https://numpy.org/devdocs/release/1.20.0-notes.html under "ArrayLike objects which do not define __len__ and __getitem__" or [1] numpy/numpy#17973
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This fixes issue gh-17965. The slightly annoying thing is that
there is no simple way to opt-in to the new behaviour and the old
behaviour is a bit quirky to begin with (honoring the dtype, but
not the shape).
Marking as a draft for now, this still needs:
__array__and__array_struct__, since in principle they might behave differently.