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ENH: numpy.where: don't silently truncate Python scalars - #30803
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Since NumPy 2.0, code like the following will cause a scalar value to be
truncated:
>>> np.where([False], np.array([1], dtype=np.uint8), 1000)
array([232], dtype=uint8)
(in NumPy 1.x, it would instead output a uint16 array)
This is dangerous, and inconsistent with other NumPy functions, e.g.:
>>> np.multiply(np.array([1], dtype=np.uint8), 1000)
Traceback (most recent call last):
File "<python-input-3>", line 1, in <module>
np.multiply(np.array([1], dtype=np.uint8), 1000)
~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
OverflowError: Python integer 1000 out of bounds for uint8
Use `npy_update_operand_for_scalar` to bring the behavior of `where` in line
with other functions.
Closes #27006.
SpecLad
marked this pull request as ready for review
February 8, 2026 21:11
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jorenham
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numpy.where: don't silently truncate Python scalars
seberg
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Mar 6, 2026
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Thanks, sorry for not looking at it closer earlier. I hadn't realized that we already fixed the promotion part, but just the error was missing.
LGTM (Staring at this now, I am wondering if we may want to push this into the iterator even, but not sure that is good and it isn't relevant here).
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Since NumPy 2.0, code like the following will cause a scalar value to be truncated:
(in NumPy 1.x, it would instead output a uint16 array)
This is dangerous, and inconsistent with other NumPy functions, e.g.:
Use
npy_update_operand_for_scalarto bring the behavior ofwherein line with other functions.Closes #27006.