[Python] Why keyword argument 'weights' doesn't work when calling NumPy histogram in Numba?

This Python 3.13.5 script with numpy 2.2.6 and numba 0.61.2:

import numpy as np, numba as nb

@nb.njit(fastmath=True)
def f(a, b):
return np.histogram(a, 10, weights=b)

a = np.random.randint(0, 256, (100,)).astype(np.uint8)
b = np.random.randint(0, 256, (100,)).astype(np.uint8)

print(np.histogram(a, 10, weights=b)) # no problems
print(f(a, b)) # fails here


fails with this error:

numba.core.errors.TypingError: Failed in nopython mode pipeline (step: nopython frontend)
No implementation of function Function(<function histogram at 0x7244459565c0>) found for signature:

>>> histogram(array(uint8, 1d, C), Literal[int](10), weights=array(uint8, 1d, C))

There are 2 candidate implementations:
- Of which 2 did not match due to:
Overload in function 'np_histogram': File: numba/np/old_arraymath.py: Line 3942.
With argument(s): '(array(uint8, 1d, C), int64, weights=array(uint8, 1d, C))':
Rejected as the implementation raised a specific error:
TypingError: got an unexpected keyword argument 'weights'
raised from /home/paul/st-python/test-3.13/.venv/lib/python3.13/site-packages/numba/core/typing/templates.py:791

During: resolving callee type: Function(<function histogram at 0x7244459565c0>)
During: typing of call at /home/paul/st-python/test-3.13/so-numba-hist.py (5)


File "so-numba-hist.py", line 5:
def f(a, b):
return np.histogram(a, 10, weights=b)
^

During: Pass nopython_type_inference


Why Numba doesn't accept a legal weights= argument? BTW, this is just a shortened example, my use case is a longer function, which calls np.histogram().

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