Closed
Description
xref #12028
Here's what you currently see if __array_function__ returns NotImplemented:
In [1]: import numpy as np
In [2]: class MyArray:
...: def __array_function__(*args, **kwargs):
...: return NotImplemented
...:
In [3]: np.sum(MyArray())
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-3-c8a80bb1d37e> in <module>()
----> 1 np.sum(MyArray())
~/dev/numpy/numpy/core/overrides.py in public_api(*args, **kwargs)
149 relevant_args = dispatcher(*args, **kwargs)
150 return array_function_implementation_or_override(
--> 151 implementation, public_api, relevant_args, args, kwargs)
152
153 # TODO: remove this when we drop Python 2 support (functools.wraps
~/dev/numpy/numpy/core/overrides.py in array_function_implementation_or_override(implementation, public_api, relevant_args, args, kwargs)
108 raise TypeError('no implementation found for {} on types that implement '
109 '__array_function__: {}'
--> 110 .format(public_api, list(map(type, overloaded_args))))
111
112
TypeError: no implementation found for <function sum at 0x10e070bf8> on types that implement __array_function__: [<class '__main__.MyArray'>]
This error message should look something like this instead: TypeError: no implementation found for 'numpy.sum' on types that implement __array_function__: [<class '__main__.MyArray'>]
I think we will need to add a name parameter to array_function_override to do this properly. The best we could hope for with introspection is to use __module__ and __name__ to come up with something like numpy.core.fromnumeric.sum. This would be better what we currently have and could be a reasonable default, but we really don't want people reaching directly into internal modules like fromnumeric.