[FIXED] Why does numba work on numpy string vectors but not on numpy strings?

Issue

Consider the simplest possible function

@numba.jit
def foo(s1):
    return s1

Now constructing an array of np.bytes_ objects

> a = np.array(['abc']*5, dtype='S5')
> a
array([b'abc', b'abc', b'abc', b'abc', b'abc'], dtype='|S5')

Why does calling foo with the vector work:

> foo(a)
array([b'abc', b'abc', b'abc', b'abc', b'abc'], dtype='|S5')

But calling foo with a single element raises an exception

> foo(a[0])
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
~\AppData\Local\Temp/ipykernel_8124/2559272744.py in <module>
----> 1 foo(a[0])

TypeError: bad argument type for built-in operation

(This is running numba 0.54.1 from conda-forge on Windows with Python 3.9.7 and numpy 1.20.3)

Solution

Neither bytes nor np.bytes_ types are listed in the set of types supported by numba as of the latest release. The closest things it supports would be:

1. Character sequences (read: str) (though it specifically says "no operations are available on them", so this is pretty useless); your function would work if you called foo(a[0].decode()) to make it text (but only because it's a pretty useless function)
2. Actual numpy arrays; the cost to view the bytes/np.bytes_ as an np.array is pretty low, so you could just do: foo(np.frombuffer(a[0], np.uint8)) and produce something that is more programmatically useful and represents the same data.

Answered By - ShadowRanger