[targafarian]

Note that the alternative in Numba is incredibly convenient, where you can trivially create a function where the body of the function operates on a scalar, but then using the @vectorize decorator which makes it into a numpy ufunc automatically. This generalizes the function to operate equally well on scalars or numpy arrays of any dimensionality (just like "built-in" numpy functions do).

Oh, and if you use set target='gpu', your function also works on GPUs, too. Or you can use target='parallel' to make it parallelize automatically across CPU cores.