numba is a true horror to use, because supported subset of python language is an ever-moving target and overall small. cython is good but needs time to meddle with. For loop-intensive, simple function I'd advise FFI.
I disagree that it's a "true horror to use." The set of supported built-in classes grows significantly by the day. It's not as good when used for wholly unstructured streams of data (e.g. tuples of mixed type, dicts with complex objects inside of them), but if you can spend the design time to arange things in a structured manner, it's super easy to use, and can seriously boost performance on simple algos.
I've had a ton of success using it in statistical and computational geometry applications.
FWIW I agree with you. I’ve always found cython easier than Numba. And more performant.
I think Numba has a lot of potential and will improve as they fill out remaining language coverage and finalize the API. The idea of a LLVM JIT compiler for python makes a ton of sense.
andreareina|5 years ago
guram11|5 years ago
jojo2000|5 years ago
qfwfq_|5 years ago
I've had a ton of success using it in statistical and computational geometry applications.
datanecdote|5 years ago
I think Numba has a lot of potential and will improve as they fill out remaining language coverage and finalize the API. The idea of a LLVM JIT compiler for python makes a ton of sense.