You actually can do the "offset by 2 bytes back" with a reshape + indexing + reshape back. But I suspect I'm still missing something. I need to read things in m

You actually can do the "offset by 2 bytes back" with a reshape + indexing + reshape back. But I suspect I'm still missing something. I need to read things in more depth and try it out locally. By "numbs" here, I'm assuming you mean numba. If that's not correct, I apologize in advance! There are several things where Cython is a better fit than numba (and to be fair, several cases where the opposite is true). There are two that stick out in my mind: First off, the optimizations for cython are explicit and a matter of how you implement the actual code. It's a separate language (technically a superset of python). There's no "magic". That's often a significant advantage in and of itself. Personally, I often find larger speedups with Cython, but then again, I'm more familiar with it, and understand what settings to turn on/off in different situations. Numba is much more of a black box given than it's a JIT compiler. With that said, it can also do things that Cython can't _because_ it's a JIT compiler. If you want to run python code as-is, then yeah, numba is the better choice. You won't see a speedup at all with Cython unless you change the way you've written things. The second key thing is one that's likely the most overlooked. Cython is arguably the best way to write a python wrapper around C code where you want to expose things as numpy arrays. It takes a _huge_ amount of the boilerplate out. That alone makes it worth learning, i.m.o.