I've played with numba a bit, and my feeling is that if you're going to accept the disadvantages of just in time compilation, why not just write in Julia (where the experience is a lot more seamless)?
Julia was also faster in my experiments.
Julia was also faster in my experiments.
I have tried Julia but I found the promised "everything will be as easy to write as python but as fast as C" is often not true. There are quite a few pitfalls (e.g. don't use abstract data types), which one has to consider and code can start looking looking more like cython than python if one wants to optimise for speed. I also dislike some of the design decisions they made (in particular making multiply a matrix operation and using the '.' for broadcasting which is incredibly easy to overlook and one of the main sources of bugs in matlab code in my experience).
That said there are great things happening in the Julia ecosystem, just don't promote it as the be all of scientific computing all the time.
And when thinking about something more than optimizing a single function, but about a large codebase and the context in which you need it, Julia is rarely a compelling option.