Comment by kibwen
20 hours ago
Assuming that the biggest bang-for-buck of JIT compilation is optimizing hot loops (which is also the biggest bang-for-buck of optimization in every other context as well), and assuming that, per the historical best practices, all hot loops in Python are already written in C (or Rust, these days), this outcome is somewhat what I would expect.
The performance of python indicates otherwise. There are some performance critical libraries written in C or C++ but a lot of python is written in python.
Python in itself is poorly suited to ever become performant as it lacks the types required. I imagine that causes some issues for effective jit-ing too.
They had a chance to fix this when adding type annotations, but instead of making it "optional/gradual typing" they opted to make it "documentation or linting support", which is obviously the wrong choice, but there were cultural reasons
Does optional/gradual typing even help with JIT?
If you know the type you need fewer checks in the jitted code, and you can optimise to native types.
If it helps python specifically, given that the types themselves are pretty dynamic, who knows. A python integer doesn't map well to a native integer etc. Python really isn't designed for performance, and retrofitting it is hard.