PyCon 2024 showcased a number of ways to speed the pokey Python programming language including sub-interpreters, immortal objects, just-in-time compilation and more.
Or you could use cython, which is much easier to integrate with a python project. It is only marginally slower than Rust but a little less safe. Numpy libraries are usually the fast. Numba is a little clunky, but can also speed up code. There’s lots of options to speed up python code.
You can also use numba if you just need to accelerate one part of the app. We did that with a heavy part of the app and our naïve Python (using numpy) was about as fast as our naïve Rust, but only when wr turned on parallel processing in numba (I could’ve easily beat it with parallel Rust, but that requires extra work and wouldn’t fit as nicely into the rest of the app).
Or you could use cython, which is much easier to integrate with a python project. It is only marginally slower than Rust but a little less safe. Numpy libraries are usually the fast. Numba is a little clunky, but can also speed up code. There’s lots of options to speed up python code.
Yup, Cython rocks.
You can also use numba if you just need to accelerate one part of the app. We did that with a heavy part of the app and our naïve Python (using numpy) was about as fast as our naïve Rust, but only when wr turned on parallel processing in numba (I could’ve easily beat it with parallel Rust, but that requires extra work and wouldn’t fit as nicely into the rest of the app).