this post was submitted on 15 Jun 2024
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When you need speed in Python, after profiling, checking for errors, and making damn sure you actually need it, you code the slow bit in C and call it.
When you need speed in C, after profiling, checking for errors, and making damn sure you actually need it, you code the slow bit in Assembly and call it.
When you need speed in Assembly, after profiling, checking for errors, and making damn sure you actually need it, you're screwed.
Which is not to say faster Python is unwelcome, just that IMO its focus is frameworking, prototyping or bashing out quick and perhaps dirty things that work, and that's a damn good thing.
I'd really like to see Rust fit in where C(++) does now for Python. I know some libraties do it (e.g. Pydantic), but it really should be more common. It should work really well with the GIL... (or the TIL or whatever the new one is)
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).