First, How fast is the Zstd decoder in python at runtime? If rust and python are essentially the same cost, then chose rust.
Second, I am surprised that python scored slightly better than rust. My own experience is that, when programming python, Claude would spend so much more time dealing with the code not working at runtime, while for any given rust problem, rust would likely fail at compile time, iterating faster and taking less tokens. Some tasks in python it just completely failed at, writing awful garbage. I suspect that is because there is much more awful garbage written in python. (I was trying to write an AI harness. Python seemed like the obvious choice. It was decidedly not).
But in this article, python took slightly less time and tokens than rust for both experiments.
I asked Claude: could you write a decoder, from memory, in python (dont do it, just tell me if you could)
> Honestly: I could write something that's structurally right and would not decode a real .zst file.
> The control flow I'm confident about from memory — frame/block parsing, the literals section dispatch, Huffman weight reconstruction, the backward bitstream reader, the interleaved three-state FSE loop, sequence execution with the repeat-offset rules and the overlapping-copy hazard. I'd expect to get that architecture right, and it would be readable.
So perhaps asking it to do things that are in its memory is not a good benchmark. It was trained with the C "educational decoder, and every third-party port in Rust, Go, Java, JS." and offered a working link [1] to the former.
[1] https://github.com/facebook/zstd/blob/dev/doc/educational_decoder/zstd_decompress.c