That was what I was trying to say when I said "the code required to implement the challenges is large enough that they are considered too inconvenient to use". This makes sense to me.
Thank you for this benchmark! I'll probably switch to spyql now from jq.
> So, orjson is part of the reason why a python-based tool outperforms tools written in C, Go, etc and deserves credit.
Yes, I definitely think this is worth mentioning upfront in the future, since, IIUC, orison's core uses Rust (the serde library, specifically). The initial title gave me the impression that a pure-Python json parsing-and-querying solution was the fastest out there.
A parallel I think is helpful to think about is saying something like "the fastest BERT implementation is written Python[0]". While the linked implementation is written in Python, it offloads the performance critical parts to C/C++ through TensorFlow.
I'm not sure how such claims advance our understanding of the tradeoffs of programming languages. I initially thought that I was going to change my mind about my impression that "python is not a good tool to implement fast parsing/querying", but now I haven't, so I do think the title is a bit misleading.
