python-rapidjson VS pysimdjson

> * Human readable

Computers are the main consumers of APIs, and ISO 8601 is far from machine-readable.

For example, in Elixir, DateTime.from_iso8601/1 won't recognize "2022-03-12T07:36:08" even though it's valid. I had to rewrite a chunk of Python's radidjson wrapper to 1-9 digit fractional seconds (1).

I'm willing to bet 99% of ISO8601 will fail to handle all aspects of the spec. So when you say "ISO8601" what you're really saying is "our [probably undocumented, and possibly different depending on what system you're hitting] version of the ISO-86001 spec."

(1) https://github.com/python-rapidjson/python-rapidjson/pull/13...

Its magic function wrapping comes at a cost, trading ease of use for runtime performance. When you have a single C++ function to call that will run for a "long" time, pybind all the way. But pysimdjson tends to call a single function very quickly, and the overhead of a single function call is orders of magnitude slower than with cython when being explit with types and signatures. Wrap a class in pybind11 and cython and compare the stack trace between the two, and the difference is startling.

Ex: https://github.com/TkTech/pysimdjson/issues/73

simdjson

You are aware of simdjson being available in python if you really need some json crunching, albeit json module in Python is implemented in C itself, so I don't think understand why do you think Python is slow there?

json: 113.79130696877837 ms

While `orjson`, is faster than `ujson`/`json` here, it's only ~6% faster (in this benchmark). `simdjson` and `msgspec` (my library, see https://jcristharif.com/msgspec/) are much faster due to them avoiding creating PyObjects for fields that are never used.

If spyql's query engine can determine the fields it will access statically before processing, you might find using `msgspec` for JSON gives a nice speedup (it'll also type check the JSON if you know the type of each field). If this information isn't known though, you may find using `pysimdjson` (https://pysimdjson.tkte.ch/) gives an easy speed boost, as it should be more of a drop-in for `orjson`.

I don't think JSON is really the problem - parsing 10MB of JSON is not so slow. For example, using Python's json.load takes about 800ms for a 47MB file on my system, using something like simdjson cuts that down to ~70ms.