streamcpy VS ultrajson

I wrote a Python C extension to make Python programs run faster, and even faster than C++ after comparison (but I don't know why). The package is for stream computing like in Java. It was my first time to write a Python C extension and please give me some advice thx! Here is the repo : https://github.com/littlebutt/streamcpy

ujson

For most cases, you would want to go with python’s standard json library which removes dependencies on other libraries. On other hand you could try out ujsonwhich is simple replacement for python’s json library. If you want more speed and also want dataclass, datetime, numpy, and UUID instances and you are ready to deal with more complex code, then you can try your hands on orjson

I asked about this on the Github issue regarding these benchmarks as well.

I'm curious as to why libraries like ultrajson[0] and orjson[1] weren't explored. They aren't command line tools, but neither is pandas right? Is it perhaps because the code required to implement the challenges is large enough that they are considered too inconvenient to use through the same way pandas was used (ie, `python -c "..."`)?

[0] https://github.com/ultrajson/ultrajson