orjson VS dacite

orjson is the fastest JSON library available for python. It natively manages dataclass objects, datetime, numpy and UUID objects.

As we began venturing down that road, a few things emerged that would constitute significant changes to some of the core parts of Litestar, but there were two things in particular that started a chain reaction of changes by opening up further possibilities: The new DTOs and our switch from orjson to msgspec.

In version 1.45.0, we introduced msgspec as our serialization backend, replacing orjson. This had some immediate performance benefits, but that's not the main reason we made the switch.

Doesn't orjson do that already?

orjson

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

Try https://github.com/ijl/orjson. Not exactly sure if that can help.

This is a good approach, but FYI there are already very good libraries that can be used to create objects from JSON/dicts in a similar way to your example, like dacite or pydantic. A lot of boilerplate can be avoided with these.

You'll need to be able to serialize ProjectState objects into some file format that you can save to disk, like json. When working with dataclasses, dacite can also be very helpful to convert to/from dictionaries. (There's other options available, of course.)

You also can't read any nested dataclassed from a dictionary. dacite! will help with this, but witihout it you can't just initialize it with NestedDataclass(**some_dict) or somethings like this. In the way it works for Plain dataclass.

There are also tools such as dacite and desert, which take a different approach to dealing with serialized data