pokebase VS dacite

100% honesty, I started with Pokebase and tried the other python wrappers and was having a hard time getting to work as documented and then ran across Pokefetch that had already written 99% of the scraping and opted to "get something to work" for my son and went with it.

this: https://github.com/PokeAPI/pokebase/blob/master/pokebase/interface.py

Having spent the last few months creating a pokemon themed dataset for multitask machine learning, PokeBase is your friend next time 😉

On the documentation, it includes a list of wrapper libraries for various languages. The wrapper for Python 3 is pokebase. I'm just learning to use APIs and have not used wrappers before. I read a bit about them but I'm still a bit confused.

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