Add pydantic request models and documentation to API

[matthiasschaub]

Description

Add pydantic request models and documentation to API.

Now through swagger it is possible to see which values are allowed for following parameters: dataset, fidField, indicator_name, report_name.
Also some documentation is added, which will be available through the swagger interface.

Corresponding issue

Adresses in part #2 and #120

Checklist

• I have updated my branch to main (e.g. through git rebase main)
• My code follows the style guide and was checked with pre-commit before committing
• I have commented my code
• I have added sufficient unit and integration tests
  • Extend tests on definitions.py
• I have updated the CHANGELOG.md

[joker234]

I only had a brief look over your changes right now. At first glance it looks like a good change. The only general question that comes up is why they are called request models and not response models 🤔

[joker234]

Wow, that was a lot of work. Thank you!

Some questions:

• If I see this correctly, the parameters and field names in GET and POST requests will be different? Why do we have to stick with the camelCase parameter names in GET requests?
• Where are the classmethods from request_models.py used?

[matthiasschaub]

Wow, that was a lot of work. Thank you!

Some questions:

* If I see this correctly, the parameters and field names in GET and POST requests will be different? Why do we have to stick with the camelCase parameter names in GET requests?

* Where are the classmethods from `request_models.py` used?

I am glad to hear to work is appreciated. Thanks for your throughout review of this big PR. I will give my best to keep PRs small in the future.

To speak to your first question: The parameter and field names will stay the same as it was before (regardless of the request type POST or GET). The trick here is the alias_generator attribute of the Config class inside the BaseModel, which point to a funtion to translate variable names in snake case to lower camel case (snake_to_lower_camel).

Second question: The class methods will be called on each initialization of the class. pydantic magic will take care of that.