With this, we get tooling support, from editors and mypy as this code is correct in terms of types, but we also get the data filtering from FastAPI.

How does this work? Let's check that out. 🤓

### Type Annotations and Tooling { #type-annotations-and-tooling }

First let's see how editors, mypy and other tools would see this.

/// info

If you already went through all the tutorial and came back to see more about types, a good resource is <a href="https://mypy.readthedocs.io/en/latest/cheat_sheet_py3.html" class="external-link" target="_blank">the "cheat sheet" from `mypy`</a>.

This will be especially useful when you use it in a **large code base** where you use **the same dependencies** over and over again in **many *path operations***.

    * Because pydantic data structures are just instances of classes you define; auto-completion, linting, mypy and your intuition should all work properly with your validated data.
* Validate **complex structures**:
    * Use of hierarchical Pydantic models, Python `typing`’s `List` and `Dict`, etc.

* 📝 Update includes in `docs/vi/docs/tutorial/first-steps.md`. PR [#12754](https://github.com/fastapi/fastapi/pull/12754) by [@MxPy](https://github.com/MxPy).
* 📝 Update includes for `docs/pt/docs/advanced/wsgi.md`. PR [#12769](https://github.com/fastapi/fastapi/pull/12769) by [@Nimitha-jagadeesha](https://github.com/Nimitha-jagadeesha).

* Alternatywna dokumentacja również pokaże zaktualizowane parametry i treść żądania (body):

![ReDoc](https://fastapi.tiangolo.com/img/index/index-06-redoc-02.png)

### Podsumowanie

Podsumowując, musiałeś zadeklarować typy parametrów, treści żądania (body) itp. tylko **raz**, i są one dostępne jako parametry funkcji.

Robisz to tak samo jak ze standardowymi typami w Pythonie.