So, in the documentation for third-party ASGI middlewares they will probably tell you to do something like:

```Python
from unicorn import UnicornMiddleware

app = SomeASGIApp()

new_app = UnicornMiddleware(app, some_config="rainbow")
```

But FastAPI (actually Starlette) provides a simpler way to do it that makes sure that the internal middlewares to handle server errors and custom exception handlers work properly.

```

Whenever you need the client to pass information in the request and you don't know how to, you can search (Google) how to do it in `httpx`, or even how to do it with `requests`, as HTTPX's design is based on Requests' design.

Then you just do the same in your tests.

E.g.:

* To pass a *path* or *query* parameter, add it to the URL itself.

```

</div>

#### Translation specific tips and guidelines

* Translate only the Markdown documents (`.md`). Do not translate the code examples at `./docs_src`.

* In code blocks within the Markdown document, translate comments (`# a comment`), but leave the rest unchanged.

* Do not change anything enclosed in "``" (inline code).

FastAPI to nowoczesny, wydajny framework webowy do budowania API z użyciem Pythona bazujący na standardowym typowaniu Pythona.

Kluczowe cechy:

* **Wydajność**: FastAPI jest bardzo wydajny, na równi z **NodeJS** oraz **Go** (dzięki Starlette i Pydantic). [Jeden z najszybszych dostępnych frameworków Pythonowych](#wydajnosc).
* **Szybkość kodowania**: Przyśpiesza szybkość pisania nowych funkcjonalności o około 200% do 300%. *

```

</div>

É **ALTAMENTE recomendado** que você escreva ou copie o código, edite-o e rode-o localmente.

Usá-lo em seu editor é o que realmente te mostra os benefícios do FastAPI, ver quão pouco código você tem que escrever, todas as conferências de tipo, auto completações etc.

---

## Instale o FastAPI

O primeiro passo é instalar o FastAPI.

* It takes each **request** that comes to your application.
* It can then do something to that **request** or run any needed code.
* Then it passes the **request** to be processed by the rest of the application (by some *path operation*).
* It then takes the **response** generated by the application (by some *path operation*).
* It can do something to that **response** or run any needed code.
* Then it returns the **response**.

* data documentation, etc.

This works the same way as with Pydantic models. And it is actually achieved in the same way underneath, using Pydantic.

!!! info
    Keep in mind that dataclasses can't do everything Pydantic models can do.

    So, you might still need to use Pydantic models.

    But if you have a bunch of dataclasses laying around, this is a nice trick to use them to power a web API using FastAPI. 🤓

FastAPI will use this `response_model` to do all the data documentation, validation, etc. and also to **convert and filter the output data** to its type declaration.

!!! tip
    If you have strict type checks in your editor, mypy, etc, you can declare the function return type as `Any`.

  - name: Feature Request
    about: To suggest an idea or ask about a feature, please start with a question saying what you would like to achieve. There might be a way to do it already.
    url: https://github.com/tiangolo/fastapi/discussions/categories/questions
  - name: Show and tell
    about: Show what you built with FastAPI or to be used with FastAPI.

from fastapi import FastAPI

description = """
ChimichangApp API helps you do awesome stuff. 🚀

## Items

You can **read items**.

## Users

You will be able to:

* **Create users** (_not implemented_).
* **Read users** (_not implemented_).
"""

app = FastAPI(
    title="ChimichangApp",
    description=description,
    summary="Deadpool's favorite app. Nuff said.",
    version="0.0.1",