Vedrai la seguente risposta JSON:

```JSON
{"item_id": 5, "q": "somequery"}
```

Hai appena creato un'API che:

* Riceve richieste HTTP sui _paths_ `/` and `/items/{item_id}`.
* Entrambi i _paths_ accettano`GET` operations (conosciuti anche come <abbr title="metodi HTTP">HTTP _methods_</abbr>).

<img src="https://fastapi.tiangolo.com/img/async/parallel-burgers/parallel-burgers-03.png" alt="illustration">

Como tu y esa persona 😍 están ocupados en impedir que alguien se ponga delante y recoja tus hamburguesas apenas llegan 🕙, tampoco puedes prestarle atención a esa persona 😞.

* 📝 Add external link: Serve a machine learning model using Sklearn, FastAPI and Docker. PR [#2974](https://github.com/tiangolo/fastapi/pull/2974) by [@rodrigo-arenas](https://github.com/rodrigo-arenas).
* ✏️ Fix typo on docstring in datastructures file. PR [#2887](https://github.com/tiangolo/fastapi/pull/2887) by [@Kludex](https://github.com/Kludex).

        // moving as she/he scrolls
        const finish = this.generateFinish()
        finish.style.visibility = 'hidden'
        this.container.appendChild(finish)
        // Appends dynamically loaded lines to existing line elements.
        this.lines = [...this.container.querySelectorAll(`[${this.pfx}]`)].concat(this.lineData);
        for (let line of this.lines) {
            line.style.visibility = 'hidden'

## Pydantic

Toda la validación de datos es realizada tras bastidores por <a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a>, así que obtienes todos sus beneficios. Así sabes que estás en buenas manos.

Puedes usar las mismas declaraciones de tipos con `str`, `float`, `bool` y otros tipos de datos más complejos.

Exploraremos varios de estos tipos en los próximos capítulos del tutorial.

## El orden importa

    link: https://www.azepug.az/posts/fastapi/#building-simple-e-commerce-with-nuxtjs-and-fastapi-series
    title: Building simple E-Commerce with NuxtJS and FastAPI
  - author: Rodrigo Arenas
    author_link: https://rodrigo-arenas.medium.com/
    link: https://medium.com/analytics-vidhya/serve-a-machine-learning-model-using-sklearn-fastapi-and-docker-85aabf96729b
    title: "Serve a machine learning model using Sklearn, FastAPI and Docker"

```

### Cache the OpenAPI schema

You can use the property `.openapi_schema` as a "cache", to store your generated schema.

That way, your application won't have to generate the schema every time a user opens your API docs.

It will be generated only once, and then the same cached schema will be used for the next requests.

```Python hl_lines="13-14  25-26"
{!../../../docs_src/extending_openapi/tutorial001.py!}
```

    Including how to handle lifespan state that can be used in other areas of your code.

## Sub Applications

### <a href="https://webargs.readthedocs.io/en/latest/" class="external-link" target="_blank">Webargs</a>

Outro grande recurso necessário pelas APIs é a <abbr title="ler e converter para dados Python">análise</abbr> de dados vindos de requisições.

Webargs é uma ferramente feita para fornecer o que está no topo de vários frameworks, inclusive Flask.