- required:
                        - cluster
                      properties:
                        cluster:
                          description: Match on envoy cluster attributes.
                          properties:
                            name:
                              description: The exact name of the cluster to match.
                              type: string

    *   `Estimator.export_savedmodel` has been renamed to `export_saved_model`.
    *   When saving to SavedModel, Estimators will strip default op attributes.
        This is almost always the correct behavior, as it is more forwards
        compatible, but if you require that default attributes to be saved with
        the model, please use `tf.compat.v1.Estimator`.
    *   Feature Columns have been upgraded to be more Eager-friendly and to work

                      - required:
                        - cluster
                      properties:
                        cluster:
                          description: Match on envoy cluster attributes.
                          properties:
                            name:
                              description: The exact name of the cluster to match.
                              type: string

        * Before this, the return content was first passed through `jsonable_encoder` to ensure it was a "jsonable" object, like a `dict`, instead of an arbitrary object with attributes (like an ORM model). That's why you should make sure to update your Pydantic models for objects with attributes to use `orm_mode = True`.
        * If you don't have a `response_model`, the return object will still be passed through `jsonable_encoder` first.

* Bei `PUT`-Anfragen an `/items/{item_id}` den Body als JSON lesen:
    * Prüfen, ob er ein erforderliches Attribut `name` hat, das ein `str` sein muss.
    * Prüfen, ob er ein erforderliches Attribut `price` hat, das ein `float` sein muss.
    * Prüfen, ob er ein optionales Attribut `is_offer` hat, das ein `bool` sein muss, falls vorhanden.
    * All dies würde auch für tief verschachtelte JSON-Objekte funktionieren.

* Per le richieste `PUT` su `/items/{item_id}`, leggerà il body come JSON, questo comprende:
    * verifica che la richiesta abbia un attributo obbligatorio `name` e che sia di tipo `str`.
    * verifica che la richiesta abbia un attributo obbligatorio `price` e che sia di tipo `float`.
    * verifica che la richiesta abbia un attributo opzionale `is_offer` e che sia di tipo `bool`, se presente.
    * Tutto questo funzionerebbe anche con oggetti JSON più complessi.

```Python
from typing import List

my_list: List[str]
```

Essa é a sintaxe padrão do Python para declarações de tipo.

Use a mesma sintaxe padrão para atributos de modelo com tipos internos.

Portanto, em nosso exemplo, podemos fazer com que `tags` sejam especificamente uma "lista de strings":


```Python hl_lines="14"
{!../../../docs_src/body_nested_models/tutorial002.py!}

    * Vérifier qu'il a un attribut obligatoire `name` qui devrait être un `str`.
    * Vérifier qu'il a un attribut obligatoire `prix` qui doit être un `float`.
    * Vérifier qu'il a un attribut facultatif `is_offer`, qui devrait être un `bool`, s'il est présent.

{!../../../docs_src/body/tutorial001.py!}
```

## Crie seu modelo de dados

Então você declara seu modelo de dados como uma classe que herda `BaseModel`.

Utilize os tipos Python padrão para todos os atributos:

```Python hl_lines="7-11"
{!../../../docs_src/body/tutorial001.py!}
```

!!! info
    Webhooks are available in OpenAPI 3.1.0 and above, supported by FastAPI `0.99.0` and above.

## An app with webhooks

When you create a **FastAPI** application, there is a `webhooks` attribute that you can use to define *webhooks*, the same way you would define *path operations*, for example with `@app.webhooks.post()`.

```Python hl_lines="9-13  36-53"
{!../../../docs_src/openapi_webhooks/tutorial001.py!}
```