# to be read from files and other types, but I'm not even sure it's a good idea
    # to support it as a first class "feature"
    assert is_bytes_sequence_annotation(Union[List[str], List[bytes]])


def test_is_uploadfile_sequence_annotation():
    # For coverage
    # TODO: in theory this would allow declaring types that could be lists of UploadFile

📥 👥 🔜 👀 🖼 ⚙️ **<a href="https://www.couchbase.com/" class="external-link" target="_blank">🗄</a>**, <abbr title="Document here refers to a JSON object (a dict), with keys and values, and those values can also be other JSON objects, arrays (lists), numbers, strings, booleans, etc.">📄</abbr> 🧢 ☁ 💽.

👆 💪 🛠️ ⚫️ 🙆 🎏 ☁ 💽 💖:

* **✳**
* **👸**
* **✳**
* **🇸🇲**
* **✳**, ♒️.

!!! tip

`response_model` receives the same type you would declare for a Pydantic model field, so, it can be a Pydantic model, but it can also be, e.g. a `list` of Pydantic models, like `List[Item]`.

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

You can adapt it to any other NoSQL database like:

* **MongoDB**
* **Cassandra**
* **CouchDB**
* **ArangoDB**
* **ElasticSearch**, etc.

    ```

This will make `tags` be a list, although it doesn't declare the type of the elements of the list.

## List fields with type parameter

But Python has a specific way to declare lists with internal types, or "type parameters":

### Import typing's `List`

In Python 3.9 and above you can use the standard `list` to declare these type annotations as we'll see below. 💡

  ]
}
```

#### Utiliser `list`

Il est aussi possible d'utiliser directement `list` plutôt que `List[str]` :

```Python hl_lines="7"
{!../../../docs_src/query_params_str_validations/tutorial013.py!}
```

!!! note
    Dans ce cas-là, **FastAPI** ne vérifiera pas le contenu de la liste.

```Python
my_list: list[str]
```

Und in Python-Versionen vor 3.9:

```Python
from typing import List

my_list: List[str]
```

Das ist alles Standard-Python-Syntax für Typdeklarationen.

Verwenden Sie dieselbe Standardsyntax für Modellattribute mit inneren Typen.

In unserem Beispiel können wir also bewirken, dass `tags` spezifisch eine „Liste von Strings“ ist:

=== "Python 3.10+"

    ```Python hl_lines="12"

## Usando el `jsonable_encoder` en una `Response`

Como **FastAPI** no realiza ningún cambio en la `Response` que devuelves, debes asegurarte de que el contenido está listo.

Por ejemplo, no puedes poner un modelo Pydantic en una `JSONResponse` sin primero convertirlo a un `dict` con todos los tipos de datos (como `datetime`, `UUID`, etc) convertidos a tipos compatibles con JSON.

## List of models

The same way, you can declare responses of lists of objects.

For that, use the standard Python `typing.List` (or just `list` in Python 3.9 and above):

=== "Python 3.9+"

    ```Python hl_lines="18"
    {!> ../../../docs_src/extra_models/tutorial004_py39.py!}

Mais, **tout fonctionne** par défaut.

### Validation

* Validation pour la plupart (ou tous?) les **types de données** Python incluant:
    * objets JSON (`dict`).
    * listes JSON (`list`) définissant des types d'éléments.
    * Champs String (`str`), définition de longueur minimum ou maximale.
    * Nombres (`int`, `float`) avec valeur minimale and maximale, etc.