On peut aussi ajouter plus d'informations sur le paramètre.

Ces informations seront incluses dans le schéma `OpenAPI` généré et utilisées par la documentation interactive ou les outils externes utilisés.

!!! note
    Gardez en tête que les outils externes utilisés ne supportent pas forcément tous parfaitement OpenAPI.

This decoupling of parts, and being a "microframework" that could be extended to cover exactly what is needed was a key feature that I wanted to keep.

Given the simplicity of Flask, it seemed like a good match for building APIs. The next thing to find was a "Django REST Framework" for Flask.

### Testado

* 100% <abbr title="A quantidade de código que é testada automaticamente">de cobertura de testes</abbr>.
* 100% do código utiliza <abbr title="Type annotations do Python, com isso seu editor e ferramentas externas podem te dar um suporte melhor">type annotations</abbr>.
* Usado para aplicações em produção.

## Recursos do Starlette

### Testé

* 100% <abbr title="La quantité de code qui est testé automatiquement">de couverture de test</abbr>.
* 100% <abbr title="Annotation de types Python, avec cela votre éditeur et autres outils externes peuvent vous fournir un meilleur support">d'annotations de type</abbr> dans le code.
* Utilisé dans des applications mises en production.

## Fonctionnalités de Starlette

### Probado

* <abbr title="La cantidad de código que es probado automáticamente">Cobertura de pruebas</abbr> al 100%.
*  Base de código 100% <abbr title="Type annotations de Python, con esto tu editor y otras herramientas externas pueden darte mejor soporte">anotada con tipos</abbr>.
* Usado en aplicaciones en producción.

## Características de Starlette

        )
        flat_dependant.path_params.extend(flat_sub.path_params)
        flat_dependant.query_params.extend(flat_sub.query_params)
        flat_dependant.header_params.extend(flat_sub.header_params)
        flat_dependant.cookie_params.extend(flat_sub.cookie_params)
        flat_dependant.body_params.extend(flat_sub.body_params)
        flat_dependant.security_requirements.extend(flat_sub.security_requirements)
    return flat_dependant

            if route.response_fields:
                responses_from_routes.extend(route.response_fields.values())
            if route.callbacks:
                callback_flat_models.extend(get_fields_from_routes(route.callbacks))
            params = get_flat_params(route.dependant)
            request_fields_from_routes.extend(params)

    flat_models = callback_flat_models + list(

Usando essa combinação levou a criação de vários geradores Flask _full-stack_. Há muitas _stacks_ que eu (e vários times externos) estou utilizando até agora:

* <a href="https://github.com/tiangolo/full-stack" class="external-link" target="_blank">https://github.com/tiangolo/full-stack</a>

                    errors=[error], model=RequestErrorModel
                ).errors()
                use_errors.extend(new_errors)
            elif isinstance(error, list):
                use_errors.extend(_normalize_errors(error))
            else:
                use_errors.append(error)
        return use_errors

    def _model_rebuild(model: Type[BaseModel]) -> None:

    You can set `schema_extra` with a `dict` containing any additional data you would like to show up in the generated JSON Schema, including `examples`.

!!! tip
    You could use the same technique to extend the JSON Schema and add your own custom extra info.

    For example you could use it to add metadata for a frontend user interface, etc.

!!! info