# Module mockwebserver

# Module okhttp-sse

/**
 * A test which demonstrates maven's recursive inheritance where
 * a distinct value is taken from each parent contributing to
 * the final model of the project being assembled. There is no
 * overriding going on amongst the models being used in this test:
 * each model in the lineage is providing a value that is not present
 * anywhere else in the lineage. We are just making sure that values

///

## Importer le `BaseModel` de Pydantic { #import-pydantics-basemodel }

Commencez par importer la classe `BaseModel` du module `pydantic` :

{* ../../docs_src/body/tutorial001_py310.py hl[2] *}

## Créer votre modèle de données { #create-your-data-model }

Déclarez ensuite votre modèle de données en tant que classe qui hérite de `BaseModel`.

Utilisez les types Python standard pour tous les attributs :

import binascii
from base64 import b64decode
from typing import Annotated

from annotated_doc import Doc
from fastapi.exceptions import HTTPException
from fastapi.openapi.models import HTTPBase as HTTPBaseModel
from fastapi.openapi.models import HTTPBearer as HTTPBearerModel
from fastapi.security.base import SecurityBase
from fastapi.security.utils import get_authorization_scheme_param
from pydantic import BaseModel
from starlette.requests import Request

     */
    static class ResolvedPathSource extends PathSource implements ModelSource {
        @Nullable
        private final String modelId;

        ResolvedPathSource(Path path, String location, String modelId) {
            super(path, location);
            this.modelId = modelId;
        }

        @Override
        public Path getPath() {
            return null;
        }

        @Override

* data validation
* data serialization
* 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.

Es verbessert die Editor-Unterstützung für Pydantic-Modelle, mit:

* Code-Vervollständigung
* Typüberprüfungen
* Refaktorisierung
* Suche
* Inspektionen

///

## Das Modell verwenden { #use-the-model }

Innerhalb der Funktion können Sie alle Attribute des Modellobjekts direkt verwenden:

De la même manière, cette base de données n'accepterait pas un modèle Pydantic (un objet avec des attributs), seulement un `dict`.

Vous pouvez utiliser `jsonable_encoder` pour cela.

Elle reçoit un objet, comme un modèle Pydantic, et renvoie une version compatible JSON :

{* ../../docs_src/encoder/tutorial001_py310.py hl[4,21] *}

Dans cet exemple, elle convertirait le modèle Pydantic en `dict`, et le `datetime` en `str`.

Da mesma forma, este banco de dados não receberia um modelo Pydantic (um objeto com atributos), apenas um `dict`.

Você pode usar a função `jsonable_encoder` para resolver isso.

A função recebe um objeto, como um modelo Pydantic e retorna uma versão compatível com JSON:

{* ../../docs_src/encoder/tutorial001_py310.py hl[4,21] *}

Neste exemplo, ele converteria o modelo Pydantic em um `dict`, e o `datetime` em um `str`.