* the item's current state.
     * </p>
     *
     * @param dictId the dictionary ID to store the character mapping item in
     * @param charMappingItem the character mapping item to store
     */
    public void store(final String dictId, final CharMappingItem charMappingItem) {
        getCharMappingFile(dictId).ifPresent(file -> {
            if (charMappingItem.getId() == 0) {

from fastapi import FastAPI

app = FastAPI()


@app.get("/")
def read_root():
    return {"Hello": "World"}


@app.get("/items/{item_id}")
def read_item(item_id: int, q: Union[str, None] = None):
    return {"item_id": item_id, "q": q}
```

### Dockerfile { #dockerfile }

Erstellen Sie nun im selben Projektverzeichnis eine Datei `Dockerfile` mit:

```{ .dockerfile .annotate }

from fastapi import FastAPI

app = FastAPI()


@app.get("/")
def read_root():
    return {"Hello": "World"}


@app.get("/items/{item_id}")
def read_item(item_id: int, q: Union[str, None] = None):
    return {"item_id": item_id, "q": q}
```

### Dockerfile { #dockerfile }

Agora, no mesmo diretório do projeto, crie um arquivo `Dockerfile` com:

```{ .dockerfile .annotate }

from fastapi import FastAPI

app = FastAPI()


@app.get("/")
def read_root():
    return {"Hello": "World"}


@app.get("/items/{item_id}")
def read_item(item_id: int, q: Union[str, None] = None):
    return {"item_id": item_id, "q": q}
```

### Dockerfile { #dockerfile }

Ahora, en el mismo directorio del proyecto, crea un archivo `Dockerfile` con:

```{ .dockerfile .annotate }

from fastapi import FastAPI

app = FastAPI()


@app.get("/")
def read_root():
    return {"Hello": "World"}


@app.get("/items/{item_id}")
def read_item(item_id: int, q: Union[str, None] = None):
    return {"item_id": item_id, "q": q}
```

### Dockerfile

现在在相同的project目录创建一个名为`Dockerfile`的文件:

```{ .dockerfile .annotate }
# (1)
FROM python:3.9

# (2)

{* ../../docs_src/pydantic_v1_in_v2/tutorial003_an_py310.py hl[2:3,6,12,21:22] *}

En el ejemplo anterior, el modelo de entrada es un modelo de Pydantic v1 y el modelo de salida (definido en `response_model=ItemV2`) es un modelo de Pydantic v2.

### Parámetros de Pydantic v1 { #pydantic-v1-parameters }

{* ../../docs_src/pydantic_v1_in_v2/tutorial003_an_py310.py hl[2:3,6,12,21:22] *}

No exemplo acima, o modelo de entrada é um modelo Pydantic v1, e o modelo de saída (definido em `response_model=ItemV2`) é um modelo Pydantic v2.

### Parâmetros do Pydantic v1 { #pydantic-v1-parameters }

    client = TestClient(mod.app)
    access_token = get_access_token(client=client)
    response = client.get(
        "/users/me/items/", headers={"Authorization": f"Bearer {access_token}"}
    )
    assert response.status_code == 200, response.text
    assert response.json() == [{"item_id": "Foo", "owner": "johndoe"}]


def test_openapi_schema(mod: ModuleType):
    client = TestClient(mod.app)

    client = TestClient(mod.app)
    access_token = get_access_token(scope="me items", client=client)
    response = client.get(
        "/users/me/items/", headers={"Authorization": f"Bearer {access_token}"}
    )
    assert response.status_code == 200, response.text
    assert response.json() == [{"item_id": "Foo", "owner": "johndoe"}]


def test_read_system_status(mod: ModuleType):

        from pydantic import BaseModel

        class Item(BaseModel):
            name: str
            description: str | None = None

        app = FastAPI()
        router = APIRouter()

        @router.put("/items/{item_id}")
        def replace_item(item_id: str, item: Item):
            return {"message": "Item replaced", "id": item_id}

        app.include_router(router)
        ```