And tools will also be happy because both `RedirectResponse` and `JSONResponse` are subclasses of `Response`, so the type annotation is correct.

### Annotate a Response Subclass { #annotate-a-response-subclass }

You can also use a subclass of `Response` in the type annotation:

{* ../../docs_src/response_model/tutorial003_03_py39.py hl[8:9] *}

package org.codelibs.fess.suggest.request;

/**
 * The Response interface serves as a marker interface for all response types
 * in the suggestion system. Implementations of this interface are used to
 * encapsulate the results of various operations and queries within the system.
 *
 * <p>Classes implementing this interface should provide specific details and
 * data relevant to the type of response they represent.</p>
 */
public interface Response {

            val response1 = chain.proceed(chain.request())
            response1.body.close()
            chain.proceed(chain.request())
          },
        ).build()
    val request =
      Request
        .Builder()
        .url(server.url("/"))
        .build()
    val response = client.newCall(request).execute()
    assertThat("b").isEqualTo(response.body.string())
  }

E as ferramentas também ficarão felizes porque `RedirectResponse` e ​​`JSONResponse` são subclasses de `Response`, então a anotação de tipo está correta.

### Anote uma subclasse de Response { #annotate-a-response-subclass }

Você também pode usar uma subclasse de `Response` na anotação de tipo:

    client_no = get_app_client(separate_input_output_schemas=False)
    response = client.post("/items/", json={"name": "Plumbus"})
    response2 = client_no.post("/items/", json={"name": "Plumbus"})
    assert response.status_code == response2.status_code == 200, response.text
    assert (
        response.json()
        == response2.json()
        == {"name": "Plumbus", "description": None, "sub": None}
    )

因此，**FastAPI** 将会负责过滤掉未在输出模型中声明的所有数据（使用 Pydantic）。

## 在文档中查看

当你查看自动化文档时，你可以检查输入模型和输出模型是否都具有自己的 JSON Schema：

<img src="https://fastapi.tiangolo.com/img/tutorial/response-model/image01.png">

并且两种模型都将在交互式 API 文档中使用：

<img src="https://fastapi.tiangolo.com/img/tutorial/response-model/image02.png">

## 响应模型编码参数

你的响应模型可以具有默认值，例如：

{* ../../docs_src/response_model/tutorial004.py hl[11,13:14] *}

        assertNull(response2.getNextResponse());

        // Verify each response maintains its own notifications
        assertEquals(1, response1.getNotifyInformation().size());
        assertEquals(mockNotifyInfo1, response1.getNotifyInformation().get(0));

        assertEquals(1, response2.getNotifyInformation().size());
        assertEquals(mockNotifyInfo2, response2.getNotifyInformation().get(0));
    }

# Código de status de resposta { #response-status-code }

Da mesma forma que você pode especificar um modelo de resposta, você também pode declarar o código de status HTTP usado para a resposta com o parâmetro `status_code` em qualquer uma das *operações de rota*:

* `@app.get()`
* `@app.post()`
* `@app.put()`
* `@app.delete()`
* etc.

{* ../../docs_src/response_status_code/tutorial001_py39.py hl[6] *}

/// note | Nota

## ドキュメントを見る

自動ドキュメントを見ると、入力モデルと出力モデルがそれぞれ独自のJSON Schemaを持っていることが確認できます。

<img src="https://fastapi.tiangolo.com/img/tutorial/response-model/image01.png">

そして、両方のモデルは、対話型のAPIドキュメントに使用されます:

<img src="https://fastapi.tiangolo.com/img/tutorial/response-model/image02.png">

## レスポンスモデルのエンコーディングパラメータ

レスポンスモデルにはデフォルト値を設定することができます:

{* ../../docs_src/response_model/tutorial004.py hl[11,13,14] *}

            response.readBytesWireFormat(buffer1, 0);
            assertEquals(1024, response.getCount());
            assertEquals(512, response.getRemaining());

            // Second read - should update values
            byte[] buffer2 = createValidWriteResponse(2048, 1024);
            response.readBytesWireFormat(buffer2, 0);
            assertEquals(2048, response.getCount());