full_name = user_dict["full_name"],
    disabled = user_dict["disabled"],
    hashed_password = user_dict["hashed_password"],
)
```

/// info | 说明

`user_dict` 的说明，详见[**更多模型**一章](../extra-models.md#user_indict){.internal-link target=_blank}。

///

## 返回 Token

`token` 端点的响应必须是 JSON 对象。

响应返回的内容应该包含 `token_type`。本例中用的是**Bearer**Token，因此， Token 类型应为**`bearer`**。

inside and make sure it is serializable as JSON, using the same [JSON Compatible Encoder](../tutorial/encoder.md){.internal-link target=_blank} explained in the tutorial. This is what allows you to return **arbitrary objects**, for example database models.

But if you are certain that the content that you are returning is **serializable with JSON**, you can pass it directly to the response class and avoid the extra overhead that FastAPI would have by passing your return content through the...

    * Convert Python types (`str`, `int`, `float`, `bool`, `list`, etc).
    * `datetime` objects.
    * `UUID` objects.
    * Database models.
    * ...and many more.
* Automatic interactive API documentation, including 2 alternative user interfaces:
    * Swagger UI.
    * ReDoc.

---

Coming back to the previous code example, **FastAPI** will:

/// tip

Pydantic 是 FastAPI 中所有数据验证和序列化的核心，当你在没有设默认值的情况下使用 `Optional` 或 `Union[Something, None]` 时，它具有特殊行为，你可以在 Pydantic 文档中阅读有关<a href="https://docs.pydantic.dev/latest/concepts/models/#required-optional-fields" class="external-link" target="_blank">必需可选字段</a>的更多信息。

///

## 查询参数列表 / 多个值

当你使用 `Query` 显式地定义查询参数时，你还可以声明它去接收一组值，或换句话来说，接收多个值。

例如，要声明一个可在 URL 中出现多次的查询参数 `q`，你可以这样写：

    full_name = user_dict["full_name"],
    disabled = user_dict["disabled"],
    hashed_password = user_dict["hashed_password"],
)
```

/// info | 정보

`**user_dict`에 대한 자세한 설명은 [**추가 모델** 문서](../extra-models.md#about-user_indict){.internal-link target=_blank}를 다시 읽어봅시다.

///

## 토큰 반환하기

`token` 엔드포인트의 응답은 JSON 객체여야 합니다.

`token_type`이 있어야 합니다. 여기서는 "Bearer" 토큰을 사용하므로 토큰 유형은 "`bearer`"여야 합니다.

            assertNotNull(parentElement.child("version").orElse(null));
        }

        @Test
        @DisplayName("should not apply dependency inference to 4.0.0 models")
        void shouldNotApplyDependencyInferenceTo400Models() throws Exception {
            String moduleAPomXml = PomBuilder.create()
                    .namespace("http://maven.apache.org/POM/4.0.0")

     *
     * @return the settings instance
     */
    @Nonnull
    Settings getSettings();

    /**
     * Retrieves toolchain models that have been explicitly configured.
     *
     * @return the toolchain models
     */
    @Nonnull
    Collection<ToolchainModel> getToolchains();

    /**
     * Retrieves the local repository associated with this session.
     *

Вы можете объявлять примеры данных, которые ваше приложение может получать.

Вот несколько способов, как это сделать.

## Дополнительные данные JSON Schema в моделях Pydantic { #extra-json-schema-data-in-pydantic-models }

Вы можете объявить `examples` для модели Pydantic, которые будут добавлены в сгенерированную JSON Schema.

//// tab | Pydantic v2

{* ../../docs_src/schema_extra_example/tutorial001_py310.py hl[13:24] *}

////

            field_info=FieldInfo(annotation=model),
            name=model.__name__,
            mode="validation",
        )
        for model in flat_validation_models
    ]
    flat_serialization_model_fields = [
        ModelField(
            field_info=FieldInfo(annotation=model),
            name=model.__name__,
            mode="serialization",
        )
        for model in flat_serialization_models
    ]

    * Convert Python types (`str`, `int`, `float`, `bool`, `list`, etc).
    * `datetime` objects.
    * `UUID` objects.
    * Database models.
    * ...and many more.
* Automatic interactive API documentation, including 2 alternative user interfaces:
    * Swagger UI.
    * ReDoc.

---

Coming back to the previous code example, **FastAPI** will: