/// 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 | 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`**。

from collections.abc import Sequence
from dataclasses import dataclass
from enum import Enum
from typing import Annotated, Any, Callable, Optional, Union

from fastapi.exceptions import FastAPIDeprecationWarning
from fastapi.openapi.models import Example
from pydantic import AliasChoices, AliasPath
from pydantic.fields import FieldInfo
from typing_extensions import Literal, deprecated

from ._compat import (
    Undefined,
)

You do that with standard modern Python types.

You don't have to learn a new syntax, the methods or classes of a specific library, etc.

Just standard **Python**.

For example, for an `int`:

```Python
item_id: int
```

or for a more complex `Item` model:

```Python
item: Item
```

...and with that single declaration you get:

     *
     * @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.
     *

            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
    ]

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...

    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.

                    .build();

            Document moduleADoc = Document.of(moduleAPomXml);
            Document moduleBDoc = Document.of(moduleBPomXml);

            Map<Path, Document> pomMap = new HashMap<>();
            pomMap.put(Paths.get("project", "module-a", "pom.xml"), moduleADoc);
            pomMap.put(Paths.get("project", "module-b", "pom.xml"), moduleBDoc);

package tests_test

import (
	"context"
	"testing"

	"gorm.io/gorm"
	"gorm.io/gorm/clause"
	. "gorm.io/gorm/utils/tests"
)

// BelongsToCompany and BelongsToUser models for belongs to tests - using existing User and Company models

// Test Set + Create with Association OpCreate operation using real database
func TestClauseAssociationSetCreateWithOpCreate(t *testing.T) {
	ctx := context.Background()