Vous pouvez retourner un dictionnaire (`dict`), une liste (`list`), des valeurs seules comme des chaines de caractères (`str`) et des entiers (`int`), etc.

Vous pouvez aussi retourner des models **Pydantic** (qui seront détaillés plus tard).

Il y a de nombreux autres objets et modèles qui seront automatiquement convertis en JSON. Essayez d'utiliser vos favoris, il est fort probable qu'ils soient déjà supportés.

{* ../../docs_src/path_params/tutorial005_py39.py hl[1,6:9] *}

/// tip

If you are wondering, "AlexNet", "ResNet", and "LeNet" are just names of Machine Learning <abbr title="Technically, Deep Learning model architectures">models</abbr>.

///

### Declare a *path parameter* { #declare-a-path-parameter }

Then create a *path parameter* with a type annotation using the enum class you created (`ModelName`):

/// 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`**。

import org.apache.maven.project.MavenProject;
import org.eclipse.aether.RepositorySystemSession;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

/**
 * Builds consumer POMs from project models, transforming them into a format suitable for downstream consumers.
 * <p>
 * A consumer POM is a simplified version of a project's POM that is published for consumption by other projects.

    return get_model_fields(model)  # type: ignore[return-value]


# Duplicate of several schema functions from Pydantic v1 to make them compatible with
# Pydantic v2 and allow mixing the models

TypeModelOrEnum = Union[type["BaseModel"], type[Enum]]
TypeModelSet = set[TypeModelOrEnum]


def normalize_name(name: str) -> str:
    return re.sub(r"[^a-zA-Z0-9.\-_]", "_", name)

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:

	// Volume operations.
	MakeVol(ctx context.Context, volume string) (err error)
	MakeVolBulk(ctx context.Context, volumes ...string) (err error)
	ListVols(ctx context.Context) (vols []VolInfo, err error)
	StatVol(ctx context.Context, volume string) (vol VolInfo, err error)
	DeleteVol(ctx context.Context, volume string, forceDelete bool) (err error)

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,
)