```Python hl_lines="10"
{!../../docs_src/security/tutorial001.py!}
```

✋️ 👈 🚫 👈 ⚠.

➡️ ⚒ ⚫️ 🤝 👥 ⏮️ 👩‍💻.

## ✍ 👩‍💻 🏷

🥇, ➡️ ✍ Pydantic 👩‍💻 🏷.

🎏 🌌 👥 ⚙️ Pydantic 📣 💪, 👥 💪 ⚙️ ⚫️ 🙆 🙆:

//// tab | 🐍 3️⃣.6️⃣ & 🔛

```Python hl_lines="5  12-16"
{!> ../../docs_src/security/tutorial002.py!}
```

////

//// tab | 🐍 3️⃣.1️⃣0️⃣ & 🔛

from typing import Optional

from dirty_equals import IsDict
from fastapi import Depends, FastAPI, Security
from fastapi.security import OAuth2, OAuth2PasswordRequestFormStrict
from fastapi.testclient import TestClient
from pydantic import BaseModel

app = FastAPI()

reusable_oauth2 = OAuth2(
    flows={
        "password": {
            "tokenUrl": "token",
            "scopes": {"read:users": "Read the users", "write:users": "Create users"},

Da mesma forma, este banco de dados não receberia um modelo Pydantic (um objeto com atributos), apenas um `dict`.

Você pode usar a função `jsonable_encoder` para resolver isso.

A função recebe um objeto, como um modelo Pydantic e retorna uma versão compatível com JSON:

//// tab | Python 3.10+

```Python hl_lines="4  21"

## Pydantic 的 `Settings`

幸运的是，Pydantic 提供了一个很好的工具来处理来自环境变量的设置，即<a href="https://docs.pydantic.dev/latest/concepts/pydantic_settings/" class="external-link" target="_blank">Pydantic: Settings management</a>。

### 创建 `Settings` 对象

从 Pydantic 导入 `BaseSettings` 并创建一个子类，与 Pydantic 模型非常相似。

与 Pydantic 模型一样，您使用类型注释声明类属性，还可以指定默认值。

您可以使用与 Pydantic 模型相同的验证功能和工具，比如不同的数据类型和使用 `Field()` 进行附加验证。

## Zusätzliche JSON-Schemadaten in Pydantic-Modellen

Sie können `examples` („Beispiele“) für ein Pydantic-Modell deklarieren, welche dem generierten JSON-Schema hinzugefügt werden.

//// tab | Python 3.10+ Pydantic v2

```Python hl_lines="13-24"
{!> ../../docs_src/schema_extra_example/tutorial001_py310.py!}
```

////

//// tab | Python 3.10+ Pydantic v1

```Python hl_lines="13-23"

* `Decimal`:
    * Standard Python `Decimal`.
    * In requests and responses, handled the same as a `float`.
* You can check all the valid Pydantic data types here: <a href="https://docs.pydantic.dev/latest/usage/types/types/" class="external-link" target="_blank">Pydantic data types</a>.

## Example

Here's an example *path operation* with parameters using some of the above types.

//// tab | Python 3.10+

使用 <a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a> 模型声明**请求体**，能充分利用它的功能和优点。

/// info | "说明"

发送数据使用 `POST`（最常用）、`PUT`、`DELETE`、`PATCH` 等操作。

规范中没有定义使用 `GET` 发送请求体的操作，但不管怎样，FastAPI 也支持这种方式，只不过仅用于非常复杂或极端的用例。

我们不建议使用 `GET`，因此，在 Swagger UI 交互文档中不会显示有关 `GET` 的内容，而且代理协议也不一定支持 `GET`。

///

## 导入 Pydantic 的 `BaseModel`

从 `pydantic` 中导入 `BaseModel`：

{!> ../../docs_src/extra_models/tutorial001_py310.py!}
```

////

### 🔃 `**user_in.dict()`

#### Pydantic `.dict()`

`user_in` Pydantic 🏷 🎓 `UserIn`.

Pydantic 🏷 ✔️ `.dict()` 👩‍🔬 👈 📨 `dict` ⏮️ 🏷 💽.

, 🚥 👥 ✍ Pydantic 🎚 `user_in` 💖:

```Python
user_in = UserIn(username="john", password="secret", email="******@****.***")
```

& ⤴️ 👥 🤙:

            Any,
            Doc(
                """
                The type to use for the response.

                It could be any valid Pydantic *field* type. So, it doesn't have to
                be a Pydantic model, it could be other things, like a `list`, `dict`,
                etc.

                It will be used for:

* 100% test coverage.
* 100% type annotated codebase.

## Pydantic features

**FastAPI** is fully compatible with (and based on) <a href="https://docs.pydantic.dev/" class="external-link" target="_blank"><strong>Pydantic</strong></a>. So, any additional Pydantic code you have, will also work.