Моделі Pydantic мають метод `.model_dump()`, який повертає `dict` з даними моделі.

Отже, якщо ми створимо об’єкт Pydantic `user_in` так:

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

і викличемо:

```Python
user_dict = user_in.model_dump()
```

тепер ми маємо `dict` з даними у змінній `user_dict` (це `dict`, а не об’єкт моделі Pydantic).

      new SecretKeySpec("secret key".getBytes(UTF_8), "HmacMD5");
  private static final SecretKey SHA1_KEY =
      new SecretKeySpec("secret key".getBytes(UTF_8), "HmacSHA1");
  private static final SecretKey SHA256_KEY =
      new SecretKeySpec("secret key".getBytes(UTF_8), "HmacSHA256");
  private static final SecretKey SHA512_KEY =
      new SecretKeySpec("secret key".getBytes(UTF_8), "HmacSHA512");

Los modelos Pydantic tienen un método `.model_dump()` que devuelve un `dict` con los datos del modelo.

Así que, si creamos un objeto Pydantic `user_in` como:

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

y luego llamamos a:

```Python
user_dict = user_in.model_dump()
```

A única regra rígida para títulos é que o LLM deixe a parte do hash dentro de chaves inalterada, o que garante que os links não quebrem.

Veja a seção `### Headings` no prompt geral em `scripts/translate.py`.

Para algumas instruções específicas do idioma, veja, por exemplo, a seção `### Headings` em `docs/de/llm-prompt.md`.

////

## Termos usados na documentação { #terms-used-in-the-docs }

//// tab | Teste

///

## JWT token'larını yönetme { #handle-jwt-tokens }

Kurulu modülleri import edelim.

JWT token'larını imzalamak için kullanılacak rastgele bir secret key oluşturalım.

Güvenli, rastgele bir secret key üretmek için şu komutu kullanın:

<div class="termy">

```console
$ openssl rand -hex 32

09d25e094faa6ca2556c818166b7a9563b93f7099f6f0f4caa6cf63b88e8d3e7
```

Les modèles Pydantic ont une méthode `.model_dump()` qui renvoie un `dict` avec les données du modèle.

Ainsi, si nous créons un objet Pydantic `user_in` comme :

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

et que nous appelons ensuite :

```Python
user_dict = user_in.model_dump()
```

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

就能以如下方式调用：

```Python
user_dict = user_in.model_dump()
```

现在，变量 `user_dict` 中的是包含数据的 `dict`（它是 `dict`，不是 Pydantic 模型对象）。

以如下方式调用：

```Python
print(user_dict)
```

输出的就是 Python `dict`：

```Python
{
    'username': 'john',
    'password': 'secret',
    'email': '******@****.***',

    /**
     * Access key for cloud storage authentication.
     * Used to authenticate with cloud storage services.
     */
    @Size(max = 1000)
    public String storageAccessKey;

    /**
     * Secret key for cloud storage authentication.
     * Used in conjunction with the access key for cloud storage.
     */
    @Size(max = 1000)
    public String storageSecretKey;

    /**

Pydantic modellerinde, model verilerini içeren bir `dict` döndüren `.model_dump()` metodu bulunur.

Yani, şöyle bir Pydantic nesnesi `user_in` oluşturursak:

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

ve sonra şunu çağırırsak:

```Python
user_dict = user_in.model_dump()
```

Aqui tem um mini [tutorial de como usar SQLModel com FastAPI](https://sqlmodel.tiangolo.com/tutorial/fastapi/). ✨