///

## Motivatie

Laten we beginnen met een eenvoudig voorbeeld:

{* ../../docs_src/python_types/tutorial001.py *}


Het aanroepen van dit programma leidt tot het volgende resultaat:

```
John Doe
```

De functie voert het volgende uit:

* Neem een `first_name` en een `last_name`
* Converteer de eerste letter van elk naar een hoofdletter met `title()`.
``

# Een Pydantic model
class User(BaseModel):
    id: int
    name: str
    joined: date
```

Vervolgens kan je het op deze manier gebruiken:

```Python
my_user: User = User(id=3, name="John Doe", joined="2018-07-19")

second_user_data = {
    "id": 4,
    "name": "Mary",
    "joined": "2018-11-30",
}

my_second_user: User = User(**second_user_data)
```

/// info

<img src="/img/tutorial/security/image08.png">

Call the endpoint `/users/me/`, you will get the response as:

```JSON
{
  "username": "johndoe",
  "email": "******@****.***",
  "full_name": "John Doe",
  "disabled": false
}
```

<img src="/img/tutorial/security/image09.png">

// Bean metadata introspection
BeanDesc beanDesc = BeanDescFactory.getBeanDesc(MyBean.class);
PropertyDesc nameProperty = beanDesc.getPropertyDesc("name");
nameProperty.setValue(bean, "John Doe");

// Bean copying with flexible options
BeanUtil.copyBeanToBean(source, destination);
BeanUtil.copyBeanToBean(source, destination, options -> 
    options.exclude("password", "internalId"));

///

<img src="/img/tutorial/security/image08.png">

Вызвав эндпоинт `/users/me/`, вы получите ответ в виде:

```JSON
{
  "username": "johndoe",
  "email": "******@****.***",
  "full_name": "John Doe",
  "disabled": false
}
```

<img src="/img/tutorial/security/image09.png">

# Pydantic modeli
class User(BaseModel):
    id: int
    name: str
    joined: date
```

Sonrasında bu şekilde kullanabilirsin

```Python
my_user: User = User(id=3, name="John Doe", joined="2018-07-19")

second_user_data = {
    "id": 4,
    "name": "Mary",
    "joined": "2018-11-30",
}

my_second_user: User = User(**second_user_data)
```

/// info

# Model Pydantic
class User(BaseModel):
    id: int
    name: str
    joined: date
```

A one będą mogły zostać później użyte w następujący sposób:

```Python
my_user: User = User(id=3, name="John Doe", joined="2018-07-19")

second_user_data = {
    "id": 4,
    "name": "Mary",
    "joined": "2018-11-30",
}

my_second_user: User = User(**second_user_data)
```

/// info

# Ein Pydantic-Modell
class User(BaseModel):
    id: int
    name: str
    joined: date
```

Das kann nun wie folgt verwendet werden:

```Python
my_user: User = User(id=3, name="John Doe", joined="2018-07-19")

second_user_data = {
    "id": 4,
    "name": "Mary",
    "joined": "2018-11-30",
}

my_second_user: User = User(**second_user_data)
```

/// info

    return user_id


# A Pydantic model
class User(BaseModel):
    id: int
    name: str
    joined: date
```

That can then be used like:

```Python
my_user: User = User(id=3, name="John Doe", joined="2018-07-19")

second_user_data = {
    "id": 4,
    "name": "Mary",
    "joined": "2018-11-30",
}

my_second_user: User = User(**second_user_data)
```

/// info

### 자신의 유저 데이터 가져오기

이제 `/users/me` 경로에 `GET` 작업을 진행합시다.

다음과 같은 사용자 데이터를 얻을 수 있습니다:

```JSON
{
  "username": "johndoe",
  "email": "******@****.***",
  "full_name": "John Doe",
  "disabled": false,
  "hashed_password": "fakehashedsecret"
}
```

<img src="/img/tutorial/security/image06.png">

잠금 아이콘을 클릭하고 로그아웃한 다음 동일한 작업을 다시 시도하면 다음과 같은 HTTP 401 오류가 발생합니다.

```JSON