}
	return validDN, err
}

// GetValidatedUserDN validates the given user DN. Will error out if conn is nil. The returned
// boolean is true iff the user DN is found under one of the LDAP user base DNs.
func (l *Config) GetValidatedUserDN(conn *ldap.Conn, userDN string) (*xldap.DNSearchResult, bool, error) {
	return l.GetValidatedDNUnderBaseDN(conn, userDN,
		l.LDAP.GetUserDNSearchBaseDistNames(), l.LDAP.GetUserDNAttributesList())
}

Por exemplo, vamos supor que você possua 4 endpoints na sua API (*operações de rota*):

* `/items/public/`
* `/items/private/`
* `/users/{user_id}/activate`
* `/items/pro/`

Você poderia adicionar diferentes requisitos de permissão para cada um deles utilizando apenas dependências e sub-dependências:

```mermaid
graph TB

cluster now additionally requests a token with the  "userinfo.email" scope. This way, users can write ClusterRoleBindings/RoleBindings with the email address of the service account directly. (This is a breaking change if the numeric uniqueIDs of the Google service accounts were being used in RBAC role bindings. The behavior can be overridden by explicitly specifying the scope values as comma-separated string in the "users[*].config.scopes" field in the KUBECONFIG file.) This way, users can now  set a Google...

from pydantic import BaseModel

# Declare a variable as a str
# and get editor support inside the function
def main(user_id: str):
    return user_id


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

Sau đó có thể được sử dụng:

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

second_user_data = {
    "id": 4,
    "name": "Mary",

from pydantic import BaseModel

# Declare a variable as a str
# and get editor support inside the function
def main(user_id: str):
    return user_id


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

可以像这样来使用：

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

second_user_data = {
    "id": 4,
    "name": "Mary",

这会需要一些“等待时间”。

但是由于 SQLAlchemy 不具有`await`直接使用的兼容性，因此类似于：

```Python
user = await db.query(User).first()
```

...相反，我们可以使用：

```Python
user = db.query(User).first()
```

然后我们应该声明*路径操作函数*和不带 的依赖关系`async def`，只需使用普通的`def`，如下：

```Python hl_lines="2"
@app.get("/users/{user_id}", response_model=schemas.User)
def read_user(user_id: int, db: Session = Depends(get_db)):

/// note | "기술 세부사항"

응답 모델은 함수의 타입 어노테이션 대신 이 매개변수로 선언하는데, 경로 함수가 실제 응답 모델을 반환하지 않고 `dict`, 데이터베이스 객체나 기타 다른 모델을 `response_model`을 사용하여 필드 제한과 직렬화를 수행하고 반환할 수 있기 때문입니다

///

## 동일한 입력 데이터 반환

여기서 우리는 평문 비밀번호를 포함하는 `UserIn` 모델을 선언합니다:

```Python hl_lines="9  11"
{!../../docs_src/response_model/tutorial002.py!}
```

그리고 이 모델을 사용하여 입력을 선언하고 같은 모델로 출력을 선언합니다:

```Python hl_lines="17-18"

	}

	if err := DB.Delete(&user).Error; err != nil {
		t.Fatalf("No error should happen when soft delete user, but got %v", err)
	}

	if sql.NullTime(user.DeletedAt).Time.IsZero() {
		t.Fatalf("user's deleted at is zero")
	}

	sql := DB.Session(&gorm.Session{DryRun: true}).Delete(&user).Statement.SQL.String()

/**
 * A {@link Graph} whose elements and structural relationships will never change. Instances of this
 * class may be obtained with {@link #copyOf(Graph)}.
 *
 * <p>See the Guava User's Guide's <a
 * href="https://github.com/google/guava/wiki/GraphsExplained#immutable-implementations">discussion
 * of the {@code Immutable*} types</a> for more information on the properties and guarantees
 * provided by this class.

from datetime import date

from pydantic import BaseModel

# 변수를 str로 선언
# 그 후 함수 안에서 편집기 지원을 받으세요
def main(user_id: str):
    return user_id


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

위의 코드는 다음과 같이 사용될 수 있습니다:

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

second_user_data = {
    "id": 4,
    "name": "Mary",