}
}

func TestScopes(t *testing.T) {
	users := []*User{
		GetUser("ScopeUser1", Config{}),
		GetUser("ScopeUser2", Config{}),
		GetUser("ScopeUser3", Config{}),
	}

	DB.Create(&users)

	var users1, users2, users3 []User
	DB.Scopes(NameIn1And2).Find(&users1)
	if len(users1) != 2 {
		t.Errorf("Should found two users's name in 1, 2, but got %v", len(users1))
	}

	DB.Scopes(NameIn1And2, NameIn2And3).Find(&users2)

# und bekommen Sie Editor-Unterstützung innerhalb der Funktion
def main(user_id: str):
    return user_id


# 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",

Nehmen wir zum Beispiel an, Sie haben vier API-Endpunkte (*Pfadoperationen*):

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

Dann könnten Sie für jeden davon unterschiedliche Berechtigungsanforderungen hinzufügen, nur mit Abhängigkeiten und Unterabhängigkeiten:

```mermaid
graph TB

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
```

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",

# Değişkeni str olarak belirt
# ve o fonksiyon için harika bir editör desteği al
def main(user_id: str):
    return user_id


# 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",

///

### `**user_in.dict()` 에 대하여

#### Pydantic의 `.dict()`

`user_in`은 Pydantic 모델 클래스인 `UserIn`입니다.

Pydantic 모델은 모델 데이터를 포함한 `dict`를 반환하는 `.dict()` 메서드를 제공합니다.

따라서, 다음과 같이 Pydantic 객체 `user_in`을 생성할 수 있습니다:

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

그 다음, 다음과 같이 호출합니다:

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

For example, let's say you have 4 API endpoints (*path operations*):

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

then you could add different permission requirements for each of them just with dependencies and sub-dependencies:

```mermaid
graph TB

current_user(["current_user"])

# Объявляем параметр как `str`
# и получаем поддержку редактора кода внутри функции
def main(user_id: str):
    return user_id


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

Это можно использовать так:

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

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

### `**user_in.dict()`について

#### Pydanticの`.dict()`

`user_in`は`UserIn`クラスのPydanticモデルです。

Pydanticモデルには、モデルのデータを含む`dict`を返す`.dict()`メソッドがあります。

そこで、以下のようなPydanticオブジェクト`user_in`を作成すると:

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

そして呼び出すと:

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

# Declare uma variável como str
# e obtenha suporte do editor dentro da função
def main(user_id: str):
    return user_id


# Um modelo do Pydantic
class User(BaseModel):
    id: int
    name: str
    joined: date
```

Que então pode ser usado como:

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

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