for _, join := range joins {
			if _, ok := relationships.Relations[join]; ok && name == join {
				joined = true
				continue
			}
			joinNames := strings.SplitN(join, ".", 2)
			if len(joinNames) == 2 {
				if _, ok := relationships.Relations[joinNames[0]]; ok && name == joinNames[0] {
					joined = true
					nestedJoins = append(nestedJoins, joinNames[1])
				}
			}
		}
		return joined, nestedJoins
	}

    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",
    "joined": "2018-11-30",
}

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

/// info | "Информация"

    return user_id


# Un modèle Pydantic
class User(BaseModel):
    id: int
    name: str
    joined: date
```
Qui peuvent ensuite être utilisés comme cela:

```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
```

که سپس میتوان به این شکل از آن استفاده کرد:

```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


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

Este puede ser usado como:

```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 | Información

    return user_id


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

👈 💪 ⤴️ ⚙️ 💖:

```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

`**second_user_data` ⛓:

    return user_id


# 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

On Windows, [Current] has been made considerably faster when
the current user is joined to a slow domain, which is the
usual case for many corporate users. The new implementation
performance is now in the order of milliseconds, compared to
the previous implementation which could take several seconds,

    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",
    "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