assert response.json() == {
        "user_me": {
            "user_me": "user_me_1",
            "current_user": {
                "user": "user_1",
                "scopes": ["me"],
                "db_session": "db_session_1",
            },
        },
        "user_items": {
            "user_items": "user_items_1",
            "user_me": {
                "user_me": "user_me_2",
                "current_user": {

### About `**user_in.model_dump()` { #about-user-in-model-dump }

#### Pydantic's `.model_dump()` { #pydantics-model-dump }

`user_in` is a Pydantic model of class `UserIn`.

Pydantic models have a `.model_dump()` method that returns a `dict` with the model's data.

So, if we create a Pydantic object `user_in` like:

```Python

     * Handles user authentication setup and database persistence.
     * If the surname is blank, it will be set to the user's name.
     *
     * @param user the user entity to store
     */
    public void store(final User user) {
        final String username = user.getName();
        final boolean isUpdate = StringUtil.isNotBlank(user.getId());

        if (logger.isDebugEnabled()) {

def fake_save_user(user_in: UserIn):
    hashed_password = fake_password_hasher(user_in.password)
    user_in_db = UserInDB(**user_in.model_dump(), hashed_password=hashed_password)
    print("User saved! ..not really")
    return user_in_db


@app.post("/user/", response_model=UserOut)
async def create_user(user_in: UserIn):
    user_saved = fake_save_user(user_in)

def fake_save_user(user_in: UserIn):
    hashed_password = fake_password_hasher(user_in.password)
    user_in_db = UserInDB(**user_in.model_dump(), hashed_password=hashed_password)
    print("User saved! ..not really")
    return user_in_db


@app.post("/user/", response_model=UserOut)
async def create_user(user_in: UserIn):
    user_saved = fake_save_user(user_in)

Wenn wir also ein Pydantic-Objekt `user_in` erstellen, etwa so:

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

und dann aufrufen:

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

haben wir jetzt ein `dict` mit den Daten in der Variablen `user_dict` (es ist ein `dict` statt eines Pydantic-Modellobjekts).

///

### Про `**user_in.dict()` { #about-user-in-dict }

#### `.dict()` из Pydantic { #pydantics-dict }

`user_in` - это Pydantic-модель класса `UserIn`.

У Pydantic-моделей есть метод `.dict()`, который возвращает `dict` с данными модели.

Поэтому, если мы создадим Pydantic-объект `user_in` таким способом:

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

///

### Sobre `**user_in.dict()` { #about-user-in-dict }

#### O `.dict()` do Pydantic { #pydantics-dict }

`user_in` é um modelo Pydantic da classe `UserIn`.

Os modelos Pydantic possuem um método `.dict()` que retorna um `dict` com os dados do modelo.

Então, se criarmos um objeto Pydantic `user_in` como:

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

        assertEquals("Abc", StringUtil.capitalize("abc"));
        assertEquals("Abc", StringUtil.capitalize("Abc"));
        assertEquals("ABC", StringUtil.capitalize("ABC"));
        assertEquals("UserId", StringUtil.capitalize("userId"));
    }

    /**
     * @throws Exception
     */
    @Test
    public void testDecapitalize() throws Exception {
        assertEquals("abc", StringUtil.decapitalize("abc"));

from fastapi import APIRouter

router = APIRouter()


@router.get("/users/", tags=["users"])
async def read_users():
    return [{"username": "Rick"}, {"username": "Morty"}]


@router.get("/users/me", tags=["users"])
async def read_user_me():
    return {"username": "fakecurrentuser"}


@router.get("/users/{username}", tags=["users"])
async def read_user(username: str):