email: EmailStr
    full_name: str | None = None


class UserIn(UserBase):
    password: str


class UserOut(UserBase):
    pass


class UserInDB(UserBase):
    hashed_password: str


def fake_password_hasher(raw_password: str):
    return "supersecret" + raw_password


def fake_save_user(user_in: UserIn):
    hashed_password = fake_password_hasher(user_in.password)

from pydantic import BaseModel, EmailStr

app = FastAPI()


class UserIn(BaseModel):
    username: str
    password: str
    email: EmailStr
    full_name: str | None = None


class UserOut(BaseModel):
    username: str
    email: EmailStr
    full_name: str | None = None


@app.post("/user/", response_model=UserOut)
async def create_user(user: UserIn) -> Any:

from fastapi import FastAPI
from pydantic import BaseModel, EmailStr

app = FastAPI()


class UserIn(BaseModel):
    username: str
    password: str
    email: EmailStr
    full_name: str | None = None


# Don't do this in production!
@app.post("/user/")
async def create_user(user: UserIn) -> UserIn:

    return "supersecret" + raw_password


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)

app = FastAPI()


class BaseUser(BaseModel):
    username: str
    email: EmailStr
    full_name: str | None = None


class UserIn(BaseUser):
    password: str


@app.post("/user/")
async def create_user(user: UserIn) -> BaseUser:

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

and then we call:

```Python

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

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

`user_in` 是一個 `UserIn` 類別的 Pydantic 模型。

Pydantic 模型有 `.model_dump()` 方法，會回傳包含該模型資料的 `dict`。

因此，若我們建立一個 Pydantic 物件 `user_in` 如：

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

接著呼叫：

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

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

`user_in` - це модель Pydantic класу `UserIn`.

Моделі Pydantic мають метод `.model_dump()`, який повертає `dict` з даними моделі.

Отже, якщо ми створимо об’єкт Pydantic `user_in` так:

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

і викличемо:

```Python

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

`user_in` es un modelo Pydantic de la clase `UserIn`.

Los modelos Pydantic tienen un método `.model_dump()` que devuelve un `dict` con los datos del modelo.

Así que, si creamos un objeto Pydantic `user_in` como:

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

y luego llamamos a:

```Python

#### La méthode `.model_dump()` de Pydantic { #pydantics-model-dump }

`user_in` est un modèle Pydantic de classe `UserIn`.

Les modèles Pydantic ont une méthode `.model_dump()` qui renvoie un `dict` avec les données du modèle.

Ainsi, si nous créons un objet Pydantic `user_in` comme :

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

et que nous appelons ensuite :

```Python