* Pass the internal type(s) as "type parameters" using square brackets: `[` and `]`

In Python 3.9 it would be:

```Python
my_list: list[str]
```

In versions of Python before 3.9, it would be:

```Python
from typing import List

my_list: List[str]
```

That's all standard Python syntax for type declarations.

Use that same standard syntax for model attributes with internal types.

```Python
from datetime import date

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
```

که سپس میتوان به این شکل از آن استفاده کرد:

```Python

=== "파이썬 3.7 이상"

    ```Python hl_lines="25"
    {!> ../../../docs_src/security/tutorial002.py!}
    ```

=== "파이썬 3.10 이상"

    ```Python hl_lines="23"
    {!> ../../../docs_src/security/tutorial002_py310.py!}
    ```

## 유저 가져오기

`get_current_user`는 토큰을 `str`로 취하고 Pydantic `User` 모델을 반환하는 우리가 만든 (가짜) 유틸리티 함수를 사용합니다.

### Erstellen Sie eine `Enum`-Klasse

Importieren Sie `Enum` und erstellen Sie eine Unterklasse, die von `str` und `Enum` erbt.

Indem Sie von `str` erben, weiß die API Dokumentation, dass die Werte des Enums vom Typ `str` sein müssen, und wird in der Lage sein, korrekt zu rendern.

Erstellen Sie dann Klassen-Attribute mit festgelegten Werten, welches die erlaubten Werte sein werden:

В Python версии 3.9 это будет выглядеть так:

```Python
my_list: list[str]
```

В версиях Python до 3.9 это будет выглядеть так:

```Python
from typing import List

my_list: List[str]
```

Это всё стандартный синтаксис Python для объявления типов.

Используйте этот же стандартный синтаксис для атрибутов модели с внутренними типами.

from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    price: float
    is_offer: Union[bool, None] = None


@app.get("/")
def read_root():
    return {"Hello": "World"}


@app.get("/items/{item_id}")
def read_item(item_id: int, q: Union[str, None] = None):
    return {"item_id": item_id, "q": q}


@app.put("/items/{item_id}")

from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    price: float
    is_offer: Union[bool, None] = None


@app.get("/")
def read_root():
    return {"Hello": "World"}


@app.get("/items/{item_id}")
def read_item(item_id: int, q: Union[str, None] = None):
    return {"item_id": item_id, "q": q}


@app.put("/items/{item_id}")

{!../../../docs_src/python_types/tutorial009.py!}
```

`str` yerine `Optional[str]` kullanmak editorün bu değerin her zaman `str` tipinde değil bazen `None` tipinde de olabileceğini belirtir ve hataları tespit etmemizde yardımcı olur.

#### Generic tipler

Köşeli parantez içinde tip parametreleri alan bu türler, örneğin:

* `List`
* `Tuple`
* `Set`
* `Dict`
* `Optional`
* ...and others.

| `contact` | `dict` | 公开的 API 的联系信息。它可以包含多个字段。<details><summary><code>contact</code>...

```

O uso de `Opcional [str]` em vez de apenas `str` permitirá que o editor o ajude a detectar erros, onde você pode estar assumindo que um valor é sempre um `str`, quando na verdade também pode ser `None`.

#### Tipos genéricos

Esses tipos que usam parâmetros de tipo entre colchetes, como:

* `List`
* `Tuple`
* `Set`
* `Dict`
* `Opcional`
* ...e outros.