요약하면, 여러분은 매개변수의 타입, 본문 등을 함수 매개변수로서 **한번에** 선언했습니다.

여러분은 현대 표준 파이썬 타입으로 이를 행했습니다.

새로운 문법, 특정 라이브러리의 메소드나 클래스 등을 배울 필요가 없습니다.

그저 표준 **Python** 입니다.

예를 들어, `int`에 대해선:

```Python
item_id: int
```

또는 좀 더 복잡한 `Item` 모델에 대해선:

```Python
item: Item
```

...그리고 단 하나의 선언으로 여러분이 얻는 것은:

* 다음을 포함한 편집기 지원:
    * 자동완성.
    * 타입 검사.
* 데이터 검증:

## `async` and `await` { #async-and-await }

Modern versions of Python have a very intuitive way to define asynchronous code. This makes it look just like normal "sequential" code and do the "awaiting" for you at the right moments.

When there is an operation that will require waiting before giving the results and has support for these new Python features, you can code it like:

```Python
burgers = await get_burgers(2)
```

# BEGIN TF TEST SUITE OPTIONS
# These are convenience config options that effectively declare TF's CI test suites. Look
# at the scripts of ci/official/ to see how TF's CI uses them.

# PYTHON TESTS run a suite of Python tests intended for verifying that the Python wheel
# will work properly. These are usually run Nightly or upon Release.
# CPU WHEEL

        map sigbuild-r2.12-clang-python3.10 2.12-python3.10
        map sigbuild-r2.12-clang-python3.11 2.12-python3.11
        # TF 2.13
        map sigbuild-r2.13 2.13-python3.9
        map sigbuild-r2.13-python3.8 2.13-python3.8
        map sigbuild-r2.13-python3.9 2.13-python3.9
        map sigbuild-r2.13-python3.10 2.13-python3.10
        map sigbuild-r2.13-python3.11 2.13-python3.11

</div>

////

## Ler Variáveis de Ambiente no Python { #read-env-vars-in-python }

Você também pode criar variáveis de ambiente **fora** do Python, no terminal (ou com qualquer outro método) e depois **lê-las no Python**.

Por exemplo, você poderia ter um arquivo `main.py` com:

```Python hl_lines="3"
import os

name = os.getenv("MY_NAME", "World")
print(f"Hello {name} from Python")
```

/// tip | Dica

</div>

////

## Leer Variables de Entorno en Python { #read-env-vars-in-python }

También podrías crear variables de entorno **fuera** de Python, en la terminal (o con cualquier otro método), y luego **leerlas en Python**.

Por ejemplo, podrías tener un archivo `main.py` con:

```Python hl_lines="3"
import os

name = os.getenv("MY_NAME", "World")
print(f"Hello {name} from Python")
```

/// tip | Consejo

Beachten Sie, wie wir `CommonQueryParams` im obigen Code zweimal schreiben:

//// tab | Python 3.9+

```Python
commons: Annotated[CommonQueryParams, Depends(CommonQueryParams)]
```

////

//// tab | Python 3.9+ nicht annotiert

/// tip | Tipp

Bevorzugen Sie die `Annotated`-Version, falls möglich.

///

```Python
commons: CommonQueryParams = Depends(CommonQueryParams)
```

////

```

</div>

////

## Read env vars in Python { #read-env-vars-in-python }

You could also create environment variables **outside** of Python, in the terminal (or with any other method), and then **read them in Python**.

For example you could have a file `main.py` with:

```Python hl_lines="3"
import os

name = os.getenv("MY_NAME", "World")
print(f"Hello {name} from Python")
```

/// tip

Ключевым фактором является то, что зависимость должна быть «вызываемой».

В Python «**вызываемый**» — это всё, что Python может «вызвать», как функцию.

Так, если у вас есть объект `something` (который может и _не_ быть функцией) и вы можете «вызвать» его (выполнить) так:

```Python
something()
```

или

```Python
something(some_argument, some_keyword_argument="foo")
```

El factor clave es que una dependencia debe ser un "callable".

Un "**callable**" en Python es cualquier cosa que Python pueda "llamar" como una función.

Entonces, si tienes un objeto `something` (que podría _no_ ser una función) y puedes "llamarlo" (ejecutarlo) como:

```Python
something()
```

o

```Python
something(some_argument, some_keyword_argument="foo")
```

entonces es un "callable".