prp.store(out, header);
    }

    /**
     * List the properties in the <code>Config</code>.
     *
     * @param out the print stream to write the properties to
     * @throws IOException if an I/O error occurs
     */

    public static void list(final PrintStream out) throws IOException {
        prp.list(out);
    }

    /**

উদাহরণস্বরূপ, আপনার `main.py` নামে একটি ফাইল থাকতে পারেঃ

```Python hl_lines="3"
import os

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

/// tip

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

```Python
with open("./somefile.txt") as f:
    contents = f.read()
    print(contents)
```

Underneath, the `open("./somefile.txt")` creates an object that is called a "Context Manager".

When the `with` block finishes, it makes sure to close the file, even if there were exceptions.

```Python
with open("./somefile.txt") as f:
    contents = f.read()
    print(contents)
```

その後の`open("./somefile.txt")`は「コンテキストマネージャ」と呼ばれるオブジェクトを作成します。

`with`ブロックが終了すると、例外があったとしてもファイルを確かに閉じます。

`yield`を依存関係を作成すると、**FastAPI** は内部的にそれをコンテキストマネージャに変換し、他の関連ツールと組み合わせます。

which is an integer.
        * ScaleRef of type SubresourceReference in HorizontalPodAutoscalerSpec which
referred to scale subresource of the resource being scaled was replaced by
ScaleTargetRef which points just to the resource being scaled.
        * In extensions/v1beta1 if CPUUtilization in HorizontalPodAutoscalerSpec was not
specified it was set to 80 by default while in autoscaling/v1 HPA object

```Python
with open("./somefile.txt") as f:
    contents = f.read()
    print(contents)
```

Internamente, `open("./somefile.txt")` crea un objeto llamado "Context Manager".

Cuando el bloque `with` termina, se asegura de cerrar el archivo, incluso si hubo excepciones.

errors.invalid_header_for_request_file=Invalid header line: {0}
errors.could_not_delete_logged_in_user=You cannot delete a user who is logged in.
errors.unauthorized_request=Unauthorized request.
errors.failed_to_print_thread_dump=Failed to print a thread dump.
errors.file_is_not_supported={0} is not supported.
errors.plugin_file_is_not_found={0} is not found.
errors.failed_to_install_plugin=Failed to install {0}.

errors.invalid_header_for_request_file=Invalid header line: {0}
errors.could_not_delete_logged_in_user=You cannot delete a user who is logged in.
errors.unauthorized_request=Unauthorized request.
errors.failed_to_print_thread_dump=Failed to print a thread dump.
errors.file_is_not_supported={0} is not supported.
errors.plugin_file_is_not_found={0} is not found.
errors.failed_to_install_plugin=Failed to install {0}.

```

그 다음, 다음과 같이 호출합니다:

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

이제 변수 `user_dict`에 데이터가 포함된 `dict`를 가지게 됩니다(이는 Pydantic 모델 객체가 아닌 `dict`입니다).

그리고 다음과 같이 호출하면:

```Python
print(user_dict)
```

Python의 `dict`가 다음과 같이 출력됩니다:

```Python
{
    'username': 'john',
    'password': 'secret',
    'email': '******@****.***',
    'full_name': None,
}
```