import org.dbflute.optional.OptionalEntity;
import org.lastaflute.web.Execute;
import org.lastaflute.web.response.HtmlResponse;
import org.lastaflute.web.response.StreamResponse;
import org.lastaflute.web.ruts.process.ActionRuntime;

/**
 * Admin action for Design management.
 *
 */
public class AdminDesignAction extends FessAdminAction {

    /**
     * Default constructor.
     */
    public AdminDesignAction() {

    String content = InputStreamUtil.getUTF8String(input);
}

// Resource traversal for processing multiple files
ResourceTraversalUtil.forEach("META-INF", (resource, is) -> {
    // Process each resource in the META-INF directory
    System.out.println("Processing: " + resource);
});
```

### Text Processing and JSON
```java
import org.codelibs.core.text.*;

 *  Fix: Immediately update the connection's flow control window instead of waiting for the
    receiving stream to process it.

    This change may increase OkHttp's memory use for applications that make many concurrent HTTP
    calls and that can receive data faster than they can process it. Previously, OkHttp limited
    HTTP/2 to 16 MiB of unacknowledged data per connection. With this fix there is a limit of 16 MiB

///

### `response`의 전과 후

*경로 작동*을 받기 전 `request`와 함께 작동할 수 있는 코드를 추가할 수 있습니다.

그리고 `response` 또한 생성된 후 반환되기 전에 코드를 추가 할 수 있습니다.

예를 들어, 요청을 수행하고 응답을 생성하는데 까지 걸린 시간 값을 가지고 있는 `X-Process-Time` 같은 사용자 정의 헤더를 추가할 수 있습니다.

{* ../../docs_src/middleware/tutorial001.py hl[10,12:13] *}

## 다른 미들웨어

미들웨어에 대한 더 많은 정보는 [숙련된 사용자 안내서: 향상된 미들웨어](../advanced/middleware.md){.internal-link target=\_blank}에서 확인할 수 있습니다.

Puedes añadir código que se ejecute con la `request`, antes de que cualquier *path operation* la reciba.

Y también después de que se genere la `response`, antes de devolverla.

Por ejemplo, podrías añadir un custom header `X-Process-Time` que contenga el tiempo en segundos que tomó procesar la request y generar una response:

{* ../../docs_src/middleware/tutorial001.py hl[10,12:13] *}

/// tip | Consejo

            }
        };

        InputStreamThread thread = new InputStreamThread(is, StandardCharsets.UTF_8, 100, callback);
        thread.start();

        assertTrue("Should process all lines within timeout", latch.await(3, TimeUnit.SECONDS));

        thread.join(1000);

        assertEquals("All lines should be processed", 5000, receivedLines.size());

 *
 * The task runner is also responsible for releasing held threads when the library is unloaded.
 * This is for the benefit of container environments that implement code unloading.
 *
 * Most applications should share a process-wide [TaskRunner] and use queues for per-client work.
 */
class TaskRunner(
  val backend: Backend,
  internal val logger: Logger = TaskRunner.logger,
) : Lockable {
  private var nextQueueName = 10000

 * (or {@link FluentFuture#transform(com.google.common.base.Function, Executor)
 * FluentFuture.transform}), but you will often find it easier to use a framework. Frameworks
 * automate the process, often adding features like monitoring, debugging, and cancellation.
 * Examples of frameworks include:
 *
 * <ul>
 *   <li><a href="https://dagger.dev/producers.html">Dagger Producers</a>
 * </ul>
 *

    this.backingThreadFactory = checkNotNull(backingThreadFactory);
    return this;
  }

  /**
   * Returns a new thread factory using the options supplied during the building process. After
   * building, it is still possible to change the options used to build the ThreadFactory and/or
   * build again. State is not shared amongst built instances.
   *

    checkArgument(isFinite(x1) && isFinite(y1));
    return new LinearTransformationBuilder(x1, y1);
  }

  /**
   * This is an intermediate stage in the construction process. It is returned by {@link
   * LinearTransformation#mapping}. You almost certainly don't want to keep instances around, but
   * instead use method chaining. This represents a single point mapping, i.e. a mapping between one