In einigen Fällen müssen Sie möglicherweise immer noch Pydantics Version von `dataclasses` verwenden. Zum Beispiel, wenn Sie Fehler in der automatisch generierten API-Dokumentation haben.

In diesem Fall können Sie einfach die Standard-`dataclasses` durch `pydantic.dataclasses` ersetzen, was einen direkten Ersatz darstellt:

```{ .python .annotate hl_lines="1  5  8-11  14-17  23-25  28" }
{!../../docs_src/dataclasses/tutorial003.py!}

	        SET newparams=!newparams! !current!
        ) ELSE (
            SET newparams=!current!
        )
	)
	
    IF "x!params!" NEQ "x" (
		GOTO loop
	)
)

SET HOSTNAME=%COMPUTERNAME%

CALL "%~dp0fess.in.bat"
IF ERRORLEVEL 1 (
	IF NOT DEFINED nopauseonerror (
		PAUSE
	)
	EXIT /B %ERRORLEVEL%
)

"%JAVA_HOME%\bin\java" %FESS_JAVA_OPTS% !newparams! -cp "%FESS_CLASSPATH%" "org.codelibs.fess.FessBoot"

   *
   * <p><b>Nodes must be unique</b>, just as {@code Map} keys must be. They must also be non-null.
   *
   * @return {@code true} if the graph was modified as a result of this call
   */
  @CanIgnoreReturnValue
  boolean addNode(N node);

  /**
   * Adds an edge connecting {@code nodeU} to {@code nodeV} if one is not already present, and sets

 *
 * <p>{@code RuntimeException}s thrown by tasks are simply logged and the executor keeps trucking.
 * If an {@code Error} is thrown, the error will propagate and execution will stop until it is
 * restarted by a call to {@link #execute}.
 */
@J2ktIncompatible
@GwtIncompatible
@ElementTypesAreNonnullByDefault
final class SequentialExecutor implements Executor {

 *
 * <p>{@code RuntimeException}s thrown by tasks are simply logged and the executor keeps trucking.
 * If an {@code Error} is thrown, the error will propagate and execution will stop until it is
 * restarted by a call to {@link #execute}.
 */
@J2ktIncompatible
@GwtIncompatible
@ElementTypesAreNonnullByDefault
final class SequentialExecutor implements Executor {

- Replace scale down forbidden window with scale down stabilization window. Rather than waiting a fixed period of time between scale downs HPA now scales down to the highest recommendation it during the scale down stabilization window. ([#68122](https://github.com/kubernetes/kubernetes/pull/68122), [@krzysztof-jastrzebski](https://github.com/krzysztof-jastrzebski))...

Auf die gleiche Weise können Sie Logik (Code) definieren, die ausgeführt werden soll, wenn die Anwendung **heruntergefahren** wird. In diesem Fall wird dieser Code **einmal** ausgeführt, **nachdem** möglicherweise **viele Requests** bearbeitet wurden.

public final class GcFinalization {
  private GcFinalization() {}

  /**
   * 10 seconds ought to be long enough for any object to be GC'ed and finalized. Unless we have a
   * gigantic heap, in which case we scale by heap size.
   */
  private static long timeoutSeconds() {
    // This class can make no hard guarantees.  The methods in this class are inherently flaky, but

s-request title: How to profile a FastAPI asynchronous request - author: Stephen Siegert - Neon link: https://neon.tech/blog/deploy-a-serverless-fastapi-app-with-neon-postgres-and-aws-app-runner-at-any-scale title: Deploy a Serverless FastAPI App with Neon Postgres and AWS App Runner at any scale - author: Kurtis Pykes - NVIDIA link: https://developer.nvidia.com/blog/building-a-machine-learning-microservice-with-fastapi/ title: Building a Machine Learning Microservice with FastAPI - author: Ravgeet...

   * for APIs like {@link #whenAllComplete whenAllComplete(...)}{@code .}{@link
   * FutureCombiner#call(Callable, Executor) call(...)}, where it is easy to use a new input from
   * the {@code call} implementation but forget to add it to the arguments of {@code
   * whenAllComplete}.
   *