Class<?> cls;
      try {
        cls = classInfo.load();
      } catch (NoClassDefFoundError e) {
        // In case there were linking problems, this is probably not a class we care to test anyway.
        logger.log(Level.SEVERE, "Cannot load class " + classInfo + ", skipping...", e);
        continue;
      }
      if (!cls.isInterface()) {

                throw new DictionaryException("Failed to write: " + line, e);
            }
        }

        /**
         * Commits the changes to the dictionary file.
         * If there is a pending new item, it is written to the file.
         *
         * @return The committed item, or null if no item was committed.
         * @throws DictionaryException if an I/O error occurs.
         */

| `minio_node_ilm_transition_active_tasks`                     | Number of active ILM transition tasks.                                                                     |

    int NT_STATUS_OBJECT_PATH_SYNTAX_BAD = 0xC000003b;
    /** The process cannot access the file because it is being used by another process */
    int NT_STATUS_SHARING_VIOLATION = 0xC0000043;
    /** The file is pending deletion */
    int NT_STATUS_DELETE_PENDING = 0xC0000056;
    /** There are currently no logon servers available to service the logon request */
    int NT_STATUS_NO_LOGON_SERVERS = 0xC000005e;

    * Doordat pydantic's datastructuren enkel instanties zijn van klassen, die je definieert, werkt automatische aanvulling, linting, mypy en je intuïtie allemaal goed met je gevalideerde data.
* Valideer **complexe structuren**:
    * Gebruik van hiërarchische Pydantic modellen, Python `typing`'s `List` en `Dict`, enz.

                throw new DictionaryException("Failed to write: " + line, e);
            }
        }

        /**
         * Commits the changes to the dictionary file.
         * If there is a pending new item, it is written to the file.
         *
         * @return The committed item, or null if no item was committed.
         * @throws DictionaryException if an I/O error occurs.
         */

    protected boolean forceUnicode = false;
    /** Whether SMB signing is preferred but not required */
    protected boolean signingPreferred = false;
    /** Whether SMB signing is enforced (required) */
    protected boolean signingEnforced = false;
    /** Whether to enforce signing for IPC connections */
    protected boolean ipcSigningEnforced = true;
    /** Whether SMB3 encryption is enabled */

  //   have observed 12 micros on 64-bit linux systems to wake up a parked thread). So if the
  //   timeout is small we shouldn't park(). This needs to be traded off with the cpu overhead of
  //   spinning, so we use SPIN_THRESHOLD_NANOS which is what AbstractQueuedSynchronizer uses for
  //   similar purposes.
  // * We want to behave reasonably for timeouts of 0

	}
}

func (z *erasureServerPools) decommissionInBackground(ctx context.Context, idx int) error {
	pool := z.serverPools[idx]
	z.poolMetaMutex.RLock()
	pending := z.poolMeta.PendingBuckets(idx)
	z.poolMetaMutex.RUnlock()

	for _, bucket := range pending {
		z.poolMetaMutex.RLock()
		isDecommissioned := z.poolMeta.isBucketDecommissioned(idx, bucket.String())
		z.poolMetaMutex.RUnlock()
		if isDecommissioned {

    * Pydantic'in veri yapıları aslında sadece senin tanımladığın classlar; Bu yüzden doğrulanmış dataların ile otomatik tamamlama, linting ve mypy'ı kullanarak sorunsuz bir şekilde çalışabilirsin
* **En kompleks** yapıları bile doğrula:
    * Hiyerarşik Pydantic modellerinin kullanımı ile beraber, Python `typing`’s `List` and `Dict`, vs gibi şeyleri doğrula.