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.
         */

  //   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

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    public void stopWatching(String directoryPath) {
        ChangeNotificationHandle handle = activeWatchers.remove(directoryPath);
        if (handle != null) {
            handle.setActive(false);
            // Cancel any pending notifications
            cancelNotification(handle);
            // Clean up failure count to prevent memory leak
            failureCounts.remove(directoryPath);
        }
    }

    /**

    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 */

	}
}

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.

    * Ponieważ struktury danych Pydantic to po prostu instancje klas, które definiujesz; autouzupełnianie, linting, mypy i twoja intuicja powinny działać poprawnie z Twoimi zwalidowanymi danymi.
* Walidacja **złożonych struktur**:
    * Wykorzystanie hierarchicznych modeli Pydantic, Pythonowego modułu `typing` zawierającego `List`, `Dict`, itp.

    * Weil Pydantics Datenstrukturen einfach nur Instanzen ihrer definierten Klassen sind; Autovervollständigung, Linting, mypy und ihre Intuition sollten alle einwandfrei mit ihren validierten Daten funktionieren.
* Validierung von **komplexen Strukturen**:
    * Benutzung von hierarchischen Pydantic-Modellen, Python-`typing`s `List` und `Dict`, etc.

{* ../../docs_src/handling_errors/tutorial006.py hl[2:5,15,21] *}