*
   * Lock lockA = factory1.newReentrantLock(MyLockOrder.FIRST);
   * Lock lockB = factory1.newReentrantLock(MyLockOrder.FIRST);
   * Lock lockC = factory2.newReentrantLock(MyLockOrder.FIRST);
   *
   * lockA.lock();
   *
   * lockB.lock(); // will throw an IllegalStateException
   * lockC.lock(); // will throw an IllegalStateException
   *
   * lockA.lock(); // reentrant acquisition is okay
   * }

    }

    /**
     * Internal method to acquire a distributed lock with retry control.
     *
     * @param operationName the operation name used as the lock document ID.
     * @param data optional data to store with the operation document.
     * @param remainingRetries the number of remaining retry attempts for stale lock cleanup.
     * @return {@code true} if the lock was acquired.
     */

      in.defaultReadObject();
      lock = new Object();
    }

    @GwtIncompatible @J2ktIncompatible private static final long serialVersionUID = 0;
  }

  private static final class NonSerializableMemoizingSupplier<T extends @Nullable Object>
      implements Supplier<T> {
    private final Object lock = new Object();

    private volatile @Nullable Supplier<T> delegate;

   * of reads may not be immediately reflected on the algorithm's data structures. These structures
   * are guarded by a lock and operations are applied in batches to avoid lock contention. The
   * penalty of applying the batches is spread across threads so that the amortized cost is slightly
   * higher than performing just the operation without enforcing the capacity constraint.

   * of reads may not be immediately reflected on the algorithm's data structures. These structures
   * are guarded by a lock and operations are applied in batches to avoid lock contention. The
   * penalty of applying the batches is spread across threads so that the amortized cost is slightly
   * higher than performing just the operation without enforcing the capacity constraint.

   * of reads may not be immediately reflected on the algorithm's data structures. These structures
   * are guarded by a lock and operations are applied in batches to avoid lock contention. The
   * penalty of applying the batches is spread across threads so that the amortized cost is slightly
   * higher than performing just the operation without enforcing the capacity constraint.

            - .github/workflows/test.yml
            - docs_src/**
            - fastapi/**
            - scripts/**
            - tests/**
            - .python-version
            - pyproject.toml
            - uv.lock

  test:
    needs:
      - changes
    if: needs.changes.outputs.src == 'true' || github.ref == 'refs/heads/master'
    strategy:
      matrix:
        os: [ windows-latest, macos-latest ]

coordinator.poll.interval=60
# Time-to-live (ms) for instance heartbeat documents.
coordinator.heartbeat.ttl=180000
# Time-to-live (ms) for operation lock documents.
coordinator.operation.ttl=7200000
# Maximum number of retries for acquiring an operation lock.
coordinator.operation.retry=3
# Time-to-live (ms) for event notification documents.
coordinator.event.ttl=600000

repos:
  - repo: https://github.com/pre-commit/pre-commit-hooks
    rev: v6.0.0
    hooks:
      - id: check-added-large-files
        args: ['--maxkb=750']
        exclude: ^uv.lock$
      - id: check-toml
      - id: check-yaml
        args:
        - --unsafe
      - id: end-of-file-fixer
      - id: trailing-whitespace

  - repo: local
    hooks:
      - id: local-ruff-check

of an interface type or of elements of a composite type remains unchanged:
</p>

<pre>
// A Mutex is a data type with two methods, Lock and Unlock.
type Mutex struct         { /* Mutex fields */ }
func (m *Mutex) Lock()    { /* Lock implementation */ }
func (m *Mutex) Unlock()  { /* Unlock implementation */ }

// NewMutex has the same composition as Mutex but its method set is empty.