State Synchronization Pattern

Overview

The State Synchronization pattern provides mechanisms for reconciling state between different systems, components, or representations. It enables bidirectional updates while handling conflicts, transformations, and partial synchronization, ensuring consistent state across system boundaries.

Key Concepts

• Models: Representations of state with defined structure
• Differencing: Identifying changes between state versions
• Reconciliation: Resolving conflicts and merging changes
• Bidirectional Updates: Changes flowing in both directions
• Adapters: Components that translate between different state representations

Benefits

• Consistency: Maintains coherent state across system boundaries
• Flexibility: Supports partial updates and different data models
• Conflict Resolution: Handles conflicting changes systematically
• Change Tracking: Provides visibility into what changed and why
• Efficiency: Transmits only modified data instead of complete state

Implementation Considerations

• Conflict Resolution Strategy: Approaches for handling concurrent modifications
• Performance Impact: Efficient differencing for large state objects
• Complexity Management: Making sophisticated reconciliation logic maintainable
• Error Handling: Recovering from synchronization failures
• Versioning: Managing structural changes in synchronized models

Implementation with DiffSync

The State Synchronization pattern in NERV is implemented using the DiffSync library, which provides tools for differential synchronization between data models. DiffSync was chosen for the following reasons:

1. Bidirectional Sync: Supports changes in both directions
2. Conflict Resolution: Includes strategies for handling conflicting changes
3. Efficient Differencing: Optimized algorithms for state comparison
4. Flexible Adapters: Easily adapts to different data models
5. Python Native: Designed for Python applications with modern type hints

Core DiffSync Components

Component	Purpose
DiffSync	Base class for synchronization engine
DiffModel	Base class for synchronized data models
Adapter	Translator between external data and DiffModels
Store	Storage for model instances and their relationships
Diff	Representation of changes between models

Synchronization Process

DiffSync implements a robust synchronization process:

# Type definitions only - not full implementation
class SynchronizationProcess:
    """Coordinates the synchronization between systems."""

    def diff_and_sync(self, source, target):
        """Generate diff and apply changes bidirectionally."""
        # Identify differences between models
        diff = source.diff_from(target)

        # Apply changes in both directions
        source.update_from_diff(diff)
        target.update_from_diff(diff)

        # Resolve any conflicts
        self.resolve_conflicts(source, target)

Pattern Variations

Unidirectional Synchronization

Simpler flow where changes only propagate in one direction.

# Type definitions only - not full implementation
class UnidirectionalSync:
    """One-way synchronization from source to target."""

    def sync_to_target(self, source, target):
        """Sync changes from source to target only."""
        # Generate diff from source to target
        diff = source.diff_from(target)

        # Apply changes to target only
        target.update_from_diff(diff)

Event-Driven Synchronization

Syncs triggered by events rather than scheduled operations.

# Type definitions only - not full implementation
class EventDrivenSync:
    """Synchronization triggered by events."""

    def __init__(self, event_bus):
        """Initialize with event bus."""
        self.event_bus = event_bus
        self.models = {}

        # Subscribe to state change events
        self.event_bus.subscribe(
            EventType.STATE_CHANGED,
            self.handle_state_change
        )

    def handle_state_change(self, event):
        """Handle state change event by triggering sync."""
        # Implementation details...

Hierarchical Synchronization

Syncs nested structures with parent-child relationships.

# Type definitions only - not full implementation
class HierarchicalSync:
    """Synchronization for hierarchical data structures."""

    def sync_tree(self, source_root, target_root):
        """Synchronize entire tree structures."""
        # Sync root nodes
        self.sync_node(source_root, target_root)

        # Recursively sync children
        for source_child in source_root.children:
            # Find matching target child or create
            target_child = self.find_or_create_child(
                target_root, source_child
            )
            self.sync_tree(source_child, target_child)

Common Synchronization Scenarios

The State Synchronization pattern addresses these common scenarios:

Client-Server State Reconciliation

Keeping client views in sync with server state.

# Type definitions only - not full implementation
class ClientServerSync:
    """Manages state synchronization between client and server."""

    def initial_sync(self, client_state, server_state):
        """Initial full sync to establish baseline."""
        # Implementation details...

    def incremental_sync(self, client_updates, server_updates):
        """Reconcile incremental changes from both sides."""
        # Implementation details...

    def conflict_resolution(self, client_change, server_change):
        """Resolve conflicts with configurable strategies."""
        # Implementation details...

Configuration Synchronization

Keeping configuration consistent across system components.

# Type definitions only - not full implementation
class ConfigSync:
    """Synchronizes configuration across components."""

    def sync_config(self, central_config, component_configs):
        """Sync central configuration with component instances."""
        for component, config in component_configs.items():
            # Create adapter for component-specific mapping
            adapter = ConfigAdapter(component)

            # Perform bidirectional sync
            diff = adapter.diff(central_config, config)
            adapter.apply_diff(central_config, config, diff)

Data Migration and Transformation

Synchronizing data while transforming between schemas.

# Type definitions only - not full implementation
class SchemaMigrationSync:
    """Synchronizes data during schema migrations."""

    def migrate_data(self, old_schema_data, new_schema_adapter):
        """Migrate data from old schema to new schema."""
        # Create compatible representation
        old_adapter = self.create_adapter(old_schema_data)

        # Perform transformation and sync
        transformed_data = new_schema_adapter.create_empty()
        old_adapter.sync_to(transformed_data)

        return transformed_data

Integration with Other NERV Patterns

Integration with Reactive Event Mesh

# Type definitions only - not full implementation
class EventBasedSynchronizer:
    """Synchronizer that uses events for updates."""

    def __init__(self, event_bus, source_system, target_system):
        """Initialize with event bus and systems."""
        self.event_bus = event_bus
        self.source = source_system
        self.target = target_system

        # Subscribe to relevant events
        self.event_bus.subscribe(
            EventType.SOURCE_STATE_CHANGED,
            self.handle_source_change
        )

        self.event_bus.subscribe(
            EventType.TARGET_STATE_CHANGED,
            self.handle_target_change
        )

    def handle_source_change(self, event):
        """Handle changes from source system."""
        # Sync changes to target
        diff = self.source.diff_from(self.target)
        self.target.update_from_diff(diff)

Integration with Temporal Versioning

# Type definitions only - not full implementation
class VersionedSynchronizer:
    """Synchronizer with version history tracking."""

    def __init__(self, temporal_store, diff_sync):
        """Initialize with temporal store and diff sync."""
        self.temporal_store = temporal_store
        self.diff_sync = diff_sync

    def sync_with_history(self, source, target):
        """Sync while preserving version history."""
        # Create diff between states
        diff = self.diff_sync.diff(source, target)

        # Apply changes to both sides
        self.diff_sync.apply(source, target, diff)

        # Store versions with changes applied
        source_version = self.temporal_store.commit(
            source.get_state(),
            f"Sync changes from {target.id}"
        )

        target_version = self.temporal_store.commit(
            target.get_state(),
            f"Sync changes from {source.id}"
        )

        # Track relationship between versions
        self.temporal_store.add_relation(
            source_version, target_version, "synchronized_with"
        )

Integration with State Projection

# Type definitions only - not full implementation
class ProjectionSynchronizer:
    """Synchronizes state projections with original state."""

    def __init__(self, state_projector):
        """Initialize with state projector."""
        self.state_projector = state_projector

    def sync_projections(self, original_state, projections):
        """Keep projections in sync with original state."""
        for projection_name, projection in projections.items():
            # Get current projection
            current_projection = self.state_projector.project(
                original_state, projection_name
            )

            # Compute diff
            diff = DiffSync.diff(current_projection, projection)

            # If projection has changes, update original state
            if diff.has_changes():
                self.state_projector.apply_reversed_projection(
                    original_state, projection_name, diff
                )

Performance Considerations

When implementing the State Synchronization pattern, consider these performance factors:

1. Efficient Differencing: Optimize algorithms for identifying changes
2. Partial Synchronization: Sync only necessary parts of large state objects
3. Incremental Updates: Process changes incrementally rather than full state
4. Concurrency Control: Handle multiple synchronization processes efficiently
5. Caching: Cache intermediate results for complex transformations

Related Patterns

• Observer Pattern
• Mediator Pattern
• Command Pattern
• Memento Pattern
• Event Sourcing Pattern

Implementation Reference

See the implementation component: DiffSynchronizer