flutter-caching-data

Implementing Flutter Caching and Offline-First Architectures

Contents

• Selecting a Caching Strategy
• Implementing Offline-First Data Synchronization
• Managing File System and SQLite Persistence
• Optimizing UI, Scroll, and Image Caching
• Caching the FlutterEngine (Android)
• Workflows

Selecting a Caching Strategy

Apply the appropriate caching mechanism based on the data lifecycle and size requirements.

• If storing small, non-critical UI states or preferences: Use shared_preferences.
• If storing large, structured datasets: Use on-device databases (SQLite via sqflite, Drift, Hive CE, or Isar).
• If storing binary data or large media: Use file system caching via path_provider.
• If retaining user session state (navigation, scroll positions): Implement Flutter's built-in state restoration to sync the Element tree with the engine.
• If optimizing Android initialization: Pre-warm and cache the FlutterEngine.

Implementing Offline-First Data Synchronization

Design repositories as the single source of truth, combining local databases and remote API clients.

Read Operations (Stream Approach)

Yield local data immediately for fast UI rendering, then fetch remote data, update the local cache, and yield the fresh data.

Stream<UserProfile> getUserProfile() async* {
  // 1. Yield local cache first
  final localProfile = await _databaseService.fetchUserProfile();
  if (localProfile != null) yield localProfile;

  // 2. Fetch remote, update cache, yield fresh data
  try {
    final remoteProfile = await _apiClientService.getUserProfile();
    await _databaseService.updateUserProfile(remoteProfile);
    yield remoteProfile;
  } catch (e) {
    // Handle network failure; UI already has local data
  }
}