Swift Actors for Thread-Safe Persistence

Patterns for building thread-safe data persistence layers using Swift actors. Combines in-memory caching with file-backed storage, leveraging the actor model to eliminate data races at compile time.

When to Activate

• Building a data persistence layer in Swift 5.5+
• Need thread-safe access to shared mutable state
• Want to eliminate manual synchronization (locks, DispatchQueues)
• Building offline-first apps with local storage

Core Pattern

Actor-Based Repository

The actor model guarantees serialized access — no data races, enforced by the compiler.

public actor LocalRepository<T: Codable & Identifiable> where T.ID == String {
    private var cache: [String: T] = [:]
    private let fileURL: URL

    public init(directory: URL = .documentsDirectory, filename: String = "data.json") {
        self.fileURL = directory.appendingPathComponent(filename)
        // Synchronous load during init (actor isolation not yet active)
        self.cache = Self.loadSynchronously(from: fileURL)
    }

    // MARK: - Public API

    public func save(_ item: T) throws {
        cache[item.id] = item
        try persistToFile()
    }

    public func delete(_ id: String) throws {
        cache[id] = nil
        try persistToFile()
    }

    public func find(by id: String) -> T? {
        cache[id]
    }

    public func loadAll() -> [T] {
        Array(cache.values)
    }

    // MARK: - Private

    private func persistToFile() throws {
        let data = try JSONEncoder().encode(Array(cache.values))
        try data.write(to: fileURL, options: .atomic)
    }

    private static func loadSynchronously(from url: URL) -> [String: T] {
        guard let data = try? Data(contentsOf: url),
              let items = try? JSONDecoder().decode([T].self, from: data) else {
            return [:]
        }
        return Dictionary(uniqueKeysWithValues: items.map { ($0.id, $0) })
    }
}

Usage

All calls are automatically async due to actor isolation:

let repository = LocalRepository<Question>()

// Read — fast O(1) lookup from in-memory cache
let question = await repository.find(by: "q-001")
let allQuestions = await repository.loadAll()

// Write — updates cache and persists to file atomically
try await repository.save(newQuestion)
try await repository.delete("q-001")

Combining with @Observable ViewModel

@Observable
final class QuestionListViewModel {
    private(set) var questions: [Question] = []
    private let repository: LocalRepository<Question>

    init(repository: LocalRepository<Question> = LocalRepository()) {
        self.repository = repository
    }

    func load() async {
        questions = await repository.loadAll()
    }

    func add(_ question: Question) async throws {
        try await repository.save(question)
        questions = await repository.loadAll()
    }
}

Key Design Decisions

Best Practices

• Use Sendable types for all data crossing actor boundaries
• Keep the actor's public API minimal — only expose domain operations, not persistence details
• Use .atomic writes to prevent data corruption if the app crashes mid-write
• Load synchronously in init — async initializers add complexity with minimal benefit for local files
• Combine with @Observable ViewModels for reactive UI updates

Anti-Patterns to Avoid

• Using DispatchQueue or NSLock instead of actors for new Swift concurrency code
• Exposing the internal cache dictionary to external callers
• Making the file URL configurable without validation
• Forgetting that all actor method calls are await — callers must handle async context
• Using nonisolated to bypass actor isolation (defeats the purpose)

When to Use

• Local data storage in iOS/macOS apps (user data, settings, cached content)
• Offline-first architectures that sync to a server later
• Any shared mutable state that multiple parts of the app access concurrently
• Replacing legacy DispatchQueue-based thread safety with modern Swift concurrency