durable_queue 0.5.4

A backend-agnostic persistent task queue for Dart and Flutter with retries, backoff, concurrency control, and recovery.

durable_queue

Persistent, retryable task execution for Dart and Flutter.

The problem

Apps constantly start work that must not be lost: uploading a photo, sending a message, syncing an edit. The first attempt often fails because the network drops, the server returns 503, or the user closes the app mid-request. A try/catch around the call handles one failure, but then you have to decide:

• where the work lives until it can be retried, and whether it survives a restart;
• how long to wait between attempts, and when to give up;
• how to stop a double tap from uploading the same photo twice;
• how many uploads may run at once, and which ones go first;
• what happens to step 3 when step 2 fails.

durable_queue answers those questions in one small, framework-free engine. Work is described as data (a serializable task), stored through a pluggable storage interface, and executed by a worker that owns retries, concurrency, ordering, and recovery.

Features

• Tasks are data, so they can be stored and rebuilt after a restart
• Fixed and exponential retry with optional jitter, and a retryIf filter
• Concurrency limits and priorities
• Scheduled tasks: start at a given time or after a delay
• Rate limits per task type, or per key such as an API host
• Gates: tasks that need the network wait while offline, without using attempts
• Task dependencies, chains, and groups
• Deduplication and idempotency keys
• Cooperative cancellation, pause, resume, and stop
• drain: run what is ready within a time limit, for background jobs
• Hand-off: a task can wait for work the operating system finishes, such as a background upload
• Lifecycle events and queries by status or group
• Startup recovery of tasks interrupted by a crash
• An injectable clock, so retry logic is testable without waiting
• Pure Dart: no HTTP client, database, Flutter, or state-management dependency

Install

dependencies:
  durable_queue: ^0.5.4

Packages

durable_queue is the core: pure Dart, with no database, HTTP client, or Flutter dependency. Integrations are separate packages from the same repository, so you add only what you use.

Package	What it adds
durable_queue	The engine: tasks, retries, priorities, dependencies, rate limits, gates.
durable_queue_sqlite	SQLite storage that survives restarts, on Android, iOS, macOS, Windows, Linux, and the web.
durable_queue_dio	Dio integration: retry rules for HTTP errors, Retry-After, idempotency headers, cancellation, queued HTTP requests.
durable_queue_flutter	Flutter integration: start the queue with the app, pause it in the background, and rebuild widgets from stored tasks.
durable_queue_connectivity	A network gate for Flutter on connectivity_plus, with an optional reachability check against your server.
durable_queue_transfer	Uploads and downloads that keep going after the app is minimised or closed, run by the operating system through background_downloader.
durable_queue_workmanager	Background jobs on Android and iOS: runs the queue from Workmanager while the app is away, with a lease so the app and the job never run it at once.

Need an integration that is not listed? Ask in Discussions.

Quick start

import 'package:durable_queue/durable_queue.dart';

final class UploadPhotoTask extends DurableTask {
  UploadPhotoTask({required this.path});

  final String path;

  @override
  String get type => 'upload_photo';

  @override
  Map<String, dynamic> toJson() => {'path': path};

  static UploadPhotoTask fromJson(Map<String, dynamic> json) =>
      UploadPhotoTask(path: json['path'] as String);
}

Future<void> main() async {
  final queue = DurableQueue(
    storage: MemoryQueueStorage(), // use a persistent adapter in an app
    maxConcurrentTasks: 3,
  );

  queue.register<UploadPhotoTask>(
    type: 'upload_photo',
    decoder: UploadPhotoTask.fromJson,
    handler: (task, context) async {
      await photoApi.upload(task.path); // your code
    },
  );

  await queue.start();

  await queue.enqueue(
    UploadPhotoTask(path: '/storage/avatar.jpg'),
    retryPolicy: RetryPolicy.exponential(
      maxAttempts: 5,
      initialDelay: Duration(seconds: 1),
    ),
  );
}

enqueue returns once the task is stored. The worker runs it in the background of your process and retries it if the handler throws.

How the packages fit together

The core engine decides when each task runs. Everything else plugs into one of three slots: a gate decides whether a task may start now, storage decides where tasks live, and a handler does the actual work. durable_queue_flutter connects the queue to your app's lifecycle and UI, and durable_queue_workmanager runs it in background jobs while the app is away.

                    Your Flutter or Dart app
         enqueue tasks · show status · react to results
                               │
  durable_queue_flutter ──────▶│  starts the queue with the app,
  (optional)                   │  pauses it in the background,
                               │  rebuilds widgets from tasks
                               │
  durable_queue_workmanager ──▶│  runs it in background jobs
  (optional)                   │  while the app is away
                               ▼
 ┌─────────────────────────────────────────────────────────────┐
 │                 durable_queue · core engine                 │
 │  retries · priorities · dependencies · rate limits · events │
 ├───────────────────┬───────────────────┬─────────────────────┤
 │ Gates             │ Storage           │ Handlers            │
 │ may a task start? │ where tasks live  │ what a task does    │
 └─────────▲─────────┴─────────▲─────────┴──────────▲──────────┘
           │                   │                    │
           │                   │                    │
 durable_queue_        durable_queue_      durable_queue_dio
 connectivity          sqlite              HTTP requests, retry
 waits while offline   survives restarts   rules, Retry-After

                                           durable_queue_transfer
                                           uploads, downloads the
                                           OS finishes in the
                                           background

 built in:             built in:           built in:
 ManualQueueGate       MemoryQueueStorage  any async function

Every package is optional. Start with the core and its built-in pieces, then swap in a package for the slot you need: SQLite when tasks must survive restarts, the connectivity gate when work needs the network, Dio for HTTP, transfers for uploads and downloads that must finish after the app is closed. Your own gates, storage adapters, and handlers fit the same slots.

How it works

            Your app (Flutter or Dart)
                       │
         enqueue(task, retry, priority, dependsOn, group)
                       │
                       ▼
           ┌───────────────────────┐
           │     QueueStorage      │  memory, file, SQLite, ...
           │ pending · waiting ·   │  (survives restarts with a
           │ retryScheduled · ...  │   persistent adapter)
           └───────────┬───────────┘
                       │  worker claims the next ready task:
                       │  • dependencies completed
                       │  • retry time reached
                       │  • highest priority, then oldest
                       │  • a concurrency slot is free
                       ▼
           ┌───────────────────────┐
           │   your task handler   │
           └───────────┬───────────┘
              returns  │  throws
          ┌────────────┴──────────────┐
          ▼                           ▼
     completed              retryIf + RetryPolicy
          │                  ┌────────┴─────────┐
          │                  ▼                  ▼
          │           retryScheduled         failed
          │          (backoff, then           (or cancelled
          │           claimed again)           if requested)
          │                                     │
          └────────────────┬────────────────────┘
                           ▼
          tasks waiting on it are released, cancelled,
          failed, or run, per their DependencyFailurePolicy

Every state change is written to storage before the matching event is emitted. On the next launch, start recovers tasks that were left running when the process died.

Real-world use cases

• Media upload. Retry network failures with backoff, fail fast on a rejected file, and send an idempotency key so the server never stores a photo twice. See example/image_upload.dart.
• Offline-first edits. Queue each change while offline, deduplicate repeated saves of the same record, and let the queue drain when connectivity returns.
• Multi-step workflows. Upload, then process, then notify, as a chain where a failed step cancels the rest. See example/orchestration.dart.
• Background sync. Group related sync tasks so they can be listed or cancelled together on logout.
• Priority work. Let a chat message jump ahead of analytics uploads that are already waiting.

Tasks

A task is a JSON payload plus a type name, like UploadPhotoTask above. The queue stores toJson(), never a closure, and rebuilds the task with the registered decoder. Register each type before enqueuing it; the type passed to register must match the task's type getter.

The handler's context carries the task id, attempt number, attempt budget, idempotency key, and whether cancellation was requested. Handlers that do not need it can ignore it.

Retry

RetryPolicy.none();

RetryPolicy.fixed(
  maxAttempts: 3,
  delay: Duration(seconds: 2),
);

RetryPolicy.exponential(
  maxAttempts: 5,
  initialDelay: Duration(seconds: 1),
  maxDelay: Duration(minutes: 1),
  jitter: true,
);

maxAttempts includes the first run. retryIf chooses which errors are eligible:

queue.register<UploadPhotoTask>(
  type: 'upload_photo',
  decoder: UploadPhotoTask.fromJson,
  handler: upload,
  retryIf: (error, stackTrace) => error is TemporaryUploadException,
);

The default retries handler errors until the attempt budget is spent. Decode failures are not retried.

When the error itself says how long to wait, such as an HTTP 429 or 503 with a Retry-After header, return that wait from retryDelay. It replaces the policy's delay for that retry; return null to let the policy decide:

queue.register<UploadPhotoTask>(
  type: 'upload_photo',
  decoder: UploadPhotoTask.fromJson,
  handler: upload,
  retryDelay: (error, stackTrace) =>
      error is RateLimitedException ? error.retryAfter : null,
);

The attempt still counts toward maxAttempts. Negative waits count as zero, and waits are capped at RetryPolicy.maxSchedulableDelay.

The core does not speak HTTP. durable_queue_dio provides ready-made retryIf and retryDelay rules for Dio, including Retry-After, plus a deferOn rule for network gates and per-host rate limits for queued requests.

Deduplication and idempotency

await queue.enqueue(
  SyncUserTask(userId: '123'),
  deduplicationKey: 'sync-user:123',
  idempotencyKey: '123',
);

If a task with that deduplication key is already pending, waiting, running, or retryScheduled, enqueue returns the existing id and leaves it unchanged. A completed, failed, or cancelled task does not block the key.

The idempotency key is stored and exposed on TaskContext. The handler decides how to send it. The same key does not, by itself, collapse two tasks.

Scheduled tasks

Give a task an earliest start time with runAt or delay:

await queue.enqueue(SendReminderTask(id), runAt: DateTime(2026, 11, 1, 9));
await queue.enqueue(SyncTask(), delay: Duration(minutes: 15));

The task is stored at once and starts when its time comes and a slot is free. While it waits it is pending, counts as active, and holds its deduplication key. A time in the past means "now". With dependsOn, the task starts once its dependencies have completed and its time has come. enqueueChain applies the time to the first step.

The queue only runs while your app runs: a task scheduled for 3 a.m. starts at 3 a.m. if the app is running then, or on the next launch otherwise.

Priorities

await queue.enqueue(SendMessageTask(text: 'hi'), priority: 10);
await queue.enqueue(UploadLogsTask(), priority: -5);

Among tasks that are ready to start, higher priority goes first; equal priorities keep enqueue order. The default is 0. Priority decides which task gets the next free slot. It never interrupts a handler that is already running.

Dependencies and chains

A task can wait for other tasks:

final upload = await queue.enqueue(UploadPhotoTask(path: path));
final resize = await queue.enqueue(
  ResizePhotoTask(path: path),
  dependsOn: [upload],
);

Until every dependency is completed, the dependent task is waiting and does not use a concurrency slot. If a dependency fails, is cancelled, or no longer exists, onDependencyFailure decides what happens:

DependencyFailurePolicy	Effect on the waiting task
cancel (default)	Becomes cancelled without running.
fail	Becomes failed without running.
run	Runs anyway once every dependency has finished. Good for cleanup.

The outcome cascades: if resize is cancelled, tasks waiting on resize follow their own policy. The task's lastFailure names the dependency that blocked it.

enqueueChain stores steps that run one after another, even when maxConcurrentTasks is greater than one:

final ids = await queue.enqueueChain([
  UploadPhotoTask(path: path),
  ResizePhotoTask(path: path),
  NotifyFriendsTask(path: path),
], group: 'photo:$path');

With the default policy, a failed step cancels the rest of the chain. Dependencies must already be stored when you enqueue, so cycles cannot be created.

Groups

await queue.enqueue(SyncContactsTask(), group: 'sync');
await queue.enqueue(SyncCalendarTask(), group: 'sync');

final syncTasks = await queue.getTasks(group: 'sync');
final cancelled = await queue.cancelGroup('sync');

A group is a label. cancelGroup cancels every active task in it, using the same rules as cancel, and returns how many tasks it affected.

Rate limits

Limit how often tasks start. Every attempt counts, retries included, because each one reaches the service you are protecting.

// At most 10 uploads per minute.
queue.register<UploadPhotoTask>(
  type: 'upload_photo',
  decoder: UploadPhotoTask.fromJson,
  handler: upload,
  rateLimit: RateLimit(10, per: Duration(minutes: 1)),
);

// At most 5 requests per second to each API host, across task types.
queue.addRateLimit(
  'per-host',
  RateLimit(5, per: Duration(seconds: 1)),
  types: {'upload_photo', 'send_message'},
  keyOf: (task) => Uri.parse(task.payload['url'] as String).host,
);

Up to count tasks may start back to back, then starts are spaced by per / count. A task that has to wait is deferred: it keeps its status, attempt count, and place in line, and gets a reserved slot, so it is rescheduled once rather than polled. Other task types keep running meanwhile. A task must satisfy every limit that applies to it. Limits live in memory and start empty after a restart.

When a service asks you to slow down, hold a limit so every task in that bucket waits, not only the one that got the answer:

queue.holdRateLimit('per-host', key: 'api.example.com', duration: Duration(seconds: 30));

After the hold, starts resume at the steady rate. durable_queue_dio does this for you when a server answers 429 or 503 with Retry-After.

Gates: waiting for the network and other conditions

A gate is a condition a task type needs before it starts, such as network access. While a required gate is closed, matching tasks are deferred without using attempts, other work keeps running, and the deferred tasks start as soon as the gate opens.

final network = ManualQueueGate();
queue.addGate('network', network); // add gates before registering types that need them

queue.register<UploadPhotoTask>(
  type: 'upload_photo',
  decoder: UploadPhotoTask.fromJson,
  handler: upload,
  requires: {'network'},
  // A connection error means "offline", not "this upload failed".
  deferOn: (error, stackTrace) =>
      error is SocketException ? 'network' : null,
);

// Open and close it from whatever tracks connectivity in your app:
connectivity.onConnectivityChanged.listen((results) {
  network.set(!results.contains(ConnectivityResult.none));
});

• Closing a gate does not cancel tasks that are already running.
• deferOn maps a handler error to one of the type's gates. The task is deferred instead of failing, the attempt does not count, and the gate's recheck is called. The task tries again after gateErrorDelay (default 30 seconds), or as soon as the gate closes and reopens.
• A gate that never reports opening is checked again every gateRecheckInterval (default five minutes).
• Implement QueueGate for other conditions, such as Wi-Fi only, charging, or signed in.

A connection-type report (Wi-Fi, mobile) does not prove the internet is reachable, for example behind a captive portal. deferOn covers that case: the request fails, the task waits, and the gate can probe.

On Flutter, durable_queue_connectivity provides this gate ready-made: ConnectivityGate.create() on connectivity_plus, an optional HttpProbe against your own server, and deferOnConnectionError('network').

Cancellation and controls

await queue.cancel(taskId);
await queue.pause();
await queue.resume();
await queue.stop();

Cancelling queued or waiting work marks it cancelled immediately. Cancelling a running task does not abort the future. The handler can check context.isCancellationRequested, or wait on context.whenCancellationRequested, and throw TaskCancelledException to stop. If it returns normally, the task is completed.

whenCancellationRequested completes the moment the task is cancelled, so it can abort work that accepts a cancel signal:

handler: (task, context) async {
  final token = CancelToken();
  context.whenCancellationRequested.then((_) => token.cancel());
  await dio.post(task.url, data: task.body, cancelToken: token);
},

pause finishes handlers that have already started and does not start new ones. stop waits for those handlers and leaves everything else stored.

Retry, delete, and purge finished tasks

Completed, failed, and cancelled tasks stay in storage until you remove them.

// Run a failed or cancelled task again with a fresh attempt budget.
await queue.retry(taskId);

// Remove one finished task.
await queue.delete(taskId);

// Remove completed tasks older than a week. Returns the number removed.
final removed = await queue.purge(
  statuses: {TaskStatus.completed},
  olderThan: Duration(days: 7),
);

Failed tasks are the queue's dead-letter queue: they stay stored, with their last error in lastFailure, until you retry, delete, or purge them. To retry them all at once, for example after a server outage:

final retried = await queue.retryFailed(); // or retryFailed(group: 'uploads')

retry keeps the task id, payload, keys, priority, group, and dependencies, and can take a new retryPolicy. It refuses tasks that are still active, refuses when another active task already holds the same deduplication key, and refuses when a dependency did not complete (retry that dependency first). Tasks cancelled because a dependency failed are not revived automatically. delete and purge only touch terminal tasks, and never remove a task that a waiting task still depends on.

When the queue is no longer needed, close stops it and closes the events and storageErrors streams:

await queue.close();

Running in a limited time window

drain starts the queue, runs what is ready, and stops when nothing is left to start or a time limit passes. Use it where the app gets a short window to work, such as a background job started by the operating system:

final result = await queue.drain(timeLimit: Duration(seconds: 25));
print('${result.completed} done, ${result.failed} failed, stopped: ${result.reason.name}');
// result.nextWakeAt: when the next scheduled task, retry, or deferral is due.

• Tasks scheduled for later, retries, and tasks held by a gate or rate limit do not keep the drain going. Pass waitForScheduled: true to also wait for timed work due before the limit.
• At the limit no new task starts; tasks already running finish first, so leave headroom for your longest task.
• The queue must be idle when drain is called, and is idle again when it returns.

On Android and iOS, durable_queue_workmanager runs drain from Workmanager jobs. Its lease keeps the job and the app's own queue from running the same storage at once.

Work that finishes outside the queue

Some work outlives the handler that starts it. An upload given to the operating system's background transfer service keeps going after the app is suspended or closed, and its result arrives later, maybe after a restart. A handler hands such a task off instead of waiting:

queue.register<UploadPhotoTask>(
  type: 'upload_photo',
  decoder: UploadPhotoTask.fromJson,
  handler: (task, context) async {
    final transferId = await startSystemUpload(task.path); // returns at once
    context.handOff(transferId);
  },
);

// Later, when the transfer reports back (in this run of the app or a later one):
await queue.completeHandOff(taskId, reference: transferId);
await queue.failHandOff(taskId, error, reference: transferId); // retry rules apply

• A handed-off task stays running with handOffReference set (StoredTask.isHandedOff). It does not hold a concurrency slot, start does not treat it as interrupted, and tasks that depend on it wait for its outcome.
• completeHandOff completes it. failHandOff applies the type's retryIf, retryDelay, and deferOn rules and the retry policy, as if the handler had thrown; a retry runs the handler again, which starts the work again. A TaskCancelledException cancels it.
• Both take the reference the handler gave and return false when it does not match the current attempt, or the task is no longer handed off, so a late or repeated report is harmless.
• cancel stops waiting at once: the task becomes cancelled and a TaskCancelled event (wasRunning: true) tells whoever runs the outside work to stop it.
• The reference is stored as soon as handOff is called, so a crash before the handler returns does not start the work twice.

durable_queue_transfer does this for uploads and downloads with background_downloader.

Observation

queue.events.listen((event) {
  // TaskEnqueued (with runAt for scheduled tasks), TaskStarted,
  // TaskRetryScheduled, TaskDeferred,
  // TaskCompleted, TaskFailed, TaskCancelled
});

final failed = await queue.getTasks(status: TaskStatus.failed);

TaskDeferred says why a task waits (rateLimit, gateClosed, or gateError), which limit or gate is responsible, and until when.

The event stream is broadcast and does not replay events that happened before the listener subscribed.

Worker storage errors are reported as values on queue.storageErrors and retried after storageRetryDelay (default one second). A failed result write retries persistence without running the handler again. Storage outages hold serialized operations, so enqueue, queries, cancellation, pause, and stop can wait until storage recovers. Failed startup recovery leaves the queue idle and allows another start() call.

Using it in Flutter

The core package does not depend on Flutter. durable_queue_flutter connects a queue to the app:

Future<void> main() async {
  WidgetsFlutterBinding.ensureInitialized();
  final queue = DurableQueue(storage: await openStorage()); // e.g. durable_queue_sqlite
  queue.register<UploadPhotoTask>(
    type: 'upload_photo',
    decoder: UploadPhotoTask.fromJson,
    handler: (task, context) => api.upload(task.path),
  );
  // Starts the queue, pauses it in the background, resumes in the foreground.
  runApp(DurableQueueScope(queue: queue, child: const MyApp()));
}

// Anywhere in the UI:
QueueTaskBuilder(
  taskId: uploadId,
  builder: (context, task) => Text(task?.status.name ?? '...'),
);

Without that package, create the queue the same way, call await queue.start() before runApp, and build UI from queue.events, getTask, and getTasks.

The queue runs while your app's process runs. It does not wake a terminated app; it starts again on the next launch. To keep work going while the app is away, run it from background jobs with durable_queue_workmanager.

Storage

The engine talks to storage only through QueueStorage, so you choose where tasks live.

Storage	Survives restart	Status
MemoryQueueStorage	No	Included. For tests and process-lifetime queues.
JsonFileStorage	Yes	Example in example/json_file_storage.dart, checked against the full storage contract. Rewrites one file per change, so it suits small queues.
durable_queue_sqlite	Yes	Separate package. Indexed, transactional SQLite storage for Android, iOS, macOS, Windows, Linux, and the web. Use 0.2.1 or later with durable_queue 0.5.
Hive, Isar, others	Yes	Adapters are welcome as separate packages; say what you need in Discussions.

Adapters stay in separate packages so the core never forces a database on you.

To write an adapter, implement QueueStorage and run the shared contract tests against it:

final class MyStorage implements QueueStorage {
  // save, get, update, delete, getNextReady, getWaitingDependents, ...
}

// test/my_storage_test.dart
void main() => queueStorageContractTests(MyStorage.new);

queueStorageContractTests lives in storage_contract.dart in the repository's test-support package; copy it into your adapter's tests. STORAGE.md lists every method, ordering rule, and atomicity requirement.

When to use durable_queue

	Manual try/catch + retry loop	Simple in-memory queue	durable_queue	OS background scheduler (e.g. Android WorkManager)
Work survives an app restart	No	No	Yes, with a persistent storage adapter	Yes
Runs while the app is terminated	No	No	No	Yes, within OS limits
Retry with backoff and a retry filter	You write it	Usually you write it	Built in	Varies by platform
Deduplication and idempotency keys	You write it	Usually you write it	Built in	Varies by platform
Dependencies, chains, priorities	You write it	Rarely	Built in	Varies by platform
Rate limits, waiting for the network	You write it	Rarely	Built in	Network constraints only
Testable without real waiting	Depends on your code	Depends	Yes (FakeQueueClock)	Limited
Platforms	Any	Any	Any Dart platform	One platform per API

Use durable_queue when work must outlive a failed request or an app restart, and the app is allowed to finish it the next time it runs. Use an OS scheduler when the work must run while the app is closed; the two can be combined, with the OS job calling start. A plain try/catch is enough for work that is fine to lose. This table compares capabilities only; no performance benchmarks have been published.

Guarantees

Execution is at least once. A crash after a side effect but before the completion write can run the task again.

start recovers a task left in running: that attempt counts, then the retry policy either schedules another try or fails the task. Handlers should be idempotent when a repeated side effect would be harmful.

When a task finishes, the tasks waiting on it are updated before its own result is written. A crash in between never leaves a task waiting forever behind a dependency that already finished. The worst case is that dependents were released or cancelled for an outcome that recovery then records again.

Persistence is not background execution. A terminated app stays terminated until something else launches it. After the next launch, call start again.

Do not put secrets in task payloads or exception text. The queue stores them as plain data. MemoryQueueStorage does not encrypt anything.

Examples

dart run example/main.dart           # one task, one retry
dart run example/image_upload.dart   # uploads that survive a restart
dart run example/orchestration.dart  # chains, dependencies, priorities
dart run example/rate_limits_and_gates.dart  # rate limits, offline gate

Contributing and feedback

• Questions, feature ideas, and storage-integration requests: GitHub Discussions.
• Bugs: issue tracker.
• Code and adapters: see CONTRIBUTING.md.