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Rust-powered task queue for Python. No broker required.

Project description

taskito

A Rust-powered task queue for Python. No broker required — just SQLite or Postgres.

PyPI version Python versions License

pip install taskito                # SQLite (default)
pip install taskito[postgres]      # with Postgres backend

Quickstart

1. Define tasks in tasks.py:

from taskito import Queue

queue = Queue(db_path="tasks.db")

@queue.task()
def add(a: int, b: int) -> int:
    return a + b

2. Start a worker:

taskito worker --app tasks:queue

3. Enqueue jobs:

from tasks import add

job = add.delay(2, 3)
print(job.result(timeout=10))  # 5

Why taskito?

Most Python task queues need a separate broker (Redis, RabbitMQ) even for single-machine workloads. taskito embeds storage, scheduling, and worker management into one pip install with no external services. An optional Postgres backend adds multi-machine workers with the same API.

The engine runs in Rust — a Tokio async scheduler, an OS-thread worker pool, and Diesel over SQLite in WAL mode. The GIL is held only during task execution; run --pool prefork for true parallelism on CPU-bound work.

Features

  • Reliability — retries with exponential backoff, dead letter queue with replay, circuit breakers, exception filtering
  • Scheduling — priorities, rate limiting, periodic (cron) tasks, delayed execution, job expiration
  • Workflowschain / group / chord, task dependencies with cascade cancel
  • Control — cooperative cancellation, soft timeouts, unique/idempotent tasks, queue pause/resume
  • Observability — web dashboard, events, HMAC-signed webhooks, structured logging, worker heartbeats
  • Extensibility — pluggable serializers, per-task middleware, async API, Postgres/Redis backends

Examples

from taskito import chain, group, chord

# Sequential pipeline — each step receives the previous result
chain(fetch.s(url), parse.s(), store.s()).apply()

# Parallel fan-out, then a callback once all complete
chord([download.s(u) for u in urls], merge.s()).apply()
@queue.task(max_retries=5, retry_backoff=2.0, rate_limit="100/m")
def fetch_url(url: str) -> str:
    return requests.get(url).text

More examples — dependencies, progress tracking, middleware, FastAPI — in the docs.

Integrations

Extra Install What you get
Flask pip install taskito[flask] Taskito(app) extension, flask taskito worker CLI
FastAPI pip install taskito[fastapi] TaskitoRouter for instant REST API over the queue
Django pip install taskito[django] Admin integration, management commands
OpenTelemetry pip install taskito[otel] Distributed tracing with span-per-task
Prometheus pip install taskito[prometheus] PrometheusMiddleware, queue depth gauges, /metrics server
Sentry pip install taskito[sentry] SentryMiddleware with auto error capture and task tags
Postgres pip install taskito[postgres] Multi-machine workers via PostgreSQL backend
Redis pip install taskito[redis] Redis storage backend

Testing

Built-in test mode — no worker needed:

def test_add():
    with queue.test_mode() as results:
        add.delay(2, 3)
        assert results[0].return_value == 5

Documentation

Read the docs → — guides, API reference, and architecture. Coming from Celery? See the Migration Guide.

Comparison

Feature taskito Celery RQ Dramatiq Huey
Broker required No Yes Yes Yes Yes
Core language Rust + Python Python Python Python Python
Priority queues Yes Yes No No Yes
Rate limiting Yes Yes No Yes No
Dead letter queue Yes No Yes No No
Task dependencies Yes No No No No
Built-in dashboard Yes No No No No
FastAPI integration Yes No No No No
Cancel running tasks Yes Yes No No No
Postgres backend Yes Yes No No No
Setup pip install Broker + backend Redis Broker Redis

License

MIT

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