RQ 2.12 — Lightweight Python Redis Queue

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Overview

RQ (Redis Queue) turns Python function calls into background jobs stored in Redis or Valkey and processed by independent workers. It provides priority queues, retries, scheduling, repeating jobs, uniqueness, and webhooks through a relatively small API.

Features and best fit

Based on official documentation; not hands-on tested · Content checked: 2026-10-06

Key features

Enqueue Python functions and process them in independent workers

Queue.enqueue() stores a Python function call and arguments as a job in Redis or Valkey, while rq worker processes jobs in a separate worker process. Multiple queues such as high and low can be ordered for priority handling.

Sources: [2]

Add retries, scheduling, repetition, unique jobs, and webhooks

RQ includes Retry, delayed and scheduled execution, repeating jobs, duplicate prevention through unique jobs, and completion or failure webhooks. Version 2.12 also adds CronJobRegistry for tracking cron job history.

Sources: [2][4]

Best fit

Fits Python backends that want background work with an existing Redis deployment

It works well for email delivery, report generation, image processing, and similar work that should leave the request path without introducing a larger broker stack, especially when Redis or Valkey already exists in the service.

Sources: [2]

Before adoption

RQ 2.12 requires Python 3.10+ and Redis 5+ or Valkey 7.2+; review pickle and worker choices

RQ 2.12 requires Python 3.10 or newer and Redis 5+ or Valkey 7.2+. The default serializer uses pickle and is unsafe with untrusted Redis data, so use only trusted instances or a safer serializer. Production guidance favors Worker or SpawnWorker for isolation and hard timeouts, with SimpleWorker reserved for measured short-job bottlenecks.

Sources: [2][3]

Official sources

[1]rq/rq — GitHub repository(2026-10-06)
[2]RQ 2.12 — README(2026-10-06)
[3]RQ 2.12 — pyproject.toml(2026-10-06)
[4]RQ 2.12 release(2026-10-06)
[5]RQ BSD-2-Clause license(2026-10-06)

Supplemental curator note

RQ is a strong fit when an existing Redis deployment can support a small background-job stack. The default pickle serializer and worker isolation model directly affect the trust boundary, so decide those choices before production rollout.

Try it in 3 steps

1
Install RQ 2.12
Pin the reviewed stable release. Python 3.10 or newer and a trusted Redis 5+ or Valkey 7.2+ instance are required.
python -m pip install "rq==2.12"
2
Create a job to enqueue
Create a minimal function and enqueue script without external HTTP access. Redis or Valkey is expected to be running on localhost.
cat > tasks.py <<'PY' def add(x, y): return x + y PY cat > enqueue.py <<'PY' from redis import Redis from rq import Queue from tasks import add q = Queue(connection=Redis()) job = q.enqueue(add, 2, 3) print(job.id) PY
3
Start a worker and enqueue the job
Start the worker, enqueue the job from another terminal, and confirm successful execution in the worker log. The default serializer uses pickle, so only use trusted Redis data.
rq worker # In another terminal: python enqueue.py

Check the official README

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GitHub Topics

async
background-jobs
delayed-jobs
delayed-tasks
job-queue
python
redis
rq
task
task-queue
workers

Stars: 10,693
Forks: 1,503
Watchers: 194
Open issues: 261
Contributors: 316
Owner type: Organization
Primary language: Python
License: BSD-2-Clause
Repository last updated: Oct 3, 2026

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