taskiq-redis
Redis integration for taskiq
Decision gist · record as of 2026-08-14
Yes. The package is actively maintained, has no known vulnerabilities, low install friction, and a permissive MIT license. It fills a clear role as a production-ready Redis backend for taskiq. Install it if you need distributed task queuing with Redis and are already using or planning to adopt taskiq.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a running Redis server and taskiq library installed; Python 3.10 or later.
- Low friction: pure Python wheel with only two runtime dependencies (redis and taskiq).
- Actively maintained with recent commits and no known vulnerabilities.
License · maintenance · safety
MIT (permissive) — MIT license permits use, modification, and distribution with minimal restrictions—suitable for commercial and open-source projects.
last release 2026-06-23 (52 days) · last repo commit 2026-06-23 · 91 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 1,467,669 downloads/mo, #3,874 on PyPI
Alternatives
Verify before relying
pip install taskiq-redis
from taskiq_redis import RedisStreamBroker, RedisAsyncResultBackend
broker = RedisStreamBroker(url="redis://localhost:6379")
broker = broker.with_result_backend(
RedisAsyncResultBackend(redis_url="redis://localhost:6379")
)
@broker.task
async def my_task():
return "done"
await my_task.kiq()- Performance characteristics and throughput limits under high task volume.
- Cluster and Sentinel broker stability and failover behavior in production.
- Memory overhead and scaling behavior with large result sets.
What it is and what it does
TaskIQ-Redis is a plugin that integrates Redis into taskiq, a distributed async task framework. It provides three broker types—Stream, PubSub, and ListQueue—each available for single-node Redis, Redis Cluster, and Redis Sentinel deployments. The Stream broker supports acknowledgements and is recommended for durability; PubSub and ListQueue are simpler but do not guarantee message delivery if a worker crashes during processing. The package also includes RedisAsyncResultBackend for storing task results and schedule sources for managing dynamic task schedules.
You use it by instantiating a broker, decorating async functions with @broker.task, and then kicking tasks into the queue. Workers consume and execute tasks, with results stored back in Redis. The package handles connection pooling, serialization, and queue routing, letting you focus on task logic rather than Redis plumbing.
Use it for
- Build a microservice that processes long-running jobs asynchronously without blocking HTTP responses.
- Distribute periodic cron tasks across multiple workers using dynamic schedule sources.
- Route tasks to different queues by priority or tenant, using dynamic queue names at runtime.
- Store and retrieve task results durably in Redis with configurable expiration times.
- Scale task processing horizontally by adding workers that consume from the same Redis broker.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
The package is actively maintained, has no known vulnerabilities, low install friction, and a permissive MIT license. It fills a clear role as a production-ready Redis backend for taskiq. Install it if you need distributed task queuing with Redis and are already using or planning to adopt taskiq.
Install
taskiq-redis on PyPI
Before you install
Low friction: pure Python wheel with only two runtime dependencies (redis and taskiq). Actively maintained with recent commits and no known vulnerabilities.
Requires a running Redis server and taskiq library installed; Python 3.10 or later.
License in practice
MIT license permits use, modification, and distribution with minimal restrictions—suitable for commercial and open-source projects.
Quickstart
pip install taskiq-redis
from taskiq_redis import RedisStreamBroker, RedisAsyncResultBackend
broker = RedisStreamBroker(url="redis://localhost:6379")
broker = broker.with_result_backend(
RedisAsyncResultBackend(redis_url="redis://localhost:6379")
)
@broker.task
async def my_task():
return "done"
await my_task.kiq()Verify before relying
- Performance characteristics and throughput limits under high task volume.
- Cluster and Sentinel broker stability and failover behavior in production.
- Memory overhead and scaling behavior with large result sets.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagesredistaskiq |
| Maintenance | Actively maintained 52 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 1,467,669 / month, #3,874 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Programming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13 |
Evidence: taskiq_redis-1.2.3-py3-none-any.whl
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See also redis-simple-mq · taskiq · taskiq-fastapi · taskiq-aio-pika · arq · channels-redis · pydocket · rq-scheduler · render_sdk · faststream