taskiq
Distributed task queue with full async support
Decision gist · record as of 2026-08-14
Yes, if you need async-first distributed task processing. Taskiq is actively maintained, has low install friction, carries no known vulnerabilities, and is MIT-licensed. The main gotcha is that you must run a separate message broker—it's not a standalone queue. Requires Python 3.10 or later.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later; production use requires a separate message broker backend (NATS, Redis, RabbitMQ, Kafka, etc.).
- Low friction installation with a pure Python wheel.
- The project is actively maintained with a recent release and 2290 repository stars.
License · maintenance · safety
MIT (permissive) — MIT license (permissive) means you can use taskiq freely in commercial and private projects with minimal restrictions—just include the license notice.
last release 2026-05-08 (98 days) · last repo commit 2026-08-01 · 2,290 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 1,816,026 downloads/mo, #3,522 on PyPI
Alternatives
Verify before relying
pip install taskiq
from taskiq import InMemoryBroker
import asyncio
broker = InMemoryBroker()
@broker.task
async def my_task(a: int, b: int) -> None:
print("Result:", a + b)
async def main():
await broker.startup()
await my_task.kiq(1, 2)
await broker.shutdown()
if __name__ == "__main__":
asyncio.run(main())- Which message broker backends are officially supported and their setup requirements.
- Performance characteristics and throughput limits in real-world deployments.
- Maturity level and stability guarantees given the Alpha development status classifier.
What it is and what it does
Taskiq is a distributed task queue framework for Python that lets you offload work to background workers. Unlike traditional task queues, it handles both synchronous and asynchronous functions natively and integrates with async frameworks like FastAPI and AioHTTP. You define tasks by decorating functions with a broker decorator, then send them to a queue where worker processes pick them up and execute them.
The package is built around type hints and PEP-612 to provide strong IDE autocompletion. It requires a separate message broker to run—taskiq itself is the client library and worker runner. You start workers via a CLI command that discovers your tasks, optionally with hot-reload support. The framework is actively maintained, supports Python 3.10 through 3.14, and carries no known security vulnerabilities.
Use it for
- Offload long-running computations from a FastAPI or AioHTTP web request to execute asynchronously in background workers.
- Schedule periodic tasks using cron expressions via pycron for time-based job execution.
- Distribute work across multiple machines by pointing workers at a shared message broker.
- Reuse web application dependencies in background tasks through framework integrations.
- Build a microservice architecture where different services enqueue tasks for each other via a common broker.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need async-first distributed task processing.
Taskiq is actively maintained, has low install friction, carries no known vulnerabilities, and is MIT-licensed. The main gotcha is that you must run a separate message broker—it's not a standalone queue. Requires Python 3.10 or later.
Install
taskiq on PyPI
Before you install
Low friction installation with a pure Python wheel. The project is actively maintained with a recent release and 2290 repository stars. Seven runtime dependencies are all well-established packages, suggesting a stable dependency chain.
Requires Python 3.10 or later; production use requires a separate message broker backend (NATS, Redis, RabbitMQ, Kafka, etc.).
License in practice
MIT license (permissive) means you can use taskiq freely in commercial and private projects with minimal restrictions—just include the license notice.
Quickstart
pip install taskiq
from taskiq import InMemoryBroker
import asyncio
broker = InMemoryBroker()
@broker.task
async def my_task(a: int, b: int) -> None:
print("Result:", a + b)
async def main():
await broker.startup()
await my_task.kiq(1, 2)
await broker.shutdown()
if __name__ == "__main__":
asyncio.run(main())Verify before relying
- Which message broker backends are officially supported and their setup requirements.
- Performance characteristics and throughput limits in real-world deployments.
- Maturity level and stability guarantees given the Alpha development status classifier.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release <4,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 7 packagesaiohttpanyiopackagingpycronpydantictaskiq-dependenciestyping-extensions |
| Maintenance | Actively maintained 98 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 1,816,026 / month, #3,522 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 3 - AlphaIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: System :: NetworkingTyping :: Typed |
Evidence: taskiq-0.12.4-py3-none-any.whl
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See also celery · taskiq-fastapi · taskiq-redis · dvc-task · vercel-workers · dramatiq · taskiq-aio-pika · faststream · arq · celery-batches