---
id: taskiq
version: "0.12.4"
license: MIT
license_treatment: permissive
maintenance: active
---

# taskiq — Distributed task queue with full async support

License: permissive · Maintenance: active · Downloads: 1.8M/mo

## 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 above — verify before relying.

Taskiq is an asynchronous distributed task queue that lets you send and run both sync and async functions across worker processes, with built-in integrations for FastAPI and AioHTTP.

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

pip install taskiq
uv add taskiq
poetry add taskiq

## Installing taskiq

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.

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())

Requires Python 3.10 or later; production use requires a separate message broker backend (NATS, Redis, RabbitMQ, Kafka, etc.).

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_current
- Install friction: low
- Maintenance: active
- Downloads: 1.8M/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

async task queue, distributed task processing, celery alternative python, async worker queue, background job scheduler, task broker framework, async task runner, async-first, background-jobs, message-broker

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