mrq
Distributed worker task queue in Python using Redis & gevent.
Pricing
Free tier
Flat rate
Adoption
↘CoolingLicense
Open Source
Data freshness
Aging · Jun 8, 2026Overview
What is mrq?
mrq is a distributed task queue system built with Python, leveraging Redis for message passing and gevent for concurrency. It's designed to handle background tasks efficiently across multiple workers.
Key differentiator
“mrq stands out by offering a Python-centric approach to distributed task queuing with built-in support for concurrency through gevent, making it ideal for developers who prefer simplicity and efficiency in their background job processing.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
API requires Python-specific patterns, TypeScript SDK is community-maintained
v0.1 to v0.2 migration required rewriting chain definitions
Primary development and maintenance focus is on Python, with minimal official support for other languages
Redis scalability issues can lead to slower task processing times in high-load scenarios
Fit analysis
Who is it for?
✓ Best for
Developers building Python-based systems that require efficient handling of asynchronous tasks.
Teams needing a scalable solution for distributed task processing.
✕ Not a fit for
Projects requiring real-time data streaming and processing, as mrq is designed for batch jobs.
Applications where the overhead of Redis and gevent might be prohibitive.
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Works well with
Next step
Get Started with mrq
Step-by-step setup guide with code examples and common gotchas.