Can I use this with any message broker?

While the provided examples focus on Redis, the configuration patterns and task definitions are standard for Celery and can be easily adapted for brokers like RabbitMQ.

Does this support different priorities for tasks?

Yes, it provides comprehensive queue routing configurations to separate workloads, allowing you to prioritize critical tasks over heavy, low-priority background jobs.

How do I handle tasks that might hang or run too long?

The skill includes patterns for setting both soft and hard time limits (TTL), which gracefully terminate tasks that exceed their expected execution window.

How does this skill improve task reliability?

It implements patterns like 'task_acks_late' and 'task_reject_on_worker_lost' to ensure tasks are only acknowledged after successful completion or automatically requeued if a worker fails.

Celery Task Worker

Name: Celery Task Worker
Author: adelabdelgawad

byadelabdelgawad

Desarrollo de API

Configures production-ready Celery workers and distributed task queues for scalable background processing.

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The Celery Worker skill provides a comprehensive blueprint for implementing robust background task processing in Python applications. It offers standardized configurations for Redis brokers, task routing, and reliability patterns like late acknowledgments and exponential backoffs. Designed for scalability, it helps developers set up distributed workers that can handle everything from high-volume email queues to heavy file processing, ensuring system responsiveness by offloading long-running jobs from the main application thread.

Características Principales

Advanced task routing and queue management
Detailed task tracking and result backend setup
0 GitHub stars
Production-ready worker and broker configuration
Performance optimization for high-concurrency workloads
Automated retry strategies with exponential backoff

Casos de Uso

Offloading time-consuming tasks like image processing or PDF generation from an API
Managing high-volume transactional emails and notifications via dedicated queues
Implementing scheduled background jobs and periodic system maintenance tasks

Acerca de

Características Principales

Advanced task routing and queue management
Detailed task tracking and result backend setup
0 GitHub stars
Production-ready worker and broker configuration
Performance optimization for high-concurrency workloads
Automated retry strategies with exponential backoff

Casos de Uso

Offloading time-consuming tasks like image processing or PDF generation from an API
Managing high-volume transactional emails and notifications via dedicated queues
Implementing scheduled background jobs and periodic system maintenance tasks