How does this skill handle Celery retries?

It provides standardized patterns for automatic retries with exponential backoff, jitter, and specific exception handling to ensure robust task execution even when external services fail.

Does it support FastAPI integration?

Absolutely, it includes specific implementation patterns for triggering tasks from FastAPI endpoints and tracking task status or results via AsyncResult.

Can I use this for periodic tasks?

Yes, the skill includes full configuration examples and crontab patterns for Celery Beat to manage scheduled jobs, daily reports, and system maintenance.

How do I test my Celery tasks using this skill?

The skill provides pytest configurations for 'task_always_eager' mode, allowing you to run and test tasks synchronously during development and within unit testing suites.

What are the recommended brokers for this skill?

While it covers general configuration, it focuses on Redis and RabbitMQ as the primary brokers for reliable message passing and result storage.

Celery Task Queue Integration

Name: Celery Task Queue Integration
Author: FortiumPartners

byFortiumPartners

0•

API Development

Implements distributed task queues, periodic scheduling, and asynchronous processing using Celery 5.3+ and Python.

This skill equips Claude with the expertise to design, implement, and optimize distributed task processing systems using Celery and the Beat scheduler. It covers application setup, task definitions with retry logic, complex workflow patterns like chains and groups, and seamless integration with modern frameworks like FastAPI. Ideal for developers building scalable backend services that require background job execution, periodic maintenance tasks, or high-performance asynchronous processing with Redis or RabbitMQ brokers.

Key Features

010 GitHub stars

02Advanced task definitions with automatic retries, backoff, and rate limiting

03Comprehensive Celery 5.3+ application configuration and broker setup

04Complex workflow orchestration using chains, groups, and chords

05Seamless FastAPI integration for triggering and monitoring background jobs

06Testing configurations using eager mode and memory brokers for CI/CD

Use Cases

01Offloading long-running processes like report generation or email delivery to background workers

02Implementing multi-stage data processing pipelines with sequential and parallel execution

03Scheduling periodic maintenance tasks and automated cleanup scripts via Celery Beat

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add fortiumpartners/ensemble-vnext using-celery

For use in Claude.ai and ChatGPT

Key Features

010 GitHub stars

02Advanced task definitions with automatic retries, backoff, and rate limiting

03Comprehensive Celery 5.3+ application configuration and broker setup

04Complex workflow orchestration using chains, groups, and chords

05Seamless FastAPI integration for triggering and monitoring background jobs

06Testing configurations using eager mode and memory brokers for CI/CD

Use Cases

01Offloading long-running processes like report generation or email delivery to background workers

02Implementing multi-stage data processing pipelines with sequential and parallel execution

03Scheduling periodic maintenance tasks and automated cleanup scripts via Celery Beat

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add fortiumpartners/ensemble-vnext using-celery

For use in Claude.ai and ChatGPT