python-background-jobs

What problem does it solve? Long-running operations like sending emails, processing payments, or generating reports block request/response cycles and degrade user experience. This Skill provides patterns to decouple that work into background workers that process jobs asynchronously. ## Core Features & Use Cases - Task Queue Patterns: Return a job ID immediately while Celery workers process tasks in the background, with status polling endpoints for clients. - Reliability Patterns: Idempotent task design, exponential backoff retries, dead letter queues for failed jobs, and persisted job state machines. - Workflow Composition: Chain, group, and chord primitives for building multi-step pipelines and parallel fan-out processing. - Use Case: When a user requests a large data export, enqueue the job, return a job ID instantly, let a worker generate the file, and expose a /jobs/{id} endpoint so the client can poll for completion. ## Quick Start Set up a Celery background task that sends a welcome email asynchronously when a new user signs up, with retries and a job status endpoint.