Does this skill require Celery to function?

No, the skill is designed with a bridge pattern that allows tasks to run 'inline' within the FastAPI process if Celery is disabled or unavailable.

Can I use this for distributed environments?

Yes, it includes distributed locking and instance registration to ensure that scheduled jobs don't run multiple times across different application instances.

What types of scheduling does it support?

It supports both 'Interval' scheduling (e.g., every 5 minutes) and 'Cron' scheduling (e.g., every Monday at 3:00 AM).

How are task results and history managed?

The system includes database models that track every execution, including start/end times, duration, status, and error messages for full observability.

Distributed Task Management

Name: Distributed Task Management
Author: adelabdelgawad

byadelabdelgawad

API 개발

Implements robust background task scheduling and distributed execution using FastAPI, APScheduler, and Celery.

소개

This skill provides a comprehensive framework for managing background processes and scheduled jobs within FastAPI applications. It bridges APScheduler's flexible scheduling (Cron and Interval) with Celery's distributed execution capabilities, allowing for reliable, asynchronous processing. The system includes built-in patterns for database persistence of job states, execution history tracking, and sophisticated error handling with exponential backoff. It is ideal for developers needing to offload long-running tasks, manage recurring maintenance, or ensure high availability through distributed locking and instance coordination.

주요 기능

Dual-mode execution supporting both distributed Celery workers and inline FastAPI processing
Comprehensive job persistence and execution tracking via SQLAlchemy database models
Fault-tolerant task patterns featuring exponential backoff, retries, and execution time limits
Advanced scheduling engine with support for complex Cron expressions and interval-based triggers
Infrastructure for distributed locking and instance heartbeat monitoring to prevent job duplication
0 GitHub stars

사용 사례

Scheduling recurring system maintenance such as database cleanups, audit logs, or report generation
Offloading heavy API computations or external integrations to background workers to maintain low latency
Managing complex notification systems that require guaranteed delivery and retry logic

소개

주요 기능

Dual-mode execution supporting both distributed Celery workers and inline FastAPI processing
Comprehensive job persistence and execution tracking via SQLAlchemy database models
Fault-tolerant task patterns featuring exponential backoff, retries, and execution time limits
Advanced scheduling engine with support for complex Cron expressions and interval-based triggers
Infrastructure for distributed locking and instance heartbeat monitoring to prevent job duplication
0 GitHub stars

사용 사례

Scheduling recurring system maintenance such as database cleanups, audit logs, or report generation
Offloading heavy API computations or external integrations to background workers to maintain low latency
Managing complex notification systems that require guaranteed delivery and retry logic