Celery Tasks

Celery task definitions and distributed processing components.

Task Components:

• Setup Celery App
  • init_worker()
  • configure_dynamic_queues()
  • get_worker_queues()
  • configure_logger()
  • SQLAlchemyTask
  • make_celery_task()
  • start_celery_worker()
  • start_celery_beat()
  • Overview
  • Key Components
  • Related Documentation

Overview

The task system provides distributed processing capabilities:

Setup Celery App

Celery application configuration and task definitions.

Distributed Processing

Tasks enable the Manager/Worker pattern by providing:

• Asynchronous execution: Long-running operations don’t block managers

• Distributed processing: Work can be distributed across multiple machines

• Queue management: Tasks are routed to appropriate workers

• Fault tolerance: Failed tasks can be retried automatically

• Monitoring: Task status and progress can be tracked

Task Integration

Tasks integrate with managers to provide distributed processing:

1. Managers submit tasks to queues

2. Workers execute tasks and update database

3. Services monitor task execution and health

For understanding the complete data flow:

• Pipeline Architecture - Data processing pipeline

• Philosophy & Design Principles - Manager/Worker pattern

• Monitoring & Failure Recovery - Task monitoring and observability