$ show apache/airflow
Apache Airflow is a workflow orchestration platform for authoring, scheduling, and monitoring data pipelines. The system uses a modular architecture with core components, extensible providers, a React/TypeScript web UI, and a FastAPI-based REST API. Key entry points include the CLI (`airflow` command), web server, scheduler, and triggerer. Data flows involve DAG parsing, task scheduling via executors, and state persistence in a metadata database. External dependencies include PostgreSQL/MySQL, Redis/RabbitMQ for Celery, and various provider-specific integrations. The codebase demonstrates strong engineering practices with version compatibility patterns, plugin systems, and well-structured API layers.
The LLM identified 3 files worth highlighting for reuse:
Defines the base timetable interface for determining task execution times and handling events. Specific implementations (cron, delta, event-based) are isolated and reusable in other scheduling systems due to clear abstraction and minimal internal dependencies.
Provides the base trigger class for deferrable operators, enabling efficient waiting for events without blocking worker slots. The pattern is self-contained and could be extracted for use in any async task system requiring event-based waiting.
A complete authentication system (login, token validation, user management) for FastAPI applications. Designed as a pluggable manager with separated routes, services, models, and middleware, it can be adapted to other FastAPI apps with minimal changes.