Production-ready patterns for Apache Airflow DAGs, operators, sensors, testing, and deployment.

• Covers DAG design principles (idempotent, atomic, incremental, observable) with task dependency patterns for linear, fan-out, fan-in, and complex workflows
• Includes TaskFlow API decorators for cleaner code with automatic XCom passing, dynamic DAG generation from configs, and branching with conditional logic
• Provides sensor patterns for S3 files, external task dependencies, and custom sensors; error handling with callbacks and trigger rules; and testing strategies with pytest fixtures
• Best practices section covers idempotency, timeouts, worker slot management, and anti-patterns like hardcoded dates and stateful tasks