Best Practices¶
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Return to the Event Handling overview page with all topics.
Overview¶
| Practice | Description | Impact |
|---|---|---|
| Keep handlers fast | Event handlers execute synchronously, so keep them fast | Performance |
| Handle errors | Implement error handling in event handlers | Reliability |
| Use parallel processing | Enable parallel processing for independent events | Performance |
| Limit concurrency | Set appropriate max_concurrent_event_handlers based on resources |
Resource management |
| Idempotency | Make event handlers idempotent when possible | Reliability |
| Logging | Log important events for debugging and monitoring | Observability |
| Follow-up events | Use handler.events for multi-level chains; follow-ups run in the same pipeline (BFS or parallel) |
Design clarity |
Performance Considerations
Event handlers execute synchronously in the request context. Keep them fast to avoid blocking the main request flow.
Parallel Processing
Enable parallel event processing for independent events to improve performance. Set concurrent_event_handle_enable=True and configure max_concurrent_event_handlers.
Event handling in python-cqrs:
- Runtime Processing — Events are processed synchronously in the same request context
- Automatic Dispatch — Events are automatically dispatched to registered handlers
- Event Propagation — Handlers can return follow-up events via
events; they are processed in the same pipeline (BFS or parallel with semaphore) - Parallel Support — Multiple events can be processed in parallel with configurable limits
- Two Types — DomainEvent (in-process) and NotificationEvent (message broker)
- Side Effects — Event handlers perform side effects without blocking command execution
Use event handlers to implement side effects like notifications, read model updates, and workflow triggers while keeping your command handlers focused on business logic.