Event Sourcing & CQRS with FastAPI and Celery.

on YouTube ↗30m

" summary

Builds an append only event store with events containing id, aggregate id, type, timestamp, schema version, revision and data, and wires writes through FastAPI and Pydantic into command handlers that load aggregates, produce events, and persist them to the store and an event bus. Projections run as Celery tasks with retry/backoff (using async-to-sync shims) to update read models. Solves 10k-event replay slowness with snapshots for 10k-event streams, surfaces eventual consistency with optimistic UI or outbox status, and turns bugs into pytest time‑travel debugging.

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" chapters (17)

1. 0:00Introduction to talk
2. 1:16Classic database limitations
3. 2:01Event sourcing fundamentals
4. 4:05CQRS pattern explained
5. 7:24Write and read flows
6. 8:51FastAPI implementation
7. 10:25Command handler deep dive
8. 11:31Aggregate business logic
9. 12:36Celery for event processing
10. 14:52Handling event loss risks
11. 16:02Projection updates
12. 17:52Eventual consistency challenges
13. 21:12Outbox pattern for UI
14. 22:41Performance with snapshots
15. 24:14Debugging with event sourcing
16. 26:44When to avoid event sourcing
17. 28:39Summary and key takeaways

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