💡 Check out MongoDB Atlas: https://www.mongodb.com/atlas.

When your FastAPI list endpoint starts pulling full documents just to compute derived fields, it’s usually a sign your read and write models are drifting apart.

In this video, I refactor a tickets API (FastAPI + MongoDB) using CQRS, explain projections and eventual consistency, and show when this architecture is worth the added complexity, and when it’s not.

🔥 GitHub Repository: https://git.arjan.codes/2026/cqrs.

🎓 ArjanCodes Courses: https://www.arjancodes.com/courses.

💬 Join my Discord server: https://discord.arjan.codes.

⌨️ Keyboard I’m using: https://amzn.to/49YM97v.

🔖 Chapters:
0:00 Intro
0:48 The Starting Point: A Perfectly Reasonable FastAPI App
3:53 Where the First Real Pain Shows Up
5:28 CQRS Explained
6:50 Example: Requirements Change
7:59 Separate Command Intent
12:36 Split Write Storage and Read Storage
13:00 Why MongoDB Fits Nicely
14:33 Step 4: Add a Projector
18:49 What Improves After the Refactor
20:39 When to Use CQRS
21:09 When Not to Use CQRS
21:44 Final Thoughts

#arjancodes #softwaredesign #python

CQRS in Python: Clean Reads, Clean Writes