intermediate · backend
FastAPI in production
A Python API that survives real traffic: validation, database, auth, background work, deployment.
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By Amit Chakraborty — Kolkata, India · Remote worldwide
What you will be able to do
Ship and operate a FastAPI service that you would put your own name on.
Syllabus — 12 chapters
- 1. FastAPI in one hour — Get a typed, documented API running and understand what generated the documentation.
- 2. Pydantic as your API contract — Use validation as the boundary between the outside world and your code.
- 3. A project structure that survives fifty endpoints — Lay out routers, services and schemas so the codebase stays navigable.
- 4. Databases: SQLAlchemy sessions and the async question — Talk to Postgres correctly, and decide about async on evidence.
- 5. Migrations with Alembic — Change a schema in production without losing data.
- 6. Authentication: OAuth2, tokens and where secrets live — Implement login without inventing your own cryptography.
- 7. Dependency injection, and the testing it enables — Write code that can be tested without a running database.
- 8. Background work: tasks, queues and when you need a worker — Move slow work off the request path.
- 9. Errors, logging and structured observability — Make a production incident diagnosable from the logs you already have.
- 10. Performance: async pitfalls, pools and N plus one — Find and fix the three problems that account for most slow Python APIs.
- 11. Deploying: workers, containers and health checks — Run the service under a real process manager with a real readiness probe.
- 12. Hardening: rate limits, CORS, input size and the risks that matter — Close the vulnerabilities an internet-facing API actually gets probed for.
0 of 12 published. A new chapter every Wednesday night. Free to read.
Learn it free, elsewhere too
The documentation, videos, books and practice sites worth your time on this subject. All free. None of it is mine.