Learn TORNADO-REST with Real Code Examples

CRUD REST API endpoints

WebSocket chat server

Server-sent events (SSE) for live data feeds

Long-polling REST APIs

Async integrations with databases or external APIs

Check IOLoop for running async tasks

Ensure coroutine methods use async/await

Debug URL routing for correct handler mapping

Handle exceptions to avoid event loop crash

Monitor resource usage under high concurrency

Use `unittest` or `pytest`

Test RequestHandlers independently

Use `AsyncHTTPTestCase` for async endpoints

Mock async dependencies

Test WebSocketHandlers with `websocket_connect`

Deploy on Linux/Windows servers

Use Docker for containerized deployment

Reverse proxy with Nginx or Apache

Run multiple IOLoop instances for load balancing

Integrate CI/CD pipelines for automated deployment

Python 3.9+ runtime

Tornado core framework

Async libraries for DB, caching, and HTTP clients

WebSocket support built-in

Third-party async packages for validation and auth

Database: async libraries (SQLAlchemy Async, Motor for MongoDB)

Cache: Redis with aioredis

Message queues: RabbitMQ, Kafka via async clients

Authentication: JWT, OAuth2 libraries

Monitoring: Prometheus, Grafana, Sentry

Use async/await consistently

Reuse async clients for DB and HTTP

Keep handlers lightweight

Modularize services for maintainability

Monitor IOLoop and avoid blocking operations

Managing async/await correctly

Handling high concurrency safely

Integrating async DB clients

Testing asynchronous code

Structuring larger Tornado projects