Table of Contents
Async Python is not just sync Python with async/await sprinkled on top. It requires a different mental model for concurrency, error handling, and resource management. Many Python developers claim async experience but have never built a production async system. Here's what actually matters.
Core Async Concepts Every Engineer Must Know
Production Async Knowledge
- ✦ Distributed tracing and observability
- ✦ Rate limiting and backpressure handling
- ✦ Circuit breaker implementation
- ✦ Graceful shutdown procedures
- ✦ Memory leak investigation
- ✦ Concurrency-safe resource management
Must-Have Skills
Beyond syntax:
- ✦ Experience with async database drivers (asyncpg, aiosqlite, motor for MongoDB)
- ✦ Async HTTP clients (httpx, aiohttp) vs sync requests
- ✦ Background task management (asyncio.create_task, BackgroundTasks)
- ✦ Handling task cancellation properly
- ✦ Resource cleanup with async context managers
Testing Async Code
Sign of seniority:
- ✦ pytest-asyncio or similar for testing coroutines
- ✦ Mocking async functions (AsyncMock)
- ✦ Testing timeout and cancellation behavior
- ✦ Testing concurrent execution paths
Production Scenarios to Discuss
Interview Questions
Signals of Senior Async Engineers
- ✦ Has handled production incidents involving async systems
- ✦ Can explain tradeoffs of concurrency models
- ✦ Understands observability and tracing
- ✦ Has experience scaling APIs under real traffic
- ✦ Can mentor teams on async architecture decisions
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