async-python-patterns
Comprehensive guide to asyncio, concurrent patterns, and async/await for building high-performance, non-blocking Python applications.
- Covers core concepts (event loops, coroutines, tasks, futures) and 10+ fundamental and advanced patterns including concurrent execution, error handling, timeouts, context managers, and producer-consumer workflows
- Includes real-world examples for web scraping with aiohttp, async database operations, and WebSocket servers
- Provides performance best practices: connection pooling, batching, and proper handling of blocking code with
asyncio.to_thread()andrun_in_executor() - Highlights common pitfalls (forgetting await, blocking the event loop, mixing sync/async) and testing strategies with pytest-asyncio
Async Python Patterns
Comprehensive guidance for implementing asynchronous Python applications using asyncio, concurrent programming patterns, and async/await for building high-performance, non-blocking systems.
When to Use This Skill
- Building async web APIs (FastAPI, aiohttp, Sanic)
- Implementing concurrent I/O operations (database, file, network)
- Creating web scrapers with concurrent requests
- Developing real-time applications (WebSocket servers, chat systems)
- Processing multiple independent tasks simultaneously
- Building microservices with async communication
- Optimizing I/O-bound workloads
- Implementing async background tasks and queues
Sync vs Async Decision Guide
Before adopting async, consider whether it's the right choice for your use case.
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