async-python-patterns

Asyncio enables concurrent operations so your scraper can fetch hundreds of URLs simultaneously without blocking on slow responses. This Skill provides practical examples for implementing this high-performance pattern.

Coroutines define async functions, tasks schedule coroutines on the event loop, and futures represent pending results that may not be computed yet. This Skill covers these core asyncio concepts with practical guidance.

Yes, async/await handles I/O-bound database operations and WebSocket servers concurrently without blocking. This Skill includes real-world application examples for both use cases alongside producer-consumer and semaphore patterns.

Semaphores limit concurrent operations to a fixed count while locks ensure exclusive access to shared resources. This Skill covers these advanced synchronization patterns alongside gather and async context managers for building non-blocking systems.

Avoid async/await for CPU-bound work since asyncio only benefits I/O-bound applications like web APIs and network services. This Skill outlines best practices and common pitfalls for when asynchronous programming is inappropriate.

No external libraries are needed because asyncio is built into Python for async/await syntax, event loops, and concurrent programming. This Skill requires no dependencies and provides a quick-start script demonstrating basic asynchronous operations.