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() and run_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.