How does it handle errors in concurrent tasks?

It implements robust patterns using asyncio.gather with exception handling and safe wrappers, ensuring that a single failing task doesn't unexpectedly crash your entire operation.

When should I use this skill instead of standard Python threading?

Use this skill for I/O-bound tasks where waiting for network or disk operations is the bottleneck. Asyncio is more memory-efficient than threading for handling thousands of concurrent connections in a single-threaded event loop.

Can it help manage race conditions in async code?

Absolutely, the skill includes specific patterns for using async locks and semaphores to safely manage shared resources and prevent race conditions during concurrent execution.

Does this support specific web frameworks?

Yes, it provides patterns and best practices compatible with FastAPI, aiohttp, Sanic, and other modern async-first Python libraries.

Async Python Patterns

Name: Async Python Patterns
Author: HermeticOrmus

byHermeticOrmus

API 开发

Masters Python asyncio and concurrent programming patterns to build high-performance, non-blocking applications.

关于

This skill provides comprehensive architectural guidance and implementation patterns for asynchronous Python development using the asyncio library. It covers the core mechanics of the event loop, coroutines, and tasks, while offering production-ready templates for concurrent execution, sophisticated error handling, and resource management. Whether you are building high-throughput web APIs with FastAPI, complex web scrapers with aiohttp, or real-time communication systems, this skill helps optimize I/O-bound workloads and implement advanced synchronization patterns like producer-consumer queues and rate-limiting semaphores.

主要功能

Templates for high-performance web scraping and database integration
0 GitHub stars
Advanced concurrency control using semaphores and async locks
Core asyncio implementation patterns including gather, wait_for, and create_task
Structured error handling and exception management for concurrent operations
Resource management via async context managers and iterators

使用场景

Developing high-concurrency web crawlers and data collection systems
Optimizing database-heavy applications using asynchronous I/O drivers
Building scalable, non-blocking REST and WebSocket APIs with modern frameworks

关于

主要功能

Templates for high-performance web scraping and database integration
0 GitHub stars
Advanced concurrency control using semaphores and async locks
Core asyncio implementation patterns including gather, wait_for, and create_task
Structured error handling and exception management for concurrent operations
Resource management via async context managers and iterators

使用场景

Developing high-concurrency web crawlers and data collection systems
Optimizing database-heavy applications using asynchronous I/O drivers
Building scalable, non-blocking REST and WebSocket APIs with modern frameworks