Can this skill help prevent race conditions in async code?

Yes, it includes patterns for using async locks and synchronization primitives to manage shared resources safely in a concurrent environment.

How does this skill help with FastAPI development?

It provides optimized async patterns for handling database connections, background tasks, and concurrent API requests, ensuring your FastAPI application remains responsive under high load.

What version of Python is this skill optimized for?

The patterns follow modern Python 3.7+ standards, utilizing asyncio.run(), create_task(), and other contemporary best practices.

Does it provide support for concurrent network requests?

Absolutely. It includes specialized patterns for using aiohttp and semaphores to perform hundreds of concurrent network requests while respecting rate limits.

Async Python Patterns

Name: Async Python Patterns
Author: arthur0824hao

byarthur0824hao

API Development

Implements high-performance asynchronous Python patterns using asyncio for non-blocking I/O operations.

About

This skill provides Claude with deep expertise in Python's asynchronous ecosystem, enabling the creation of efficient, non-blocking applications. It covers everything from fundamental async/await syntax and concurrent execution with asyncio.gather to advanced patterns like producer-consumer queues, semaphores for rate limiting, and thread-safe async synchronization. It is particularly useful for developers building modern web APIs, real-time communication systems, or high-throughput data scrapers where I/O performance and system responsiveness are critical.

Key Features

Advanced asyncio pattern implementation including tasks and futures
Producer-consumer architectural patterns for background task management
Concurrency control using semaphores and async locks
Robust error and timeout handling for async operations
0 GitHub stars
Async generator and iterator patterns for efficient data streaming

Use Cases

Optimizing database and network-heavy I/O workloads
Building high-performance web APIs with FastAPI or aiohttp
Developing concurrent web scrapers and data collection tools

About

Key Features

Advanced asyncio pattern implementation including tasks and futures
Producer-consumer architectural patterns for background task management
Concurrency control using semaphores and async locks
Robust error and timeout handling for async operations
0 GitHub stars
Async generator and iterator patterns for efficient data streaming

Use Cases

Optimizing database and network-heavy I/O workloads
Building high-performance web APIs with FastAPI or aiohttp
Developing concurrent web scrapers and data collection tools