---

name: python-async description: | Master Python asyncio, concurrent programming, and async/await patterns for high-performance applications.

Triggers: asyncio, async/await, coroutines, concurrent programming, async API, I/O-bound, websockets, background tasks, semaphores, async context managers

Use when: building async APIs, concurrent systems, I/O-bound applications, implementing rate limiting, async context managers

DO NOT use when: CPU-bound optimization - use python-performance instead. DO NOT use when: testing async code - use python-testing async module.

Consult this skill for async Python patterns and concurrency. version: 1.0.0 category: async tags: [python, async, asyncio, concurrency, await, coroutines] tools: [async-analyzer, concurrency-checker] usage_patterns:

• async-api-development
• concurrent-io
• websocket-servers
• background-tasks complexity: intermediate estimated_tokens: 400 progressive_loading: true modules:
• basic-patterns
• concurrency-control
• error-handling-timeouts
• advanced-patterns
• testing-async
• real-world-applications
• pitfalls-best-practices

---

Async Python Patterns

asyncio and async/await patterns for Python applications.

Quick Start

import asyncio

async def main():
    print("Hello")
    await asyncio.sleep(1)
    print("World")

asyncio.run(main())

When to Use

• Building async web APIs (FastAPI, aiohttp)
• Implementing concurrent I/O operations
• Creating web scrapers with concurrent requests
• Developing real-time applications (WebSockets)
• Processing multiple independent tasks simultaneously
• Building microservices with async communication

Modules

This skill uses progressive loading. Content is organized into focused modules:

• basic-patterns: Core async/await, gather(), and task management
• concurrency-control: Semaphores and locks for rate limiting
• error-handling-timeouts: Error handling, timeouts, and cancellation
• advanced-patterns: Context managers, iterators, producer-consumer
• testing-async: Testing with pytest-asyncio
• real-world-applications: Web scraping and database operations
• pitfalls-best-practices: Common mistakes and best practices

Load specific modules based on your needs, or reference all for detailed guidance.

Exit Criteria

• Async patterns applied correctly
• No blocking operations in async code
• Proper error handling implemented
• Rate limiting configured where needed
• Tests pass with pytest-asyncio