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async-python-patterns

Implement asyncio concurrency patterns for non-blocking Python applications.

Updated Apr 13, 2026
Search Tags:#rate limiting#python#concurrency#asyncio#async await#event loop#aiohttp
One-click install
npx skills add https://github.com/scoots31/engineering-playbook --skill async-python-patterns-scoots31
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: async-python-patterns
Source: https://github.com/scoots31/engineering-playbook/tree/main/references/async-python-patterns
Command: npx skills add https://github.com/scoots31/engineering-playbook --skill async-python-patterns-scoots31

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires aiohttp, httpx, pytest-asyncio.

What problem does it solve? Writing concurrent Python code that handles many I/O operations without blocking is error-prone, and developers often struggle with event loops, task management, and mixing sync and async code correctly. ## Core Features & Use Cases - Concurrency Patterns: Provides ready-to-use patterns for gather(), task creation, semaphores, locks, queues, and producer-consumer workflows. - Real-World Examples: Includes implementations for web scraping with aiohttp, async database operations, WebSocket servers, and rate-limited API calls. - Pitfall Guidance: Covers common mistakes like blocking the event loop, forgetting await, and improper cancellation handling, plus testing with pytest-asyncio. - Use Case: When building a FastAPI service that must call 20 external APIs per request, use the semaphore rate-limiting pattern to run requests concurrently without overwhelming downstream services. ## Quick Start Ask the assistant to show you how to fetch multiple URLs concurrently using asyncio and aiohttp with rate limiting.

Frequently Asked Questions about async-python-patterns

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run multiple async tasks concurrently in Python?▼

Use asyncio.gather() to run multiple coroutines concurrently and collect their results as a list. For long-running work, create tasks with asyncio.create_task() and await them when needed.

How do I limit concurrent requests with asyncio?▼

Use asyncio.Semaphore to cap concurrency. Wrap each operation in 'async with semaphore' so only a fixed number of tasks run simultaneously, which is ideal for rate-limited API calls.

When should I use asyncio vs multiprocessing in Python?▼

Use asyncio for I/O-bound work like network and database calls, and multiprocessing for CPU-bound computation. For mixed workloads, offload CPU work with asyncio.to_thread() or run_in_executor().

Can I call a synchronous library inside async code?▼

Yes, wrap blocking calls with asyncio.to_thread() in Python 3.9+ or loop.run_in_executor() for older versions. Calling blocking code directly stalls the entire event loop and all concurrent tasks.

Why does my async code block the event loop?▼

Blocking happens when synchronous calls like time.sleep() or requests.get() run inside a coroutine. Replace them with asyncio.sleep() and async-native libraries such as httpx or aiohttp.

How do I test async functions with pytest?▼

Use the pytest-asyncio plugin and mark tests with @pytest.mark.asyncio. The test function can then use await directly, including assertions on timeouts with asyncio.wait_for.

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