async-python-patterns

Coordinate asynchronous I/O-bound tasks with asyncio.gather and semaphores.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/dredd-us/seashells --skill async-python-patterns-dredd-us
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: async-python-patterns
Source: https://github.com/dredd-us/seashells/tree/main/.claude/skills/async-python-patterns
Command: npx skills add https://github.com/dredd-us/seashells --skill async-python-patterns-dredd-us

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires aiohttp, asyncpg, fastapi, pytest-asyncio.

What problem does it solve?

This Skill provides robust AsyncIO patterns for Python, enabling you to perform concurrent I/O-bound operations (like HTTP requests or database queries) with near-linear scaling, significantly boosting performance for web scraping, API development, and data processing.

Core Features & Use Cases

  • Parallel Execution: Uses asyncio.gather and semaphores for efficient, rate-limited concurrent tasks.
  • FastAPI Integration: Implements async endpoints for high-performance web services.
  • Use Case: Fetch data from 100 different URLs simultaneously without blocking, or build a FastAPI endpoint that processes multiple items concurrently, achieving significant speedups.

Quick Start

Use the async-python-patterns skill to fetch data from a list of 10 URLs in parallel.

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 concurrent I/O operations in Python without blocking?▼

Concurrent I/O operations use asyncio to execute multiple tasks like HTTP requests or database queries simultaneously. AsyncIO allows tasks to yield control while waiting, enabling near-linear scaling for I/O-bound workloads without threading overhead.

Can I use async endpoints with FastAPI to handle multiple requests in parallel?▼

FastAPI supports async endpoints natively, allowing you to define coroutine handlers that process concurrent requests efficiently. Async endpoints scale I/O-bound operations by freeing worker threads while awaiting external services.

What's the best way to rate-limit parallel API calls in Python?▼

Asyncio semaphores control concurrency by limiting the number of tasks running simultaneously. Combined with asyncio.gather, semaphores enforce rate limits while executing parallel API calls, preventing overwhelming downstream services.

How do I handle errors when running multiple async tasks with asyncio.gather?▼

Asyncio.gather accepts a return_exceptions parameter to capture exceptions from individual coroutines without halting others. This enables robust error handling across concurrent I/O operations, allowing partial results and logging of failures.

Does aiohttp work with asyncio for making concurrent HTTP requests?▼

Aiohttp is an async HTTP client that integrates seamlessly with asyncio, enabling non-blocking HTTP requests across multiple URLs. It replaces blocking requests libraries in async workflows, maximizing concurrency for web scraping and API integration.

When should I use async patterns instead of threading for I/O tasks?▼

Async patterns outperform threading for I/O-bound workloads by eliminating context-switch overhead and simplifying concurrent code. Use asyncio when coordinating many simultaneous I/O operations like database queries or HTTP calls within a single process.