What is the Async Python Patterns skill used for?

It provides Claude with the specialized knowledge to implement asynchronous programming in Python, specifically for I/O-bound tasks where performance and concurrency are critical.

Is it useful for database management?

It provides patterns for async context managers, which are essential for properly opening, using, and closing asynchronous database connections.

Does it cover complex data processing workflows?

Yes, it includes advanced patterns like the Producer-Consumer model using asyncio Queues for managing complex background tasks and data pipelines.

Which Python frameworks are compatible with these patterns?

The patterns are compatible with any library using the standard asyncio library, including FastAPI, aiohttp, Sanic, and Tortoise ORM.

Can this skill help with rate limiting API calls?

Yes, it includes specific patterns using asyncio Semaphores to control the number of concurrent requests and avoid hitting API rate limits.

Async Python Patterns

Name: Async Python Patterns
Author: Microck

byMicrock

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API Development

Implements high-performance Python applications using asyncio, concurrent programming, and non-blocking I/O patterns.

About

This skill provides comprehensive guidance for mastering asynchronous Python, enabling developers to build scalable, high-performance systems. It covers fundamental and advanced patterns including coroutine management, concurrent execution with asyncio.gather, producer-consumer models, and rate limiting with semaphores. Whether building async web APIs with FastAPI, high-volume web scrapers, or real-time WebSocket servers, this skill ensures best practices for non-blocking I/O operations and efficient task scheduling within the event loop.

Key Features

Implementation of producer-consumer queues and rate-limited API calls
Async resource management with context managers and iterators
81 GitHub stars
Advanced concurrency patterns including gather(), tasks, and futures
Thread-safe synchronization primitives like async locks and semaphores
Robust error handling and timeout management for async workflows

Use Cases

Developing efficient web scrapers that process thousands of requests concurrently
Optimizing I/O-bound microservices and background task processors
Building high-concurrency web APIs with FastAPI, aiohttp, or Sanic

About

Key Features

Implementation of producer-consumer queues and rate-limited API calls
Async resource management with context managers and iterators
81 GitHub stars
Advanced concurrency patterns including gather(), tasks, and futures
Thread-safe synchronization primitives like async locks and semaphores
Robust error handling and timeout management for async workflows

Use Cases

Developing efficient web scrapers that process thousands of requests concurrently
Optimizing I/O-bound microservices and background task processors
Building high-concurrency web APIs with FastAPI, aiohttp, or Sanic