Understanding Async Python - Example Blog
Author: Jane Smith
Description: A deep dive into asyncio patterns and best practices.

# Understanding Async Python

By Jane Smith February 20, 2025

Asynchronous programming in Python has evolved significantly since the introduction of asyncio in Python 3.4. Today, async/await syntax makes it far more readable.

## The Event Loop

At the core of Python's async model is the event loop. It schedules and runs coroutines, handles I/O events, and manages callbacks. Understanding this is fundamental to writing effective async code.

## Common Patterns

Several patterns have emerged as best practices: gather for concurrent tasks, TaskGroup for structured concurrency, and Semaphore for rate limiting.

    import asyncio

    async def fetch_all(urls):
        async with asyncio.TaskGroup() as tg:
            tasks = [tg.create_task(fetch(url)) for url in urls]
        return [t.result() for t in tasks]

This pattern ensures all tasks complete or all are cancelled on failure, providing clean error semantics.