How can I optimize performance in asynchronous Python applications?

How can I optimize performance in asynchronous Python applications?

To optimize performance in asynchronous Python, consider using libraries like asyncio, aiohttp, and optimizing I/O operations.

What are some common pitfalls to avoid when using asyncio?

Common pitfalls include blocking the event loop, not using await properly, and excessive context switching.

Can you give me an example of using asyncio for web scraping?

Sure! You can use aiohttp to make concurrent requests. Here's a simple example:

import aiohttp
import asyncio

async def fetch(url):
    async with aiohttp.ClientSession() as session:
        async with session.get(url) as response:
            return await response.text()

async def main(urls):
    tasks = [fetch(url) for url in urls]
    return await asyncio.gather(*tasks)

urls = ['http://example.com', 'http://example.org']
asyncio.run(main(urls))

How does using async/await improve performance compared to threading?

Async/await allows for non-blocking I/O operations, which can lead to better performance in I/O-bound tasks compared to threading, which can be limited by the Global Interpreter Lock (GIL).