👀 Views: 0 💬 Answers: 1 📅 Created: 2025-09-12

web-scraping python-3.x asyncio beautifulsoup seo Python

I'm trying to configure I've looked through the documentation and I'm still confused about After trying multiple solutions online, I still can't figure this out..... Currently developing a web scraping tool to gather SEO data from various websites, I've run into performance issues that are affecting the speed and efficiency of the scraping process. Using libraries like `requests` and `BeautifulSoup`, the initial implementation works, but it tends to be slow, especially when scraping multiple pages. Here's a snippet of my current approach: ```python import requests from bs4 import BeautifulSoup urls = ['http://example.com/page1', 'http://example.com/page2', 'http://example.com/page3'] for url in urls: response = requests.get(url) soup = BeautifulSoup(response.text, 'html.parser') title = soup.find('title').get_text() print(title) ``` The code works fine, but scraping three pages can take a noticeable amount of time. I've also looked into using `asyncio` and `aiohttp` to perform asynchronous requests, but the learning curve has been a bit steep for me. I tried this alternative approach using `aiohttp`: ```python import aiohttp import asyncio from bs4 import BeautifulSoup 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 = ['http://example.com/page1', 'http://example.com/page2', 'http://example.com/page3'] tasks = [fetch(url) for url in urls] pages = await asyncio.gather(*tasks) for page in pages: soup = BeautifulSoup(page, 'html.parser') title = soup.find('title').get_text() print(title) asyncio.run(main()) ``` While this is certainly faster, I’m still unsure about best practices, like how to manage rate limits when scraping or handling potential errors in a robust manner. Would using a library like `Scrapy` for this project make my life easier? Are there any tips for optimizing HTTP requests or handling large datasets that are relevant for SEO scraping? Any insights would be greatly appreciated! Is there a better approach? For context: I'm using Python on Ubuntu. I'm using Python latest in this project. What am I doing wrong? This issue appeared after updating to Python LTS. Am I approaching this the right way? I'm open to any suggestions. My development environment is Windows 11. I'd love to hear your thoughts on this.