Web Scraping with Python: Complete Guide

# Web Scraping with Python: Complete Guide Web scraping is a valuable skill for data collection and automation. Here's a comprehensive guide. ## Tools Overview ### BeautifulSoup Best for: Simple, static pages ```python from bs4 import BeautifulSoup import requests response = requests.get(url) soup = BeautifulSoup(response.text, 'html.parser') ``` ### Selenium Best for: Dynamic content, JavaScript-heavy sites Automates a real browser to interact with pages. ### Scrapy Best for: Large-scale scraping with built-in features for handling requests, parsing, and storage. ## Handling Dynamic Content ### Wait for Elements Use explicit waits in Selenium to handle content that loads dynamically. ### API Inspection Check Network tab for data APIs - often easier than scraping HTML. ## Avoiding Detection ### Rotate User Agents Use different browser identifiers. ### Respect robots.txt Check what's allowed to scrape. ### Rate Limiting Don't overwhelm servers. ### Proxy Rotation Use different IP addresses. ## Best Practices 1. **Cache responses**: Don't re-scrape unnecessarily 2. **Handle errors**: Websites change frequently 3. **Structure data**: Use proper data models 4. **Legal compliance**: Respect terms of service ## Conclusion Web scraping is powerful but requires responsibility. Always scrape ethically and legally.