Learn the core definitions of web crawling for discovering URLs and web scraping for extracting information from those pages.
Discover key applications for web scraping, including training AI models, lead generation, and competitive price analysis.
Understand the legal gray areas of web scraping by examining the landmark HiQ vs. LinkedIn lawsuit and its implications.
Follow key politeness policies by respecting robots.txt, terms of service, crawl delays, user agents, sitemaps, and off-peak visit times.
Prepare for scraping by understanding data privacy laws like GDPR and DMCA, and mastering prerequisites like HTTP, HTML, and CSS selectors.
Learn strategies for handling obstacles like IP blocks, CAPTCHAs, and scraper maintenance, and understand the role of AI-powered scraping.
Decide whether to use internal APIs, external service APIs, or build your own scraper with Python libraries and no-code platforms.
Explore the capabilities of key Python libraries, including Beautiful Soup for parsing, Scrapy for large projects, and Selenium or Playwright for browser automation.
Follow a step-by-step guide to building a scraper, from selecting a webpage and checking permissions to choosing a tool and processing the data.
Watch a live coding example of how to extract blog titles, URLs, and content using both Beautiful Soup for static pages and Selenium for automation.
Review the complete workflow, from checking legality and analyzing the target website to choosing the right tool for static or dynamic content.
Jobs that call for the skills explored in this talk.