I have a collection of websites that hold the textual information I need consolidated into a single, well-structured dataset. Rather than copying the material manually, I want the process handled through reliable web-scraping tools so the capture is fast, consistent, and repeatable. Your task is straightforward: • Build (or adapt) a scraper that targets the pages I specify, pulls only the relevant text, and skips ads, navigation links, and other noise. • Deliver the harvested content in a clean CSV or Excel file with clear column headings; if you prefer a database export, let me know and we can adjust. • Include the finished script or notebook so I can rerun the extraction later. Accuracy and formatting matter more to me than sheer speed, so please allow time for basic validation before handing over the files. If you normally work with Python (BeautifulSoup, Scrapy, Selenium) or similar tooling, that’s perfect, but I’m open to alternative stacks as long as the output meets the same standard. When you reply, briefly outline: 1. The scraping approach and libraries you’d use 2. Any anti-blocking measures you apply for public sites 3. A realistic timeframe to capture, clean, and hand back the data I’m ready to start as soon as I find the right fit and will be available for quick clarifications along the way.