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Deep dives into web data infrastructure, extraction techniques, and the future of structured data at scale.
155 articles
TL;DR: The best web scraping courses depend on your language, level, and target use case. This guide compares five paid picks across Udemy, Coursera, DataCamp, and Packt, points to free supplements like official docs, and shows how to bridge from finishing a course to running production scrapers.
TL;DR: If you're working out how to scrape Realtor.com cleanly, three things matter most: stable selectors that survive their hashed class names, a request layer that survives Realtor's anti-bot stack, and code that walks both list pages and detail pages. This guide is the full Python build, with anti-block tactics and LLM-ready exports.
TL;DR: This guide walks through web scraping Booking.com end to end in Python: pulling search listings, hotel pages, nightly prices, and guest reviews. You get two complementary methods: a Selenium Wire workflow for JS-rendered pages and a faster path that calls Booking.com's internal /dml/graphql endpoint directly, plus an anti-block playbook, currency handling, and a workaround for the roughly 1,000-result paging cap.
TL;DR: Idealista is the largest property marketplace in Spain, Italy, and Portugal, but it sits behind a serious anti-bot stack that blocks naive scrapers fast. This guide walks you through how to scrape data from Idealista end-to-end in Python, covering site mapping, Selenium with undetected-chromedriver, DataDome handling, proxy rotation, and clean exports, with production hardening competitors usually skip.
TL;DR: This guide walks you through building a complete Yelp scraper in Python, covering search results, business details, and reviews with working code. You'll also learn how to handle anti-bot protections, export data to CSV or JSON, and feed scraped reviews into an LLM for sentiment analysis, something no other Yelp scraping tutorial covers.
TL;DR: A web scraping project fails on planning long before it fails on code. These ten scraping questions walk you through legality, API alternatives, anti-bot defenses, cost, refresh cadence, data quality, and governance, so you scope the work, pick the right stack, and avoid the failure modes that quietly kill scrapers in production.
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