Datahut Blog

Picture this: Your team builds a beautiful internal scraping platform using Open Source libraries. It scrapes 20 e-commerce sites, powers dashboards, feeds pricing models… and becomes part of your company’s heartbeat. You scale from 10K → 100K → 1M pages per day . Suddenly: your prices stop updating your stock signals lag your competitor feeds look “too perfect” your alerts never fire your data scientists complain about anomalies and your engineering team starts firefighting

Introduction Yes, it’s over — the era of unchecked data collection, silent tracking, and unaccountable digital practices.  The General Data Protection Regulation (GDPR) ended it for good, redefining how organizations collect, process, and protect the personal data of European Union citizens. A decade ago, user information was traded, tracked, and monetized with little scrutiny; privacy was an afterthought, not a business priority. That changed in 2018 with the enforcement of

Learn how to perform web scraping without getting blocked using curl-cffi. Discover how this Python library helps you bypass anti-bot systems, mimic real browsers, and ensure smoother, more reliable data extraction.

Introduction Ever tried shopping for vlogging equipment on Amazon? It's overwhelming. You've got thousands of microphones, cameras, and tripods to choose from, and manually comparing them all would take forever. That's exactly why I built this web scraping system - to automatically collect and organize all that product data so you can actually make informed decisions. This project shows you how to build a complete two-phase scraping system that systematically extracts vloggin