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Datahut Blog
A blog for people & companies looking to make a big business impact with data acquired using web scraping and web crawling. Learn the best practices, business use cases, legality, and how you can do your job better with data.
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The Short Shelf Life of Open Source Web Scraping Tools (And Why Scale Breaks Them)
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
tony56024
Dec 10, 20259 min read
Top 10 GDPR Fines in 2018 to 2025: A Data-Driven Analysis
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
Navin Saif
Nov 11, 20257 min read
Web Scraping Without Getting Blocked Using curl-cffi
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.
tony56024
Oct 17, 20257 min read
How to Scrape Product Data from Amazon US?
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
Shahana farvin
Oct 9, 202524 min read
Data for Fashion Retailers: The Four Problems Nobody Talks About (But Everyone Feels)
As fashion retailers look to 2026, they are adjusting with fundamentally new reality. The US tariffs have forced brands and their suppliers to rapidly adjust. Major brands like Nike, Hermès , and Ralph Lauren have already indicated or implemented price increases. The same thing happens with the consumers as well - they’re reprioritising what to spend and where. According to a Fashion–McKinsey State of Fashion Executive Survey This year, 46 percent fashion executives said th
Tony Paul
1 hour ago7 min read
Amazon vs Argos Smartwatch Pricing Analysis: What Ecommerce Brands Can Learn from Marketplace Data (2026)
What Marketplace Structure Reveals About Competitive Strategy Most brands focus on price analysis, while few examine the underlying marketplace structure. Smartwatch brands frequently monitor competitor pricing ; however, significantly fewer assess how marketplace structure influences these prices. However, marketplace structure plays a critical role. The economic logic of each platform is usually reflected through their Price dispersion, discount frequency, segmentation pat
Aarathi J
1 day ago4 min read
Why AI Web Scraping Fails :At Enterprise Scale
People often see AI web scraping as fast and simple. But when it comes to large-scale enterprise use cases, relying just on large language models (LLMs) introduces new risks that you may not notice. When large language models (LLMs) became common, many believed that web scraping problem had finally been solved. The idea was logical at first sight. If AI could read and understand language, it should also handle web pages, extract data, and adapt as sites change, which are som
Tony Paul
2 days ago4 min read
Scraping Condo Listings from Homes.com Using Playwright: A Complete Engineering Guide
Is buying a condo in California really more expensive than owning one in New York, or does the story change once the numbers are laid out side by side? To explore this question, real condo listings were carefully scraped from Homes.com , with California and New York collected separately to keep the comparison clear and fair, using publicly available listing pages such as the California condos section on Homes. Rather than relying on assumptions or headlines, this approach
Anusha P O
Feb 1219 min read
Top 10 Web Scraping Companies in 2026: The Ultimate Comparison Guide
Web data is now essential for analytics, AI, pricing, and business decisions. Still, data professionals spend almost 80% of their time on tasks like finding, cleaning, validating, and combining data from different systems instead of actual analysis. In a 40-hour workweek, that means each person spends 32 hours on tasks that don’t involve actual analysis every week. For a whole data team, this inefficiency adds up and leads to: Slower analytics and AI workflows Higher enginee
Tony Paul
Feb 611 min read
How to Scrape Macy’s Sale Section Using Python and Playwright
When you think of Macy’s, it is not just a department store—it is an American retail legacy established in 1858. What began as a humble store located in Manhattan has become one of the largest and arguably best-known retail department stores in America. Macy's currently operates in hundreds of locations across the mainland United States, including its world-renowned flagship store located at Herald Square, New York City— a retail space spanning over a million square feet. Mac
Anusha P O
Jan 2334 min read
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