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Deep dives into web data infrastructure, extraction techniques, and the future of structured data at scale.
169 articles
TL;DR: Scrapy Splash pairs Scrapy's fast crawling engine with the Splash headless browser to render JavaScript-heavy pages. This scrapy splash tutorial walks you through Docker setup, Scrapy project configuration, SplashRequest basics, Lua scripts for scrolling and clicking, proxy integration, and fixing the most common errors you will encounter.
TL;DR: Amazon product pages are packed with valuable data (prices, ratings, reviews, ASINs), but extracting it reliably requires more than a basic HTTP request. This guide walks you through building a Python scraper with Requests and BeautifulSoup, handling pagination and anti-bot defenses, exporting to CSV or JSON, and feeding the results into LLM workflows. You will also learn when to use a scraping API instead of rolling your own solution.
TL;DR: Alternative data scraping uses web collection techniques to gather non-traditional datasets (product pricing, sentiment, job postings, regulatory filings) that reveal market signals before they appear in earnings reports. This guide walks you through the highest-value data sources, how to build financial-grade pipelines, data quality validation, and the compliance guardrails you need to stay on the right side of the law.
TL;DR: Financial data is the collection of quantitative records (income, expenses, assets, liabilities, cash flow) that organizations and individuals use to make informed economic decisions. This guide breaks down the four core financial statements, compares traditional and alternative data sources, walks through modern collection methods, and covers the tools professionals rely on for analysis.
TL;DR: Job scraping tools range from lightweight API services and open-source browser automation to AI-powered extractors and visual no-code platforms. This guide compares the best job scraping tools across Google Jobs, Indeed, Monster, Upwork, and freelance marketplaces, then walks you through building a reliable pipeline with deduplication, scheduling, and anti-bot handling so you can start collecting clean job data at scale.
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