Technical tutorials covering web scraping from first principles to production scale: HTTP clients, JavaScript rendering, session management, and automatic website compatibility.
15 articles
A practical guide to evaluating scraping APIs — covering pricing, anti‑bot handling, SDKs, and more — with concrete AlterLab examples and links to get you started fast.
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Agentic web browsing gives AI agents the ability to navigate sites, make decisions, and extract data without human intervention. Learn how it works, why it matters, and how to build it responsibly.
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Learn how tool use enables AI agents to fetch live data from the web, turning static models into dynamic research assistants that can scrape, monitor, and act on real‑time information.
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Learn how to safely feed real-time web data into LLMs, avoid hallucinations, and implement reliable grounding pipelines using AlterLab's scraping API.
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This week's AlterLab engineering updates resolve SDK response drift, unblock CI migrations, enhance session binding security, and reduce WAF false positives for more reliable scraping pipelines.
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A 2026 guide showing how to scrape stack overflow with Python, Node.js, and AlterLab, covering anti‑bot hurdles, pricing tiers, and best practices for clean extraction.
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Compare rotating datacenter and residential proxies for web scraping. Learn when to use each IP type based on bot protection, speed, and cost.
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Learn how to replace brittle CSS selectors with LLM-powered zero-shot JSON extraction to build resilient, autonomous web scraping pipelines that survive UI changes.
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Learn how to reliably handle infinite scroll, cursor-based pagination, and dynamic rendering for autonomous AI web scraping agents using headless browsers.
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Build resilient e-commerce scraping pipelines for AI agents. Learn how to combine headless browser rendering, Playwright stealth, and LLM-powered JSON extraction.
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Learn how to inject session cookies and use headless browsers to reliably extract authenticated web data for your internal RAG and LLM pipelines.
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Learn how to build an n8n pipeline that extracts web data and converts it into token-efficient Markdown for LLM ingestion, minimizing context window costs.
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