How I Stopped Regexing HTML Tables and Started Using AI for Data Extraction

Short summary

Developer shares how they replaced regex and custom parsers with AI-powered HTML extraction using LLMs to handle inconsistent real-world markup through semantic understanding instead of fragile pattern-matching. The approach excels with messy, unpredictably-structured data but requires weighing costs: $0.01–$0.05 per page, 1–3 second latency, risk of AI hallucinations, and API rate limits. Sweet spot: moderate-volume scraping where layout varies wildly across sources and manual parser maintenance is too expensive.

• •Replaced regex/custom parsers with LLM-based HTML extraction to handle inconsistent markup semantically
• •Trade-offs: $0.01–$0.05/page cost, 1–3s latency, hallucination risk, requires validation layer
• •Best for moderate-volume scraping with unpredictable structure; avoid for clean HTML or massive scale

Generated with AI, which can make mistakes.