Web Scraping AI Tool

Purpose & User Intent: This tool automates the extraction of structured data from public web pages using AI-assisted selectors. Target users include data analysts, growth/SEO teams, market researchers, and developers who need repeatable, scalable scraping workflows without writing bespoke scrapers. Use it to collect product details, pricing, reviews, or metadata from multiple sites, on-demand or as part of a crawl, while preserving data quality and provenance. Example: fetch product name, price, rating from a catalog page and export to CSV.

Core Logic & Features: Required features include input of a target URL, extraction rules defined via CSS selectors or XPath/JSON-based rules, rendering or waiting for dynamic content with a headless browser, and structured data export in CSV, JSON, or JSONL. Optional features include proxies and rotation, authentication support, pagination handling, rate limiting, scheduling, deduplication, data type casting, schema mapping, and robust error reporting. The tool applies rules to each matched element, normalizes values, and accumulates records into a structured dataset with run metadata.

Inputs & Outputs: Inputs comprise target_url, depth, extraction_rules, output_format, output_destination, rate_limit, proxies, and optional authentication. Outputs are data_records, run_metadata, and an error_log.

Algorithms & Calculations: HTML parsing and DOM traversal apply selectors to locate values, with fallbacks for multiple matches. Data types are cast to string/number/date as appropriate. Dynamic pages use a headless browser, with network idle waits and simple pagination. Rate limiting and parallelism govern scheduling. Deduplication may compare primary keys across records.