Web Scraper Project

This tool offers a rule-driven web scraping workflow for SEO and market analytics. It accepts a target URL and an extraction_rules map that links fields to CSS selectors or XPath expressions, with optional attributes. It returns structured records in JSON or CSV to support indexing, audits, and competitive intelligence. Conceptually, the process fetches pages, applies selectors to extract text or attribute values, normalizes whitespace, and aggregates results. It supports pagination by following a configured next-page selector and respects rate limits to minimize impact on target sites. Users include SEO analysts, data engineers, and product marketers who need repeatable data across many pages. The tool differentiates itself with a strict rule-based extraction model, robust error handling, and straightforward exports, avoiding UI scripting requirements while delivering reliable data pipelines for downstream analysis. Core features include CSS/XPath selector support, optional attribute extraction, data normalization, deduplication by URL, and export options. Common use cases are price scraping, meta tag auditing, title and heading extraction, and mapping structured content for SERP research.