block-detector

You can detect content blocks on a web page using Puppeteer by applying semantic analysis, bounding box capture, and CSS selector generation to identify discrete page elements. This process catalogs distinct sections by analyzing semantic sections, class-based patterns, and CMS-specific data attributes.

The best way to analyze web page structure for content migration is to automate browser control to identify semantic sections and generate stable CSS selectors. This catalogs the content hierarchy by capturing bounding boxes and detecting class-based patterns within the DOM.

CSS selector generation works by analyzing the DOM during browser automation to create stable references for each detected content block. It identifies semantic sections and CMS-specific data attributes, ensuring each discrete page element has a reliable selector for easy referencing.

Yes, you need Puppeteer to identify content blocks because it provides the required browser control and DOM analysis capabilities. This dependency allows the tool to perform bounding box capture and semantic analysis to accurately catalog distinct page elements.

Yes, you can use this approach to extract a competitor's hero sections, feature grids, and call-to-action blocks. By analyzing web page structure and detecting semantic sections, it catalogs page composition to help you understand their layout and content hierarchy.

A limitation of using bounding box capture for web scraping is that it relies on visual rendering through Puppeteer, which may miss dynamically loaded content or fail if page elements lack distinct semantic sections, class-based patterns, or CMS-specific data attributes.