Selector-based scraping extracts data from web pages using rules that point to HTML elements.
Common selector methods include:
- CSS selectors
- XPath
- Regular expressions
For example, a scraper can extract every page title using the h1 selector or every product price using a price class from the HTML.
When selector-based scraping works well
Use selector-based scraping when:
- Pages share the same template
- The HTML structure is stable
- You know which element contains each value
- You need fast extraction from many similar pages
It works well for product grids, directories, tables, and pages with repeated layouts.
Limits of selector-based scraping
Selector-based scraping can break when:
- The website changes its HTML classes
- Content loads with JavaScript
- Pages use different layouts
- The data requires interpretation
- Values are mixed inside long text blocks
🔍 Practical rule
Selectors are precise but fragile. AI scraping is more flexible but needs clear instructions and result checks.
Selector scraping vs AI scraping
AI web scraping reads page content and extracts values from natural language instructions.
Selector-based scraping reads page structure and extracts values from fixed rules.
Datablist supports both workflows. Use the Smart Scraper when you know the CSS selector or regex. Use the Website AI Scraper when the page structure varies or the task needs interpretation.