Vanilla JS Web Scraper — Mstephen190 Vanilla Js Scraper

    Extract the web using familiar JavaScript methods! Extracts websites using raw HTTP requests, parses the HTML with the JSDOM package, and extracts data from the pages using Node.js code. Supports both recursive extracting and lists of URLs. This tool is a non jQuery alternative to CheerioScraper.

    1 credits per request
    ~30s
    10 runs
    Features
    Lightweight DOM Parsing
    JSON/CSV Export
    API Access
    Scalable Automation
    Use Cases
    Data Extraction
    Developer Tools

    What This Tool Does

    Vanilla JS Data Extractor — Extract the web using familiar JavaScript methods! Extracts websites using raw HTTP requests, parses the HTML with the JSDOM package, and extracts data from the pages using Node.js code. Supports both recursive extracting and lists of URLs. This tool is a non jQuery alternative to CheerioScraper.

    Use Cases

    • Data Extraction
    • Developer Tools

    Data Fields

    The output fields depend on the source data and tool configuration. Common fields include:

    FieldTypeDescription
    idstringUnique identifier of the result item
    urlstringSource URL
    titlestringTitle or name
    contentstringMain text content
    timestampstringDate/time in ISO 8601 format
    metadataobjectAdditional fields specific to this tool

    Example Request

    {
     "proxy": {
     "useApifyProxy": false
     },
     "requests": [],
     "pseudoUrls": [],
     "linkSelector": "https://example.com",
     "pageFunction": 1,
     "preNavigationHooks": "example",
     "postNavigationHooks": "example"
    }
    

    Example Response

    {
     "id": "item-001",
     "url": "https://example.com/page",
     "title": "Example Result",
     "content": "Extracted content from the source.",
     "timestamp": "2024-01-15T10:30:00.000Z",
     "metadata": {}
    }
    

    Limits and Tips

    • Processing time varies by input size and source complexity.
    • Results are returned as a JSON array. An empty array means no data matched the input.
    • Check the input schema for required and optional parameters before running.
    • For large result sets, use the max results parameter to control cost.

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