Simplescraper

Point-and-click interface to select and identify HTML elements on a webpage without writing code. Users highlight the data they want to extract directly in the browser, and the system learns the pattern.

Extracts structured data from static HTML websites by parsing the DOM and converting selected elements into organized, machine-readable format. Works best with server-rendered content that doesn't require JavaScript execution.

Automatically retries failed scraping jobs and handles common errors like timeouts, connection failures, and blocked requests. Provides error logs and status reporting.

Filters extracted data based on conditions and applies transformations like string manipulation, calculations, or conditional logic. Enables basic data processing without external tools.

Simulates user interactions like clicking buttons, filling forms, and scrolling to access data that requires user actions. Limited JavaScript execution for basic interactions.

Tracks scraper performance, data collection metrics, API usage, and provides dashboards showing success rates, data volume, and execution history.

Enables multiple team members to access, edit, and share scrapers and APIs. Includes permission management and collaborative configuration.

Automatically converts scraped web data into queryable REST APIs without manual backend development. Generated APIs include standard HTTP endpoints for accessing the extracted data.

Automatically runs web scraping jobs on a defined schedule (hourly, daily, weekly, etc.) without manual intervention. Maintains historical data and tracks changes over time.

Sends scraped data to external systems via webhooks when scraping jobs complete. Enables real-time integration with other applications, databases, or notification systems.

Learns extraction patterns from user selections and applies them to similar pages automatically. Reduces repetitive configuration by recognizing consistent data structures across multiple pages.

Automatically removes duplicate records and cleans extracted data by standardizing formats, removing empty fields, and handling common data quality issues.

Pre-built scraper templates for popular websites and data types that users can clone and customize. Reduces setup time for common scraping scenarios.

Exports extracted data in multiple formats including JSON, CSV, Excel, and direct database connections. Enables compatibility with various downstream tools and workflows.

Automatically follows pagination links and collects data across multiple pages. Supports common pagination patterns (next buttons, page numbers, infinite scroll simulation).