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Overview

Welcome to the ScrapeGraphAPI cookbook! Here you’ll find practical examples implemented as interactive Google Colab notebooks. Each example demonstrates different integration methods and use cases.
All examples are available as ready-to-use Google Colab notebooks - just click and start experimenting!

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Implementation Methods

Each example is available in multiple implementations:

SDK Direct Usage

Basic implementation using our official SDKs

LangChain Integration

Integration with LangChain for LLM workflows

LlamaIndex Integration

Using ScrapeGraph with LlamaIndex tools

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Example Projects

🏢 Company Information

Extract structured company data from websites

🌟 GitHub Trending

Monitor trending repositories and developers

📰 Wired Articles

Extract news articles and content

🏠 Homes Listings

Scrape real estate property data

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Advanced Examples

🔬 Research Agent with Tavily

Build a sophisticated research agent combining ScrapeGraph, LangGraph, and Tavily Search

💬 Chat with Webpage

Create a RAG chatbot using ScrapeGraph, Burr, and LanceDB

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Getting Started

  1. Choose an example that matches your use case
  2. Open the Colab notebook for your preferred implementation method
  3. Follow the step-by-step instructions
  4. Experiment and adapt the code for your needs
Make sure to have your ScrapeGraphAI API key ready. Get one from the dashboard if you haven’t already.

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Additional Resources

For comprehensive guidance on writing effective prompts for SmartScraper and SearchScraper, check out our Prompt Engineering Guide. This detailed tutorial covers best practices, common pitfalls, advanced techniques, and real-world examples to help you master the art of crafting prompts that deliver precise, structured results every time. For more code examples and implementations, visit our GitHub SDK Examples Repository where you’ll find additional Python examples and use cases.