🕸️ Enhanced Web Data Extractor 🔍

A powerful and user-friendly web scraping tool built with Python and Streamlit.

🌟 Features

• 🚀 Asynchronous web scraping for faster data collection
• 🌐 Depth-limited crawling to control the scope of extraction
• 🔑 Keyword filtering to focus on relevant content
• 📊 Multiple export formats: CSV, Markdown, JSON, and XML
• 🖥️ Interactive Streamlit UI for easy operation
• 🛡️ Rate limiting to respect server resources
• 📈 Real-time progress tracking

🛠️ Installation

1. Clone this repository:

   git clone https://github.com/ZeroXClem/enhanced-web-data-extractor.git
   cd enhanced-web-data-extractor
   

2. Create a virtual environment (optional but recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows, use `venv\Scripts\activate`
   

3. Install the required packages:

   pip install -r requirements.txt
   

🚀 Usage

1. Run the Streamlit app:

   streamlit run main.py
   

2. Open your web browser and navigate to the URL provided by Streamlit (usually http://localhost:8501).

3. In the Streamlit interface:

   • Enter the base URL you want to scrape
   • Set the maximum number of pages to scrape (1-100)
   • Set the maximum depth for crawling (1-10)
   • (Optional) Enter keywords to filter content
   • Set the rate limit (requests per second)
   • Choose the desired export format(s)
   • Click "Start Scraping"

4. Monitor the progress and download the extracted data when complete.

🎯 Use Cases

• 📚 Research: Gather data from academic websites or online journals
• 💼 Business Intelligence: Collect product information from e-commerce sites
• 📰 News Aggregation: Compile articles from various news sources
• 🏢 Competitive Analysis: Extract data from competitor websites
• 📊 Market Research: Gather consumer reviews and opinions

⚠️ Important Notes

• This tool is for educational purposes only.
• Always respect websites' terms of service and robots.txt files.
• Be mindful of rate limiting and don't overload servers with requests.
• Some websites may have measures in place to prevent scraping.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🤝 Contributing

Contributions, issues, and feature requests are welcome! Feel free to check issues page.

👨‍💻 Author

ZeroXClem

• GitHub: @ZeroXClem
• LinkedIn: @ZeroXClem LinkedIn

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Happy Scraping! 🎉🕷️