DataScraperMap

Project Overview

DataScraperMap is an educational web application that demonstrates the power of data scraping, API integration, and interactive data visualization. This project fetches real-time news data from various countries using the NewsAPI and displays it on an interactive world map.

Hackable Playground

You have full permission to make any changes you want, don't be afraid to push the boundaries of your imagination.

Key Features

• Fetches top headlines from multiple countries (US, Brazil, China, Russia, UK)
• Categorizes news articles (business, entertainment, general, health, science, sports, technology)
• Displays news data on an interactive map using Leaflet.js
• Implements clustering for better data visualization
• Provides a user-friendly interface for exploring global news trends

Technologies Used

• Backend: Python, Flask
• Frontend: HTML, CSS, JavaScript
• Map Visualization: Leaflet.js
• Data Source: NewsAPI
• Database: SQLite (for storing scraped data)

Educational Aspects

This project serves as a practical example of:

1. API Integration: Learn how to work with RESTful APIs and handle JSON responses.
2. Data Scraping Ethics: Understand the importance of respecting rate limits and terms of service when scraping data.
3. Data Processing: See how raw API data is transformed and categorized for meaningful visualization.
4. Web Development: Gain insights into building a full-stack web application using Flask.
5. Interactive Data Visualization: Learn how to use Leaflet.js to create engaging map-based visualizations.
6. Database Management: Understand basic database operations for storing and retrieving scraped data.

Setup and Installation

1. Clone the repository:

   git clone https://github.com/AXRoux/data_scraping_map_demo.git
   cd data_scraping_map_demo
   

2. Set up a virtual environment:

   For Windows
   
   python -m venv venv
   venv\Scripts\activate.bat or .\venv\Scripts\Activate.ps1
   

   For Linux
   
   python -m venv venv
   source venv/bin/activate or . venv/bin/activate
   

3. Install required packages:

   pip install -r requirements.txt
   

4. Set up your NewsAPI key:

   • Sign up for a free API key at NewsAPI
   • Create a .env file in the project root and add your API key:

     Setup api key in scraper.py
     

5. Initialize the database:

   python init_db.py
   

6. Run the application:

   flask run or python run.py
   

7. Open a web browser and navigate to http://localhost:5000

Project Structure

• app/: Main application directory
  • models.py: Database models
  • routes.py: Flask routes
  • scraper/: Contains scraping logic
    • scraper.py: NewsAPI integration and data fetching
  • static/: Static files (CSS, JS)
  • templates/: HTML templates
• config.py: Configuration settings
• run.py: Application entry point

How It Works

1. Data Scraping: The application uses NewsAPI to fetch top headlines from specified countries and categories.
2. Data Processing: Fetched news articles are processed and stored in the database.
3. Data Visualization: The frontend retrieves the stored data and displays it on an interactive map.
4. User Interaction: Users can click on map markers to view news headlines and details for each location.

Customization

• To add more countries, update the countries_and_languages dictionary in app/scraper/scraper.py.
• Modify the categories list in app/scraper/scraper.py to change news categories.
• Adjust map settings in app/static/js/map.js to customize the map view.

Ethical Considerations

• Always respect the API's rate limits and terms of service.
• Be mindful of the data you're scraping and how you're using it.
• Consider the impact of your scraping on the source website's servers.

Future Enhancements

• Implement user authentication for personalized news feeds.
• Add sentiment analysis to categorize news articles by tone.
• Integrate multiple news sources for a more comprehensive view.
• Implement real-time updates using WebSockets.

Contributing

Contributions to improve DataScraperMap are welcome! Please fork the repository and submit a pull request with your changes.

License

This project is open-source and available under the MIT License.