A robust Python web scraper that collects football match data from Yallakora for a specified date. The program extracts comprehensive match information including team names, scores, match status, time, round, and championship. It saves the data in a structured CSV format for easy analysis.

• Date-specific football match data scraping from Yallakora 🏆⚽
• Comprehensive match metrics including:
  • Team names
  • Match scores
  • Match status
  • Match time
  • Round number
  • Championship name
• Robust error handling
• Clean CSV output format
• User-agent handling for reliable scraping

1. Set up your environment:
   Make sure you have Python installed on your system.

2. Install dependencies:
   Run the following command to install the necessary packages:

   pip install -r requirements.txt

3. Run the Scraper:
   Execute the script:

   python main.py

   The script will:

   • Prompt you to enter a date (MM/DD/YYYY format)
   • Fetch the latest football match data for that date from Yallakora
   • Process the information
   • Generate a CSV file (football_fixtures.csv)

4. View the Results: Open the generated football_fixtures.csv file in Excel:

   • Set the page layout from right to left to properly display the Arabic data
   • You may need to adjust column widths for optimal viewing

Note: The table above is displayed from right to left to match the Arabic text direction.

def fetch_page_content(url):
    """Fetches the HTML content of a given URL."""
    headers = {
        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36"
    }
    try:
        page = requests.get(url, headers=headers, timeout=5)
        page.raise_for_status()
        return page.content
    except requests.exceptions.HTTPError as http_error:
        print(f"HTTP error occurred: {http_error}")
    # ... more error handling

• Add command-line arguments for custom output file names
• Implement data comparison with historical records
• Add data visualization capabilities
• Create a simple web interface using Flask
• Add automated scheduling for regular data updates
• Implement data validation and cleaning
• Add support for different output formats (JSON, Excel)
• Include data visualization exports

Khaled Soudy

football-fixtures-scraper/
├── main.py          # Main script with scraping logic
├── requirements.txt # Project dependencies
├── .gitignore       # Git ignore file
└── README.md        # Project documentation

The project relies on the following Python packages:

• beautifulsoup4==4.12.3
• certifi==2024.8.30
• charset-normalizer==3.4.0
• idna==3.10
• lxml==5.3.0
• requests==2.32.3
• soupsieve==2.6
• tabulate==0.9.0
• urllib3==2.2.3

Please ensure you follow Yallakora's robots.txt and terms of service when using this scraper. Be respectful of the website's resources and implement appropriate delays between requests if needed.

If you encounter any issues or have questions, please open an issue in the GitHub repository.

Contributions are welcome! Feel free to submit pull requests or open issues to improve the project.

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

Stay updated with the latest football fixtures from Yallakora! ⚽📊