Chess.com Stats

Chess.com_stats is a Python-based project designed to scrape and display user statistics from Chess.com. It utilizes Selenium for web scraping and Streamlit for a simple and interactive user interface. The project currently displays key player statistics, including ratings, number of games played, and highest ratings for different game modes (Rapid, Blitz, Bullet).

Features

• Web Scraping with Selenium: Scrapes data from Chess.com using the Chrome WebDriver.
• Streamlit UI: Provides a clean and interactive interface for displaying statistics.
• Basic Statistics: Displays key metrics:
  • Current rating across different game modes (Rapid, Blitz, Bullet)
  • Number of games played
  • Highest rating achieved
• Future Enhancements:
  • Data visualizations for performance tracking
  • Deeper analytics such as game-specific insights

Project Structure

Chess.com_stats/

├── .ipynb_checkpoints/ # Jupyter notebook checkpoints
├── README.md # Project documentation
├── chromedriver.exe # Chrome WebDriver for Selenium
├── main.py # Main script with Streamlit UI
└── scraper.ipynb # Jupyter notebook for scraping stats (Rapid, Blitz, Bullet)

Explanation of Files

• main.py: The Streamlit app that displays the stats in an interactive UI.
• scraper.ipynb: Jupyter notebook for scraping player stats (currently supports Rapid, Blitz, and Bullet modes).
• chromedriver.exe: Chrome WebDriver for Selenium scraping.
• .ipynb_checkpoints: Automatically generated Jupyter notebook checkpoints.

Installation

1. Clone the Repository:

   git clone https://github.com/dnp314/Chess.com_stats.git

2. Navigate to the Project Directory:

   cd Chess.com_stats

3. Set Up Dependencies:

   • Ensure Python 3.12.5 is installed.
   • Manually install the required packages for Selenium and Streamlit:

   pip install selenium streamlit

4. Set Up WebDriver:

   • Download and set up the Chrome WebDriver according to your Chrome version, and ensure it's added to your system's PATH or placed in the project directory.

Usage

1. Scraping Data: Run the scraper.ipynb Jupyter notebook to scrape player statistics for Rapid, Blitz, and Bullet.

2. Displaying Statistics: Launch the Streamlit UI to display the scraped data: ```bash streamlit run main.py ``` The Streamlit app will display the player's current ratings, number of games played, and highest ratings for various game modes.

3. Future Features:

   • The UI will soon support visualizations and additional performance analytics.

Future Enhancements

• Data Visualization: Add visualizations like rating trends and performance charts.
• Expanded Analytics: Incorporate insights into game-specific stats like tactics, time management, and popular openings.
• Real-time Updates: Enable real-time scraping and display of live stats.

Contributing

We welcome contributions! Feel free to open issues or submit pull requests. Please ensure that changes are well-documented and tested.