README.md

metadata

title: mona
emoji: 🤖
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 5.34.2
app_file: app.py
pinned: false

MONA Dashboard

MONA (Monitoring & Analytics) is a comprehensive Streamlit dashboard application for data visualization, monitoring, and analytics.

🚀 Features

• Interactive Dashboard: Real-time data visualization with multiple chart types
• Data Upload & Analysis: Support for CSV, Excel, JSON, and Parquet files
• Real-time Monitoring: Live system metrics and performance tracking
• Configurable Settings: Customizable themes, layouts, and preferences
• Error Handling: Robust error management and logging
• Data Storage: In-memory and session-based data persistence

📁 Project Structure

mona/
├── app.py                 # Main application entry point
├── requirements.txt       # Python dependencies
├── README.md             # Project documentation
├── pages/
│   ├── dashboard.py      # Main dashboard page
│   └── settings.py       # Settings and configuration page
└── utils/
    ├── config.py         # Configuration management
    ├── storage.py        # Data storage utilities
    ├── error_handling.py # Error handling and decorators
    └── logging.py        # Logging utilities

🛠️ Installation

1. Clone or download the project files
2. Install dependencies:

   pip install -r requirements.txt
   

3. Run the application:

   streamlit run app.py
   

📊 Usage

Dashboard Features

1. Overview Tab:

   • Key metrics and KPIs
   • Trend analysis charts
   • Category distribution visualizations

2. Analytics Tab:

   • Date range filtering
   • Multiple chart types (Line, Bar, Scatter, Area, Histogram)
   • Customizable metrics selection

3. Data Upload Tab:

   • File upload support (CSV, Excel, JSON)
   • Data preview and summary
   • Basic analytics on uploaded data

4. Real-time Tab:

   • Live system monitoring
   • Performance metrics (CPU, Memory, Network)
   • System status indicators
   • Event logs

Settings Configuration

• General Settings: Application name, performance parameters
• Display Settings: Themes, chart types, layout preferences
• Data Settings: File size limits, supported formats, cache settings
• System Settings: Configuration management, debug options

🔧 Configuration

The application uses a configuration system with the following defaults:

• Max Data Points: 1000
• Refresh Interval: 30 seconds
• Default Chart: Line chart
• Theme: Light mode
• File Size Limit: 10MB
• Supported Formats: CSV, Excel, JSON, Parquet

Configuration can be modified through the Settings page or environment variables.

🗄️ Data Storage

The application supports two storage types:

1. Memory Storage: Temporary storage for the current session
2. Session Storage: Streamlit session state persistence

Data is automatically managed and can be cleared through the Settings page.

🚨 Error Handling

The application includes comprehensive error handling:

• Data Exceptions: Validation and processing errors
• UI Exceptions: Interface and rendering errors
• File Operations: Upload and processing errors
• Configuration Errors: Settings and validation errors

All errors are logged and displayed to users with appropriate messages.

📝 Logging

Logging is configured with:

• Log Level: INFO (configurable)
• Format: Timestamp, Logger Name, Level, Message
• Output: Console/stdout
• Functions: log_error, log_info, log_warning, log_debug

🔒 Security Notes

• File uploads are limited by size and type
• No persistent file storage on server
• Session-based data isolation
• Input validation and sanitization

🐛 Troubleshooting

Common Issues

1. Import Errors: Ensure all dependencies are installed via requirements.txt
2. File Upload Issues: Check file size limits and supported formats
3. Performance Issues: Adjust max data points in settings
4. Memory Issues: Clear storage regularly or reduce data cache timeout

Debug Mode

Enable debug mode in General Settings to:

• View detailed error information
• Access session state data
• See configuration details
• Enable developer options

🤝 Contributing

To contribute to this project:

1. Report bugs through issues
2. Suggest features and improvements
3. Submit pull requests with fixes
4. Follow the existing code structure and style

📄 License

This project is open source and available under standard terms.

🔄 Version History

• v1.0.0: Initial release with core dashboard functionality
• Bug fixes and feature updates as needed

📞 Support

For support and questions:

• Check the troubleshooting section
• Review error logs in debug mode
• Ensure all dependencies are properly installed