Workbench

A powerful Flask-based web application for data manipulation, file processing, and development utilities. Workbench provides a comprehensive suite of tools for working with CSV files, raw text editing, file downloads, and command execution in a modern web interface.

Features

🗂️ File Management

• File Download: Download files from URLs with automatic filename detection
• File Viewing: View and process files directly from URLs
• Local File Support: Handle local files with proper sanitization

📊 CSV Editor

• Interactive CSV Editing: Full-featured spreadsheet-like interface
• Pagination: Handle large CSV files with configurable page sizes
• Real-time Editing: Edit cells directly with immediate updates
• Export Options: Download edited CSV files
• Data Validation: Built-in data type handling and validation

✏️ Raw Text Editor

• Syntax Highlighting: Support for various file formats
• Large File Handling: Efficient processing of large text files
• Save/Download: Save changes and download processed files
• Theme Support: Dark/light theme switching

⚡ Command Execution

• Terminal Integration: Execute system commands through the web interface
• Timeout Protection: Commands timeout after 30 seconds for safety
• Output Capture: View both stdout and stderr output
• Error Handling: Comprehensive error reporting

🎨 User Interface

• Modern Design: Clean, responsive web interface
• Dark Theme: Built-in dark mode support
• Real-time Clock: Live time and date display
• Session Management: Persistent user sessions

Installation

Prerequisites

• Python 3.10+
• pip (Python package manager)

Setup

1. Clone the repository:

   git clone <repository-url>
   cd workbench

2. Create a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

   pip install -r requirements.txt

Usage

Local Development

Run the application locally:

python workbench.py

The application will start on http://localhost:9000 (or the port specified in the PORT environment variable).

Production Deployment

The application is configured for deployment on platforms like Heroku:

# Set environment variables
export PORT=5000
export FLASK_ENV=production

# Run with gunicorn
gunicorn workbench:app --bind 0.0.0.0:$PORT

API Endpoints

Main Interface

• GET / - Main application interface
• POST / - Handle file downloads and URL processing

CSV Operations

• GET /csv-editor - CSV editor interface
• GET /csv-edit - CSV editing with pagination
• POST /csv-edit - Update CSV data
• POST /update-csv-edit - Real-time CSV cell updates
• POST /download_csv - Download CSV files

Text Editor

• GET /raw-editor - Raw text editor interface
• POST /save_raw - Save raw text content
• POST /download_raw - Download raw text files

System Operations

• POST /execute_command - Execute system commands
• POST /set-theme - Change application theme
• POST /save-settings - Save user preferences

Configuration

Environment Variables

• PORT - Server port (default: 9000)
• FLASK_ENV - Flask environment (development/production)

Settings

The application supports various user-configurable settings:

• Theme preferences (dark/light)
• CSV pagination settings
• Editor preferences

Dependencies

• Flask 2.3.3 - Web framework
• pandas 2.0.3 - Data manipulation and analysis
• numpy 1.24.3 - Numerical computing
• requests 2.31.0 - HTTP library
• gunicorn 21.2.0 - WSGI HTTP server

Security Considerations

• Commands are executed with a 30-second timeout
• File downloads are validated and sanitized
• Session management with secure keys
• Input validation for all user inputs

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Test thoroughly
5. Submit a pull request

License

This project is open source. Please check the repository for specific licensing information.

Support

For issues, questions, or contributions, please use the repository's issue tracker.