Professional Excel data processing application for iOS

Nituvim AI is a Flutter-based iOS application that brings advanced Excel data processing capabilities to mobile devices. Originally developed as a Python desktop application, this iOS version maintains all core functionality while providing a native mobile experience with Hebrew RTL support.

• Excel File Processing: Read and analyze .xlsx and .xls files
• Advanced Date Filtering: Two filtering modes for different use cases
  • Broadcast Day Logic: 07:00-06:59 (for media/broadcasting)
  • Calendar Day Logic: 00:00-23:59 (standard business hours)
• Data Analytics: Generate statistics and insights from processed data
• Export & Sharing: Create reports and share via iOS native sharing

• Files App Support: Import Excel files directly from iOS Files app
• Native Sharing: Export and share results using iOS Share Sheet
• Hebrew RTL Support: Full right-to-left layout and text support
• Dark Mode: Automatic light/dark theme switching
• iOS Design: Native iOS look and feel with Cupertino widgets

• Flutter 3.x: Cross-platform mobile framework
• Dart: Programming language optimized for mobile development

• excel: Excel file processing and manipulation
• file_picker: iOS file selection integration
• share_plus: Native iOS sharing capabilities
• intl: Internationalization and Hebrew localization
• provider: State management

• MVVM Pattern: Clean separation of concerns
• Service Layer: Business logic isolation
• Custom Widgets: Reusable UI components optimized for Hebrew text

• Flutter SDK 3.x
• Xcode 14+ (for iOS development)
• iOS 12.0+ target device

1. Clone the repository

   git clone https://github.com/RoadToMythicGlory/nituvim-ios.git
   cd nituvim-ios

2. Install dependencies

   flutter pub get
   cd ios && pod install && cd ..

3. Run the application

   flutter run

For automated environment setup:

• macOS/Linux: ./setup.sh
• Windows: setup_windows.bat

1. Import File: Tap the import button to select an Excel file from the iOS Files app
2. Configure Processing: Choose the appropriate date filtering mode
3. Process Data: Review real-time processing progress and statistics
4. Export Results: Share or save the processed data using iOS sharing options

lib/
├── main.dart                 # Application entry point
├── models/                   # Data models
├── services/                 # Business logic
│   ├── excel_processor.dart  # Core Excel processing
│   └── file_manager.dart     # File I/O operations
├── screens/                  # UI screens
├── widgets/                  # Reusable components
└── utils/                    # Constants and helpers

flutter test

flutter build ios --release

• Follow Flutter/Dart style guidelines
• Maintain test coverage for new features
• Ensure Hebrew RTL compatibility

1. Configure code signing in Xcode
2. Build release version: flutter build ios --release
3. Submit through App Store Connect

Automated pipeline configured with Codemagic for:

• Testing and validation
• iOS build generation
• Code signing and deployment

1. Fork the repository
2. Create a feature branch (git checkout -b feature/new-feature)
3. Commit your changes (git commit -m 'Add new feature')
4. Push to the branch (git push origin feature/new-feature)
5. Open a Pull Request

This project is licensed under the MIT License - see the LICENSE file for details.

• Issues: GitHub Issues
• Documentation: Check the project wiki for detailed guides

• Original Python desktop application developers
• Flutter community for excellent packages and support
• Hebrew localization contributors

Built with Flutter for the iOS ecosystem