📅 Schedulr

Schedulr is a smart scheduling and task management tool that helps users organize their work, prioritize tasks, and generate optimized schedules.

🚀 Built as part of GirlScript Summer of Code (GSSoC).

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🌟 GirlScript Summer of Code (GSSoC) 2025

🌟 Exciting News...

🚀 This project is now an official part of GirlScript Summer of Code – GSSoC'25! 💻 We're thrilled to welcome contributors from all over India and beyond to collaborate, build, and grow Schedulr! Let’s make learning and career development smarter – together! 🌟

👩‍💻 GSSoC is one of India’s largest 3-month-long open-source programs that encourages developers of all levels to contribute to real-world projects 🌍 while learning, collaborating, and growing together. 🌱

🌈 With mentorship, community support, and collaborative coding, it's the perfect platform for developers to:

• ✨ Improve their skills
• 🤝 Contribute to impactful projects
• 🏆 Get recognized for their work
• 📜 Receive certificates and swag!

🎉 I can’t wait to welcome new contributors from GSSoC 2025 to this Schedulr project family! Let's build, learn, and grow together — one commit at a time. 🔥

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✨ Features (v1)

• 📝 Add and manage tasks with deadlines
• 🤖 Auto-generate optimized daily/weekly schedules
• 📅 Visual calendar interface
• 📄 Export schedules to PDF
• 🎨 Clean and minimal UI
• 📱 Progressive Web App (PWA) support
• 🌐 Cross-platform compatibility
• 🤖 Auto-predict task priorities using ML (High / Medium / Low)

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🧠 ML Task Prioritization

This feature uses a machine learning model to automatically predict the priority of tasks based on:

• DeadlineDays: Number of days until the task is due
• Complexity: Estimated difficulty or effort required
• Importance: User-defined importance score
• OverdueCount: Number of times the task has been delayed

Files

• ml/data.csv → Synthetic dataset simulating tasks
• ml/ml_prioritization.py → ML script for training and predicting task priorities
• ml/task_priority_model.pkl → Trained model saved for future backend/API integration

How to Run

1. Navigate to the ml directory:

   cd ml

2. Run the ML script:

python ml_prioritization.py

3. Follow the prompts to enter task details and get priority predictions.

Model Details
Model Type: Random Forest Classifier

Notes

The model is trained on a synthetic dataset and may require retraining with real data for production use.

For backend integration, the model can be loaded using joblib.load('task_priority_model.pkl').
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## 🛠 Tech Stack
- **Frontend:** React 19, Tailwind CSS, React Router
- **Build Tool:** Vite
- **Backend:** Python (Flask / FastAPI) - *Coming Soon*
- **ML / Data Processing:** Python, Pandas, Scikit-learn (Random Forest for task prioritization)
- **Database:** PostgreSQL / SQLite - *Coming Soon*
- **PDF Export:** ReportLab / WeasyPrint - *Coming Soon*
- **Deployment:** Vercel + Heroku

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## 🚀 Quick Start

### Prerequisites
Before you begin, ensure you have the following installed:
- **Node.js** (v18 or higher) - [Download here](https://nodejs.org/)
- **npm** (comes with Node.js) or **yarn**
- **Git** - [Download here](https://git-scm.com/)

### 📥 Installation Steps

1. **Clone the repository**
```bash
git clone https://github.com/Caktusuki/Schedulr.git
cd Schedulr

2. Navigate to frontend directory

   cd frontend

3. Install dependencies

   npm install
   # or
   yarn install

4. Start the development server

   npm run dev
   # or
   yarn dev

5. Open your browser

   • Navigate to http://localhost:5173/
   • You should see the Schedulr application running! 🎉

🔧 Available Scripts

In the frontend directory, you can run:

• npm run dev - Starts the development server
• npm run build - Builds the app for production
• npm run preview - Preview the production build locally
• npm run lint - Run ESLint to check code quality

📁 Project Structure

Schedulr/
├── frontend/                 # React frontend application
│   ├── public/              # Static assets (favicon, manifest, etc.)
│   ├── src/
│   │   ├── components/      # Reusable UI components
│   │   ├── pages/          # Page components
│   │   ├── App.jsx         # Main app component
│   │   └── main.jsx        # App entry point
│   ├── package.json        # Dependencies and scripts
│   └── vite.config.js      # Vite configuration
├── ml/                      # ML task prioritization
│   ├── data.csv
│   ├── ml_prioritization.py
│   └── task_priority_model.pkl
├── .github/                # GitHub workflows and templates
├── LICENSE.md              # MIT License
└── README.md              # This file

🔍 Troubleshooting

Port already in use?

• The dev server will automatically find the next available port
• Or specify a custom port: npm run dev -- --port 3000

Dependencies not installing?

• Clear npm cache: npm cache clean --force
• Delete node_modules and package-lock.json, then run npm install

Build errors?

• Ensure you're using Node.js v18 or higher: node --version
• Check for TypeScript/ESLint errors: npm run lint

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🤝 Contributing

We love contributions! 🎉 Here's how you can help:

🐛 Found a Bug?

1. Check if it's already reported in Issues
2. If not, create a new issue

💡 Have a Feature Idea?

1. Check existing Issues and Discussions
2. Create a new issue with the enhancement label

🔧 Ready to Code?

1. Fork the repository
2. Clone your fork

   git clone https://github.com/YOUR_USERNAME/Schedulr.git

3. Create a feature branch

   git checkout -b feature/amazing-feature

4. Make your changes
5. Test your changes

   npm run lint
   npm run build

6. Commit your changes

   git commit -m "feat: add amazing feature"

7. Push to your fork

   git push origin feature/amazing-feature

8. Open a Pull Request

📝 Commit Message Guidelines

We follow Conventional Commits:

• feat: - New features
• fix: - Bug fixes
• docs: - Documentation changes
• style: - Code style changes
• refactor: - Code refactoring
• test: - Adding tests
• chore: - Maintenance tasks

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📜 License

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

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💡 Project Admin

• Vikyraj Deka (@Caktusuki)

🙏 Contributors

Thanks to all contributors who have helped make Schedulr better!

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📞 Support

• 🐛 Issues: GitHub Issues
• 💬 Discussions: GitHub Discussions
• 🌟 Star this repo if you find it helpful!

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Happy Scheduling! 📅✨