Route Prediction API

This project provides a simple Flask API for predicting public transport route times based on historical data. It analyzes patterns in route schedules and predicts the most likely times for future route occurrences.

🚀 Features

• List all available routes
• Predict next day's most likely times for specific routes
• Confidence scoring for predictions
• Simple REST API interface

📋 Prerequisites

• Python 3.8 or higher
• pip (Python package installer)
• Git
• Basic knowledge of REST APIs
• Your route data in CSV format

🛠️ Installation

1. Clone the repository:

git clone https://github.com/holasoymalva/data_jam.git
cd data_jam

2. Create a virtual environment and activate it:

# Create virtual environment
python -m venv venv

# Activate virtual environment
# On Windows:
venv\Scripts\activate
# On macOS/Linux:
source venv/bin/activate

3. Install required packages:

pip install -r requirements.txt

4. Place your data file:
   • Copy your route data CSV file to the data/ directory
   • Name it data_example.csv

📁 Project Structure

flask_route_predictor/
│
├── data/
│   └── data_example.csv
│
├── app/
│   ├── __init__.py
│   ├── routes.py
│   └── predictor.py
│
├── requirements.txt
└── run.py

🚀 Running the Application

1. Make sure your virtual environment is activated
2. Run the Flask application:

python run.py

The API will start running on http://localhost:5000

🔍 API Endpoints

Get All Routes

GET /routes

Returns a list of all available routes.

Example response:

{
    "status": "success",
    "data": [
        {
            "route_id": 908,
            "route_name": "82 García Gíneres"
        },
        ...
    ]
}

Get Route Predictions

GET /predict/<route_id>

Returns predictions for a specific route.

Example response:

{
    "status": "success",
    "route_id": 908,
    "predictions": [
        {
            "hour": 8,
            "predicted_time": "2024-10-27 08:00:00",
            "confidence": 85.5
        },
        ...
    ]
}

📊 Input Data Format

The CSV file should have the following columns:

• event_date
• route_id
• route_name
• (other columns will be ignored)

Example:

event_date,route_id,route_name
2024-09-22 13:44:00.000,908,82 García Gíneres

🤝 Contributing

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

📝 License

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

👤 Author

Made with ❤️ by holasoymalva

🙏 Acknowledgments

• Thanks to all contributors
• Inspired by public transport optimization needs
• Built with Flask framework

📞 Support

If you have any questions or need help, please:

1. Check the existing issues
2. Create a new issue if needed
3. Contact me through GitHub

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Remember to ⭐️ this repository if you found it helpful!