Rainfall Prediction Web Application

A machine learning-based web application that predicts rainfall probability based on weather parameters.

Features

• Real-time rainfall prediction
• Location-based weather data
• Historical prediction tracking
• Weather trend visualization
• Mobile-responsive design

Tech Stack

• Python 3.11
• Flask
• SQLite
• scikit-learn
• Tailwind CSS
• Chart.js

Setup

1. Clone the repository:

git clone https://github.com/yourusername/rainfall-prediction.git
cd rainfall-prediction

2. Install dependencies:

pip install -r requirements.txt

3. Set up environment variables: Create a .env file with:

OPENWEATHER_API_KEY=your_api_key_here
FLASK_ENV=development

4. Run the application:

python app.py

5. Open your browser and go to http://localhost:5000

Project Structure

• app.py: Main Flask application
• database.py: SQLite database operations
• templates/: HTML templates
• models/: Trained ML models
• static/: Static assets

API Endpoints

• GET /: Home page
• POST /predict: Make rainfall prediction
• GET /history: Get prediction history
• GET /locations: Get saved locations
• POST /add_location: Add new location

Contributing

1. Fork the repository
2. Create your feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request

License

MIT License