Weather Forecast Website

Project Overview

The Weather Forecast Website is a complete web application developed to display weather forecasts, leveraging machine learning models for precise predictions. The project is structured with a React-based front-end for user interaction and a Python-based back-end that handles data processing and serves the ML predictions.

Technologies Used

• Front-End: React.js, Chart.js, Axios

• Back-End: FastAPI, Uvicorn, Python

• Machine Learning: scikit-learn, numpy, joblib

Setup Instructions

Backend Setup

1. Navigate to the backend Directory:

bash 
cd backend 

2. Install Required Packages and Dependencies: Run the following command to install essential Python packages:

bash 
pip3 install -r requirements.txt 

3. Run the Model Script: Execute the model script to ensure the model is prepared and integrated properly.

bash 
python3 model.py 

4. Start the FastAPI Server: Run the following command to start the FastAPI server with live reload:

bash 
uvicorn main:app --reload 

The server should start on http://127.0.0.1:8000.

Frontend Setup

1. Navigate to the frontend Directory:

bash 
cd ../frontend 

2. Install Frontend Dependencies: Run these commands to install necessary npm packages:

bash 
npm install react react-dom react-router-dom @mui/material @mui/icons-material @mui/lab @fontsource/roboto chart.js chartjs-plugin-datalabels chartjs-plugin-zoom date-fns axios html2canvas jspdf

3. Start the Frontend Development Server: After installation, you can start the React development server with:

bash 
npm start 

The front-end application should be available on http://localhost:3000.

Configuration for AI Model Integration

• Model Loading: Verify that model.py loads models correctly and main.py has routes set for API calls.

• Preprocessing: The utils.py file should handle any data preprocessing before model input.

• Data Files: Ensure data files like merged_data.csv are formatted properly.

Running the Application

1. Start the back-end server:

bash 
cd backend 
uvicorn main:app --reload 

2. Start the front-end development server:

bash 
cd ../frontend 
npm start 

3. Access the application: Open your browser and navigate to http://localhost:3000 to use the web application.

Troubleshooting

• Ensure that your Python and Node.js versions meet the requirements.

• If the server fails to start, verify that all required dependencies are installed and that your environment variables are set up correctly. Refer to package.json and requirements.txt for any additional dependencies.

• For any issues with data loading or processing, check the utils.py logs and ensure that the CSV files are formatted as expected.