Weather Prediction Application

An application for predicting weather conditions using a machine learning model deployed with Flask and integrated with a React frontend.

Overview

This project combines Flask, React, and a machine learning model to predict weather conditions based on user input. The Flask backend serves the machine learning model, while React handles the user interface.

Interface

Technologies Used

• Backend: Flask, Python
• Frontend: React, JavaScript, HTML, Tailwind CSS
• Machine Learning: scikit-learn

Getting Started

Prerequisites

• Python 3.7+
• Node.js and npm (for React development)

Installation

Clone the repository:

git clone https://github.com/Lighting-pixel/predict-weather.git

Install Python dependencies for Flask:

cd backend
pip install -r requirements.txt

Install Node.js dependencies for React :

cd weather-forecast
npm install

Tailwind CSS

Tailwind CSS is already included in the project and should not require separate installation steps unless modifications are needed. If you need to rebuild Tailwind styles:

1. Navigate to the weather-forecast directory.
2. Run npm install to install any necessary Node.js packages.
3. Run npm run build to rebuild Tailwind CSS styles based on your tailwind.config.js configuration file.

Running the Application

Flask Backend

Start the Flask server:

cd backend
python app.py

The Flask server will run at http://localhost:5000.

React Frontend

In a separate terminal, start the React development server (if not already integrated with Flask):

cd weather-forecast
npm start

The React server typically runs at http://localhost:3000.

Usage

• Navigate to the application URL (http://localhost:3000 or as specified).
• Enter weather data (temperature, precipitation, wind speed, etc.) into the form.
• Submit the form to get a weather prediction based on the machine learning model.

Features

• Predict weather conditions based on user input.
• Display prediction results using React components.
• Validate input data to ensure accuracy and reliability.

Known issue

No known issue till now.

Roadmap

• Enhance UI/UX with more interactive features.
• Improve machine learning model accuracy with more data and fine-tuning.
• Add user authentication and data persistence.