🌦️ Advanced Global Weather Forecast & Alert Dashboard

A professional, full-stack weather forecasting and data visualization dashboard built with Python. This application fetches real-time global weather data, processes it using Pandas, and visualizes complex meteorological parameters using interactive Plotly charts.

It is designed to simulate a production-grade analytics tool used in logistics, agriculture, and event management sectors.

🚀 Key Features

• 🌍 Global Real-Time Search: Instant weather data extraction for any city worldwide using REST APIs.
• 🚨 Automated Risk Alerts: Rule-engine based system that generates instant warnings for Extreme Heat, Heavy Rain, and Poor Air Quality (AQI).
• 📊 11-Tab Deep Analytics: MSN-style interactive tabs featuring:
  • Temperature & 'Feels Like' trends
  • Precipitation & Cloud Cover analysis
  • UV Index & Air Quality metrics
  • Wind Speed, Humidity, Pressure, Visibility, and Dew Point tracking
• 🗺️ Live Interactive Radar: Integrated Windy.com global radar for real-time storm and wind tracking.
• 📸 Auto-Save Visualizations: One-click image download for all analytical charts.

📸 Dashboard Previews

(Below are the outputs generated for different global cities)

City Overview & Details Grid

Hourly Trends & Interactive Charts

7-Day Forecast & Alerts

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🛠️ Technology Stack

• Backend Logic: Python 3.11, requests (API Handling)
• Data Processing: pandas (Time-series data manipulation)
• Frontend / UI: streamlit (Dashboard interface, HTML/CSS injection)
• Data Visualization: plotly.express, plotly.graph_objects
• Security: python-dotenv (Environment variable management)

📂 Project Structure

WEATHER-FORECAST-ALERT-APP/
├── data/                   # Sample simulation data
├── images/                 # Exported charts and UI screenshots
│   ├── chandigarhoutput (1).png
│   └── delhi_outputs (1).png
├── src/                    # Additional utility scripts
├── .env                    # Hidden API Keys (Not in Repo)
├── .gitignore              # Ignored files
├── main.py                 # Streamlit Frontend UI
├── weather_engine.py       # Core Backend & API Logic
└── requirements.txt        # Project Dependencies
⚙️ Installation & Local Setup
1. Clone the Repository:

Bash
git clone https://github.com/dalimkumar452-sudo/Weather-Forecast-Alert-App.git
cd Weather-Forecast-Alert-App
2. Create a Virtual Environment:

Bash
python -m venv venv
source venv/bin/activate  # On Windows use: .\venv\Scripts\activate
3. Install Dependencies:

Bash
pip install -r requirements.txt
4. Environment Variables Configuration:
Create a .env file in the root directory and add your WeatherAPI key:

Plaintext
WEATHER_API_KEY=your_actual_api_key_here
5. Run the Application:

Bash
streamlit run main.py
🧠 Technical Learnings & Skills Demonstrated
Successfully integrated and parsed complex, deeply nested JSON responses from external APIs.

Implemented robust error handling (try-except blocks) to prevent application crashes during API limits or invalid inputs.

Transformed raw API timestamps into actionable Pandas DataFrames for seamless plotting.

Designed a highly responsive, dark-themed UI using custom CSS injection within a Streamlit wrapper.

👨‍💻 Developed by: [Dalim Kumar Tech]

Open to Software Developer, Data Analyst, and Python Backend roles.