Climatrack is a world-class, AI-powered weather intelligence platform built with Python and Streamlit. It offers a rich, interactive user interface for accessing real-time global weather data, advanced analytics, and premium visualisations, moving beyond simple forecasts to provide deep, actionable insights.
Standard weather apps provide data; Climatrack provides intelligence. In a world where weather patterns are increasingly volatile, access to simple forecasts is no longer enough. Individuals and businesses need to understand the context behind the numbers—the trends, the risks, and the potential impact on daily life and operations.
The vision for Climatrack is to bridge the gap between raw weather data and actionable intelligence. We believe that everyone deserves access to high-fidelity meteorological insights presented through an intuitive and beautiful interface. Climatrack is more than just a weather app; it's a sophisticated data analysis and visualization tool designed to empower decision-making.
Experience Climatrack live here:
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- Dynamic Dashboard: A fully customisable, widget-based dashboard that provides a comprehensive overview of current conditions. Users can add, remove, and rearrange widgets to suit their needs.
- Extended Forecast: A detailed 7-day forecast with interactive Plotly charts showing temperature trends and precipitation chances, alongside daily breakdown cards for in-depth analysis.
- Interactive Maps & Radar: An embedded live weather radar for tracking precipitation and an interactive map viewer with multiple layers (temperature, wind, clouds, etc.).
- Historical Data: The ability to look up weather conditions for any past date, complete with a summary of temperature, conditions, and wind.
- Advanced Analytics Page: An AI-driven analysis of the 7-day forecast that identifies key trends in temperature, pressure, and comfort levels. It also calculates a "Weather Change Likelihood" to predict pattern shifts.
- Deep Dive Analysis: Detailed expander sections provide insights into temperature volatility, heat wave/cold snap risks, and daily temperature range trends.
- Comfort & Activity Forecast: A unique feature that calculates a proprietary "Comfort Score" and identifies the most optimal days for outdoor activities based on a combination of weather factors.
- Location Comparison: A side-by-side view to compare real-time weather conditions for multiple user-selected locations.
- Real-time Weather Alerts: Fetches and displays official weather alerts for a given location, classified by severity and including actionable recommendations.
- AI-Enhanced Geocoding: A smart search system that can handle location names, coordinates, and points of interest. It uses multiple providers and AI-based scoring to deliver the most accurate results.
The application is cleanly architected into distinct, single-responsibility modules, making it scalable and easy to maintain:
main.py: The main application entry point. Contains thePremiumWeatherAppclass which controls the UI and application flow.weather_api.py: ThePremiumWeatherAPIclass manages all communication with the OpenWeatherMap API, including advanced features like caching, rate limiting, and data validation.location_detector.py: ThePremiumLocationDetectorclass handles all geocoding and IP-based location lookups, using AI-enhancements to improve accuracy.data_processor.py: TheAdvancedDataProcessorclass is the analytics engine. It takes raw API data and transforms it into the advanced trends, scores, and insights seen in the app.ui_components.py: TheUIComponentsclass is a library of custom-styled HTML and CSS components, ensuring a consistent and premium look and feel across the application.
For a detailed walkthrough of Climatrack's features and how to use them, check out this video:
[Video Coming Soon]
Clone and run locally using Python and Streamlit.
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Clone the repository:
git clone https://github.com/theeccentriccoder01/Climatrack.git cd Climatrack -
Install dependencies:
pip install -r requirements.txt
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Set up API key: Create a file named
secrets.tomlinside a.streamlitfolder (.streamlit/secrets.toml) and add your OpenWeatherMap API key:OPENWEATHER_API_KEY = "YOUR_32_CHARACTER_API_KEY_HERE"
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Run the app:
streamlit run main.py
Report bugs and issues or propose improvements through our GitHub repository.
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Firstly Star(⭐) the Repository
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Fork the Repository and create a new branch for any updates/changes/issue you are working on.
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Start Coding and do changes.
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Commit your changes
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Create a Pull Request which will be reviewed and suggestions would be added to improve it.
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Add Screenshots and updated website links to help us understand what changes is all about.
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Check the CONTRIBUTING.md for detailed steps...
We welcome all contributions and suggestions! Whether it's a new feature, design improvement, or a bug fix — your voice matters 💜
Your insights are invaluable to us. Reach out to us team for any inquiries, feedback, or concerns.
This project is open-source and available under the MIT License.
Developed by Eccentric Explorer
Feel free to reach out with any questions or feedback! Thanks for reading, here's a cookiepookie:
