CF Stats is an Android application that fetches your Codeforces submission data and displays it as a github-style contribution graph. This project was built as an experiment—created by someone with practically zero prior knowledge of app development. With the help of large language models (LLMs), prompt engineering, and some minor debugging, this project was brought to life as a learning exercise.
- Codeforces Integration: Fetches your submission data directly from the Codeforces API.
- Submission Graph: Visualizes your submission history with a color-coded grid.
- Home Screen Widget: Offers a widget that updates every 15 minutes, showing your latest contribution graph.
- Persistent Handle: Saves your Codeforces handle for quick and easy access every time you open the app.
You can download the signed APK from this repository.
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Download the APK:
Tap the download link for the APK file and save it to your device. -
Review Android's Prompt:
When you tap the APK, Android will ask you, "Would you like to continue installing this application?" or something similar. Simply tap Continue (or Install) when prompted. -
Installation Complete:
Once the installation finishes, you'll see a confirmation message. You can then tap Open to launch the app.
Note: Since this is an experimental project, you may encounter bugs or unexpected behavior.
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Enter Your Codeforces Handle:
When you launch the app, you'll be prompted to enter your Codeforces handle. Once you enter it and tap the button, your handle will be saved and the app will fetch your submission data. -
View the Contribution Graph:
The main screen displays a contribution graph with color-coded cells representing your submissions over the past 25 weeks. -
Home Screen Widget:
- Add the Widget: Long-press on an empty area of your home screen and select Widgets.
- Select CF Stats Widget: Drag and drop the widget onto your home screen.
- The widget will automatically update every 15 minutes with the latest data.
- Enhance error handling and UI polish.
- Add more customization options for the graph.
- Implement additional features such as historical data analysis.
Since this project was built as an experimental learning exercise, contributions are welcome! Feel free to fork the repository and submit pull requests with improvements or bug fixes.