CryptoPredictor

A cross-platform desktop application that analyzes cryptocurrency markets with ML models and surfaces investment signals. Built with BeeWare / Briefcase — the same Python codebase runs natively on macOS, Linux, Windows, Android, and iOS.

Highlights

• Cross-platform native builds — single codebase for desktop and mobile via Briefcase
• ML-driven signals — price prediction and investment-grade signal scoring
• Modular architecture — clean separation of data, models, UI, and signal logic
• Tested — pytest suite included

Project Layout

cryptopredictor/
├── src/cryptopredictor/    # application source
├── tests/                  # pytest suite
├── pyproject.toml          # Briefcase + packaging config
├── CHANGELOG
└── LICENSE

Development

pip install briefcase
briefcase dev

Build a native installer for your OS:

briefcase create
briefcase build
briefcase package

Run the test suite:

pip install pytest
pytest

Status

Active development. Core scaffolding (Briefcase 0.3.22), test harness, and packaging pipeline are in place. UI, signal engine, and ML model integration are the active work streams.

License

MIT — see LICENSE.

Disclaimer

This software is provided for educational and research purposes only. Signals or selections produced by this application are not financial advice. Trading cryptocurrencies carries substantial risk of loss. Use at your own risk.