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A high-performance terminal-native crypto signal scanner with live Z-score analytics, DEAP-based RL tuning, and automated backtesting.

Project description

Cb-signalTUI

Build

img

Features

  • Real-Time Cryptocurrency Scanning: Continuously scans a wide range of crypto pairs for trade signals.
  • Dynamic Technical Analysis: Uses adaptive Exponential Moving Averages (EMA), Z-scores, slope detection, RSI, and volatility analysis.
  • Reinforcement Learning Optimization: Dynamically tunes Z-score thresholds using DEAP-based RL algorithms.
  • Strategy Classification: Differentiates between momentum, reversal, and neutral strategies.
  • Live Terminal UI: Displays results in a color-coded, real-time TUI with rich.live.
  • Asynchronous Data Fetching: Utilizes aiohttp and retries on failure for reliable data streaming.
  • Voice Alerts: Uses pyttsx3 for real-time vocal alerts when high-confidence signals occur.
  • Database Logging: Stores all signal events with aiosqlite for historical reference.
  • Backtesting Accuracy: Includes a backtesting module to evaluate signal performance.
  • Custom Configs per Asset: Each asset has its own EMA and Z-score threshold settings.
  • Auto-Build Artifacts: Built packages are committed to /built/ on each push to main.

Project Structure

Cb-signalTUI/
├── cb_signal_tui/             # Main package directory
│   ├── __init__.py
│   └── __main__.py            # Entry point with config
├── built/                     # Auto-committed build artifacts (.whl, .tar.gz)
│   └── cb_signal_tui-*.whl
├── dist/                      # Local build output (ignored by .git)
├── .github/
│   └── workflows/
│       └── build.yml          # GitHub Actions workflow
├── requirements.txt           # Dependencies
├── pyproject.toml             # Build system config
├── README.md                  # Project documentation
└── signals.db                 # SQLite DB (optional, runtime-generated)

Installation

  1. Clone this repository:

    git clone https://github.com/LoQiseaking69/Cb-signalTUI.git
    cd Cb-signalTUI
    
  2. Install the required dependencies:

    pip install -r requirements.txt
    
  3. (Optional) Export a shortcut path to the .whl package for faster installs:

    echo 'export cb_sigTUI="$HOME/Desktop/Cb-signalTUI-main/built/*.whl"' >> ~/.bashrc
    source ~/.bashrc
    

    Now you can install with:

    pip install $cb_sigTUI
    

Dependencies

aiohttp
aiosqlite
pandas
numpy
pyttsx3
rich
scipy
deap
tabulate

Usage

Run the scanner:

cb-signal-tui

Example Output

img

Configuration

Edit settings in cb_signal_tui/__main__.py:

  • PRODUCTS: Assets to scan (BTC-USD, ETH-USD, etc.)
  • SETTINGS: EMA periods and Z-score threshold settings per asset
  • Z_SCORE_WINDOW, VOLATILITY_THRESHOLD, FLAT_SLOPE_THRESHOLD: Signal tuning
  • STRATEGY_FILTER: Control which strategies trigger alerts (momentum, reversal)
  • ALERT_CONFIDENCE_THRESHOLD: Minimum confidence for triggering an alert
  • REFRESH_INTERVAL: Refresh rate for terminal UI
  • GRANULARITY: Time granularity for fetched data (in seconds)

Database

SQLite database (signals.db) schema:

CREATE TABLE IF NOT EXISTS signals (
    timestamp TEXT,
    asset TEXT,
    price REAL,
    z_score REAL,
    signal TEXT,
    confidence REAL,
    strategy TEXT
);

Backtesting

Run the backtesting module to evaluate signal accuracy:

python3 __main__.py --backtest

The backtest fetches historical data and compares signal predictions with actual price movements.

Contributing

  1. Fork this repository.
  2. Create a new branch (git checkout -b my-feature).
  3. Make your changes.
  4. Push and open a Pull Request.

Built for precision. Tuned for performance. Stay ahead of the market.

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