cb-signal-tui 1.1.1

A high-efficiency terminal-based crypto signal scanner with live Z-score detection, strategy classification, and automated backtesting.

Cb-signalTUI

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• Database Logging: Stores all signal events with aiosqlite for historical reference.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

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:

cb-signal-tui-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.

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