Crypto Screener 📈

A real-time crypto screener with candlestick pattern detection, Bollinger Bands, VWMA, Stochastic Oscillator, and Telegram alerts. Built for desktop with modular structure — easy to extend into a Web or Mobile App.

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🚀 Features

• Live data from Binance via ccxt
• Signal detection based on Bollinger Bands & Stochastic Oscillator
• Candlestick pattern recognition
• Telegram alerts with signal summary
• CustomTkinter-based desktop UI (optional)
• Modular structure for future web/mobile deployment

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📊 Signals

Signal	Conditions
Strong Buy	Price near lower BB (within -10% to +3%) and Stoch %K, %D < 20
Buy	Same price condition but %K or %D ≥ 20
Sell	Price above upper BB and %K, %D > 80
UltraBuy	(Strong Buy or Buy) signal confirmed by Bullish Engulfing or Three White Soldiers pattern
UltraSell	Sell signal confirmed by Bearish Engulfing or Three Black Crows pattern
MediumBuy	Price dropped from upper Bollinger Band and crossed above VWMA, confirmed by bullish patterns
MediumSell	Price risen from lower Bollinger Band and crossed below VWMA, confirmed by bearish patterns

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🕯️ Candlestick Patterns

Pattern	Conditions
Bullish Engulfing	Previous candle bearish, current candle bullish; current opens below previous close and closes above previous open
Three White Soldiers	Three consecutive bullish candles with increasing opens and closes; each candle’s body is at least half of the candle’s range
Bearish Engulfing	Previous candle bullish, current candle bearish; current opens above previous close and closes below previous open
Three Black Crows	Three consecutive bearish candles with decreasing opens and closes; each candle’s body is at least half of the candle’s range

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🌐 Macro Analysis

Indicator	Description
Fear & Greed Index	Sentiment indicator ranging from 0–100, classified as Extreme Fear, Fear, Greed, or Extreme Greed
Yield Curve Spread	Spread between 10-Year and 2-Year U.S. Treasury yields; inversion (negative value) signals recession risk
Jobless Claims	Weekly U.S. unemployment claims; rising values indicate potential labor market weakness
Current Outlook	Evaluated using yield curve and jobless claims; categorizes the macro environment into 4 quadrants:
	→ Healthy Expansion, Potential Trouble, Pre-Recession Warning, or Recession Confirmed

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📁 Project Structure & Responsibilities

 modular_native_screener/
  │
  ├── main.py
  │   └─ Entry point of the application. Starts UI loop and async tasks.
  │
  ├── config.py
  │   └─ Configuration settings such as:
  │      - Telegram bot token and chat ID
  │      - Screener symbols, timeframes, intervals
  │      - Alert thresholds, appearance settings
  │
  ├── requirements.txt
  │   └─ Python dependencies required for the app
  │
  ├── README.md
  │   └─ This file. Contains project overview and documentation
  │
  ├── assets/
  │   └─ Placeholder for icons, logos, and themes used by the GUI
  │
  ├── alerts/
  │   └── telegram.py
  │       └─ Telegram integration logic:
  │          - Send alerts
  │          - Format messages
  │          - Handle errors or rate limits
  │
  ├── core/
  │   ├── indicators.py
  │   │   └─ Technical indicator functions:
  │   │      - Bollinger Bands, VWMA, Stochastic Oscillator
  │   │
  │   ├── patterns.py
  │   │   └─ Candlestick pattern recognition:
  │   │      - Bullish/Bearish Engulfing
  │   │      - Three White Soldiers, Three Black Crows
  │   │
  │   ├── signals.py
  │   │   └─ Signal evaluation logic:
  │   │      - Determines Buy, Sell, UltraBuy, etc. based on indicators + patterns
  │   │
  │   ├── scanner.py
  │   │   └─ Scanning engine:
  │   │      - Coordinates fetching market data, running indicators, patterns, and signal generation
  │   │      - Feeds results to UI and alert system
  │   │
  │   └── macro_data.py
  │       └─ Macro trend module:
  │          - Fetches and interprets external economic indicators
  │          - Fear & Greed Index, Yield Curve Spread, Jobless Claims
  │          - Determines Current Outlook (expansion, recession risk, etc.)
  │
  ├── data/
  │   └── exchange.py
  │       └─ Market data interface:
  │          - CCXT async wrappers
  │          - Fetch candles, tickers, market info
  │
  └── ui/
      └── desktop.py
          └─ CustomTkinter GUI implementation:
          - Table display of screener results
          - Appearance settings, filter controls
          - Macro analysis panel and async loop

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🛠️ Setup Instructions

git clone https://github.com/yourusername/crypto_screener.git
cd crypto_screener

# Install dependencies
pip install -r requirements.txt

✅ To Do
 - Add GUI panel using CustomTkinter
 - Add database support for logs (SQLite/MongoDB)
 - Convert to FastAPI backend for web version
 - Build Flutter or React Native mobile app

 Made with ❤️ by [junAiStrata] – Contributions welcome!