📊 Smart Money Concepts (SMC) & Stocks (Gaps, fib, S/R, chart_patterns) Analysis Toolkit

A high-performance Python toolkit for advanced stock market analysis, focusing on Smart Money Concepts (SMC) and stocks (Gaps, fib, S/R, chart_patterns) analysis.

🚀 Key Features

1. Smart Money Concepts (SMC) Analysis

• Market Structure : Vectorized detection of Swing and Internal structure (BOS, CHoCH).
• Supply & Demand : Identification of Order Blocks (OB) and Fair Value Gaps (FVG).
• Liquidity : Detection of Equal Highs and Equal Lows.
• Screener : A dedicated screener to find stocks currently trading near these institutional levels.

2. Stocks (Gaps, fib, S/R, chart_patterns) Analysis Suite

• LTP Near Gaps : Finds stocks trading near unfilled or partially filled gaps.
• Support & Resistance : Vectorized detection of high-probability S/R zones.
• Fibonacci Levels : Automated Fibonacci retracement analysis.
• Chart Patterns : Detects Head & Shoulders, Double Tops/Bottoms, Triangles, Flags, Pennants, and Wedges.
• Candle & Gap Analysis : Deep dive into daily candle patterns and gap dynamics.

3. "Super Fast" Performance Architecture

• Centralized Data Manager : Unified fetching via yfinance with robust retry logic.
• Aggressive Cache Slicing : Automatically reuses larger period caches (e.g., max) to fulfill shorter period requests (e.g., 1y, 1d) instantly.
• In-Memory Caching : Minimizes disk I/O by keeping dataframes in memory during execution.
• Vectorized Logic : Most analysis modules use NumPy and Pandas vectorization for rapid processing of hundreds of stocks.

🛠 Installation

1. Install dependencies:

   pip install .
   

📈 Usage

Run SMC Screener & Analysis

This is the primary entry point for Smart Money Concepts analysis. It provides an interactive menu to run Analysis, Screening, or Both.

python "SMC Screener.py"

Run Multi-Indicator Analysis

Executes the full suite of other indicators (Gaps, S/R, Fibonacci, Patterns) in one go.

python run_analysis.py

⚙️ Configuration

• Cache : Data is stored in data_cache/ as .pkl files. Default expiry is 24 hours.
• Output : Results are saved in outputs/ and analysis/ directories (CSV format).
• Google Sheets : Supports syncing results to Google Sheets (requires credentials.json in Credentials/).

📁 Project Structure

• SMC Screener.py : Interactive entry point for SMC pipeline.
• run_analysis.py : Main runner for multi-indicator suite.
• stock_analysis/ : Core logic modules.
  • stock_data_manager.py: High-performance data & cache handler.
  • smc_analysis.py : The SMC engine.
  • chart_patterns.py : Pattern detection logic.
  • support_resistance.py: S/R zone detection.
• data_cache/ : Local repository for stock data.

Note: This toolkit is for educational and research purposes. Always perform your own due diligence before trading.