smc-screener 0.0.1

A Python package for Smart Money Concepts (SMC) analysis and stock screening

SMC Screener 📈

A Python package for Smart Money Concepts (SMC) analysis and stock screening, designed to identify key market levels such as swing highs/lows, order blocks, fair value gaps (FVGs), and premium/discount zones.

Features ✨

• SMC Analysis: Identifies swing highs/lows, order blocks, FVGs, and market structure breaks using yfinance data. 📊
• Stock Screener: Screens stocks near key SMC levels based on a proximity percentage. 🔍
• Visualization: Generates candlestick charts with SMC levels using matplotlib. 📉
• Output Options: Saves results to CSV files and/or Google Sheets. 📄📑
• Interactive CLI: Choose tasks (analysis, screener, or both) and stock lists (e.g., Nifty 50, F&O). 🖥️

Installation 🚀

1. Install via pip:

   pip install smc-screener
   

   Note: The package is not yet on PyPI. To install locally, use the wheel file (see Development Setup 🛠️).

2. Install Dependencies: The package requires the following Python libraries:

   • yfinance>=0.2.44
   • pandas>=2.2.2
   • numpy>=1.26.4
   • matplotlib>=3.9.2
   • gspread>=6.1.2 (optional, for Google Sheets)
   • oauth2client>=4.1.3 (optional, for Google Sheets)
   • tqdm>=4.66.5

   Install them manually if needed:

   pip install yfinance pandas numpy matplotlib gspread oauth2client tqdm
   

3. Google Sheets Setup (optional, for output_format="google_sheets" or "both") 📑:

   • Create a Google Cloud project and enable the Google Sheets API and Google Drive API. 🔧
   • Create a service account and download the JSON credentials file. 🔑
   • Save the JSON file as Credentials/credentials.json in your project directory.
   • Share your Google Sheet with the service account’s email (found in the JSON file) with edit access.
   • Update the spreadsheet_id in main_pipeline.py with your Google Sheet ID (from the URL: https://docs.google.com/spreadsheets/d/<SPREADSHEET_ID>/edit).

Usage 🛠️

Command-Line Interface

Run the package directly from the command line:

smc-trading

This launches an interactive CLI where you can:

• Select a task: SMC Analysis, SMC Screener, or both. 🔄
• Choose a stock list: Nifty Top 10, Nifty 50, F&O, or Nifty 500. 📋

Example interaction:

Select the task to run:
1. SMC Analysis
2. SMC Screener
3. Both (Analysis + Screener)
Enter your choice (1, 2, or 3): 3

Select the stock list to process:
1. Nifty Top 10
2. Nifty 50
3. F&O
4. Nifty 500
Enter your choice (1, 2, 3, or 4): 1

Selected stock list: Nifty Top 10 (10 stocks)
Step 1: Running SMC Analysis... 📊
Step 2: Running SMC Screener... 🔍
Task 'both' completed for Nifty Top 10! 🎉

Programmatic Usage

Run the pipeline programmatically:

from smc_trading import main_pipeline
import asyncio
asyncio.run(main_pipeline.run_full_pipeline())

Customizing Parameters

Edit main_pipeline.py to customize:

• Stock Lists: Modify nifty_top_10, nifty_50, fn_o_stocks, or nifty_500. 📋
• Period/Interval: Change period (e.g., "1y", "max") and interval (e.g., "1d", "1h") for yfinance data. ⏳
• Output Format: Set output_format to "csv", "google_sheets", or "both". 📄
• Proximity Percentage: Adjust proximity_percentage (default 2.0) for the screener. 📏
• Visualization: Set visualize=True for charts or False for faster execution. 📉
• Clear Output: Set clear=True to overwrite existing CSV files or Google Sheets. 🗑️

Example:

await main_pipeline.main_analysis(
    stock_codes=["RELIANCE.NS"],
    spreadsheet_id="your_spreadsheet_id",
    period="6mo",
    interval="1h",
    visualize=True,
    output_format="both"
)
main_pipeline.main_screener(
    proximity_percentage=1.5,
    output_csv="screener_results.csv",
    spreadsheet_id="your_spreadsheet_id",
    output_format="both"
)

Output 📈

• SMC Analysis:
  • CSV: Saves to analysis/smc_analysis_summaries.csv (summary data) and analysis/smc_analysis_levels.csv (key levels). 📄
  • Google Sheets: Saves to Summaries and Levels worksheets (if enabled). 📑
  • Visualization: Candlestick charts with SMC levels (if visualize=True). 📉
• SMC Screener:
  • CSV: Saves to screener_results.csv with stocks near SMC levels. 📄
  • Google Sheets: Saves to Screener_Results worksheet (if enabled). 📑
  • Console: Displays a table of stocks near key levels. 🖥️

Project Structure 🛠️

smc_trading/
├── smc_trading/
│   ├── __init__.py
│   ├── smc_analysis.py
│   ├── smc_screener.py
│   └── main_pipeline.py
├── Credentials/
│   └── credentials.json
├── pyproject.toml
├── README.md
├── LICENSE
└── requirements.txt

yfinance Period & Interval Reference 📅

• Period: "1d", "5d", "1mo", "3mo", "6mo", "1y", "2y", "5y", "10y", "ytd", "max"
• Interval: "1m", "2m", "5m", "15m", "30m", "60m", "90m", "1h", "1d", "5d", "1wk", "1mo", "3mo"
• Restrictions:
  • "1m" interval: Only last 7 days max.
  • Intraday intervals ("1m", "1h", etc.): period ≤ 60d.
  • Daily/weekly/monthly: Longer periods allowed.

Troubleshooting 🐞

• yfinance Rate Limits: Reduce batch_size or increase delay in main_pipeline.py. 🕒
• Google Sheets Errors: Verify Credentials/credentials.json and share the Google Sheet with the service account. 🔑
• No Data: Check ticker validity (e.g., RELIANCE.NS). Use yf.Ticker("TICKER").info to verify. 📊
• Visualization Issues: Ensure matplotlib is installed and visualize=True. 📉
• Screener Empty: Run SMC Analysis first to generate smc_analysis_levels.csv and smc_analysis_summaries.csv. 🔍

License 📜

This project is licensed under the MIT License. See the LICENSE file for details.

Contributing 🤝

Contributions are welcome! Please submit a pull request or open an issue on the repository.

Happy trading! 🎉