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Configuration Guide

AlphaRatio Scanner is highly customizable without requiring code changes. All configurations are managed in config.yaml located in the root directory.

Core Structure

The config.yaml file is divided into three main sections:

  1. Infrastructure: Telegram API keys and Database paths.
  2. Benchmarks: The indices/assets you want to compare your stocks against.
  3. Symbols: The actual stocks you want to scan.

Realistic Configuration Pattern

Here is a production-ready example of how to structure your configuration.

telegram:
  token: "YOUR_TELEGRAM_BOT_TOKEN_HERE"
  # You can specify a single ID or a list of IDs for broadcasting
  chat_id: 
    - "123456789"    # Your personal ID
    - "-1009876543"  # A private Telegram group

database:
  # SQLite is the default. You can point this to a specific directory.
  url: "sqlite:///./data/ratio_scanner.db"

# Define the benchmarks. The engine will download data for these just like normal stocks.
benchmarks:
  - ticker: "^NSEI"
    name: "Nifty 50"
  - ticker: "^NSMIDCP"
    name: "Nifty Midcap 100"
  - ticker: "^CNXAUTO"
    name: "Nifty Auto"

# Define the universe of stocks to scan
symbols:
  # Example 1: Broad Market Comparison
  - ticker: "RELIANCE.NS"
    name: "Reliance Industries"
    benchmarks: ["^NSEI"]

  # Example 2: Multi-Benchmark Sector Comparison
  # Compare Tata Motors against both the broad market AND its sector index.
  - ticker: "TATAMOTORS.NS"
    name: "Tata Motors"
    benchmarks: ["^NSEI", "^CNXAUTO"]

  # Example 3: Midcap tracking
  - ticker: "CLEAN.NS"
    name: "Clean Science and Technology"
    benchmarks: ["^NSMIDCP"]

Security Best Practices

  • NEVER commit config.yaml to version control. It is included in the .gitignore by default.
  • If deploying via Docker, you can optionally override these yaml settings using Environment Variables (e.g., TELEGRAM_TOKEN), though the YAML structure remains the primary source of truth for the asset universe.

Modifying the Universe Dynamically

When you add or remove a ticker from the symbols list:

  • Adding: The next time main.py runs, the ConfigLoader detects the new symbol, adds it to the DB, and automatically initiates a historical backfill for that specific symbol before proceeding to the daily calculations.
  • Removing: The symbol is marked as is_active = False in the database. Historical data is retained, but no further API calls or calculations are wasted on it.