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Operational Runbook: Advanced Daily Trading Bot

1. Prerequisites

  • Python 3.9+
  • Dependencies: pandas, requests, pyyaml, yfinance, python-dotenv
  • Email Configuration: Gmail App Password required in .env.
  • News Sentiment (Optional): Local fallback scoring is built in (no external LLM key required).
  • AI Trading Bot: Remote trained-model inference endpoint URL in .env or GitHub secrets.

2. Setup

  1. Move the trading_bot folder to your desired location (e.g., home folder).
  2. pip install -r requirements.txt.
  3. Fill in your email credentials in .env.
  4. Create .env from the template and paste your keys: 
    cp .env.example .env
  5. AI trading endpoint:
    • TRAINED_MODEL_INFERENCE_URL points the AI trading bot at the hosted trained-model service.
    • TRAINED_MODEL_API_KEY optionally protects that endpoint.
    • Do not commit .env (it is gitignored).

3. Daily Workflow

The bot is fully automated:

  1. Start Scheduler: python3 scheduler.py
  2. Automated Cycle:
    • Checks for Wi-Fi and 8 AM start time.
    • Runs main.py (Price/News Ingest -> Features -> Train -> Backtest).
    • Sends Daily Email Report (combined pipeline + backtest details).
    • Updates Meta-Learner state.

4. Long-Range Backtesting (Optional)

Use the backtesting engine for historical runs and PineScript-ready strategy configuration.

  • Runner: python3 backtesting_runner.py backtest
  • Config: backtesting/config.yaml
  • Dependencies: backtesting/requirements.txt

Note: PineScript translation is a placeholder; set strategy.type: pine with a script path when ready.

4. Safety & Persistence

  • State: Positions are tracked in data/trading_bot.db.
  • Learning: Adaptations are saved in meta_learner_state.json.
  • Logs: View progress in scheduler.log.

5. Troubleshooting

  • No Email: Verify SENDER_EMAIL and SENDER_PASSWORD in .env.
  • No Data: Ensure internet connection is active (Wi-Fi check).
  • AI Strategy Not Trading:
    • If the trained-model endpoint call fails, the run continues but new AI entries are blocked.
    • Check that TRAINED_MODEL_INFERENCE_URL is set and the hosted service is healthy.