DEDBot

A sophisticated Discord bot that calculates daily Dollar Cost Averaging (DCA) entry signals for ETFs and stocks based on technical analysis metrics. The bot includes a web interface for configuration management and backtesting capabilities.

🚀 Features

• Automated Daily Scoring: Calculates entry signals for multiple tickers based on your custom formulas
• Discord Notifications: Sends daily score updates to Discord via webhooks with formatted messages and alerts
• Web Administration Interface: Full-featured web UI for managing everything - tickers, weights, formulas, and configuration (no need to edit config files!)
• Backtesting Engine: Historical performance analysis with visual results and detailed metrics
• Fully Customizable Scoring:
  • Define your own Python-based scoring formulas
  • Adjust component weights dynamically
  • Access to technical indicators (RSI, MA, momentum, volatility, etc.)
  • Real-time formula validation and preview
• Minimal Configuration: Only admin token required in config.yaml - everything else (including webhook) via web UI
• Docker Support: Fully containerized deployment with Docker Compose
• Historical Data Tracking: Persistent storage of daily scores in CSV format and SQLite database

📋 Prerequisites

• Docker and Docker Compose
• Discord webhook URL (for notifications)

🛠️ Installation

1. Clone the Repository

git clone https://github.com/lukyyy9/DEDBot.git
cd DEDBot

2. Configure the Bot

Create a minimal config.yaml with only the admin token:

# Admin token for web interface access
admin:
  admin_tokens:
    - "your-secure-admin-token-here"

3. Create Data Directory

mkdir -p data

4. Start the Services

Using the provided script:

chmod +x start-v2.sh
./start-v2.sh

Or manually with Docker Compose:

docker-compose up -d

🏗️ Architecture

The project consists of two main services:

1. DCA Bot (dca-bot)

• Runs scheduled daily scoring calculations
• Fetches market data from Yahoo Finance
• Calculates technical indicators using your custom formulas
• Sends notifications to Discord
• Logs results to CSV and SQLite database

2. Web Interface (dca-web)

• Admin authentication system
• Database-driven configuration management (no file editing required)
• Real-time configuration updates (tickers, weights, formulas, caps)
• Live scoring preview
• Backtesting interface with visual results
• Runs on port 5001

Configuration Storage

• config.yaml: Minimal bootstrap settings (admin tokens only - webhook optional)
• SQLite Database (/data/bot_config.db): All runtime configuration
  • Discord webhook URL
  • Tickers list
  • Custom formulas
  • Component weights
  • System settings (caps, periods, etc.)

📊 Scoring System

The bot calculates a composite score (0-100) based on fully customizable formulas and weights. All scoring components are user-managed through the web interface.

User-Configurable Components

The scoring system is entirely flexible - you define:

1. Custom Formulas: Create scoring formulas using Python expressions
2. Component Weights: Adjust the importance of each component
3. Available Variables:
   • drawdown - Distance from all-time high
   • rsi - Relative Strength Index
   • close, ma50, ma200 - Price and moving averages
   • momentum - Price momentum
   • vol20 - 20-day volatility
   • np - NumPy functions (clip, exp, etc.)

Example Formulas

# RSI-based scoring (oversold = opportunity)
np.clip((70.0 - rsi) / 40.0, 0.0, 1.0)

# Drawdown scoring
min(drawdown / cap, 1.0)

# Distance from MA50
np.clip((ma50 - close) / ma50 / 0.15, 0.0, 1.0)

Score Interpretation

• ✅ 55-100: Strong entry signal (triggers @everyone alert)
• ⚠️ 45-54: Neutral zone
• ❌ 0-44: Weak entry signal

🌐 Web Interface

Access the web interface at http://localhost:5001

Features

• Dashboard: Overview of current configuration and recent scores
• Tickers Management: Add/remove ETFs and stocks to monitor (no config.yaml editing needed)
• Weights Configuration: Adjust scoring component weights in real-time
  • Weight Profiles: Save and manage multiple weight configurations
  • Quickly switch between different testing profiles
  • Create, edit, and delete profiles with descriptions
  • One-click profile activation to load saved weights
• Formulas Editor: Create and manage custom Python scoring formulas with syntax validation
• Configuration Editor: Modify caps, periods, and other settings through the UI
• Backtest: Historical performance analysis with visual charts and metrics

All configuration changes are stored in a SQLite database (/data/bot_config.db) and take effect immediately.

Authentication

Use one of the admin tokens defined in config.yaml to access the interface.

🐳 Docker Configuration

Environment Variables

• TZ: Timezone (default: UTC)
• DEV: Development mode - "true" runs every minute, "false" runs daily
• SECRET_KEY: Flask secret key for web interface sessions

Volumes

• ./config.yaml:/app/config.yaml:ro - Configuration file (read-only)
• ./data:/data - Persistent data storage

Ports

• 5001: Web interface port

📁 Project Structure

.
├── bot_daily_score_v2.py    # Main bot script with scheduler
├── web_app.py               # Flask web interface
├── backtest_v2.py           # Backtesting script
├── config.yaml              # Configuration file
├── requirements.txt         # Python dependencies
├── Dockerfile               # Docker image definition
├── docker-compose.yml       # Multi-service orchestration
├── start-v2.sh              # Quick start script
├── core/                    # Core modules
│   ├── __init__.py
│   ├── config.py           # Configuration manager
│   ├── scoring.py          # Scoring engine
│   └── backtest.py         # Backtest engine
├── templates/              # HTML templates for web interface
├── static/                 # Static assets (CSS, JS)
└── data/                   # Persistent data directory
    ├── scores_history.csv
    ├── backtest_results.csv
    └── bot_daily_score.log

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📄 License

This project is open source and available under the MIT License.

🙏 Acknowledgments

• Built with yfinance for market data
• Uses Flask for the web interface
• Scheduled with APScheduler

📞 Support

For issues and questions, please open an issue on the GitHub repository.

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Note: This bot is for educational and informational purposes only. Always do your own research before making investment decisions.