Automated Crypto Trading Bot

This project is a sophisticated, multi-process automated trading bot designed to interact with the Hyperliquid decentralized exchange. It features a robust data pipeline, a flexible strategy engine, multi-agent trade execution, and a live terminal dashboard for real-time monitoring.

Features

• Multi-Process Architecture: Core components (data fetching, trading, strategies) run in parallel processes for maximum performance and stability.
• Comprehensive Data Pipeline:
  • Live price feeds for all assets.
  • Historical candle data collection for any coin and timeframe.
  • Historical market cap data fetching from the CoinGecko API.
• High-Performance Database: Uses SQLite with pandas for fast, indexed storage and retrieval of all market data.
• Configuration-Driven Strategies: Trading strategies are defined and managed in a simple JSON file (_data/strategies.json), allowing for easy configuration without code changes.
• Multi-Agent Trading: Supports multiple, independent trading agents for advanced risk segregation and PNL tracking.
• Live Terminal Dashboard: A real-time, flicker-free dashboard to monitor live prices, market caps, strategy signals, and the status of all background processes.
• Secure Key Management: Uses a .env file to securely manage all private keys and API keys, keeping them separate from the codebase.

Project Structure

The project is composed of several key scripts that work together:

• main_app.py: The central orchestrator. It launches all background processes and displays the main monitoring dashboard.
• trade_executor.py: The trading "brain." It reads signals from all active strategies and executes trades using the appropriate agent.
• data_fetcher.py: A background service that collects 1-minute historical candle data and saves it to the SQLite database.
• resampler.py: A background service that reads the 1-minute data and generates all other required timeframes (e.g., 5m, 1h, 1d).
• market_cap_fetcher.py: A scheduled service to download daily market cap data.
• strategy_*.py: Individual files containing the logic for different types of trading strategies (e.g., SMA Crossover).
• _data/strategies.json: The configuration file for defining and enabling/disabling your trading strategies.
• .env: The secure file for storing all your private keys and API keys.

Installation

1. Clone the Repository

   git clone [https://github.com/your-username/your-repo-name.git](https://github.com/your-username/your-repo-name.git)
   cd your-repo-name
   
   
   

2. Create and Activate a Virtual Environment

    # For Windows
    python -m venv .venv
    .\.venv\Scripts\activate
    # For macOS/Linux
    python3 -m venv .venv
    source .venv/bin/activate
   

3. Install Dependencies

   pip install -r requirements.txt
   
   

##Getting Started: Configuration

Before running the application, you must configure your wallets, agents, and API keys.

1. **Create the .env File In the root of the project, create a file named .env. Copy the following content into it and replace the placeholder values with your actual keys. **