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# 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.
<!-- It's a good idea to take a screenshot of your dashboard and upload it to a service like Imgur to include here -->
## 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**
```bash
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**
```bash
# For Windows
python -m venv .venv
.\.venv\Scripts\activate
# For macOS/Linux
python3 -m venv .venv
source .venv/bin/activate
3. **Install Dependencies**
```bash
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. **