1a95fe1caa
- Delete obsolete files: data_fetcher_old.py, market_old.py, base_strategy.py (root), strategy_sma_cross.py, and old architecture remnants (address_monitor.py, position_monitor.py, trade_log.py, wallet_data.py, whale_tracker.py) - Delete zero-byte Docker artifacts and runtime files (clp_hedger.log, clp_hedger/hedge_status.json) - Move one-off utility scripts to scripts/ directory - Move example/template files to .temp/ directory - Update .gitignore: add entries for clp_hedger.log, clp_hedger/hedge_status.json, Docker layer hash files, Using, Running, and backups/ - Update .dockerignore: add clp_hedger.log, clp_hedger/hedge_status.json, backups/ - Create example config files: _data/strategies.json.example, _data/backtesting_conf.json.example, _data/coin_precision.json.example - Update GEMINI.md: remove outdated session summaries and duplicate review section - Update review.md: add cleanup status section, update remaining recommendations - Update MIGRATION_PLAN.md: mark completed phases, update file references - Update DOCKER_MIGRATION_GUIDE.md: update import_csv.py path reference
49 lines
2.2 KiB
Markdown
49 lines
2.2 KiB
Markdown
# Project Overview
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This project is a sophisticated, multi-process automated trading bot for the Hyperliquid decentralized exchange. It is written in Python and uses a modular architecture to separate concerns like data fetching, strategy execution, and trade management.
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The bot uses a high-performance data pipeline with SQLite for storing market data. Trading strategies are defined and configured in a JSON file, allowing for easy adjustments without code changes. The system supports multiple, independent trading agents for risk segregation and PNL tracking. A live terminal dashboard provides real-time monitoring of market data, strategy signals, and the status of all background processes.
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## Building and Running
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### 1. Setup
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1. **Create and activate a virtual environment:**
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```bash
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# For Windows
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python -m venv .venv
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.\.venv\Scripts\activate
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# For macOS/Linux
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python3 -m venv .venv
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source .venv/bin/activate
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```
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2. **Install dependencies:**
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```bash
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pip install -r requirements.txt
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```
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3. **Configure environment variables:**
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Create a `.env` file in the root of the project (you can copy `.env.example`) and add your Hyperliquid wallet private key and any agent keys.
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4. **Configure strategies:**
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Edit `_data/strategies.json` to enable and configure your desired trading strategies.
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### 2. Running the Bot
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To run the main application, which includes the dashboard and all background processes, execute the following command:
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```bash
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python main_app.py
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```
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## Development Conventions
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* **Modularity:** The project is divided into several scripts, each with a specific responsibility (e.g., `data_fetcher.py`, `trade_executor.py`).
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* **Configuration-driven:** Strategies are defined in `_data/strategies.json`, not hardcoded. This allows for easy management of strategies.
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* **Multi-processing:** The application uses the `multiprocessing` module to run different components in parallel for performance and stability.
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* **Strategies:** Custom strategies should inherit from the `BaseStrategy` class (defined in `strategies/base_strategy.py`) and implement the `calculate_signals` method.
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* **Documentation:** The `WIKI/` directory contains detailed documentation for the project. Start with `WIKI/SUMMARY.md`.
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