diff --git a/GEMINI.md b/GEMINI.md new file mode 100644 index 0000000..89eb87c --- /dev/null +++ b/GEMINI.md @@ -0,0 +1,127 @@ +# Project Overview + +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. + +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. + +## Building and Running + +### 1. Setup + +1. **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 + ``` + +2. **Install dependencies:** + ```bash + pip install -r requirements.txt + ``` + +3. **Configure environment variables:** + 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. + +4. **Configure strategies:** + Edit `_data/strategies.json` to enable and configure your desired trading strategies. + +### 2. Running the Bot + +To run the main application, which includes the dashboard and all background processes, execute the following command: + +```bash +python main_app.py +``` + +## Development Conventions + +* **Modularity:** The project is divided into several scripts, each with a specific responsibility (e.g., `data_fetcher.py`, `trade_executor.py`). +* **Configuration-driven:** Strategies are defined in `_data/strategies.json`, not hardcoded. This allows for easy management of strategies. +* **Multi-processing:** The application uses the `multiprocessing` module to run different components in parallel for performance and stability. +* **Strategies:** Custom strategies should inherit from the `BaseStrategy` class (defined in `strategies/base_strategy.py`) and implement the `calculate_signals` method. +* **Documentation:** The `WIKI/` directory contains detailed documentation for the project. Start with `WIKI/SUMMARY.md`. + +# Project Review and Recommendations + +This review provides an analysis of the current state of the automated trading bot project, proposes specific code improvements, and identifies files that appear to be unused or are one-off utilities that could be reorganized. + +The project is a well-structured, multi-process Python application for crypto trading. It has a clear separation of concerns between data fetching, strategy execution, and trade management. The use of `multiprocessing` and a centralized `main_app.py` orchestrator is a solid architectural choice. + +The following sections detail recommendations for improving configuration management, code structure, and robustness, along with a list of files recommended for cleanup. + +--- + +## Proposed Code Changes + +### 1. Centralize Configuration + +- **Issue:** Key configuration variables like `WATCHED_COINS` and `required_timeframes` are hardcoded in `main_app.py`. This makes them difficult to change without modifying the source code. +- **Proposal:** + - Create a central configuration file, e.g., `_data/config.json`. + - Move `WATCHED_COINS` and `required_timeframes` into this new file. + - Load this configuration in `main_app.py` at startup. +- **Benefit:** Decouples configuration from code, making the application more flexible and easier to manage. + +### 2. Refactor `main_app.py` for Clarity + +- **Issue:** `main_app.py` is long and handles multiple responsibilities: process orchestration, dashboard rendering, and data reading. +- **Proposal:** + - **Abstract Process Management:** The functions for running subprocesses (e.g., `run_live_candle_fetcher`, `run_resampler_job`) contain repetitive logic for logging, shutdown handling, and process looping. This could be abstracted into a generic `ProcessRunner` class. + - **Create a Dashboard Class:** The complex dashboard rendering logic could be moved into a separate `Dashboard` class to improve separation of concerns and make the main application loop cleaner. +- **Benefit:** Improves code readability, reduces duplication, and makes the application easier to maintain and extend. + +### 3. Improve Project Structure + +- **Issue:** The root directory is cluttered with numerous Python scripts, making it difficult to distinguish between core application files, utility scripts, and old/example files. +- **Proposal:** + - Create a `scripts/` directory and move all one-off utility and maintenance scripts into it. + - Consider creating a `src/` or `app/` directory to house the core application source code (`main_app.py`, `trade_executor.py`, etc.), separating it clearly from configuration, data, and documentation. +- **Benefit:** A cleaner, more organized project structure that is easier for new developers to understand. + +### 4. Enhance Robustness and Error Handling + +- **Issue:** The agent loading in `trade_executor.py` relies on discovering environment variables by a naming convention (`_AGENT_PK`). This is clever but can be brittle if environment variables are named incorrectly. +- **Proposal:** + - Explicitly define the agent names and their corresponding environment variable keys in the proposed `_data/config.json` file. The `trade_executor` would then load only the agents specified in the configuration. +- **Benefit:** Makes agent configuration more explicit and less prone to errors from stray environment variables. + +--- + +## Identified Unused/Utility Files + +The following files were identified as likely being unused by the core application, being obsolete, or serving as one-off utilities. It is recommended to **move them to a `scripts/` directory** or **delete them** if they are obsolete. + +### Obsolete / Old Versions: +- `data_fetcher_old.py` +- `market_old.py` +- `base_strategy.py` (The one in the root directory; the one in `strategies/` is used). + +### One-Off Utility Scripts (Recommend moving to `scripts/`): +- `!migrate_to_sqlite.py` +- `import_csv.py` +- `del_market_cap_tables.py` +- `fix_timestamps.py` +- `list_coins.py` +- `create_agent.py` + +### Examples / Unused Code: +- `basic_ws.py` (Appears to be an example file). +- `backtester.py` +- `strategy_sma_cross.py` (A strategy file in the root, not in the `strategies` folder). +- `strategy_template.py` + +### Standalone / Potentially Unused Core Files: +The following files seem to have their logic already integrated into the main multi-process application. They might be remnants of a previous architecture and may not be needed as standalone scripts. +- `address_monitor.py` +- `position_monitor.py` +- `trade_log.py` +- `wallet_data.py` +- `whale_tracker.py` + +### Data / Log Files (Recommend archiving or deleting): +- `hyperliquid_wallet_data_*.json` (These appear to be backups or logs). \ No newline at end of file diff --git a/IMPROVEMENT_ROADMAP.md b/IMPROVEMENT_ROADMAP.md new file mode 100644 index 0000000..503fad1 --- /dev/null +++ b/IMPROVEMENT_ROADMAP.md @@ -0,0 +1,300 @@ +# Improvement Roadmap - Hyperliquid Trading Bot + +## Overview +This document outlines the detailed implementation plan for transforming the trading bot into a production-ready system. + +## Phase 1: Foundation (Weeks 1-2) + +### Week 1: Security & Stability + +#### Day 1-2: Critical Security Fixes +- [ ] **Implement Encrypted Key Storage** + - Create `security/key_manager.py` + - Replace environment variable key access + - Add key rotation mechanism + - **Files**: `trade_executor.py`, `create_agent.py` + +- [ ] **Add Input Validation Framework** + - Create `validation/trading_validator.py` + - Validate all trading parameters + - Add sanitization for user inputs + - **Files**: `position_manager.py`, `trade_executor.py` + +#### Day 3-4: Risk Management +- [ ] **Implement Circuit Breakers** + - Create `risk/circuit_breaker.py` + - Add trading halt conditions + - Implement automatic recovery + - **Files**: `trade_executor.py`, `position_manager.py` + +- [ ] **Fix Import Resolution Issues** + - Update relative imports + - Add `__init__.py` files where missing + - Test all module imports + - **Files**: `main_app.py`, all strategy files + +#### Day 5-7: Code Quality +- [ ] **Refactor Dashboard Display** + - Extract `DashboardRenderer` class + - Split into market/strategy/position components + - Add configuration for display options + - **Files**: `main_app.py` + +### Week 2: Configuration & Error Handling + +#### Day 8-9: Configuration Management +- [ ] **Create Centralized Configuration** + - Create `config/settings.py` + - Move all magic numbers to config + - Add environment-specific configs + - **Files**: All Python files + +- [ ] **Standardize Error Handling** + - Create `utils/error_handlers.py` + - Implement retry decorators + - Add structured exception classes + - **Files**: All core modules + +#### Day 10-12: Database Improvements +- [ ] **Implement Connection Pool** + - Create `database/connection_pool.py` + - Replace direct SQLite connections + - Add connection health monitoring + - **Files**: `base_strategy.py`, all data access files + +- [ ] **Add Database Migrations** + - Create `database/migrations/` + - Version control schema changes + - Add rollback capabilities + - **Files**: Database schema files + +#### Day 13-14: Basic Testing +- [ ] **Create Test Framework** + - Set up `tests/` directory structure + - Add pytest configuration + - Create test fixtures and mocks + - **Files**: New test files + +## Phase 2: Performance & Testing (Weeks 3-4) + +### Week 3: Performance Optimization + +#### Day 15-17: Caching Layer +- [ ] **Implement Redis/Memory Cache** + - Create `cache/cache_manager.py` + - Cache frequently accessed data + - Add cache invalidation logic + - **Files**: `data_fetcher.py`, `base_strategy.py` + +#### Day 18-19: Async Operations +- [ ] **Convert to Async/Await** + - Identify blocking operations + - Convert to async patterns + - Add async context managers + - **Files**: `live_market_utils.py`, API calls + +#### Day 20-21: Batch Processing +- [ ] **Implement Batch Operations** + - Batch database writes + - Bulk API requests + - Optimize data processing + - **Files**: Data processing modules + +### Week 4: Testing Framework + +#### Day 22-24: Unit Tests +- [ ] **Comprehensive Unit Test Suite** + - Test all core classes + - Mock external dependencies + - Achieve >80% coverage + - **Files**: `tests/unit/` + +#### Day 25-26: Integration Tests +- [ ] **End-to-End Testing** + - Test complete workflows + - Mock Hyperliquid API + - Test process communication + - **Files**: `tests/integration/` + +#### Day 27-28: Paper Trading +- [ ] **Paper Trading Mode** + - Create simulation environment + - Mock trade execution + - Add performance tracking + - **Files**: `trade_executor.py`, new simulation files + +## Phase 3: Monitoring & Observability (Weeks 5-6) + +### Week 5: Metrics & Monitoring + +#### Day 29-31: Metrics Collection +- [ ] **Add Prometheus Metrics** + - Create `monitoring/metrics.py` + - Track key performance indicators + - Add custom business metrics + - **Files**: All core modules + +#### Day 32-33: Health Checks +- [ ] **Health Check System** + - Create `monitoring/health_check.py` + - Monitor all system components + - Add dependency checks + - **Files**: `main_app.py`, all processes + +#### Day 34-35: Alerting +- [ ] **Alerting System** + - Create `monitoring/alerts.py` + - Configure alert rules + - Add notification channels + - **Files**: New alerting files + +### Week 6: Documentation & Developer Experience + +#### Day 36-38: API Documentation +- [ ] **Auto-Generated Docs** + - Set up Sphinx/ MkDocs + - Document all public APIs + - Add code examples + - **Files**: `docs/` directory + +#### Day 39-40: Setup Improvements +- [ ] **Interactive Setup** + - Create setup wizard + - Validate configuration + - Add guided configuration + - **Files**: `setup.py`, new setup files + +#### Day 41-42: Examples & Guides +- [ ] **Strategy Examples** + - Create example strategies + - Add development tutorials + - Document best practices + - **Files**: `examples/`, `WIKI/` + +## Phase 4: Advanced Features (Weeks 7-8) + +### Week 7: Advanced Risk Management + +#### Day 43-45: Position Sizing +- [ ] **Dynamic Position Sizing** + - Volatility-based sizing + - Portfolio risk metrics + - Kelly criterion implementation + - **Files**: `position_manager.py`, new risk modules + +#### Day 46-47: Advanced Orders +- [ ] **Advanced Order Types** + - Stop-loss orders + - Take-profit orders + - Conditional orders + - **Files**: `trade_executor.py` + +#### Day 48-49: Portfolio Management +- [ ] **Portfolio Optimization** + - Correlation analysis + - Risk parity allocation + - Rebalancing logic + - **Files**: New portfolio modules + +### Week 8: Production Readiness + +#### Day 50-52: Deployment +- [ ] **Production Deployment** + - Docker containerization + - Kubernetes manifests + - CI/CD pipeline + - **Files**: `docker/`, `.github/workflows/` + +#### Day 53-54: Performance Profiling +- [ ] **Profiling Tools** + - Performance monitoring + - Memory usage tracking + - Bottleneck identification + - **Files**: New profiling modules + +#### Day 55-56: Final Polish +- [ ] **Production Hardening** + - Security audit + - Load testing + - Documentation review + - **Files**: All files + +## Implementation Guidelines + +### Daily Workflow +1. **Morning Standup**: Review progress, identify blockers +2. **Development**: Focus on assigned tasks +3. **Testing**: Write tests alongside code +4. **Code Review**: Peer review all changes +5. **Documentation**: Update docs with changes + +### Quality Gates +- All code must pass linting and formatting +- New features require unit tests +- Integration tests for critical paths +- Security review for sensitive changes + +### Risk Mitigation +- Feature flags for new functionality +- Gradual rollout with monitoring +- Rollback procedures for each change +- Regular backup and recovery testing + +## Success Criteria + +### Phase 1 Success +- [ ] All security vulnerabilities fixed +- [ ] Import resolution issues resolved +- [ ] Basic test framework in place +- [ ] Configuration management implemented + +### Phase 2 Success +- [ ] Performance improvements measured +- [ ] Test coverage >80% +- [ ] Paper trading mode functional +- [ ] Async operations implemented + +### Phase 3 Success +- [ ] Monitoring dashboard operational +- [ ] Alerting system functional +- [ ] Documentation complete +- [ ] Developer experience improved + +### Phase 4 Success +- [ ] Production deployment ready +- [ ] Advanced features working +- [ ] Performance benchmarks met +- [ ] Security audit passed + +## Resource Requirements + +### Development Team +- **Senior Python Developer**: Lead architecture and security +- **Backend Developer**: Performance and database optimization +- **DevOps Engineer**: Deployment and monitoring +- **QA Engineer**: Testing framework and automation + +### Tools & Services +- **Development**: PyCharm/VSCode, Git, Docker +- **Testing**: Pytest, Mock, Coverage tools +- **Monitoring**: Prometheus, Grafana, AlertManager +- **CI/CD**: GitHub Actions, Docker Hub +- **Documentation**: Sphinx/MkDocs, ReadTheDocs + +### Infrastructure +- **Development**: Local development environment +- **Testing**: Staging environment with test data +- **Production**: Cloud deployment with monitoring +- **Backup**: Automated backup and recovery system + +## Timeline Summary + +| Phase | Duration | Key Deliverables | +|-------|----------|------------------| +| Phase 1 | 2 weeks | Security fixes, basic testing, configuration | +| Phase 2 | 2 weeks | Performance optimization, comprehensive testing | +| Phase 3 | 2 weeks | Monitoring, documentation, developer tools | +| Phase 4 | 2 weeks | Advanced features, production deployment | +| **Total** | **8 weeks** | **Production-ready trading system** | + +This roadmap provides a structured approach to transforming the trading bot into a robust, scalable, and maintainable system suitable for production use. \ No newline at end of file diff --git a/PROJECT_REVIEW_AND_PROPOSALS.md b/PROJECT_REVIEW_AND_PROPOSALS.md new file mode 100644 index 0000000..e96a1da --- /dev/null +++ b/PROJECT_REVIEW_AND_PROPOSALS.md @@ -0,0 +1 @@ +"# Comprehensive Project Review and Improvement Proposals" diff --git a/_data/backtesting_conf.json b/_data/backtesting_conf.json index 66c76cf..aec37b7 100644 --- a/_data/backtesting_conf.json +++ b/_data/backtesting_conf.json @@ -1,6 +1,6 @@ { "sma_cross_eth_5m": { - "strategy_name": "sma_cross_2", + "strategy_name": "sma_cross_1", "script": "strategies.ma_cross_strategy.MaCrossStrategy", "optimization_params": { "fast": { diff --git a/_data/coin_id_map.json b/_data/coin_id_map.json new file mode 100644 index 0000000..f6c9d78 --- /dev/null +++ b/_data/coin_id_map.json @@ -0,0 +1,208 @@ +{ + "0G": "zero-gravity", + "2Z": "doublezero", + "AAVE": "aave", + "ACE": "endurance", + "ADA": "ada-the-dog", + "AI": "sleepless-ai", + "AI16Z": "ai16z", + "AIXBT": "aixbt", + "ALGO": "dear-algorithm", + "ALT": "altlayer", + "ANIME": "anime-token", + "APE": "ape-3", + "APEX": "apex-token-2", + "APT": "aptos", + "AR": "arweave", + "ARB": "osmosis-allarb", + "ARK": "ark-3", + "ASTER": "astar", + "ATOM": "lost-bitcoin-layer", + "AVAX": "binance-peg-avalanche", + "AVNT": "avantis", + "BABY": "baby-2", + "BADGER": "badger-dao", + "BANANA": "nforbanana", + "BCH": "bitcoin-cash", + "BERA": "berachain-bera", + "BIGTIME": "big-time", + "BIO": "bio-protocol", + "BLAST": "blast", + "BLUR": "blur", + "BLZ": "bluzelle", + "BNB": "binancecoin", + "BNT": "bancor", + "BOME": "book-of-meme", + "BRETT": "brett", + "BSV": "bitcoin-cash-sv", + "BTC": "bitcoin", + "CAKE": "pancakeswap-token", + "CANTO": "canto", + "CATI": "catizen", + "CELO": "celo", + "CFX": "cosmic-force-token-v2", + "CHILLGUY": "just-a-chill-guy", + "COMP": "compound-governance-token", + "CRV": "curve-dao-token", + "CYBER": "cyberconnect", + "DOGE": "doge-on-pulsechain", + "DOOD": "doodles", + "DOT": "xcdot", + "DYDX": "dydx-chain", + "DYM": "dymension", + "EIGEN": "eigenlayer", + "ENA": "ethena", + "ENS": "ethereum-name-service", + "ETC": "ethereum-classic", + "ETH": "ethereum", + "ETHFI": "ether-fi", + "FARTCOIN": "fartcoin-2", + "FET": "fetch-ai", + "FIL": "filecoin", + "FRIEND": "friend-tech", + "FTM": "fantom", + "FTT": "ftx-token", + "GALA": "gala", + "GAS": "gas", + "GMT": "stepn", + "GMX": "gmx", + "GOAT": "goat", + "GRASS": "grass-3", + "GRIFFAIN": "griffain", + "HBAR": "hedera-hashgraph", + "HEMI": "hemi", + "HMSTR": "hamster-kombat", + "HYPE": "hyperliquid", + "HYPER": "hyper-4", + "ILV": "illuvium", + "IMX": "immutable-x", + "INIT": "initia", + "INJ": "injective-protocol", + "IO": "io", + "IOTA": "iota-2", + "IP": "story-2", + "JELLY": "jelly-time", + "JTO": "jito-governance-token", + "JUP": "jupiter-exchange-solana", + "KAITO": "kaito", + "KAS": "wrapped-kaspa", + "LAUNCHCOIN": "ben-pasternak", + "LAYER": "unilayer", + "LDO": "linea-bridged-ldo-linea", + "LINEA": "linea", + "LINK": "osmosis-alllink", + "LISTA": "lista", + "LOOM": "loom", + "LTC": "litecoin", + "MANTA": "manta-network", + "MATIC": "matic-network", + "MAV": "maverick-protocol", + "MAVIA": "heroes-of-mavia", + "ME": "magic-eden", + "MEGA": "megaeth", + "MELANIA": "melania-meme", + "MEME": "mpx6900", + "MERL": "merlin-chain", + "MET": "metya", + "MEW": "cat-in-a-dogs-world", + "MINA": "mina-protocol", + "MKR": "maker", + "MNT": "mynth", + "MON": "mon-protocol", + "MOODENG": "moo-deng-2", + "MORPHO": "morpho", + "MOVE": "movement", + "MYRO": "myro", + "NEAR": "near", + "NEO": "neo", + "NIL": "nillion", + "NOT": "nothing-3", + "NTRN": "neutron-3", + "NXPC": "nexpace", + "OGN": "origin-protocol", + "OM": "mantra-dao", + "OMNI": "omni-2", + "ONDO": "ondo-finance", + "OP": "optimism", + "ORBS": "orbs", + "ORDI": "ordinals", + "OX": "ox-fun", + "PANDORA": "pandora", + "PAXG": "pax-gold", + "PENDLE": "pendle", + "PENGU": "pudgy-penguins", + "PEOPLE": "constitutiondao-wormhole", + "PIXEL": "pixel-3", + "PNUT": "pnut", + "POL": "proof-of-liquidity", + "POLYX": "polymesh", + "POPCAT": "popcat", + "PROMPT": "wayfinder", + "PROVE": "succinct", + "PUMP": "pump-fun", + "PURR": "purr-2", + "PYTH": "pyth-network", + "RDNT": "radiant-capital", + "RENDER": "render-token", + "REQ": "request-network", + "RESOLV": "resolv", + "REZ": "renzo", + "RLB": "rollbit-coin", + "RSR": "reserve-rights-token", + "RUNE": "thorchain", + "S": "token-s", + "SAGA": "saga-2", + "SAND": "the-sandbox-wormhole", + "SCR": "scroll", + "SEI": "sei-network", + "SHIA": "shiba-saga", + "SKY": "sky", + "SNX": "havven", + "SOL": "solana", + "SOPH": "sophon", + "SPX": "spx6900", + "STBL": "stbl", + "STG": "stargate-finance", + "STRAX": "stratis", + "STRK": "starknet", + "STX": "stox", + "SUI": "sui", + "SUPER": "superfarm", + "SUSHI": "sushi", + "SYRUP": "syrup", + "TAO": "the-anthropic-order", + "TIA": "tia", + "TNSR": "tensorium", + "TON": "tontoken", + "TRB": "tellor", + "TRUMP": "trumpeffect69420", + "TRX": "tron-bsc", + "TST": "test-3", + "TURBO": "turbo", + "UMA": "uma", + "UNI": "uni", + "UNIBOT": "unibot", + "USTC": "wrapped-ust", + "USUAL": "usual", + "VINE": "vine", + "VIRTUAL": "virtual-protocol", + "VVV": "venice-token", + "W": "w", + "WCT": "connect-token-wct", + "WIF": "wif-secondchance", + "WLD": "worldcoin-wld", + "WLFI": "world-liberty-financial", + "XAI": "xai-blockchain", + "XLM": "stellar", + "XPL": "pulse-2", + "XRP": "ripple", + "YGG": "yield-guild-games", + "YZY": "yzy", + "ZEC": "zcash", + "ZEN": "zenith-3", + "ZEREBRO": "zerebro", + "ZETA": "zeta", + "ZK": "zksync", + "ZORA": "zora", + "ZRO": "layerzero" +} \ No newline at end of file diff --git a/_data/coin_precision.json b/_data/coin_precision.json index fb9d0e8..7d927f3 100644 --- a/_data/coin_precision.json +++ b/_data/coin_precision.json @@ -101,6 +101,7 @@ "MAV": 0, "MAVIA": 1, "ME": 1, + "MEGA": 0, "MELANIA": 1, "MEME": 0, "MERL": 0, diff --git a/_data/executor_managed_positions.json b/_data/executor_managed_positions.json deleted file mode 100644 index 4a80fe9..0000000 --- a/_data/executor_managed_positions.json +++ /dev/null @@ -1,7 +0,0 @@ -{ - "sma_cross_2": { - "coin": "BTC", - "side": "short", - "size": 0.0001 - } -} \ No newline at end of file diff --git a/_data/market_cap_data.json b/_data/market_cap_data.json index 967c76d..45b1096 100644 --- a/_data/market_cap_data.json +++ b/_data/market_cap_data.json @@ -1,47 +1,1043 @@ 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e4ad53e..8ea4a3a 100644 --- a/_data/strategies.json +++ b/_data/strategies.json @@ -1,12 +1,11 @@ { - "sma_cross_eth_5m": { - "enabled": true, - "script": "strategy_runner.py", + "sma_cross_1": { + "enabled": false, "class": "strategies.ma_cross_strategy.MaCrossStrategy", "agent": "scalper_agent", "parameters": { "coin": "ETH", - "timeframe": "1m", + "timeframe": "15m", "short_ma": 7, "long_ma": 44, "size": 0.0055, @@ -14,19 +13,39 @@ "leverage_short": 5 } }, - "sma_125d_btc": { - "enabled": true, - "script": "strategy_runner.py", + "sma_44d_btc": { + "enabled": false, "class": "strategies.single_sma_strategy.SingleSmaStrategy", - "agent": "swing_agent", "parameters": { + "agent": "swing", "coin": "BTC", "timeframe": "1d", "sma_period": 44, "size": 0.0001, - "leverage_long": 2, + "leverage_long": 3, "leverage_short": 1 } + }, + "copy_trader_eth": { + "enabled": true, + "is_event_driven": true, + "class": "strategies.copy_trader_strategy.CopyTraderStrategy", + "parameters": { + "agent": "scalper", + "target_address": "0x32885a6adac4375858E6edC092EfDDb0Ef46484C", + "coins_to_copy": { + "ETH": { + "size": 0.0055, + "leverage_long": 3, + "leverage_short": 3 + }, + "BTC": { + "size": 0.0002, + "leverage_long": 1, + "leverage_short": 1 + } + } + } } } diff --git a/_data/strategy_state_copy_trader_eth.json b/_data/strategy_state_copy_trader_eth.json new file mode 100644 index 0000000..003ccf3 --- /dev/null +++ b/_data/strategy_state_copy_trader_eth.json @@ -0,0 +1,7 @@ +{ + "ETH": { + "side": "long", + "size": 0.018, + "entry": 3864.2 + } +} \ No newline at end of file diff --git a/_data/strategy_status_copy_trader_eth.json b/_data/strategy_status_copy_trader_eth.json new file mode 100644 index 0000000..c75c89a --- /dev/null +++ b/_data/strategy_status_copy_trader_eth.json @@ -0,0 +1,7 @@ +{ + "strategy_name": "copy_trader_eth", + "current_signal": "WAIT", + "last_signal_change_utc": null, + "signal_price": null, + "last_checked_utc": "2025-11-02T09:55:08.460168+00:00" +} \ No newline at end of file diff --git a/_data/strategy_status_ma_cross_btc.json b/_data/strategy_status_ma_cross_btc.json deleted file mode 100644 index 7882e85..0000000 --- a/_data/strategy_status_ma_cross_btc.json +++ /dev/null @@ -1,7 +0,0 @@ -{ - "strategy_name": "ma_cross_btc", - "current_signal": "HOLD", - "last_signal_change_utc": "2025-10-12T17:00:00+00:00", - "signal_price": 114286.0, - "last_checked_utc": "2025-10-15T11:48:55.092260+00:00" -} \ No newline at end of file diff --git a/_data/strategy_status_sma_125d_btc.json b/_data/strategy_status_sma_125d_btc.json deleted file mode 100644 index 4932ea0..0000000 --- a/_data/strategy_status_sma_125d_btc.json +++ /dev/null @@ -1,7 +0,0 @@ -{ - "strategy_name": "sma_125d_btc", - "current_signal": "SELL", - "last_signal_change_utc": "2025-10-14T00:00:00+00:00", - "signal_price": 113026.0, - "last_checked_utc": "2025-10-16T10:42:03.203292+00:00" -} \ No newline at end of file diff --git a/_data/strategy_status_sma_125d_eth.json b/_data/strategy_status_sma_125d_eth.json deleted file mode 100644 index 5c77164..0000000 --- a/_data/strategy_status_sma_125d_eth.json +++ /dev/null @@ -1,7 +0,0 @@ -{ - "strategy_name": "sma_125d_eth", - "current_signal": "BUY", - "last_signal_change_utc": "2025-08-26T00:00:00+00:00", - "signal_price": 4600.63, - "last_checked_utc": "2025-10-15T17:35:17.663159+00:00" -} \ No newline at end of file diff --git a/_data/strategy_status_sma_44d_btc.json b/_data/strategy_status_sma_44d_btc.json deleted file mode 100644 index f7966e0..0000000 --- a/_data/strategy_status_sma_44d_btc.json +++ /dev/null @@ -1,7 +0,0 @@ -{ - "strategy_name": "sma_44d_btc", - "current_signal": "SELL", - "last_signal_change_utc": "2025-10-14T00:00:00+00:00", - "signal_price": 113026.0, - "last_checked_utc": "2025-10-16T10:42:03.202977+00:00" -} \ No newline at end of file diff --git a/_data/strategy_status_sma_5m_eth.json b/_data/strategy_status_sma_5m_eth.json deleted file mode 100644 index e136da7..0000000 --- a/_data/strategy_status_sma_5m_eth.json +++ /dev/null @@ -1,7 +0,0 @@ -{ - "strategy_name": "sma_5m_eth", - "current_signal": "SELL", - "last_signal_change_utc": "2025-10-15T17:30:00+00:00", - "signal_price": 3937.5, - "last_checked_utc": "2025-10-15T17:35:05.035566+00:00" -} \ No newline at end of file diff --git a/_data/strategy_status_sma_cross.json b/_data/strategy_status_sma_cross.json deleted file mode 100644 index f51a39e..0000000 --- a/_data/strategy_status_sma_cross.json +++ /dev/null @@ -1,7 +0,0 @@ -{ - "strategy_name": "sma_cross", - "current_signal": "SELL", - "last_signal_change_utc": "2025-10-15T11:45:00+00:00", - "signal_price": 111957.0, - "last_checked_utc": "2025-10-15T12:10:05.048434+00:00" -} \ No newline at end of file diff --git a/_data/strategy_status_sma_cross_1.json b/_data/strategy_status_sma_cross_1.json deleted file mode 100644 index e9a5b44..0000000 --- a/_data/strategy_status_sma_cross_1.json +++ /dev/null @@ -1,7 +0,0 @@ -{ - "strategy_name": "sma_cross_1", - "current_signal": "FLAT", - "last_signal_change_utc": "2025-10-18T20:22:00+00:00", - "signal_price": 3893.9, - "last_checked_utc": "2025-10-18T20:30:05.021192+00:00" -} \ No newline at end of file diff --git a/_data/strategy_status_sma_cross_eth_5m.json b/_data/strategy_status_sma_cross_eth_5m.json deleted file mode 100644 index 58400d0..0000000 --- a/_data/strategy_status_sma_cross_eth_5m.json +++ /dev/null @@ -1,7 +0,0 @@ -{ - "strategy_name": "sma_cross_eth_5m", - "current_signal": "SELL", - "last_signal_change_utc": "2025-10-15T11:45:00+00:00", - "signal_price": 4106.1, - "last_checked_utc": "2025-10-15T12:05:05.022308+00:00" -} \ No newline at end of file diff --git a/_data/wallets_info.json b/_data/wallets_info.json new file mode 100644 index 0000000..222a8f6 --- /dev/null +++ b/_data/wallets_info.json @@ -0,0 +1,290 @@ +{ + "Whale 1 (BTC Maxi)": { + "address": "0xb83de012dba672c76a7dbbbf3e459cb59d7d6e36", + "core_state": { + "raw_state": { + "marginSummary": { + "accountValue": "30018881.1193690002", + "totalNtlPos": "182930683.6996490061", + "totalRawUsd": "212949564.8190180063", + "totalMarginUsed": "22969943.9848450013" + }, + "crossMarginSummary": { + "accountValue": "30018881.1193690002", + "totalNtlPos": "182930683.6996490061", + "totalRawUsd": "212949564.8190180063", + "totalMarginUsed": "22969943.9848450013" + }, + "crossMaintenanceMarginUsed": "5420634.4984849999", + "withdrawable": "7043396.1885489998", + "assetPositions": [ + { + "type": "oneWay", + "position": { + "coin": "BTC", + "szi": "-546.94441", + "leverage": { + "type": "cross", + "value": 10 + }, + "entryPx": "115183.2", + "positionValue": "62795781.6009199992", + "unrealizedPnl": "203045.067519", + "returnOnEquity": "0.0322299761", + "liquidationPx": "159230.7089577085", + "marginUsed": "6279578.1600919999", + "maxLeverage": 40, + "cumFunding": { + "allTime": "-6923407.0911370004", + "sinceOpen": "-6923407.0970780002", + "sinceChange": "-1574.188052" + } + } + }, + { + "type": "oneWay", + "position": { + "coin": "ETH", + "szi": "-13938.989", + "leverage": { + "type": "cross", + "value": 10 + }, + "entryPx": "4106.64", + "positionValue": "58064252.5784000009", + "unrealizedPnl": "-821803.895073", + "returnOnEquity": "-0.1435654683", + "liquidationPx": "5895.7059682083", + "marginUsed": "5806425.2578400001", + "maxLeverage": 25, + "cumFunding": { + "allTime": "-6610045.8844170002", + "sinceOpen": "-6610045.8844170002", + "sinceChange": "-730.403023" + } + } + }, + { + "type": "oneWay", + "position": { + "coin": "SOL", + "szi": "-75080.68", + "leverage": { + "type": "cross", + "value": 10 + }, + "entryPx": "201.3063", + "positionValue": "14975592.4328000005", + "unrealizedPnl": "138627.573942", + "returnOnEquity": "0.0917199656", + "liquidationPx": "519.0933515657", + "marginUsed": "1497559.2432800001", + "maxLeverage": 20, + "cumFunding": { + "allTime": "-792893.154387", + "sinceOpen": "-922.301401", + "sinceChange": "-187.682929" + } + } + }, + { + "type": "oneWay", + "position": { + "coin": "DOGE", + "szi": "-109217.0", + "leverage": { + "type": "cross", + "value": 10 + }, + "entryPx": "0.279959", + "positionValue": "22081.49306", + "unrealizedPnl": "8494.879599", + "returnOnEquity": "2.7782496288", + "liquidationPx": "213.2654356057", + "marginUsed": "2208.149306", + "maxLeverage": 10, + "cumFunding": { + "allTime": "-1875.469799", + "sinceOpen": "-1875.469799", + "sinceChange": "45.79339" + } + } + }, + { + "type": "oneWay", + "position": { + "coin": "INJ", + "szi": "-18747.2", + "leverage": { + "type": "cross", + "value": 3 + }, + "entryPx": "13.01496", + "positionValue": "162200.7744", + "unrealizedPnl": "81793.4435", + "returnOnEquity": "1.005680924", + "liquidationPx": "1208.3529290194", + "marginUsed": "54066.9248", + "maxLeverage": 10, + "cumFunding": { + "allTime": "-539.133533", + "sinceOpen": "-539.133533", + "sinceChange": "-7.367325" + } + } + }, + { + "type": "oneWay", + "position": { + "coin": "SUI", + "szi": "-376577.6", + "leverage": { + "type": "cross", + "value": 3 + }, + "entryPx": "3.85881", + "positionValue": "989495.3017599999", + "unrealizedPnl": "463648.956001", + "returnOnEquity": "0.9571980625", + "liquidationPx": "64.3045458208", + "marginUsed": "329831.767253", + "maxLeverage": 10, + "cumFunding": { + "allTime": "-45793.455728", + "sinceOpen": "-45793.450891", + "sinceChange": "-1233.875821" + } + } + }, + { + "type": "oneWay", + "position": { + "coin": "XRP", + "szi": "-39691.0", + "leverage": { + "type": "cross", + "value": 20 + }, + "entryPx": "2.468585", + "positionValue": "105486.7707", + "unrealizedPnl": "-7506.1484", + "returnOnEquity": "-1.5321699789", + "liquidationPx": "607.2856858464", + "marginUsed": "5274.338535", + "maxLeverage": 20, + "cumFunding": { + "allTime": "-2645.400002", + "sinceOpen": "-116.036833", + "sinceChange": "-116.036833" + } + } + }, + { + "type": "oneWay", + "position": { + "coin": "HYPE", + "szi": "-750315.16", + "leverage": { + "type": "cross", + "value": 5 + }, + "entryPx": "43.3419", + "positionValue": "34957933.6195600033", + "unrealizedPnl": "-2437823.0249080001", + "returnOnEquity": "-0.3748177636", + "liquidationPx": "76.3945326684", + "marginUsed": "6991586.7239119997", + "maxLeverage": 5, + "cumFunding": { + "allTime": "-1881584.4214250001", + "sinceOpen": "-1881584.4214250001", + "sinceChange": "-45247.838743" + } + } + }, + { + "type": "oneWay", + "position": { + "coin": "FARTCOIN", + "szi": "-4122236.7999999998", + "leverage": { + "type": "cross", + "value": 10 + }, + "entryPx": "0.80127", + "positionValue": "1681584.057824", + "unrealizedPnl": "1621478.3279619999", + "returnOnEquity": "4.9090151459", + "liquidationPx": "6.034656163", + "marginUsed": "168158.405782", + "maxLeverage": 10, + "cumFunding": { + "allTime": "-72941.395024", + "sinceOpen": "-51271.5204", + "sinceChange": "-6504.295598" + } + } + }, + { + "type": "oneWay", + "position": { + "coin": "PUMP", + "szi": "-1921732999.0", + "leverage": { + "type": "cross", + "value": 5 + }, + "entryPx": "0.005551", + "positionValue": "9176275.0702250004", + "unrealizedPnl": "1491738.24016", + "returnOnEquity": "0.6991640321", + "liquidationPx": "0.0166674064", + "marginUsed": "1835255.0140450001", + "maxLeverage": 10, + "cumFunding": { + "allTime": "-196004.534539", + "sinceOpen": "-196004.534539", + "sinceChange": "-9892.654861" + } + } + } + ], + "time": 1761595358385 + }, + "account_value": 30018881.119369, + "margin_used": 22969943.984845, + "margin_utilization": 0.765183215640378, + "available_margin": 7048937.134523999, + "total_position_value": 0.0, + "portfolio_leverage": 0.0 + }, + "open_orders": { + "raw_orders": [ + { + "coin": "WLFI", + "side": "B", + "limitPx": "0.10447", + "sz": "2624.0", + "oid": 194029229960, + "timestamp": 1760131688558, + "origSz": "12760.0", + "cloid": "0x00000000000000000000001261000016" + }, + { + "coin": "@166", + "side": "A", + "limitPx": "1.01", + "sz": "103038.77", + "oid": 174787748753, + "timestamp": 1758819420037, + "origSz": "3000000.0" + } + ] + }, + "account_metrics": { + "cumVlm": "2823125892.6900000572", + "nRequestsUsed": 1766294, + "nRequestsCap": 2823135892 + } + } +} \ No newline at end of file diff --git a/_data/wallets_to_track.json b/_data/wallets_to_track.json new file mode 100644 index 0000000..bcb906d --- /dev/null +++ b/_data/wallets_to_track.json @@ -0,0 +1,7 @@ +[ + { + "name": "Whale 1 (BTC Maxi)", + "address": "0xb83de012dba672c76a7dbbbf3e459cb59d7d6e36", + "tags": ["btc", "high_leverage"] + } +] diff --git a/address_monitor.py b/address_monitor.py index 9bd768a..ced5e44 100644 --- a/address_monitor.py +++ b/address_monitor.py @@ -15,13 +15,13 @@ from logging_utils import setup_logging # --- Configuration --- DEFAULT_ADDRESSES_TO_WATCH = [ #"0xd4c1f7e8d876c4749228d515473d36f919583d1d", - "0x0fd468a73084daa6ea77a9261e40fdec3e67e0c7", + "0x47930c76790c865217472f2ddb4d14c640ee450a", # "0x4d69495d16fab95c3c27b76978affa50301079d0", # "0x09bc1cf4d9f0b59e1425a8fde4d4b1f7d3c9410d", "0xc6ac58a7a63339898aeda32499a8238a46d88e84", "0xa8ef95dbd3db55911d3307930a84b27d6e969526", # "0x4129c62faf652fea61375dcd9ca8ce24b2bb8b95", - "0xbf1935fe7ab6d0aa3ee8d3da47c2f80e215b2a1c", + "0x32885a6adac4375858E6edC092EfDDb0Ef46484C", ] MAX_FILLS_TO_DISPLAY = 10 LOGS_DIR = "_logs" diff --git a/app.py b/app.py deleted file mode 100644 index e69de29..0000000 diff --git a/base_strategy.py b/base_strategy.py new file mode 100644 index 0000000..5f0a001 --- /dev/null +++ b/base_strategy.py @@ -0,0 +1,165 @@ +from abc import ABC, abstractmethod +import pandas as pd +import json +import os +import logging +from datetime import datetime, timezone +import sqlite3 +import multiprocessing +import time + +from logging_utils import setup_logging +from hyperliquid.info import Info +from hyperliquid.utils import constants + +class BaseStrategy(ABC): + """ + An abstract base class that defines the blueprint for all trading strategies. + It provides common functionality like loading data, saving status, and state management. + """ + + def __init__(self, strategy_name: str, params: dict, trade_signal_queue: multiprocessing.Queue = None, shared_status: dict = None): + self.strategy_name = strategy_name + self.params = params + self.trade_signal_queue = trade_signal_queue + # Optional multiprocessing.Manager().dict() to hold live status (avoids file IO) + self.shared_status = shared_status + + self.coin = params.get("coin", "N/A") + self.timeframe = params.get("timeframe", "N/A") + self.db_path = os.path.join("_data", "market_data.db") + self.status_file_path = os.path.join("_data", f"strategy_status_{self.strategy_name}.json") + + self.current_signal = "INIT" + self.last_signal_change_utc = None + self.signal_price = None + + # Note: Logging is set up by the run_strategy function + + def load_data(self) -> pd.DataFrame: + """Loads historical data for the configured coin and timeframe.""" + table_name = f"{self.coin}_{self.timeframe}" + + periods = [v for k, v in self.params.items() if 'period' in k or '_ma' in k or 'slow' in k or 'fast' in k] + limit = max(periods) + 50 if periods else 500 + + try: + with sqlite3.connect(f"file:{self.db_path}?mode=ro", uri=True) as conn: + query = f'SELECT * FROM "{table_name}" ORDER BY datetime_utc DESC LIMIT {limit}' + df = pd.read_sql(query, conn, parse_dates=['datetime_utc']) + if df.empty: return pd.DataFrame() + df.set_index('datetime_utc', inplace=True) + df.sort_index(inplace=True) + return df + except Exception as e: + logging.error(f"Failed to load data from table '{table_name}': {e}") + return pd.DataFrame() + + @abstractmethod + def calculate_signals(self, df: pd.DataFrame) -> pd.DataFrame: + """The core logic of the strategy. Must be implemented by child classes.""" + pass + + def calculate_signals_and_state(self, df: pd.DataFrame) -> bool: + """ + A wrapper that calls the strategy's signal calculation, determines + the last signal change, and returns True if the signal has changed. + """ + df_with_signals = self.calculate_signals(df) + df_with_signals.dropna(inplace=True) + if df_with_signals.empty: + return False + + df_with_signals['position_change'] = df_with_signals['signal'].diff() + + last_signal_int = df_with_signals['signal'].iloc[-1] + new_signal_str = "HOLD" + if last_signal_int == 1: new_signal_str = "BUY" + elif last_signal_int == -1: new_signal_str = "SELL" + + signal_changed = False + if self.current_signal == "INIT": + if new_signal_str == "BUY": self.current_signal = "INIT_BUY" + elif new_signal_str == "SELL": self.current_signal = "INIT_SELL" + else: self.current_signal = "HOLD" + signal_changed = True + elif new_signal_str != self.current_signal: + self.current_signal = new_signal_str + signal_changed = True + + if signal_changed: + last_change_series = df_with_signals[df_with_signals['position_change'] != 0] + if not last_change_series.empty: + last_change_row = last_change_series.iloc[-1] + self.last_signal_change_utc = last_change_row.name.tz_localize('UTC').isoformat() + self.signal_price = last_change_row['close'] + + return signal_changed + + def _save_status(self): + """Saves the current strategy state to its JSON file.""" + status = { + "strategy_name": self.strategy_name, + "current_signal": self.current_signal, + "last_signal_change_utc": self.last_signal_change_utc, + "signal_price": self.signal_price, + "last_checked_utc": datetime.now(timezone.utc).isoformat() + } + # If a shared status dict is provided (Manager.dict()), update it instead of writing files + try: + if self.shared_status is not None: + try: + # store the status under the strategy name for easy lookup + self.shared_status[self.strategy_name] = status + except Exception: + # Manager proxies may not accept nested mutable objects consistently; assign a copy + self.shared_status[self.strategy_name] = dict(status) + else: + with open(self.status_file_path, 'w', encoding='utf-8') as f: + json.dump(status, f, indent=4) + except IOError as e: + logging.error(f"Failed to write status file for {self.strategy_name}: {e}") + + def run_polling_loop(self): + """ + The default execution loop for polling-based strategies (e.g., SMAs). + """ + while True: + df = self.load_data() + if df.empty: + logging.warning("No data loaded. Waiting 1 minute...") + time.sleep(60) + continue + + signal_changed = self.calculate_signals_and_state(df.copy()) + self._save_status() + + if signal_changed or self.current_signal == "INIT_BUY" or self.current_signal == "INIT_SELL": + logging.warning(f"New signal detected: {self.current_signal}") + self.trade_signal_queue.put({ + "strategy_name": self.strategy_name, + "signal": self.current_signal, + "coin": self.coin, + "signal_price": self.signal_price, + "config": {"agent": self.params.get("agent"), "parameters": self.params} + }) + if self.current_signal == "INIT_BUY": self.current_signal = "BUY" + if self.current_signal == "INIT_SELL": self.current_signal = "SELL" + + logging.info(f"Current Signal: {self.current_signal}") + time.sleep(60) + + def run_event_loop(self): + """ + A placeholder for event-driven (WebSocket) strategies. + Child classes must override this. + """ + logging.error("run_event_loop() is not implemented for this strategy.") + time.sleep(3600) # Sleep for an hour to prevent rapid error loops + + def on_fill_message(self, message): + """ + Placeholder for the WebSocket callback. + Child classes must override this. + """ + pass diff --git a/coin_id_map.py b/coin_id_map.py new file mode 100644 index 0000000..91183bc --- /dev/null +++ b/coin_id_map.py @@ -0,0 +1,95 @@ +import os +import json +import logging +import requests +from hyperliquid.info import Info +from hyperliquid.utils import constants + +from logging_utils import setup_logging + +def update_coin_mapping(): + """ + Fetches all assets from Hyperliquid and all coins from CoinGecko, + then creates and saves a mapping from the Hyperliquid symbol to the + CoinGecko ID using a robust matching algorithm. + """ + setup_logging('normal', 'CoinMapUpdater') + logging.info("Starting coin mapping update process...") + + # --- 1. Fetch all assets from Hyperliquid --- + try: + logging.info("Fetching assets from Hyperliquid...") + info = Info(constants.MAINNET_API_URL, skip_ws=True) + meta, asset_contexts = info.meta_and_asset_ctxs() + hyperliquid_assets = meta['universe'] + logging.info(f"Found {len(hyperliquid_assets)} assets on Hyperliquid.") + except Exception as e: + logging.error(f"Failed to fetch assets from Hyperliquid: {e}") + return + + # --- 2. Fetch all coins from CoinGecko --- + try: + logging.info("Fetching coin list from CoinGecko...") + response = requests.get("https://api.coingecko.com/api/v3/coins/list") + response.raise_for_status() + coingecko_coins = response.json() + + # Create more robust lookup tables + cg_symbol_lookup = {coin['symbol'].upper(): coin['id'] for coin in coingecko_coins} + cg_name_lookup = {coin['name'].upper(): coin['id'] for coin in coingecko_coins} + + logging.info(f"Found {len(coingecko_coins)} coins on CoinGecko.") + except requests.exceptions.RequestException as e: + logging.error(f"Failed to fetch coin list from CoinGecko: {e}") + return + + # --- 3. Create the mapping --- + final_mapping = {} + # Use manual overrides for critical coins where symbols are ambiguous + manual_overrides = { + "BTC": "bitcoin", + "ETH": "ethereum", + "SOL": "solana", + "BNB": "binancecoin", + "HYPE": "hyperliquid", + "PUMP": "pump-fun", + "ASTER": "astar", + "ZEC": "zcash", + "SUI": "sui", + "ACE": "endurance", + # Add other important ones you watch here + } + + logging.info("Generating symbol-to-id mapping...") + for asset in hyperliquid_assets: + asset_symbol = asset['name'].upper() + asset_name = asset.get('name', '').upper() # Use full name if available + + # Priority 1: Manual Overrides + if asset_symbol in manual_overrides: + final_mapping[asset_symbol] = manual_overrides[asset_symbol] + continue + + # Priority 2: Exact Name Match + if asset_name in cg_name_lookup: + final_mapping[asset_symbol] = cg_name_lookup[asset_name] + continue + + # Priority 3: Symbol Match + if asset_symbol in cg_symbol_lookup: + final_mapping[asset_symbol] = cg_symbol_lookup[asset_symbol] + else: + logging.warning(f"No match found for '{asset_symbol}' on CoinGecko. It will be excluded.") + + # --- 4. Save the mapping to a file --- + map_file_path = os.path.join("_data", "coin_id_map.json") + try: + with open(map_file_path, 'w', encoding='utf-8') as f: + json.dump(final_mapping, f, indent=4, sort_keys=True) + logging.info(f"Successfully saved new coin mapping with {len(final_mapping)} entries to '{map_file_path}'.") + except IOError as e: + logging.error(f"Failed to write coin mapping file: {e}") + +if __name__ == "__main__": + update_coin_mapping() + diff --git a/dashboard_data_fetcher.py b/dashboard_data_fetcher.py new file mode 100644 index 0000000..789fbeb --- /dev/null +++ b/dashboard_data_fetcher.py @@ -0,0 +1,136 @@ +import logging +import os +import sys +import json +import time +import argparse # <-- THE FIX: Added this import +from datetime import datetime +from eth_account import Account +from hyperliquid.info import Info +from hyperliquid.utils import constants +from dotenv import load_dotenv + +from logging_utils import setup_logging + +# Load .env file +load_dotenv() + +class DashboardDataFetcher: + """ + A dedicated, lightweight process that runs in a loop to fetch and save + the account's state (balances, positions) for the main dashboard to display. + """ + + def __init__(self, log_level: str): + setup_logging(log_level, 'DashboardDataFetcher') + + self.vault_address = os.environ.get("MAIN_WALLET_ADDRESS") + if not self.vault_address: + logging.error("MAIN_WALLET_ADDRESS not set in .env file. Cannot proceed.") + sys.exit(1) + + self.info = Info(constants.MAINNET_API_URL, skip_ws=True) + self.status_file_path = os.path.join("_logs", "trade_executor_status.json") + self.managed_positions_path = os.path.join("_data", "executor_managed_positions.json") + logging.info(f"Dashboard Data Fetcher initialized for vault: {self.vault_address}") + + def load_managed_positions(self) -> dict: + """Loads the state of which strategy manages which position.""" + if os.path.exists(self.managed_positions_path): + try: + with open(self.managed_positions_path, 'r') as f: + data = json.load(f) + # Create a reverse map: {coin: strategy_name} + return {v['coin']: k for k, v in data.items()} + except (IOError, json.JSONDecodeError): + logging.warning("Could not read managed positions file.") + return {} + + def fetch_and_save_status(self): + """Fetches all account data and saves it to the JSON status file.""" + try: + perpetuals_state = self.info.user_state(self.vault_address) + spot_state = self.info.spot_user_state(self.vault_address) + meta, all_market_contexts = self.info.meta_and_asset_ctxs() + coin_to_strategy_map = self.load_managed_positions() + + status = { + "last_updated_utc": datetime.now().isoformat(), + "perpetuals_account": { "balances": {}, "open_positions": [] }, + "spot_account": { "positions": [] } + } + + # 1. Extract Perpetuals Account Data + margin_summary = perpetuals_state.get("marginSummary", {}) + status["perpetuals_account"]["balances"] = { + "account_value": margin_summary.get("accountValue"), + "total_margin_used": margin_summary.get("totalMarginUsed"), + "withdrawable": margin_summary.get("withdrawable") + } + + asset_positions = perpetuals_state.get("assetPositions", []) + for asset_pos in asset_positions: + pos = asset_pos.get('position', {}) + if float(pos.get('szi', 0)) != 0: + coin = pos.get('coin') + position_value = float(pos.get('positionValue', 0)) + margin_used = float(pos.get('marginUsed', 0)) + leverage = position_value / margin_used if margin_used > 0 else 0 + + position_info = { + "coin": coin, + "strategy": coin_to_strategy_map.get(coin, "Unmanaged"), + "size": pos.get('szi'), + "position_value": pos.get('positionValue'), + "entry_price": pos.get('entryPx'), + "mark_price": pos.get('markPx'), + "pnl": pos.get('unrealizedPnl'), + "liq_price": pos.get('liquidationPx'), + "margin": pos.get('marginUsed'), + "funding": pos.get('fundingRate'), + "leverage": f"{leverage:.1f}x" + } + status["perpetuals_account"]["open_positions"].append(position_info) + + # 2. Extract Spot Account Data + price_map = { asset.get("universe", {}).get("name"): asset.get("markPx") for asset in all_market_contexts if asset.get("universe", {}).get("name") } + spot_balances = spot_state.get("balances", []) + for bal in spot_balances: + total_balance = float(bal.get('total', 0)) + if total_balance > 0: + coin = bal.get('coin') + mark_price = float(price_map.get(coin, 0)) + status["spot_account"]["positions"].append({ + "coin": coin, "balance_size": total_balance, + "position_value": total_balance * mark_price, "pnl": "N/A" + }) + + # 3. Write to file + # Use atomic write to prevent partial reads from main_app + temp_file_path = self.status_file_path + ".tmp" + with open(temp_file_path, 'w', encoding='utf-8') as f: + json.dump(status, f, indent=4) + # Rename is atomic + os.replace(temp_file_path, self.status_file_path) + + logging.debug(f"Successfully updated dashboard status file.") + + except Exception as e: + logging.error(f"Failed to fetch or save account status: {e}") + + def run(self): + """Main loop to periodically fetch and save data.""" + while True: + self.fetch_and_save_status() + time.sleep(5) # Update dashboard data every 5 seconds + +if __name__ == "__main__": + parser = argparse.ArgumentParser(description="Run the Dashboard Data Fetcher.") + parser.add_argument("--log-level", default="normal", choices=['off', 'normal', 'debug']) + args = parser.parse_args() + + fetcher = DashboardDataFetcher(log_level=args.log_level) + try: + fetcher.run() + except KeyboardInterrupt: + logging.info("Dashboard Data Fetcher stopped.") diff --git a/del_market_cap_tables.py b/del_market_cap_tables.py new file mode 100644 index 0000000..d18050c --- /dev/null +++ b/del_market_cap_tables.py @@ -0,0 +1,56 @@ +import sqlite3 +import logging +import os + +from logging_utils import setup_logging + +def cleanup_market_cap_tables(): + """ + Scans the database and drops all tables related to market cap data + to allow for a clean refresh. + """ + setup_logging('normal', 'DBCleanup') + db_path = os.path.join("_data", "market_data.db") + + if not os.path.exists(db_path): + logging.error(f"Database file not found at '{db_path}'. Nothing to clean.") + return + + logging.info(f"Connecting to database at '{db_path}'...") + try: + with sqlite3.connect(db_path) as conn: + cursor = conn.cursor() + + # Find all tables that were created by the market cap fetcher + cursor.execute(""" + SELECT name FROM sqlite_master + WHERE type='table' + AND (name LIKE '%_market_cap' OR name LIKE 'TOTAL_%') + """) + + tables_to_drop = cursor.fetchall() + + if not tables_to_drop: + logging.info("No market cap tables found to clean up. Database is already clean.") + return + + logging.warning(f"Found {len(tables_to_drop)} market cap tables to remove...") + + for table in tables_to_drop: + table_name = table[0] + try: + logging.info(f"Dropping table: {table_name}...") + conn.execute(f'DROP TABLE IF EXISTS "{table_name}"') + except Exception as e: + logging.error(f"Failed to drop table {table_name}: {e}") + + conn.commit() + logging.info("--- Database cleanup complete ---") + + except sqlite3.Error as e: + logging.error(f"A database error occurred: {e}") + except Exception as e: + logging.error(f"An unexpected error occurred: {e}") + +if __name__ == "__main__": + cleanup_market_cap_tables() diff --git a/hyperliquid_wallet_data_0xb83de012_20251026_220802.json b/hyperliquid_wallet_data_0xb83de012_20251026_220802.json new file mode 100644 index 0000000..b374856 --- /dev/null +++ b/hyperliquid_wallet_data_0xb83de012_20251026_220802.json @@ -0,0 +1,46694 @@ +{ + "wallet_address": "0xb83de012dba672c76a7dbbbf3e459cb59d7d6e36", + "timestamp": "2025-10-26T22:07:48.803578", + "data": { + "user_state": { + "marginSummary": { + "accountValue": "25033828.5842700005", + "totalNtlPos": "59726120.0227459967", + "totalRawUsd": "84759948.6070159972", + "totalMarginUsed": "10633668.9945899993" + }, + "crossMarginSummary": { + "accountValue": "25033828.5842700005", + "totalNtlPos": "59726120.0227459967", + "totalRawUsd": "84759948.6070159972", + "totalMarginUsed": "10633668.9945899993" + }, + "crossMaintenanceMarginUsed": "3346352.2036270001", + "withdrawable": "14394703.1855350006", + "assetPositions": [ + { + "type": "oneWay", + "position": { + "coin": "BTC", + "szi": "-9.2773", + "leverage": { + "type": "cross", + "value": 10 + }, + "entryPx": "111481.6", + "positionValue": "1052713.7856000001", + "unrealizedPnl": "-18465.438981", + "returnOnEquity": "-0.1785397003", + "liquidationPx": "2422304.285110943", + "marginUsed": "105271.37856", + "maxLeverage": 40, + "cumFunding": { + "allTime": "-6916690.8522610003", + "sinceOpen": "-6916690.8582020001", + "sinceChange": "-507.085023" + } + } + }, + { + "type": "oneWay", + "position": { + "coin": "ETH", + "szi": "-2870.7419", + "leverage": { + "type": "cross", + "value": 10 + }, + "entryPx": "3854.16", + "positionValue": "11679039.2717700005", + "unrealizedPnl": "-614712.378103", + "returnOnEquity": "-0.555580456", + "liquidationPx": "11474.8285164535", + "marginUsed": "1167903.9271770001", + "maxLeverage": 25, + "cumFunding": { + "allTime": "-6602429.8642870001", + "sinceOpen": "-6602429.8642870001", + "sinceChange": "-3302.472764" + } + } + }, + { + "type": "oneWay", + "position": { + "coin": "SOL", + "szi": "-359.37", + "leverage": { + "type": "cross", + "value": 10 + }, + "entryPx": "194.4727", + "positionValue": "70943.2317", + "unrealizedPnl": "-1055.571958", + "returnOnEquity": "-0.1510383896", + "liquidationPx": "59074.092923144", + "marginUsed": "7094.32317", + "maxLeverage": 20, + "cumFunding": { + "allTime": "-792037.43021", + "sinceOpen": "-66.577224", + "sinceChange": "-49.712167" + } + } + }, + { + "type": "oneWay", + "position": { + "coin": "DOGE", + "szi": "-109217.0", + "leverage": { + "type": "cross", + "value": 10 + }, + "entryPx": "0.279959", + "positionValue": "21963.5387", + "unrealizedPnl": "8612.833959", + "returnOnEquity": "2.8168265919", + "liquidationPx": "189.0359900372", + "marginUsed": "2196.35387", + "maxLeverage": 10, + "cumFunding": { + "allTime": "-1870.350749", + "sinceOpen": "-1870.350749", + "sinceChange": "50.91244" + } + } + }, + { + "type": "oneWay", + "position": { + "coin": "INJ", + "szi": "-18747.2", + "leverage": { + "type": "cross", + "value": 3 + }, + "entryPx": "13.01496", + "positionValue": "165190.9528", + "unrealizedPnl": "78803.2651", + "returnOnEquity": "0.9689155642", + "liquidationPx": "1067.3558466468", + "marginUsed": "55063.650933", + "maxLeverage": 10, + "cumFunding": { + "allTime": "-517.598809", + "sinceOpen": "-517.598809", + "sinceChange": "14.167399" + } + } + }, + { + "type": "oneWay", + "position": { + "coin": "SUI", + "szi": "-376577.6", + "leverage": { + "type": "cross", + "value": 3 + }, + "entryPx": "3.85881", + "positionValue": "986859.25856", + "unrealizedPnl": "466284.999201", + "returnOnEquity": "0.962640144", + "liquidationPx": "57.2710127936", + "marginUsed": "328953.086186", + "maxLeverage": 10, + "cumFunding": { + "allTime": "-45506.073364", + "sinceOpen": "-45506.068527", + "sinceChange": "-946.493457" + } + } + }, + { + "type": "oneWay", + "position": { + "coin": "XRP", + "szi": "-39691.0", + "leverage": { + "type": "cross", + "value": 20 + }, + "entryPx": "2.468585", + "positionValue": "103795.9341", + "unrealizedPnl": "-5815.3118", + "returnOnEquity": "-1.1870330405", + "liquidationPx": "535.6959884153", + "marginUsed": "5189.796705", + "maxLeverage": 20, + "cumFunding": { + "allTime": "-2615.635014", + "sinceOpen": "-86.271845", + "sinceChange": "-86.271845" + } + } + }, + { + "type": "oneWay", + "position": { + "coin": "HYPE", + "szi": "-750315.16", + "leverage": { + "type": "cross", + "value": 5 + }, + "entryPx": "43.3419", + "positionValue": "35077233.7299999967", + "unrealizedPnl": "-2557123.1353480001", + "returnOnEquity": "-0.3931602766", + "liquidationPx": "73.0268082932", + "marginUsed": "7015446.7460000003", + "maxLeverage": 5, + "cumFunding": { + "allTime": "-1870235.87934", + "sinceOpen": "-1870235.87934", + "sinceChange": "-33899.296658" + } + } + }, + { + "type": "oneWay", + "position": { + "coin": "FARTCOIN", + "szi": "-4122236.7999999998", + "leverage": { + "type": "cross", + "value": 10 + }, + "entryPx": "0.80127", + "positionValue": "1681955.059136", + "unrealizedPnl": "1621107.3266499999", + "returnOnEquity": "4.9078919418", + "liquidationPx": "5.392820006", + "marginUsed": "168195.505913", + "maxLeverage": 10, + "cumFunding": { + "allTime": "-71663.182179", + "sinceOpen": "-49993.307555", + "sinceChange": "-5226.082753" + } + } + }, + { + "type": "oneWay", + "position": { + "coin": "PUMP", + "szi": "-1921732999.0", + "leverage": { + "type": "cross", + "value": 5 + }, + "entryPx": "0.005551", + "positionValue": "8878406.4553800002", + "unrealizedPnl": "1789606.855005", + "returnOnEquity": "0.8387723201", + "liquidationPx": "0.0151424891", + "marginUsed": "1775681.2910760001", + "maxLeverage": 10, + "cumFunding": { + "allTime": "-193383.578999", + "sinceOpen": "-193383.578999", + "sinceChange": "-7271.699321" + } + } + }, + { + "type": "oneWay", + "position": { + "coin": "ASTER", + "szi": "-7075.0", + "leverage": { + "type": "cross", + "value": 3 + }, + "entryPx": "1.820644", + "positionValue": "8018.805", + "unrealizedPnl": "4862.256517", + "returnOnEquity": "1.1324198345", + "liquidationPx": "2787.8312966454", + "marginUsed": "2672.935", + "maxLeverage": 5, + "cumFunding": { + "allTime": "-618894.880123", + "sinceOpen": "-618894.880123", + "sinceChange": "-5.32473" + } + } + } + ], + "time": 1761512869992 + }, + "spot_state": { + "balances": [ + { + "coin": "USDC", + "token": 0, + "total": "85165.03263363", + "hold": "0.0", + "entryNtl": "0.0" + }, + { + "coin": "HYPE", + "token": 150, + "total": "45401.36651867", + "hold": "0.0", + "entryNtl": "1742715.1297323401" + }, + { + "coin": "UBTC", + "token": 197, + "total": "0.0", + "hold": "0.0", + "entryNtl": "0.0" + }, + { + "coin": "LATINA", + "token": 223, + "total": "35470.3668", + "hold": "0.0", + "entryNtl": "0.0" + }, + { + "coin": "USDT0", + "token": 268, + "total": "106501.47093445", + "hold": "103038.77", + "entryNtl": "106521.92756495" + }, + { + "coin": "UFART", + "token": 269, + "total": "4132582.4960630001", + "hold": "0.0", + "entryNtl": "3313065.8106947001" + }, + { + "coin": "UPUMP", + "token": 299, + "total": "358268528.5250939727", + "hold": "0.0", + "entryNtl": "2442751.2693156502" + }, + { + "coin": "LICKO", + "token": 307, + "total": "11189.06185739", + "hold": "0.0", + "entryNtl": "0.06713437" + } + ] + }, + "open_orders": [ + { + "coin": "WLFI", + "side": "B", + "limitPx": "0.10447", + "sz": "2624.0", + "oid": 194029229960, + "timestamp": 1760131688558, + "origSz": "12760.0", + "cloid": "0x00000000000000000000001261000016" + }, + { + "coin": "@166", + "side": "A", + "limitPx": "1.01", + "sz": "103038.77", + "oid": 174787748753, + "timestamp": 1758819420037, + "origSz": "3000000.0" + } + ], + "recent_fills": [ + { + "coin": "ETH", + "px": "3952.4", + "sz": "4.4456", + "side": "A", + "time": 1761431190137, + "startPosition": "-2866.2963", + "dir": "Open Short", + "closedPnl": "0.0", + "hash": "0x205e41af2da9230221d7042e32826a0202300094c8ac41d4c426ed01ecacfcec", + "oid": 212480484440, + "crossed": true, + "fee": "3.689865", + "tid": 874416766660940, + "feeToken": "USDC", + "twapId": null + }, + { + "coin": "ETH", + "px": "3952.4", + "sz": "4.5544", + "side": "A", + "time": 1761431190137, + "startPosition": "-2861.7419", + "dir": "Open Short", + "closedPnl": "0.0", + "hash": "0x205e41af2da9230221d7042e32826a0202300094c8ac41d4c426ed01ecacfcec", + "oid": 212480484440, + "crossed": true, + "fee": "3.78017", + "tid": 590508408223701, + "feeToken": "USDC", + "twapId": null + }, + { + "coin": "ETH", + "px": "3929.3", + "sz": "2.545", + "side": "A", + "time": 1761375252759, + "startPosition": "-2859.1969", + "dir": "Open Short", + "closedPnl": "0.0", + "hash": "0xb35fe2d490260506b4d9042e27996d02024900ba2b2923d857288e274f29def1", + "oid": 212001147287, + "crossed": true, + "fee": "2.100014", + "tid": 1060683286404896, + "cloid": "0x00000000000000000000000001000102", + "feeToken": "USDC", + "twapId": null + }, + { + "coin": "ETH", + "px": "3929.4", + "sz": "2.4944", + "side": "A", + "time": 1761375242272, + "startPosition": "-2856.7025", + "dir": "Open Short", + "closedPnl": "0.0", + "hash": "0x1e2305168bd734fd1f9c042e2798f302029e00fc26da53cfc1ebb0694adb0ee7", + "oid": 212001055058, + "crossed": true, + "fee": "2.058314", + "tid": 382559690764395, + "cloid": 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+import time +from datetime import datetime, timezone +from hyperliquid.info import Info +from hyperliquid.utils import constants +import sqlite3 +from queue import Queue +from threading import Thread + +from logging_utils import setup_logging + +class LiveCandleFetcher: + """ + Connects to Hyperliquid to maintain a complete and up-to-date database of + 1-minute candles using a robust producer-consumer architecture to prevent + data corruption and duplication. + """ + + def __init__(self, log_level: str, coins: list): + setup_logging(log_level, 'LiveCandleFetcher') + self.db_path = os.path.join("_data", "market_data.db") + self.coins_to_watch = set(coins) + if not self.coins_to_watch: + logging.error("No coins provided to watch. Exiting.") + sys.exit(1) + + self.info = Info(constants.MAINNET_API_URL, skip_ws=False) + self.candle_queue = Queue() # Thread-safe queue for candles + self._ensure_tables_exist() + + def _ensure_tables_exist(self): + """ + Ensures that all necessary tables are created with the correct schema and PRIMARY KEY. + If a table exists with an incorrect schema, it attempts to migrate the data. + """ + with sqlite3.connect(self.db_path) as conn: + for coin in self.coins_to_watch: + table_name = f"{coin}_1m" + cursor = conn.cursor() + cursor.execute(f"PRAGMA table_info('{table_name}')") + columns = cursor.fetchall() + + if columns: + pk_found = any(col[1] == 'timestamp_ms' and col[5] == 1 for col in columns) + if not pk_found: + logging.warning(f"Schema migration needed for table '{table_name}': 'timestamp_ms' is not the PRIMARY KEY.") + logging.warning("Attempting to automatically rebuild the table...") + try: + # 1. Rename old table + conn.execute(f'ALTER TABLE "{table_name}" RENAME TO "{table_name}_old"') + logging.info(f" -> Renamed existing table to '{table_name}_old'.") + + # 2. Create new table with correct schema + self._create_candle_table(conn, table_name) + logging.info(f" -> Created new '{table_name}' table with correct schema.") + + # 3. Copy unique data from old table to new table + conn.execute(f''' + INSERT OR IGNORE INTO "{table_name}" (datetime_utc, timestamp_ms, open, high, low, close, volume, number_of_trades) + SELECT datetime_utc, timestamp_ms, open, high, low, close, volume, number_of_trades + FROM "{table_name}_old" + ''') + conn.commit() + logging.info(" -> Copied data to new table.") + + # 4. Drop the old table + conn.execute(f'DROP TABLE "{table_name}_old"') + logging.info(f" -> Removed old table. Migration for '{table_name}' complete.") + except Exception as e: + logging.error(f"FATAL: Automatic schema migration for '{table_name}' failed: {e}") + logging.error("Please delete the database file '_data/market_data.db' manually and restart.") + sys.exit(1) + else: + # If table does not exist, create it + self._create_candle_table(conn, table_name) + logging.info("Database tables verified.") + + def _create_candle_table(self, conn, table_name: str): + """Creates a new candle table with the correct schema.""" + conn.execute(f''' + CREATE TABLE "{table_name}" ( + datetime_utc TEXT, + timestamp_ms INTEGER PRIMARY KEY, + open REAL, + high REAL, + low REAL, + close REAL, + volume REAL, + number_of_trades INTEGER + ) + ''') + + def on_message(self, message): + """ + Callback function to process incoming candle messages. This is the "Producer". + It puts the raw message onto the queue for the DB writer. + """ + try: + if message.get("channel") == "candle": + candle_data = message.get("data", {}) + if candle_data: + self.candle_queue.put(candle_data) + except Exception as e: + logging.error(f"Error in on_message: {e}") + + def _database_writer_thread(self): + """ + This is the "Consumer" thread. It runs forever, pulling candles from the + queue and writing them to the database, ensuring all writes are serial. + """ + while True: + try: + candle = self.candle_queue.get() + if candle is None: # A signal to stop the thread + break + + coin = candle.get('coin') + if not coin: + continue + + table_name = f"{coin}_1m" + record = ( + datetime.fromtimestamp(candle['t'] / 1000, tz=timezone.utc).strftime('%Y-%m-%d %H:%M:%S'), + candle['t'], + candle.get('o'), candle.get('h'), candle.get('l'), candle.get('c'), + candle.get('v'), candle.get('n') + ) + + with sqlite3.connect(self.db_path) as conn: + conn.execute(f''' + INSERT OR REPLACE INTO "{table_name}" (datetime_utc, timestamp_ms, open, high, low, close, volume, number_of_trades) + VALUES (?, ?, ?, ?, ?, ?, ?, ?) + ''', record) + conn.commit() + logging.debug(f"Upserted candle for {coin} at {record[0]}") + + except Exception as e: + logging.error(f"Error in database writer thread: {e}") + + def _get_last_timestamp_from_db(self, coin: str) -> int: + """Gets the most recent millisecond timestamp from a coin's 1m table.""" + table_name = f"{coin}_1m" + try: + with sqlite3.connect(self.db_path) as conn: + result = conn.execute(f'SELECT MAX(timestamp_ms) FROM "{table_name}"').fetchone() + return int(result[0]) if result and result[0] is not None else None + except Exception as e: + logging.error(f"Could not read last timestamp from table '{table_name}': {e}") + return None + + def _fetch_historical_candles(self, coin: str, start_ms: int, end_ms: int): + """Fetches historical candles and puts them on the queue for the writer.""" + logging.info(f"Fetching historical data for {coin} from {datetime.fromtimestamp(start_ms/1000)}...") + current_start = start_ms + + while current_start < end_ms: + try: + http_info = Info(constants.MAINNET_API_URL, skip_ws=True) + batch = http_info.candles_snapshot(coin, "1m", current_start, end_ms) + if not batch: + break + + for candle in batch: + candle['coin'] = coin + self.candle_queue.put(candle) + + last_ts = batch[-1]['t'] + if last_ts < current_start: + break + current_start = last_ts + 1 + time.sleep(0.5) + except Exception as e: + logging.error(f"Error fetching historical chunk for {coin}: {e}") + break + + logging.info(f"Historical data fetching for {coin} is complete.") + + def run(self): + """ + Starts the database writer, catches up on historical data, then + subscribes to the WebSocket for live updates. + """ + db_writer = Thread(target=self._database_writer_thread, daemon=True) + db_writer.start() + + logging.info("--- Starting Historical Data Catch-Up Phase ---") + now_ms = int(time.time() * 1000) + for coin in self.coins_to_watch: + last_ts = self._get_last_timestamp_from_db(coin) + start_ts = last_ts + 60000 if last_ts else now_ms - (7 * 24 * 60 * 60 * 1000) + if start_ts < now_ms: + self._fetch_historical_candles(coin, start_ts, now_ms) + + logging.info("--- Historical Catch-Up Complete. Starting Live WebSocket Feed ---") + for coin in self.coins_to_watch: + # --- FIX: Use a lambda to create a unique callback for each subscription --- + # This captures the 'coin' variable and adds it to the message data. + callback = lambda msg, c=coin: self.on_message({**msg, 'data': {**msg.get('data',{}), 'coin': c}}) + subscription = {"type": "candle", "coin": coin, "interval": "1m"} + self.info.subscribe(subscription, callback) + logging.info(f"Subscribed to 1m candles for {coin}") + time.sleep(0.2) + + print("\nListening for live candle data... Press Ctrl+C to stop.") + try: + while True: + time.sleep(1) + except KeyboardInterrupt: + print("\nStopping WebSocket listener...") + self.info.ws_manager.stop() + self.candle_queue.put(None) + db_writer.join() + print("Listener stopped.") + + +if __name__ == "__main__": + parser = argparse.ArgumentParser(description="A hybrid historical and live candle data fetcher for Hyperliquid.") + parser.add_argument( + "--coins", + nargs='+', + required=True, + help="List of coin symbols to fetch (e.g., BTC ETH)." + ) + parser.add_argument( + "--log-level", + default="normal", + choices=['off', 'normal', 'debug'], + help="Set the logging level for the script." + ) + args = parser.parse_args() + + fetcher = LiveCandleFetcher(log_level=args.log_level, coins=args.coins) + fetcher.run() + diff --git a/live_market_utils.py b/live_market_utils.py new file mode 100644 index 0000000..bab9129 --- /dev/null +++ b/live_market_utils.py @@ -0,0 +1,187 @@ +import logging +import json +import time +import os +import traceback +import sys +from hyperliquid.info import Info +from hyperliquid.utils import constants + +from logging_utils import setup_logging + +# --- Configuration for standalone error logging --- +LOGS_DIR = "_logs" +ERROR_LOG_FILE = os.path.join(LOGS_DIR, "live_market_errors.log") + +def log_error(error_message: str, include_traceback: bool = True): + """A simple, robust file logger for any errors.""" + try: + if not os.path.exists(LOGS_DIR): + os.makedirs(LOGS_DIR) + + with open(ERROR_LOG_FILE, 'a') as f: + timestamp = time.strftime('%Y-%m-%d %H:%M:%S', time.gmtime()) + f.write(f"--- ERROR at {timestamp} UTC ---\n") + f.write(error_message + "\n") + if include_traceback: + f.write(traceback.format_exc() + "\n") + f.write("="*50 + "\n") + except Exception: + print(f"CRITICAL: Failed to write to error log file: {error_message}", file=sys.stderr) + + +def on_message(message, shared_prices_dict): + """ + Callback function to process incoming WebSocket messages for 'bbo' and 'trades' + and update the shared memory dictionary. + """ + try: + logging.debug(f"Received WebSocket message: {message}") + channel = message.get("channel") + + # --- Parser 1: Handle Best Bid/Offer messages --- + if channel == "bbo": + data = message.get("data") + if not data: + logging.warning("BBO message received with no data.") + return + + coin = data.get("coin") + if not coin: + logging.warning("BBO data received with no coin identifier.") + return + + bid_ask_data = data.get("bbo") + + if not bid_ask_data or not isinstance(bid_ask_data, list) or len(bid_ask_data) < 2: + logging.warning(f"[{coin}] Received BBO message with invalid 'bbo' array: {bid_ask_data}") + return + + try: + bid_price_str = bid_ask_data[0].get('px') + ask_price_str = bid_ask_data[1].get('px') + + if not bid_price_str or not ask_price_str: + logging.warning(f"[{coin}] BBO data missing 'px' field.") + return + + bid_price = float(bid_price_str) + ask_price = float(ask_price_str) + + # Update the shared dictionary for Bid and Ask + shared_prices_dict[f"{coin}_bid"] = bid_price + shared_prices_dict[f"{coin}_ask"] = ask_price + + logging.info(f"Updated {coin} (BBO): Bid={bid_price:.4f}, Ask={ask_price:.4f}") + + except (ValueError, TypeError, IndexError) as e: + logging.error(f"[{coin}] Error parsing BBO data: {e}. Data: {bid_ask_data}") + + # --- Parser 2: Handle Live Trade messages --- + elif channel == "trades": + trade_list = message.get("data") + + if not trade_list or not isinstance(trade_list, list) or len(trade_list) == 0: + logging.warning(f"Received 'trades' message with invalid data: {trade_list}") + return + + # Process all trades in the batch + for trade in trade_list: + try: + coin = trade.get("coin") + price_str = trade.get("px") + + if not coin or not price_str: + logging.warning(f"Trade data missing 'coin' or 'px': {trade}") + continue + + price = float(price_str) + + # Update the shared dictionary for the "Live Price" column + shared_prices_dict[coin] = price + + logging.info(f"Updated {coin} (Live Price) to last trade: {price:.4f}") + + except (ValueError, TypeError) as e: + logging.error(f"Error parsing trade data: {e}. Data: {trade}") + + except Exception as e: + log_error(f"Error in WebSocket on_message: {e}") + +def start_live_feed(shared_prices_dict, coins_to_watch: list, log_level='off'): + """ + Main function for the WebSocket process. + Subscribes to BOTH 'bbo' and 'trades' for all watched coins. + """ + setup_logging(log_level, 'LiveMarketFeed_Combined') + + info = None + callback = lambda msg: on_message(msg, shared_prices_dict) + + def connect_and_subscribe(): + """Establishes a new WebSocket connection and subscribes to both streams.""" + try: + logging.info("Connecting to Hyperliquid WebSocket...") + new_info = Info(constants.MAINNET_API_URL, skip_ws=False) + + # --- MODIFIED: Subscribe to 'bbo' AND 'trades' for each coin --- + for coin in coins_to_watch: + # Subscribe to Best Bid/Offer + bbo_sub = {"type": "bbo", "coin": coin} + new_info.subscribe(bbo_sub, callback) + logging.info(f"Subscribed to 'bbo' for {coin}.") + + # Subscribe to Live Trades + trades_sub = {"type": "trades", "coin": coin} + new_info.subscribe(trades_sub, callback) + logging.info(f"Subscribed to 'trades' for {coin}.") + + logging.info("WebSocket connected and all subscriptions sent.") + return new_info + except Exception as e: + log_error(f"Failed to connect to WebSocket: {e}") + return None + + info = connect_and_subscribe() + + if info is None: + logging.critical("Initial WebSocket connection failed. Exiting process.") + log_error("Initial WebSocket connection failed. Exiting process.", include_traceback=False) + time.sleep(10) # Wait before letting the process manager restart it + return + + logging.info("Starting Combined (BBO + Trades) live price feed process.") + + try: + while True: + # --- Watchdog Logic --- + time.sleep(15) # Check the connection every 15 seconds + + if not info.ws_manager.is_alive(): + error_msg = "WebSocket connection lost. Attempting to reconnect..." + logging.warning(error_msg) + log_error(error_msg, include_traceback=False) # Log it to the file + + try: + info.ws_manager.stop() # Clean up old manager + except Exception as e: + log_error(f"Error stopping old ws_manager: {e}") + + info = connect_and_subscribe() + + if info is None: + logging.error("Reconnect failed, will retry in 15s.") + else: + logging.info("Successfully reconnected to WebSocket.") + else: + logging.debug("Watchdog check: WebSocket connection is active.") + + except KeyboardInterrupt: + logging.info("Stopping WebSocket listener...") + except Exception as e: + log_error(f"Live Market Feed process crashed: {e}") + finally: + if info and info.ws_manager: + info.ws_manager.stop() + logging.info("Combined Listener stopped.") + diff --git a/main_app.py b/main_app.py index 47670b4..345013d 100644 --- a/main_app.py +++ b/main_app.py @@ -9,21 +9,26 @@ import schedule import sqlite3 import pandas as pd from datetime import datetime, timezone +import importlib +# --- REMOVED: import signal --- +# --- REMOVED: from queue import Empty --- from logging_utils import setup_logging +# --- Using the new high-performance WebSocket utility for live prices --- +from live_market_utils import start_live_feed +# --- Import the base class for type hinting (optional but good practice) --- +from strategies.base_strategy import BaseStrategy # --- Configuration --- WATCHED_COINS = ["BTC", "ETH", "SOL", "BNB", "HYPE", "ASTER", "ZEC", "PUMP", "SUI"] -COIN_LISTER_SCRIPT = "list_coins.py" -MARKET_FEEDER_SCRIPT = "market.py" -DATA_FETCHER_SCRIPT = "data_fetcher.py" +LIVE_CANDLE_FETCHER_SCRIPT = "live_candle_fetcher.py" RESAMPLER_SCRIPT = "resampler.py" -MARKET_CAP_FETCHER_SCRIPT = "market_cap_fetcher.py" +# --- REMOVED: Market Cap Fetcher --- +# --- REMOVED: trade_executor.py is no longer a script --- +DASHBOARD_DATA_FETCHER_SCRIPT = "dashboard_data_fetcher.py" STRATEGY_CONFIG_FILE = os.path.join("_data", "strategies.json") -PRICE_DATA_FILE = os.path.join("_data", "current_prices.json") DB_PATH = os.path.join("_data", "market_data.db") -STATUS_FILE = os.path.join("_data", "fetcher_status.json") -MARKET_CAP_SUMMARY_FILE = os.path.join("_data", "market_cap_data.json") +# --- REMOVED: Market Cap File --- LOGS_DIR = "_logs" TRADE_EXECUTOR_STATUS_FILE = os.path.join(LOGS_DIR, "trade_executor_status.json") @@ -41,52 +46,64 @@ def format_market_cap(mc_value): return f"${mc_value:,.2f}" -def run_market_feeder(): - """Target function to run market.py and redirect its output to a log file.""" - log_file = os.path.join(LOGS_DIR, "market_feeder.log") - while True: +def run_live_candle_fetcher(): + """Target function to run the live_candle_fetcher.py script in a resilient loop.""" + + # --- GRACEFUL SHUTDOWN HANDLER --- + import signal + shutdown_requested = False + + def handle_shutdown_signal(signum, frame): + nonlocal shutdown_requested + # Use print here as logging may not be set up + print(f"[CandleFetcher] Shutdown signal ({signum}) received. Will stop after current run.") + shutdown_requested = True + + signal.signal(signal.SIGTERM, handle_shutdown_signal) + signal.signal(signal.SIGINT, handle_shutdown_signal) + # --- END GRACEFUL SHUTDOWN HANDLER --- + + log_file = os.path.join(LOGS_DIR, "live_candle_fetcher.log") + + while not shutdown_requested: # <-- MODIFIED + process = None try: with open(log_file, 'a') as f: - subprocess.run( - [sys.executable, MARKET_FEEDER_SCRIPT, "--log-level", "off"], - check=True, stdout=f, stderr=subprocess.STDOUT - ) + command = [sys.executable, LIVE_CANDLE_FETCHER_SCRIPT, "--coins"] + WATCHED_COINS + ["--log-level", "off"] + f.write(f"\n--- Starting {LIVE_CANDLE_FETCHER_SCRIPT} at {datetime.now()} ---\n") + + # Use Popen instead of run to be non-blocking + process = subprocess.Popen(command, stdout=f, stderr=subprocess.STDOUT) + + # Poll the process and check for shutdown request + while process.poll() is None and not shutdown_requested: + time.sleep(0.5) # Poll every 500ms + + if shutdown_requested and process.poll() is None: + print(f"[CandleFetcher] Terminating subprocess {LIVE_CANDLE_FETCHER_SCRIPT}...") + process.terminate() # Terminate the child script + process.wait() # Wait for it to exit + print(f"[CandleFetcher] Subprocess terminated.") + except (subprocess.CalledProcessError, Exception) as e: + if shutdown_requested: + break # Don't restart if we're shutting down with open(log_file, 'a') as f: f.write(f"\n--- PROCESS ERROR at {datetime.now()} ---\n") - f.write(f"Market feeder script failed: {e}. Restarting...\n") + f.write(f"Live candle fetcher failed: {e}. Restarting...\n") time.sleep(5) - - -def run_data_fetcher_job(): - """Defines the job for the data fetcher, redirecting output to a log file.""" - log_file = os.path.join(LOGS_DIR, "data_fetcher.log") - try: - command = [sys.executable, DATA_FETCHER_SCRIPT, "--coins"] + WATCHED_COINS + ["--days", "7", "--log-level", "off"] - with open(log_file, 'a') as f: - f.write(f"\n--- Starting data_fetcher.py job at {datetime.now()} ---\n") - subprocess.run(command, check=True, stdout=f, stderr=subprocess.STDOUT) - except Exception as e: - with open(log_file, 'a') as f: - f.write(f"\n--- SCHEDULER ERROR at {datetime.now()} ---\n") - f.write(f"Failed to run data_fetcher.py job: {e}\n") - - -def data_fetcher_scheduler(): - """Schedules the data_fetcher.py script.""" - setup_logging('off', 'DataFetcherScheduler') - run_data_fetcher_job() - schedule.every(1).minutes.do(run_data_fetcher_job) - while True: - schedule.run_pending() - time.sleep(1) + + if shutdown_requested: + break # Exit outer loop + + print("[CandleFetcher] Live candle fetcher shutting down.") def run_resampler_job(timeframes_to_generate: list): """Defines the job for the resampler, redirecting output to a log file.""" log_file = os.path.join(LOGS_DIR, "resampler.log") try: - command = [sys.executable, RESAMPLER_SCRIPT, "--coins"] + WATCHED_COINS + ["--timeframes"] + timeframes_to_generate + ["--log-level", "off"] + command = [sys.executable, RESAMPLER_SCRIPT, "--coins"] + WATCHED_COINS + ["--timeframes"] + timeframes_to_generate + ["--log-level", "normal"] with open(log_file, 'a') as f: f.write(f"\n--- Starting resampler.py job at {datetime.now()} ---\n") subprocess.run(command, check=True, stdout=f, stderr=subprocess.STDOUT) @@ -98,61 +115,240 @@ def run_resampler_job(timeframes_to_generate: list): def resampler_scheduler(timeframes_to_generate: list): """Schedules the resampler.py script.""" + + # --- GRACEFUL SHUTDOWN HANDLER --- + import signal + shutdown_requested = False + + def handle_shutdown_signal(signum, frame): + nonlocal shutdown_requested + try: + logging.info(f"Shutdown signal ({signum}) received. Exiting loop...") + except NameError: + print(f"[ResamplerScheduler] Shutdown signal ({signum}) received. Exiting loop...") + shutdown_requested = True + + signal.signal(signal.SIGTERM, handle_shutdown_signal) + signal.signal(signal.SIGINT, handle_shutdown_signal) + # --- END GRACEFUL SHUTDOWN HANDLER --- + setup_logging('off', 'ResamplerScheduler') run_resampler_job(timeframes_to_generate) - schedule.every(4).minutes.do(run_resampler_job, timeframes_to_generate) - while True: + # Schedule to run every minute at the :01 second mark + schedule.every().minute.at(":01").do(run_resampler_job, timeframes_to_generate=timeframes_to_generate) + logging.info("Resampler scheduled to run every minute at :01.") + + while not shutdown_requested: # <-- MODIFIED schedule.run_pending() - time.sleep(1) + time.sleep(0.5) # Check every 500ms to not miss the scheduled time and be responsive + + logging.info("ResamplerScheduler shutting down.") -def run_market_cap_fetcher_job(): - """Defines the job for the market cap fetcher, redirecting output.""" - log_file = os.path.join(LOGS_DIR, "market_cap_fetcher.log") +# --- REMOVED: run_market_cap_fetcher_job function --- + +# --- REMOVED: market_cap_fetcher_scheduler function --- + + +def run_trade_executor(order_execution_queue: multiprocessing.Queue): + """ + Target function to run the TradeExecutor class in a resilient loop. + It now consumes from the order_execution_queue. + """ + + # --- GRACEFUL SHUTDOWN HANDLER --- + import signal + + def handle_shutdown_signal(signum, frame): + # We can just raise KeyboardInterrupt, as it's handled below + logging.info(f"Shutdown signal ({signum}) received. Initiating graceful exit...") + raise KeyboardInterrupt + + signal.signal(signal.SIGTERM, handle_shutdown_signal) + # --- END GRACEFUL SHUTDOWN HANDLER --- + + log_file_path = os.path.join(LOGS_DIR, "trade_executor.log") try: - command = [sys.executable, MARKET_CAP_FETCHER_SCRIPT, "--coins"] + WATCHED_COINS + ["--log-level", "off"] - with open(log_file, 'a') as f: - f.write(f"\n--- Starting {MARKET_CAP_FETCHER_SCRIPT} job at {datetime.now()} ---\n") - subprocess.run(command, check=True, stdout=f, stderr=subprocess.STDOUT) + sys.stdout = open(log_file_path, 'a', buffering=1) + sys.stderr = sys.stdout except Exception as e: - with open(log_file, 'a') as f: - f.write(f"\n--- SCHEDULER ERROR at {datetime.now()} ---\n") - f.write(f"Failed to run {MARKET_CAP_FETCHER_SCRIPT} job: {e}\n") + print(f"Failed to open log file for TradeExecutor: {e}") - -def market_cap_fetcher_scheduler(): - """Schedules the market_cap_fetcher.py script to run daily at a specific UTC time.""" - setup_logging('off', 'MarketCapScheduler') - schedule.every().day.at("00:15", "UTC").do(run_market_cap_fetcher_job) + setup_logging('normal', f"TradeExecutor") + logging.info("\n--- Starting Trade Executor process ---") + while True: - schedule.run_pending() - time.sleep(60) + try: + from trade_executor import TradeExecutor + + executor = TradeExecutor(log_level="normal", order_execution_queue=order_execution_queue) + + # --- REVERTED: Call executor.run() directly --- + executor.run() + + except KeyboardInterrupt: + logging.info("Trade Executor interrupted. Exiting.") + return + except Exception as e: + logging.error(f"Trade Executor failed: {e}. Restarting...\n", exc_info=True) + time.sleep(10) + +def run_position_manager(trade_signal_queue: multiprocessing.Queue, order_execution_queue: multiprocessing.Queue): + """ + Target function to run the PositionManager class in a resilient loop. + Consumes from trade_signal_queue, produces for order_execution_queue. + """ + + # --- GRACEFUL SHUTDOWN HANDLER --- + import signal + + def handle_shutdown_signal(signum, frame): + # Raise KeyboardInterrupt, as it's handled by the loop + logging.info(f"Shutdown signal ({signum}) received. Initiating graceful exit...") + raise KeyboardInterrupt + + signal.signal(signal.SIGTERM, handle_shutdown_signal) + # --- END GRACEFUL SHUTDOWN HANDLER --- + + log_file_path = os.path.join(LOGS_DIR, "position_manager.log") + try: + sys.stdout = open(log_file_path, 'a', buffering=1) + sys.stderr = sys.stdout + except Exception as e: + print(f"Failed to open log file for PositionManager: {e}") + + setup_logging('normal', f"PositionManager") + logging.info("\n--- Starting Position Manager process ---") + + while True: + try: + from position_manager import PositionManager + + manager = PositionManager( + log_level="normal", + trade_signal_queue=trade_signal_queue, + order_execution_queue=order_execution_queue + ) + + # --- REVERTED: Call manager.run() directly --- + manager.run() + + except KeyboardInterrupt: + logging.info("Position Manager interrupted. Exiting.") + return + except Exception as e: + logging.error(f"Position Manager failed: {e}. Restarting...\n", exc_info=True) + time.sleep(10) -def run_strategy(strategy_name: str, config: dict): - """Target function to run a strategy, redirecting its output to a log file.""" - log_file = os.path.join(LOGS_DIR, f"strategy_{strategy_name}.log") - script_name = config['script'] - params_str = json.dumps(config['parameters']) - command = [sys.executable, script_name, "--name", strategy_name, "--params", params_str, "--log-level", "normal"] +def run_strategy(strategy_name: str, config: dict, trade_signal_queue: multiprocessing.Queue): + """ + This function BECOMES the strategy runner. It is executed as a separate + process and pushes signals to the shared queue. + """ + # These imports only happen in the new, lightweight process + import importlib + import os + import sys + import time + import logging + import signal # <-- ADDED + from logging_utils import setup_logging + from strategies.base_strategy import BaseStrategy + + # --- GRACEFUL SHUTDOWN HANDLER --- + def handle_shutdown_signal(signum, frame): + # Raise KeyboardInterrupt, as it's handled by the loop + try: + logging.info(f"Shutdown signal ({signum}) received. Initiating graceful exit...") + except NameError: + print(f"[Strategy-{strategy_name}] Shutdown signal ({signum}) received. Initiating graceful exit...") + raise KeyboardInterrupt + + signal.signal(signal.SIGTERM, handle_shutdown_signal) + # --- END GRACEFUL SHUTDOWN HANDLER --- + + # --- Setup logging to file for this specific process --- + log_file_path = os.path.join(LOGS_DIR, f"strategy_{strategy_name}.log") + try: + sys.stdout = open(log_file_path, 'a', buffering=1) # 1 = line buffering + sys.stderr = sys.stdout + except Exception as e: + print(f"Failed to open log file for {strategy_name}: {e}") + + setup_logging('normal', f"Strategy-{strategy_name}") + + while True: + try: + logging.info(f"--- Starting strategy '{strategy_name}' ---") + + if 'class' not in config: + logging.error(f"Strategy config for '{strategy_name}' is missing the 'class' key. Exiting.") + return + + module_path, class_name = config['class'].rsplit('.', 1) + module = importlib.import_module(module_path) + StrategyClass = getattr(module, class_name) + + strategy = StrategyClass(strategy_name, config['parameters'], trade_signal_queue) + + if config.get("is_event_driven", False): + logging.info(f"Starting EVENT-DRIVEN logic loop...") + strategy.run_event_loop() # This is a blocking call + else: + logging.info(f"Starting POLLING logic loop...") + strategy.run_polling_loop() # This is the original blocking call + + # --- REVERTED: Added back simple KeyboardInterrupt handler --- + except KeyboardInterrupt: + logging.info(f"Strategy {strategy_name} process stopping.") + return + except Exception as e: + # --- REVERTED: Removed specific check for KeyboardInterrupt --- + logging.error(f"Strategy '{strategy_name}' failed: {e}", exc_info=True) + logging.info("Restarting strategy in 10 seconds...") + time.sleep(10) + + +def run_dashboard_data_fetcher(): + """Target function to run the dashboard_data_fetcher.py script.""" + + # --- GRACEFUL SHUTDOWN HANDLER --- + import signal + + def handle_shutdown_signal(signum, frame): + # Raise KeyboardInterrupt, as it's handled by the loop + try: + logging.info(f"Shutdown signal ({signum}) received. Initiating graceful exit...") + except NameError: + print(f"[DashboardDataFetcher] Shutdown signal ({signum}) received. Initiating graceful exit...") + raise KeyboardInterrupt + + signal.signal(signal.SIGTERM, handle_shutdown_signal) + # --- END GRACEFUL SHUTDOWN HANDLER --- + + log_file = os.path.join(LOGS_DIR, "dashboard_data_fetcher.log") while True: try: with open(log_file, 'a') as f: - f.write(f"\n--- Starting strategy '{strategy_name}' at {datetime.now()} ---\n") - subprocess.run(command, check=True, stdout=f, stderr=subprocess.STDOUT) + f.write(f"\n--- Starting Dashboard Data Fetcher at {datetime.now()} ---\n") + subprocess.run([sys.executable, DASHBOARD_DATA_FETCHER_SCRIPT, "--log-level", "normal"], check=True, stdout=f, stderr=subprocess.STDOUT) + except KeyboardInterrupt: # --- MODIFIED: Added to catch interrupt --- + logging.info("Dashboard Data Fetcher stopping.") + break except (subprocess.CalledProcessError, Exception) as e: with open(log_file, 'a') as f: f.write(f"\n--- PROCESS ERROR at {datetime.now()} ---\n") - f.write(f"Strategy '{strategy_name}' failed: {e}. Restarting...\n") + f.write(f"Dashboard Data Fetcher failed: {e}. Restarting...\n") time.sleep(10) class MainApp: - def __init__(self, coins_to_watch: list, processes: dict, strategy_configs: dict): + def __init__(self, coins_to_watch: list, processes: dict, strategy_configs: dict, shared_prices: dict): self.watched_coins = coins_to_watch + self.shared_prices = shared_prices self.prices = {} - self.market_caps = {} - self.last_db_update_info = "Initializing..." + # --- REMOVED: self.market_caps --- self.open_positions = {} self.background_processes = processes self.process_status = {} @@ -160,27 +356,14 @@ class MainApp: self.strategy_statuses = {} def read_prices(self): - """Reads the latest prices from the JSON file.""" - if os.path.exists(PRICE_DATA_FILE): - try: - with open(PRICE_DATA_FILE, 'r', encoding='utf-8') as f: - self.prices = json.load(f) - except (json.JSONDecodeError, IOError): - logging.debug("Could not read price file.") + """Reads the latest prices directly from the shared memory dictionary.""" + try: + # --- FIX: Use .copy() for thread-safe iteration --- + self.prices = self.shared_prices.copy() + except Exception as e: + logging.debug(f"Could not read from shared prices dict: {e}") - def read_market_caps(self): - """Reads the latest market cap summary from its JSON file.""" - if os.path.exists(MARKET_CAP_SUMMARY_FILE): - try: - with open(MARKET_CAP_SUMMARY_FILE, 'r', encoding='utf-8') as f: - summary_data = json.load(f) - - for coin in self.watched_coins: - table_key = f"{coin}_market_cap" - if table_key in summary_data: - self.market_caps[coin] = summary_data[table_key].get('market_cap') - except (json.JSONDecodeError, IOError): - logging.debug("Could not read market cap summary file.") + # --- REMOVED: read_market_caps method --- def read_strategy_statuses(self): """Reads the status JSON file for each enabled strategy.""" @@ -203,64 +386,80 @@ class MainApp: if os.path.exists(TRADE_EXECUTOR_STATUS_FILE): try: with open(TRADE_EXECUTOR_STATUS_FILE, 'r', encoding='utf-8') as f: - self.open_positions = json.load(f) + # --- FIX: Read the 'open_positions' key from the file --- + status_data = json.load(f) + self.open_positions = status_data.get('open_positions', {}) except (IOError, json.JSONDecodeError): logging.debug("Could not read trade executor status file.") else: self.open_positions = {} - - def get_overall_db_status(self): - """Reads the fetcher status from the status file.""" - if os.path.exists(STATUS_FILE): - try: - with open(STATUS_FILE, 'r', encoding='utf-8') as f: - status = json.load(f) - coin = status.get("last_updated_coin") - timestamp_utc_str = status.get("last_run_timestamp_utc") - num_candles = status.get("num_updated_candles", 0) - if timestamp_utc_str: - dt_utc = datetime.fromisoformat(timestamp_utc_str.replace('Z', '+00:00')).replace(tzinfo=timezone.utc) - dt_local = dt_utc.astimezone(None) - - offset = dt_local.utcoffset() - offset_hours = int(offset.total_seconds() / 3600) - sign = '+' if offset_hours >= 0 else '' - offset_str = f"UTC{sign}{offset_hours}" - timestamp_display = f"{dt_local.strftime('%Y-%m-%d %H:%M:%S')} {offset_str}" - else: - timestamp_display = "N/A" - self.last_db_update_info = f"{coin} at {timestamp_display} | {num_candles} candles" - except (IOError, json.JSONDecodeError): - self.last_db_update_info = "Error reading status file." - def check_process_status(self): """Checks if the background processes are still running.""" for name, process in self.background_processes.items(): self.process_status[name] = "Running" if process.is_alive() else "STOPPED" + def _format_price(self, price_val, width=10): + """Helper function to format prices for the dashboard.""" + try: + price_float = float(price_val) + if price_float < 1: + price_str = f"{price_float:>{width}.6f}" + elif price_float < 100: + price_str = f"{price_float:>{width}.4f}" + else: + price_str = f"{price_float:>{width}.2f}" + except (ValueError, TypeError): + price_str = f"{'Loading...':>{width}}" + return price_str + def display_dashboard(self): """Displays a formatted dashboard with side-by-side tables.""" print("\x1b[H\x1b[J", end="") # Clear screen - left_table_lines = [] - left_table_width = 44 - left_table_lines.append("--- Market Dashboard ---") + left_table_lines = ["--- Market Dashboard ---"] + # --- MODIFIED: Adjusted width for new columns --- + left_table_width = 65 left_table_lines.append("-" * left_table_width) - left_table_lines.append(f"{'#':<2} | {'Coin':^6} | {'Live Price':>10} | {'Market Cap':>15} |") + # --- MODIFIED: Replaced Market Cap with Gap --- + left_table_lines.append(f"{'#':<2} | {'Coin':^6} | {'Best Bid':>10} | {'Live Price':>10} | {'Best Ask':>10} | {'Gap':>10} |") left_table_lines.append("-" * left_table_width) for i, coin in enumerate(self.watched_coins, 1): - price = self.prices.get(coin, "Loading...") - market_cap = self.market_caps.get(coin) - formatted_mc = format_market_cap(market_cap) - left_table_lines.append(f"{i:<2} | {coin:^6} | {price:>10} | {formatted_mc:>15} |") + # --- MODIFIED: Fetch all three price types --- + mid_price = self.prices.get(coin, "Loading...") + bid_price = self.prices.get(f"{coin}_bid", "Loading...") + ask_price = self.prices.get(f"{coin}_ask", "Loading...") + + # --- MODIFIED: Use the new formatting helper --- + formatted_mid = self._format_price(mid_price) + formatted_bid = self._format_price(bid_price) + formatted_ask = self._format_price(ask_price) + + # --- MODIFIED: Calculate gap --- + gap_str = f"{'Loading...':>10}" + try: + # Calculate the spread + gap_val = float(ask_price) - float(bid_price) + # Format gap with high precision, similar to price + if gap_val < 1: + gap_str = f"{gap_val:>{10}.6f}" + else: + gap_str = f"{gap_val:>{10}.4f}" + except (ValueError, TypeError): + pass # Keep 'Loading...' + + # --- REMOVED: Market Cap logic --- + + # --- MODIFIED: Print all price columns including gap --- + left_table_lines.append(f"{i:<2} | {coin:^6} | {formatted_bid} | {formatted_mid} | {formatted_ask} | {gap_str} |") left_table_lines.append("-" * left_table_width) - right_table_lines = [] - right_table_width = 154 - right_table_lines.append("--- Strategy Status ---") + right_table_lines = ["--- Strategy Status ---"] + # --- FIX: Adjusted table width after removing parameters --- + right_table_width = 105 right_table_lines.append("-" * right_table_width) - right_table_lines.append(f"{'#':^2} | {'Strategy Name':<25} | {'Coin':^6} | {'Signal':^8} | {'Signal Price':>12} | {'Last Change':>17} | {'TF':^5} | {'Size':^8} | {'Parameters':<45} |") + # --- FIX: Removed 'Parameters' from header --- + right_table_lines.append(f"{'#':^2} | {'Strategy Name':<25} | {'Coin':^6} | {'Signal':^8} | {'Signal Price':>12} | {'Last Change':>17} | {'TF':^5} | {'Size':^8} |") right_table_lines.append("-" * right_table_width) for i, (name, status) in enumerate(self.strategy_statuses.items(), 1): signal = status.get('current_signal', 'N/A') @@ -274,14 +473,37 @@ class MainApp: last_change_display = dt_local.strftime('%Y-%m-%d %H:%M') config_params = self.strategy_configs.get(name, {}).get('parameters', {}) - coin = config_params.get('coin', 'N/A') - timeframe = config_params.get('timeframe', 'N/A') - size = config_params.get('size', 'N/A') - other_params = {k: v for k, v in config_params.items() if k not in ['coin', 'timeframe', 'size']} - params_str = ", ".join([f"{k}={v}" for k, v in other_params.items()]) - - right_table_lines.append(f"{i:^2} | {name:<25} | {coin:^6} | {signal:^8} | {price_display:>12} | {last_change_display:>17} | {timeframe:^5} | {size:>8} | {params_str:<45} |") + # --- FIX: Read coin/size from status file first, fallback to config --- + coin = status.get('coin', config_params.get('coin', 'N/A')) + + # --- FIX: Handle nested 'coins_to_copy' logic for size --- + # --- MODIFIED: Read 'size' from status first, then config, then 'Multi' --- + size = status.get('size') + if not size: + if 'coins_to_copy' in config_params: + size = 'Multi' + else: + size = config_params.get('size', 'N/A') + + timeframe = config_params.get('timeframe', 'N/A') + + # --- FIX: Removed parameter string logic --- + + # --- FIX: Removed 'params_str' from the formatted line --- + + size_display = f"{size:>8}" + if isinstance(size, (int, float)): + # --- MODIFIED: More flexible size formatting --- + if size < 0.0001: + size_display = f"{size:>8.6f}" + elif size < 1: + size_display = f"{size:>8.4f}" + else: + size_display = f"{size:>8.2f}" + # --- END NEW LOGIC --- + + right_table_lines.append(f"{i:^2} | {name:<25} | {coin:^6} | {signal:^8} | {price_display:>12} | {last_change_display:>17} | {timeframe:^5} | {size_display} |") right_table_lines.append("-" * right_table_width) output_lines = [] @@ -292,8 +514,6 @@ class MainApp: left_part = left_table_lines[i] if i < len(left_table_lines) else " " * left_table_width right_part = indent + right_table_lines[i] if i < len(right_table_lines) else "" output_lines.append(f"{left_part}{separator}{right_part}") - - output_lines.append(f"\nDB Status: Last update -> {self.last_db_update_info}") output_lines.append("\n--- Open Positions ---") pos_table_width = 100 @@ -301,38 +521,32 @@ class MainApp: output_lines.append(f"{'Account':<10} | {'Coin':<6} | {'Size':>15} | {'Entry Price':>12} | {'Mark Price':>12} | {'PNL':>15} | {'Leverage':>10} |") output_lines.append("-" * pos_table_width) - perps_positions = self.open_positions.get('perpetuals_account', {}).get('open_positions', []) - spot_positions = self.open_positions.get('spot_account', {}).get('positions', []) - - if not perps_positions and not spot_positions: - output_lines.append("No open positions found.") + # --- FIX: Correctly read and display open positions --- + if not self.open_positions: + output_lines.append(f"{'No open positions.':^{pos_table_width}}") else: - for pos in perps_positions: - # --- FIX: Safely handle potentially None values before formatting --- - try: - pnl = float(pos.get('pnl', 0.0)) - pnl_str = f"${pnl:,.2f}" - except (ValueError, TypeError): - pnl_str = "Error" - - coin = pos.get('coin') or '-' - size = pos.get('size') or '-' - entry_price = pos.get('entry_price') or '-' - mark_price = pos.get('mark_price') or '-' - leverage = pos.get('leverage') or '-' - - output_lines.append(f"{'Perps':<10} | {coin:<6} | {size:>15} | {entry_price:>12} | {mark_price:>12} | {pnl_str:>15} | {leverage:>10} |") + for account, positions in self.open_positions.items(): + if not positions: + continue + for coin, pos in positions.items(): + try: + size_f = float(pos.get('size', 0)) + entry_f = float(pos.get('entry_price', 0)) + mark_f = float(self.prices.get(coin, 0)) + pnl_f = (mark_f - entry_f) * size_f if size_f > 0 else (entry_f - mark_f) * abs(size_f) + lev = pos.get('leverage', 1) + + size_str = f"{size_f:>{15}.5f}" + entry_str = f"{entry_f:>{12}.2f}" + mark_str = f"{mark_f:>{12}.2f}" + pnl_str = f"{pnl_f:>{15}.2f}" + lev_str = f"{lev}x" + + output_lines.append(f"{account:<10} | {coin:<6} | {size_str} | {entry_str} | {mark_str} | {pnl_str} | {lev_str:>10} |") + except (ValueError, TypeError): + output_lines.append(f"{account:<10} | {coin:<6} | {'Error parsing data...':^{pos_table_width-20}} |") - for pos in spot_positions: - pnl = pos.get('pnl', 'N/A') - coin = pos.get('coin') or '-' - balance_size = pos.get('balance_size') or '-' - output_lines.append(f"{'Spot':<10} | {coin:<6} | {balance_size:>15} | {'-':>12} | {'-':>12} | {pnl:>15} | {'-':>10} |") output_lines.append("-" * pos_table_width) - - output_lines.append("\n--- Background Processes ---") - for name, status in self.process_status.items(): - output_lines.append(f"{name:<25}: {status}") final_output = "\n".join(output_lines) print(final_output) @@ -342,30 +556,21 @@ class MainApp: """Main loop to read data, display dashboard, and check processes.""" while True: self.read_prices() - self.read_market_caps() - self.get_overall_db_status() + # --- REMOVED: self.read_market_caps() --- self.read_strategy_statuses() self.read_executor_status() - self.check_process_status() + # --- REMOVED: self.check_process_status() --- self.display_dashboard() - time.sleep(2) - + time.sleep(0.5) if __name__ == "__main__": setup_logging('normal', 'MainApp') if not os.path.exists(LOGS_DIR): os.makedirs(LOGS_DIR) - - logging.info(f"Running coin lister: '{COIN_LISTER_SCRIPT}'...") - try: - subprocess.run([sys.executable, COIN_LISTER_SCRIPT], check=True, capture_output=True, text=True) - except subprocess.CalledProcessError as e: - logging.error(f"Failed to run '{COIN_LISTER_SCRIPT}'. Error: {e.stderr}") - sys.exit(1) - + processes = {} - strategy_configs = {} + # --- REVERTED: Removed process groups --- try: with open(STRATEGY_CONFIG_FILE, 'r') as f: @@ -374,45 +579,107 @@ if __name__ == "__main__": logging.error(f"Could not load strategies from '{STRATEGY_CONFIG_FILE}': {e}") sys.exit(1) - required_timeframes = set() - for name, config in strategy_configs.items(): - if config.get("enabled", False): - tf = config.get("parameters", {}).get("timeframe") - if tf: - required_timeframes.add(tf) + # --- FIX: Hardcoded timeframes --- + required_timeframes = [ + "3m", "5m", "15m", "30m", "1h", "2h", "4h", "8h", + "12h", "1d", "3d", "1w", "1M", "148m", "37m" + ] + logging.info(f"Using fixed timeframes for resampler: {required_timeframes}") - if not required_timeframes: - logging.warning("No timeframes required by any enabled strategy. Resampler will not run effectively.") + with multiprocessing.Manager() as manager: + shared_prices = manager.dict() + # --- FIX: Create TWO queues --- + trade_signal_queue = manager.Queue() + order_execution_queue = manager.Queue() - - processes["Market Feeder"] = multiprocessing.Process(target=run_market_feeder, daemon=True) - processes["Data Fetcher"] = multiprocessing.Process(target=data_fetcher_scheduler, daemon=True) - processes["Resampler"] = multiprocessing.Process(target=resampler_scheduler, args=(list(required_timeframes),), daemon=True) - processes["Market Cap Fetcher"] = multiprocessing.Process(target=market_cap_fetcher_scheduler, daemon=True) - - for name, config in strategy_configs.items(): - if config.get("enabled", False): - if not os.path.exists(config['script']): - logging.error(f"Strategy script '{config['script']}' for strategy '{name}' not found. Skipping.") - continue - proc = multiprocessing.Process(target=run_strategy, args=(name, config), daemon=True) - processes[f"Strategy: {name}"] = proc + # --- REVERTED: All processes are daemon=True and in one dict --- + + # --- FIX: Pass WATCHED_COINS to the start_live_feed process --- + # --- MODIFICATION: Set log level back to 'off' --- + processes["Live Market Feed"] = multiprocessing.Process( + target=start_live_feed, + args=(shared_prices, WATCHED_COINS, 'off'), + daemon=True + ) + processes["Live Candle Fetcher"] = multiprocessing.Process(target=run_live_candle_fetcher, daemon=True) + processes["Resampler"] = multiprocessing.Process(target=resampler_scheduler, args=(list(required_timeframes),), daemon=True) + # --- REMOVED: Market Cap Fetcher Process --- + processes["Dashboard Data"] = multiprocessing.Process(target=run_dashboard_data_fetcher, daemon=True) - for name, proc in processes.items(): - logging.info(f"Starting process '{name}'...") - proc.start() - - time.sleep(3) + processes["Position Manager"] = multiprocessing.Process( + target=run_position_manager, + args=(trade_signal_queue, order_execution_queue), + daemon=True + ) + processes["Trade Executor"] = multiprocessing.Process( + target=run_trade_executor, + args=(order_execution_queue,), + daemon=True + ) + + for name, config in strategy_configs.items(): + if config.get("enabled", False): + if 'class' not in config: + logging.error(f"Strategy '{name}' is missing 'class' key. Skipping.") + continue + proc = multiprocessing.Process(target=run_strategy, args=(name, config, trade_signal_queue), daemon=True) + processes[f"Strategy: {name}"] = proc # Add to strategy group + + # --- REVERTED: Removed combined dict --- - app = MainApp(coins_to_watch=WATCHED_COINS, processes=processes, strategy_configs=strategy_configs) - try: - app.run() - except KeyboardInterrupt: - logging.info("Shutting down...") - for proc in processes.values(): - if proc.is_alive(): proc.terminate() - for proc in processes.values(): - if proc.is_alive(): proc.join() + for name, proc in processes.items(): + logging.info(f"Starting process '{name}'...") + proc.start() + + time.sleep(3) + + app = MainApp(coins_to_watch=WATCHED_COINS, processes=processes, strategy_configs=strategy_configs, shared_prices=shared_prices) + try: + app.run() + except KeyboardInterrupt: + # --- MODIFIED: Staged shutdown --- + logging.info("Shutting down...") + + strategy_procs = {} + other_procs = {} + for name, proc in processes.items(): + if name.startswith("Strategy:"): + strategy_procs[name] = proc + else: + other_procs[name] = proc + + # --- 1. Terminate strategy processes --- + logging.info("Shutting down strategy processes first...") + for name, proc in strategy_procs.items(): + if proc.is_alive(): + logging.info(f"Terminating process: '{name}'...") + proc.terminate() + + # --- 2. Wait for 5 seconds --- + logging.info("Waiting 5 seconds for strategies to close...") + time.sleep(5) + + # --- 3. Terminate all other processes --- + logging.info("Shutting down remaining core processes...") + for name, proc in other_procs.items(): + if proc.is_alive(): + logging.info(f"Terminating process: '{name}'...") + proc.terminate() + + # --- 4. Join all processes (strategies and others) --- + logging.info("Waiting for all processes to join...") + for name, proc in processes.items(): # Iterate over the original dict to get all + if proc.is_alive(): + logging.info(f"Waiting for process '{name}' to join...") + proc.join(timeout=5) # Wait up to 5 seconds + if proc.is_alive(): + # If it's still alive, force kill + logging.warning(f"Process '{name}' did not terminate, forcing kill.") + proc.kill() + # --- END MODIFIED --- + logging.info("Shutdown complete.") sys.exit(0) + + diff --git a/market_cap_fetcher.py b/market_cap_fetcher.py index ac25ba6..9b26fa5 100644 --- a/market_cap_fetcher.py +++ b/market_cap_fetcher.py @@ -8,47 +8,106 @@ import requests import time from datetime import datetime, timezone, timedelta import json +from dotenv import load_dotenv + +load_dotenv() -# Assuming logging_utils.py is in the same directory from logging_utils import setup_logging class MarketCapFetcher: """ Fetches historical daily market cap data from the CoinGecko API and - intelligently updates the SQLite database. It processes individual coins, - aggregates stablecoins, and captures total market cap metrics. + intelligently upserts it into the SQLite database for all coins. """ - COIN_ID_MAP = { - "BTC": "bitcoin", - "ETH": "ethereum", - "SOL": "solana", - "BNB": "binancecoin", - "HYPE": "hyperliquid", - "ASTER": "astar", - "ZEC": "zcash", - "PUMP": "pump-fun", # Correct ID is 'pump-fun' - "SUI": "sui" - } - - STABLECOIN_ID_MAP = { - "USDT": "tether", - "USDC": "usd-coin", - "USDE": "ethena-usde", - "DAI": "dai", - "PYUSD": "paypal-usd" - } - - def __init__(self, log_level: str, coins: list): + def __init__(self, log_level: str): setup_logging(log_level, 'MarketCapFetcher') - self.coins_to_fetch = coins self.db_path = os.path.join("_data", "market_data.db") self.api_base_url = "https://api.coingecko.com/api/v3" self.api_key = os.environ.get("COINGECKO_API_KEY") - if not self.api_key: logging.error("CoinGecko API key not found. Please set the COINGECKO_API_KEY environment variable.") sys.exit(1) + + self.COIN_ID_MAP = self._load_coin_id_map() + if not self.COIN_ID_MAP: + logging.error("Coin ID map is empty. Run 'update_coin_map.py' to generate it.") + sys.exit(1) + + self.coins_to_fetch = list(self.COIN_ID_MAP.keys()) + + self.STABLECOIN_ID_MAP = { + "USDT": "tether", "USDC": "usd-coin", "USDE": "ethena-usde", + "DAI": "dai", "PYUSD": "paypal-usd" + } + + self._ensure_tables_exist() + + def _ensure_tables_exist(self): + """Ensures all market cap tables exist with timestamp_ms as PRIMARY KEY.""" + all_tables_to_check = [f"{coin}_market_cap" for coin in self.coins_to_fetch] + all_tables_to_check.extend(["STABLECOINS_market_cap", "TOTAL_market_cap_daily"]) + + with sqlite3.connect(self.db_path) as conn: + for table_name in all_tables_to_check: + cursor = conn.cursor() + cursor.execute(f"PRAGMA table_info('{table_name}')") + columns = cursor.fetchall() + if columns: + pk_found = any(col[1] == 'timestamp_ms' and col[5] == 1 for col in columns) + if not pk_found: + logging.warning(f"Schema for table '{table_name}' is incorrect. Dropping and recreating table.") + try: + conn.execute(f'DROP TABLE "{table_name}"') + self._create_market_cap_table(conn, table_name) + logging.info(f"Successfully recreated schema for '{table_name}'.") + except Exception as e: + logging.error(f"FATAL: Failed to recreate table '{table_name}': {e}. Please delete 'market_data.db' and restart.") + sys.exit(1) + else: + self._create_market_cap_table(conn, table_name) + logging.info("All market cap table schemas verified.") + + def _create_market_cap_table(self, conn, table_name): + """Creates a new market cap table with the correct schema.""" + conn.execute(f''' + CREATE TABLE IF NOT EXISTS "{table_name}" ( + datetime_utc TEXT, + timestamp_ms INTEGER PRIMARY KEY, + market_cap REAL + ) + ''') + + def _load_coin_id_map(self) -> dict: + """Loads the dynamically generated coin-to-id mapping.""" + map_file_path = os.path.join("_data", "coin_id_map.json") + try: + with open(map_file_path, 'r') as f: + return json.load(f) + except (FileNotFoundError, json.JSONDecodeError) as e: + logging.error(f"Could not load '{map_file_path}'. Please run 'update_coin_map.py' first. Error: {e}") + return {} + + def _upsert_market_cap_data(self, conn, table_name: str, df: pd.DataFrame): + """Upserts a DataFrame of market cap data into the specified table.""" + if df.empty: + return + + records_to_upsert = [] + for index, row in df.iterrows(): + records_to_upsert.append(( + row['datetime_utc'].strftime('%Y-%m-%d %H:%M:%S'), + row['timestamp_ms'], + row['market_cap'] + )) + + cursor = conn.cursor() + cursor.executemany(f''' + INSERT OR REPLACE INTO "{table_name}" (datetime_utc, timestamp_ms, market_cap) + VALUES (?, ?, ?) + ''', records_to_upsert) + conn.commit() + logging.info(f"Successfully upserted {len(records_to_upsert)} records into '{table_name}'.") def run(self): """ @@ -58,7 +117,6 @@ class MarketCapFetcher: with sqlite3.connect(self.db_path) as conn: conn.execute("PRAGMA journal_mode=WAL;") - # 1. Process individual coins for coin_symbol in self.coins_to_fetch: coin_id = self.COIN_ID_MAP.get(coin_symbol.upper()) if not coin_id: @@ -71,30 +129,21 @@ class MarketCapFetcher: logging.error(f"An unexpected error occurred while processing {coin_symbol}: {e}") time.sleep(2) - # 2. Process and aggregate stablecoins self._update_stablecoin_aggregate(conn) - - # 3. Process total market cap metrics self._update_total_market_cap(conn) - - # 4. Save a summary of the latest data self._save_summary(conn) logging.info("--- Market cap fetch process complete ---") def _save_summary(self, conn): - """ - Queries the last record from each market cap table and saves a summary to a JSON file. - """ + # ... (This function is unchanged) logging.info("--- Generating Market Cap Summary ---") summary_data = {} summary_file_path = os.path.join("_data", "market_cap_data.json") - try: cursor = conn.cursor() cursor.execute("SELECT name FROM sqlite_master WHERE type='table' AND (name LIKE '%_market_cap' OR name LIKE 'TOTAL_%');") tables = [row[0] for row in cursor.fetchall()] - for table_name in tables: try: df_last = pd.read_sql(f'SELECT * FROM "{table_name}" ORDER BY datetime_utc DESC LIMIT 1', conn) @@ -102,40 +151,24 @@ class MarketCapFetcher: summary_data[table_name] = df_last.to_dict('records')[0] except Exception as e: logging.error(f"Could not read last record from table '{table_name}': {e}") - if summary_data: summary_data['summary_last_updated_utc'] = datetime.now(timezone.utc).isoformat() - with open(summary_file_path, 'w', encoding='utf-8') as f: json.dump(summary_data, f, indent=4) logging.info(f"Successfully saved market cap summary to '{summary_file_path}'") else: logging.warning("No data found to create a summary.") - except Exception as e: logging.error(f"Failed to generate summary: {e}") def _update_total_market_cap(self, conn): - """ - Fetches the current total market cap and saves it for the current date. - """ + """Fetches the current total market cap and upserts it for the current date.""" logging.info("--- Processing Total Market Cap ---") table_name = "TOTAL_market_cap_daily" - try: - # --- FIX: Use the current date instead of yesterday's --- today_date = datetime.now(timezone.utc).date() - - cursor = conn.cursor() - cursor.execute(f"SELECT name FROM sqlite_master WHERE type='table' AND name='{table_name}';") - table_exists = cursor.fetchone() - - if table_exists: - # Check if we already have a record for today - cursor.execute(f"SELECT 1 FROM \"{table_name}\" WHERE date(datetime_utc) = ? LIMIT 1", (today_date.isoformat(),)) - if cursor.fetchone(): - logging.info(f"Total market cap for {today_date} already exists. Skipping.") - return + today_dt = pd.to_datetime(today_date) + today_ts = int(today_dt.timestamp() * 1000) logging.info("Fetching current global market data...") url = f"{self.api_base_url}/global" @@ -147,10 +180,11 @@ class MarketCapFetcher: if total_mc: df_total = pd.DataFrame([{ - 'datetime_utc': pd.to_datetime(today_date), + 'datetime_utc': today_dt, + 'timestamp_ms': today_ts, 'market_cap': total_mc }]) - df_total.to_sql(table_name, conn, if_exists='append', index=False) + self._upsert_market_cap_data(conn, table_name, df_total) logging.info(f"Saved total market cap for {today_date}: ${total_mc:,.2f}") except requests.exceptions.RequestException as e: @@ -158,7 +192,6 @@ class MarketCapFetcher: except Exception as e: logging.error(f"An error occurred while updating total market cap: {e}") - def _update_stablecoin_aggregate(self, conn): """Fetches data for all stablecoins and saves the aggregated market cap.""" logging.info("--- Processing aggregated stablecoin market cap ---") @@ -168,7 +201,6 @@ class MarketCapFetcher: logging.info(f"Fetching historical data for stablecoin: {symbol}...") df = self._fetch_historical_data(coin_id, days=365) if not df.empty: - df['coin'] = symbol all_stablecoin_df = pd.concat([all_stablecoin_df, df]) time.sleep(2) @@ -176,31 +208,30 @@ class MarketCapFetcher: logging.warning("No data fetched for any stablecoins. Cannot create aggregate.") return - aggregated_df = all_stablecoin_df.groupby(all_stablecoin_df['datetime_utc'].dt.date)['market_cap'].sum().reset_index() - aggregated_df['datetime_utc'] = pd.to_datetime(aggregated_df['datetime_utc']) + aggregated_df = all_stablecoin_df.groupby('timestamp_ms').agg( + datetime_utc=('datetime_utc', 'first'), + market_cap=('market_cap', 'sum') + ).reset_index() table_name = "STABLECOINS_market_cap" - last_date_in_db = self._get_last_date_from_db(table_name, conn) + last_date_in_db = self._get_last_date_from_db(table_name, conn, is_timestamp_ms=True) if last_date_in_db: - aggregated_df = aggregated_df[aggregated_df['datetime_utc'] > last_date_in_db] + aggregated_df = aggregated_df[aggregated_df['timestamp_ms'] > last_date_in_db] if not aggregated_df.empty: - aggregated_df.to_sql(table_name, conn, if_exists='append', index=False) - logging.info(f"Successfully saved {len(aggregated_df)} daily records to '{table_name}'.") + self._upsert_market_cap_data(conn, table_name, aggregated_df) else: logging.info("Aggregated stablecoin data is already up-to-date.") - def _update_market_cap_for_coin(self, coin_id: str, coin_symbol: str, conn): """Fetches and appends new market cap data for a single coin.""" table_name = f"{coin_symbol}_market_cap" - - last_date_in_db = self._get_last_date_from_db(table_name, conn) + last_date_in_db = self._get_last_date_from_db(table_name, conn, is_timestamp_ms=True) days_to_fetch = 365 if last_date_in_db: - delta_days = (datetime.now() - last_date_in_db).days + delta_days = (datetime.now(timezone.utc) - datetime.fromtimestamp(last_date_in_db/1000, tz=timezone.utc)).days if delta_days <= 0: logging.info(f"Market cap data for '{coin_symbol}' is already up-to-date.") return @@ -215,24 +246,30 @@ class MarketCapFetcher: return if last_date_in_db: - df = df[df['datetime_utc'] > last_date_in_db] + df = df[df['timestamp_ms'] > last_date_in_db] if not df.empty: - df.to_sql(table_name, conn, if_exists='append', index=False) - logging.info(f"Successfully saved {len(df)} new daily market cap records for {coin_symbol}.") + self._upsert_market_cap_data(conn, table_name, df) else: logging.info(f"Data was fetched, but no new records needed saving for '{coin_symbol}'.") - def _get_last_date_from_db(self, table_name: str, conn) -> pd.Timestamp: - """Gets the most recent date from a market cap table as a pandas Timestamp.""" + def _get_last_date_from_db(self, table_name: str, conn, is_timestamp_ms: bool = False): + """Gets the most recent date or timestamp from a market cap table.""" try: cursor = conn.cursor() cursor.execute(f"SELECT name FROM sqlite_master WHERE type='table' AND name='{table_name}';") if not cursor.fetchone(): return None + + col_to_query = "timestamp_ms" if is_timestamp_ms else "datetime_utc" + last_val = pd.read_sql(f'SELECT MAX({col_to_query}) FROM "{table_name}"', conn).iloc[0, 0] + + if pd.isna(last_val): + return None + if is_timestamp_ms: + return int(last_val) + return pd.to_datetime(last_val) - last_date_str = pd.read_sql(f'SELECT MAX(datetime_utc) FROM "{table_name}"', conn).iloc[0, 0] - return pd.to_datetime(last_date_str) if last_date_str else None except Exception as e: logging.error(f"Could not read last date from table '{table_name}': {e}") return None @@ -245,7 +282,7 @@ class MarketCapFetcher: try: logging.debug(f"Fetching last {days} days for {coin_id}...") - response = requests.get(url, headers=headers) + response = requests.get(url, headers=headers, params=params) response.raise_for_status() data = response.json() @@ -253,9 +290,16 @@ class MarketCapFetcher: if not market_caps: return pd.DataFrame() df = pd.DataFrame(market_caps, columns=['timestamp_ms', 'market_cap']) - df['datetime_utc'] = pd.to_datetime(df['timestamp_ms'], unit='ms') - df.drop_duplicates(subset=['datetime_utc'], keep='last', inplace=True) - return df[['datetime_utc', 'market_cap']] + + # --- FIX: Normalize all timestamps to the start of the day (00:00:00 UTC) --- + # This prevents duplicate entries for the same day (e.g., a "live" candle vs. the daily one) + df['datetime_utc'] = pd.to_datetime(df['timestamp_ms'], unit='ms').dt.normalize() + + # Recalculate the timestamp_ms to match the normalized 00:00:00 datetime + df['timestamp_ms'] = (df['datetime_utc'].astype('int64') // 10**6) + + df.drop_duplicates(subset=['timestamp_ms'], keep='last', inplace=True) + return df[['datetime_utc', 'timestamp_ms', 'market_cap']] except requests.exceptions.RequestException as e: logging.error(f"API request failed for {coin_id}: {e}.") @@ -264,12 +308,6 @@ class MarketCapFetcher: if __name__ == "__main__": parser = argparse.ArgumentParser(description="Fetch historical market cap data from CoinGecko.") - parser.add_argument( - "--coins", - nargs='+', - default=["BTC", "ETH", "SOL", "BNB", "HYPE", "ASTER", "ZEC", "PUMP", "SUI"], - help="List of coin symbols to fetch (e.g., BTC ETH)." - ) parser.add_argument( "--log-level", default="normal", @@ -278,6 +316,6 @@ if __name__ == "__main__": ) args = parser.parse_args() - fetcher = MarketCapFetcher(log_level=args.log_level, coins=args.coins) + fetcher = MarketCapFetcher(log_level=args.log_level) fetcher.run() diff --git a/position_logic/__init__.py b/position_logic/__init__.py new file mode 100644 index 0000000..c4127c9 --- /dev/null +++ b/position_logic/__init__.py @@ -0,0 +1,2 @@ +# This file can be empty. +# It tells Python that 'position_logic' is a directory containing modules. diff --git a/position_logic/base_logic.py b/position_logic/base_logic.py new file mode 100644 index 0000000..a6cbe99 --- /dev/null +++ b/position_logic/base_logic.py @@ -0,0 +1,31 @@ +from abc import ABC, abstractmethod +import logging + +class BasePositionLogic(ABC): + """ + Abstract base class for all strategy-specific position logic. + Defines the interface for how the PositionManager interacts with logic modules. + """ + def __init__(self, strategy_name: str, send_order_callback, log_trade_callback): + self.strategy_name = strategy_name + self.send_order = send_order_callback + self.log_trade = log_trade_callback + logging.info(f"Initialized position logic for '{strategy_name}'") + + @abstractmethod + def handle_signal(self, signal_data: dict, current_strategy_positions: dict) -> dict: + """ + The core logic method. This is called by the PositionManager when a + new signal arrives for this strategy. + + Args: + signal_data: The full signal dictionary from the strategy. + current_strategy_positions: A dict of this strategy's current positions, + keyed by coin (e.g., {"BTC": {"side": "long", ...}}). + + Returns: + A dictionary representing the new state for the *specific coin* in the + signal (e.g., {"side": "long", "size": 0.1}). + Return None to indicate the position for this coin should be closed/removed. + """ + pass diff --git a/position_logic/default_flip_logic.py b/position_logic/default_flip_logic.py new file mode 100644 index 0000000..c8dfb9a --- /dev/null +++ b/position_logic/default_flip_logic.py @@ -0,0 +1,83 @@ +import logging +from position_logic.base_logic import BasePositionLogic + +class DefaultFlipLogic(BasePositionLogic): + """ + The standard "flip-on-signal" logic used by most simple strategies + (SMA, MA Cross, and even the per-coin Copy Trader signals). + + - BUY signal: Closes any short, opens a long. + - SELL signal: Closes any long, opens a short. + - FLAT signal: Closes any open position. + """ + def handle_signal(self, signal_data: dict, current_strategy_positions: dict) -> dict: + """ + Processes a BUY, SELL, or FLAT signal and issues the necessary orders + to flip or open a position. + """ + name = self.strategy_name + params = signal_data['config']['parameters'] + coin = signal_data['coin'] + desired_signal = signal_data['signal'] + signal_price = signal_data.get('signal_price', 0) + + size = params.get('size') + leverage_long = int(params.get('leverage_long', 2)) + leverage_short = int(params.get('leverage_short', 2)) + agent_name = signal_data['config'].get("agent", "default").lower() + + # --- This logic now correctly targets a specific coin --- + current_position = current_strategy_positions.get(coin) + new_position_state = None # Return None to close position + + if desired_signal == "BUY" or desired_signal == "INIT_BUY": + new_position_state = {"coin": coin, "side": "long", "size": size} + + if not current_position: + logging.warning(f"[{name}]-[{coin}] ACTION: Setting leverage to {leverage_long}x and opening LONG.") + self.send_order(agent_name, "update_leverage", coin, is_buy=True, size=leverage_long) + self.send_order(agent_name, "market_open", coin, is_buy=True, size=size) + self.log_trade(strategy=name, coin=coin, action="OPEN_LONG", price=signal_price, size=size, signal=desired_signal) + + elif current_position['side'] == 'short': + logging.warning(f"[{name}]-[{coin}] ACTION: Closing SHORT and opening LONG with {leverage_long}x leverage.") + self.send_order(agent_name, "update_leverage", coin, is_buy=True, size=leverage_long) + self.send_order(agent_name, "market_open", coin, is_buy=True, size=current_position['size'], reduce_only=True) + self.log_trade(strategy=name, coin=coin, action="CLOSE_SHORT", price=signal_price, size=current_position['size'], signal=desired_signal) + self.send_order(agent_name, "market_open", coin, is_buy=True, size=size) + self.log_trade(strategy=name, coin=coin, action="OPEN_LONG", price=signal_price, size=size, signal=desired_signal) + + else: # Already long, do nothing + logging.info(f"[{name}]-[{coin}] INFO: Already LONG, no action taken.") + new_position_state = current_position # State is unchanged + + elif desired_signal == "SELL" or desired_signal == "INIT_SELL": + new_position_state = {"coin": coin, "side": "short", "size": size} + + if not current_position: + logging.warning(f"[{name}]-[{coin}] ACTION: Setting leverage to {leverage_short}x and opening SHORT.") + self.send_order(agent_name, "update_leverage", coin, is_buy=False, size=leverage_short) + self.send_order(agent_name, "market_open", coin, is_buy=False, size=size) + self.log_trade(strategy=name, coin=coin, action="OPEN_SHORT", price=signal_price, size=size, signal=desired_signal) + + elif current_position['side'] == 'long': + logging.warning(f"[{name}]-[{coin}] ACTION: Closing LONG and opening SHORT with {leverage_short}x leverage.") + self.send_order(agent_name, "update_leverage", coin, is_buy=False, size=leverage_short) + self.send_order(agent_name, "market_open", coin, is_buy=False, size=current_position['size'], reduce_only=True) + self.log_trade(strategy=name, coin=coin, action="CLOSE_LONG", price=signal_price, size=current_position['size'], signal=desired_signal) + self.send_order(agent_name, "market_open", coin, is_buy=False, size=size) + self.log_trade(strategy=name, coin=coin, action="OPEN_SHORT", price=signal_price, size=size, signal=desired_signal) + + else: # Already short, do nothing + logging.info(f"[{name}]-[{coin}] INFO: Already SHORT, no action taken.") + new_position_state = current_position # State is unchanged + + elif desired_signal == "FLAT": + if current_position: + logging.warning(f"[{name}]-[{coin}] ACTION: Close {current_position['side']} position.") + is_buy = current_position['side'] == 'short' # To close a short, we buy + self.send_order(agent_name, "market_open", coin, is_buy=is_buy, size=current_position['size'], reduce_only=True) + self.log_trade(strategy=name, coin=coin, action=f"CLOSE_{current_position['side'].upper()}", price=signal_price, size=current_position['size'], signal=desired_signal) + # new_position_state is already None, which will remove it + + return new_position_state diff --git a/position_manager.py b/position_manager.py new file mode 100644 index 0000000..c355c29 --- /dev/null +++ b/position_manager.py @@ -0,0 +1,170 @@ +import logging +import os +import sys +import json +import time +import multiprocessing +import numpy as np # Import numpy to handle np.float64 + +from logging_utils import setup_logging +from trade_log import log_trade + +class PositionManager: + """ + (Stateless) Listens for EXPLICIT signals (e.g., "OPEN_LONG") from all + strategies and converts them into specific execution orders + (e.g., "market_open") for the TradeExecutor. + + It holds NO position state. + """ + + def __init__(self, log_level: str, trade_signal_queue: multiprocessing.Queue, order_execution_queue: multiprocessing.Queue): + # Note: Logging is set up by the run_position_manager function + + self.trade_signal_queue = trade_signal_queue + self.order_execution_queue = order_execution_queue + + # --- REMOVED: All state management --- + + logging.info("Position Manager (Stateless) started.") + + # --- REMOVED: _load_managed_positions method --- + # --- REMOVED: _save_managed_positions method --- + # --- REMOVED: All tick/rounding/meta logic --- + + def send_order(self, agent: str, action: str, coin: str, is_buy: bool, size: float, reduce_only: bool = False, limit_px=None, sl_px=None, tp_px=None): + """Helper function to put a standardized order onto the execution queue.""" + order_data = { + "agent": agent, + "action": action, + "coin": coin, + "is_buy": is_buy, + "size": size, + "reduce_only": reduce_only, + "limit_px": limit_px, + "sl_px": sl_px, + "tp_px": tp_px, + } + logging.info(f"Sending order to executor: {order_data}") + self.order_execution_queue.put(order_data) + + def run(self): + """ + Main execution loop. Blocks and waits for a signal from the queue. + Converts explicit strategy signals into execution orders. + """ + logging.info("Position Manager started. Waiting for signals...") + while True: + try: + trade_signal = self.trade_signal_queue.get() + if not trade_signal: + continue + + logging.info(f"Received signal: {trade_signal}") + + name = trade_signal['strategy_name'] + config = trade_signal['config'] + params = config['parameters'] + coin = trade_signal['coin'].upper() + + # --- NEW: The signal is now the explicit action --- + desired_signal = trade_signal['signal'] + + status = trade_signal + + signal_price = status.get('signal_price') + if isinstance(signal_price, np.float64): + signal_price = float(signal_price) + + if not signal_price or signal_price <= 0: + logging.warning(f"[{name}] Signal received with invalid or missing price ({signal_price}). Skipping.") + continue + + # --- This logic is still needed for copy_trader's nested config --- + # --- But ONLY for finding leverage, not size --- + if 'coins_to_copy' in params: + logging.info(f"[{name}] Detected 'coins_to_copy'. Entering copy_trader logic...") + matching_coin_key = None + for key in params['coins_to_copy'].keys(): + if key.upper() == coin: + matching_coin_key = key + break + + if matching_coin_key: + coin_specific_config = params['coins_to_copy'][matching_coin_key] + else: + coin_specific_config = {} + + # --- REMOVED: size = coin_specific_config.get('size') --- + + params['leverage_long'] = coin_specific_config.get('leverage_long', 2) + params['leverage_short'] = coin_specific_config.get('leverage_short', 2) + + # --- FIX: Read the size from the ROOT of the trade signal --- + size = trade_signal.get('size') + if not size or size <= 0: + logging.error(f"[{name}] Signal received with no 'size' or invalid size ({size}). Skipping trade.") + continue + # --- END FIX --- + + leverage_long = int(params.get('leverage_long', 2)) + leverage_short = int(params.get('leverage_short', 2)) + + agent_name = (config.get("agent") or "default").lower() + + logging.info(f"[{name}] Agent set to: {agent_name}") + + # --- REMOVED: current_position check --- + + # --- Use pure signal_price directly for the limit_px --- + limit_px = signal_price + logging.info(f"[{name}] Using pure signal price for limit_px: {limit_px}") + + # --- NEW: Stateless Signal-to-Order Conversion --- + + if desired_signal == "OPEN_LONG": + logging.warning(f"[{name}] ACTION: Opening LONG for {coin}.") + # --- REMOVED: Leverage update signal --- + self.send_order(agent_name, "market_open", coin, True, size, limit_px=limit_px) + log_trade(strategy=name, coin=coin, action="OPEN_LONG", price=signal_price, size=size, signal=desired_signal) + + elif desired_signal == "OPEN_SHORT": + logging.warning(f"[{name}] ACTION: Opening SHORT for {coin}.") + # --- REMOVED: Leverage update signal --- + self.send_order(agent_name, "market_open", coin, False, size, limit_px=limit_px) + log_trade(strategy=name, coin=coin, action="OPEN_SHORT", price=signal_price, size=size, signal=desired_signal) + + elif desired_signal == "CLOSE_LONG": + logging.warning(f"[{name}] ACTION: Closing LONG position for {coin}.") + # A "market_close" for a LONG is a SELL order + self.send_order(agent_name, "market_close", coin, False, size, limit_px=limit_px) + log_trade(strategy=name, coin=coin, action="CLOSE_LONG", price=signal_price, size=size, signal=desired_signal) + + elif desired_signal == "CLOSE_SHORT": + logging.warning(f"[{name}] ACTION: Closing SHORT position for {coin}.") + # A "market_close" for a SHORT is a BUY order + self.send_order(agent_name, "market_close", coin, True, size, limit_px=limit_px) + log_trade(strategy=name, coin=coin, action="CLOSE_SHORT", price=signal_price, size=size, signal=desired_signal) + + # --- NEW: Handle leverage update signals --- + elif desired_signal == "UPDATE_LEVERAGE_LONG": + logging.warning(f"[{name}] ACTION: Updating LONG leverage for {coin} to {size}x") + # 'size' field holds the leverage value for this signal + self.send_order(agent_name, "update_leverage", coin, True, size) + + elif desired_signal == "UPDATE_LEVERAGE_SHORT": + logging.warning(f"[{name}] ACTION: Updating SHORT leverage for {coin} to {size}x") + # 'size' field holds the leverage value for this signal + self.send_order(agent_name, "update_leverage", coin, False, size) + + else: + logging.warning(f"[{name}] Received unknown signal '{desired_signal}'. No action taken.") + + # --- REMOVED: _save_managed_positions() --- + + except Exception as e: + logging.error(f"An error occurred in the position manager loop: {e}", exc_info=True) + time.sleep(1) + +# This script is no longer run directly, but is called by main_app.py + diff --git a/position_monitor.py b/position_monitor.py new file mode 100644 index 0000000..e20ec5d --- /dev/null +++ b/position_monitor.py @@ -0,0 +1,159 @@ +import os +import sys +import time +import json +import argparse +from datetime import datetime, timezone +from hyperliquid.info import Info +from hyperliquid.utils import constants +from dotenv import load_dotenv +import logging + +from logging_utils import setup_logging + +# Load .env file +load_dotenv() + +class PositionMonitor: + """ + A standalone, read-only dashboard for monitoring all open perpetuals + positions, spot balances, and their associated strategies. + """ + + def __init__(self, log_level: str): + setup_logging(log_level, 'PositionMonitor') + + self.wallet_address = os.environ.get("MAIN_WALLET_ADDRESS") + if not self.wallet_address: + logging.error("MAIN_WALLET_ADDRESS not set in .env file. Cannot proceed.") + sys.exit(1) + + self.info = Info(constants.MAINNET_API_URL, skip_ws=True) + self.managed_positions_path = os.path.join("_data", "executor_managed_positions.json") + self._lines_printed = 0 + + logging.info(f"Monitoring vault address: {self.wallet_address}") + + def load_managed_positions(self) -> dict: + """Loads the state of which strategy manages which position.""" + if os.path.exists(self.managed_positions_path): + try: + with open(self.managed_positions_path, 'r') as f: + # Create a reverse map: {coin: strategy_name} + data = json.load(f) + return {v['coin']: k for k, v in data.items()} + except (IOError, json.JSONDecodeError): + logging.warning("Could not read managed positions file.") + return {} + + def run(self): + """Main loop to continuously refresh the dashboard.""" + try: + while True: + self.display_dashboard() + time.sleep(5) # Refresh every 5 seconds + except KeyboardInterrupt: + logging.info("Position monitor stopped.") + + def display_dashboard(self): + """Fetches all data and draws the dashboard without blinking.""" + if self._lines_printed > 0: + print(f"\x1b[{self._lines_printed}A", end="") + + output_lines = [] + try: + perp_state = self.info.user_state(self.wallet_address) + spot_state = self.info.spot_user_state(self.wallet_address) + coin_to_strategy_map = self.load_managed_positions() + + output_lines.append(f"--- Live Position Monitor for {self.wallet_address[:6]}...{self.wallet_address[-4:]} ---") + + # --- 1. Perpetuals Account Summary --- + margin_summary = perp_state.get('marginSummary', {}) + account_value = float(margin_summary.get('accountValue', 0)) + margin_used = float(margin_summary.get('totalMarginUsed', 0)) + utilization = (margin_used / account_value) * 100 if account_value > 0 else 0 + + output_lines.append("\n--- Perpetuals Account Summary ---") + output_lines.append(f" Account Value: ${account_value:,.2f} | Margin Used: ${margin_used:,.2f} | Utilization: {utilization:.2f}%") + + # --- 2. Spot Balances Summary --- + output_lines.append("\n--- Spot Balances ---") + spot_balances = spot_state.get('balances', []) + if not spot_balances: + output_lines.append(" No spot balances found.") + else: + balances_str = ", ".join([f"{b.get('coin')}: {float(b.get('total', 0)):,.4f}" for b in spot_balances if float(b.get('total', 0)) > 0]) + output_lines.append(f" {balances_str}") + + # --- 3. Open Positions Table --- + output_lines.append("\n--- Open Perpetual Positions ---") + positions = perp_state.get('assetPositions', []) + open_positions = [p for p in positions if p.get('position') and float(p['position'].get('szi', 0)) != 0] + + if not open_positions: + output_lines.append(" No open perpetual positions found.") + output_lines.append("") # Add a line for stable refresh + else: + self.build_positions_table(open_positions, coin_to_strategy_map, output_lines) + + except Exception as e: + output_lines = [f"An error occurred: {e}"] + + final_output = "\n".join(output_lines) + "\n\x1b[J" # \x1b[J clears to end of screen + print(final_output, end="") + + self._lines_printed = len(output_lines) + sys.stdout.flush() + + def build_positions_table(self, positions: list, coin_to_strategy_map: dict, output_lines: list): + """Builds the text for the positions summary table.""" + header = f"| {'Strategy':<25} | {'Coin':<6} | {'Side':<5} | {'Size':>15} | {'Entry Price':>12} | {'Mark Price':>12} | {'PNL':>15} | {'Leverage':>10} |" + output_lines.append(header) + output_lines.append("-" * len(header)) + + for position in positions: + pos = position.get('position', {}) + coin = pos.get('coin', 'Unknown') + size = float(pos.get('szi', 0)) + entry_px = float(pos.get('entryPx', 0)) + mark_px = float(pos.get('markPx', 0)) + unrealized_pnl = float(pos.get('unrealizedPnl', 0)) + + # Get leverage + position_value = float(pos.get('positionValue', 0)) + margin_used = float(pos.get('marginUsed', 0)) + leverage = (position_value / margin_used) if margin_used > 0 else 0 + + side_text = "LONG" if size > 0 else "SHORT" + pnl_sign = "+" if unrealized_pnl >= 0 else "" + + # Find the strategy that owns this coin + strategy_name = coin_to_strategy_map.get(coin, "Unmanaged") + + # Format all values as strings + strategy_str = f"{strategy_name:<25}" + coin_str = f"{coin:<6}" + side_str = f"{side_text:<5}" + size_str = f"{size:>15.4f}" + entry_str = f"${entry_px:>11,.2f}" + mark_str = f"${mark_px:>11,.2f}" + pnl_str = f"{pnl_sign}${unrealized_pnl:>14,.2f}" + lev_str = f"{leverage:>9.1f}x" + + output_lines.append(f"| {strategy_str} | {coin_str} | {side_str} | {size_str} | {entry_str} | {mark_str} | {pnl_str} | {lev_str} |") + + output_lines.append("-" * len(header)) + +if __name__ == "__main__": + parser = argparse.ArgumentParser(description="Monitor a Hyperliquid wallet's positions in real-time.") + parser.add_argument( + "--log-level", + default="normal", + choices=['off', 'normal', 'debug'], + help="Set the logging level for the script." + ) + args = parser.parse_args() + + monitor = PositionMonitor(log_level=args.log_level) + monitor.run() diff --git a/resampler.py b/resampler.py index 09fec2d..ffbeb59 100644 --- a/resampler.py +++ b/resampler.py @@ -5,7 +5,7 @@ import sys import sqlite3 import pandas as pd import json -from datetime import datetime, timezone +from datetime import datetime, timezone, timedelta # Assuming logging_utils.py is in the same directory from logging_utils import setup_logging @@ -13,7 +13,8 @@ from logging_utils import setup_logging class Resampler: """ Reads new 1-minute candle data from the SQLite database, resamples it to - various timeframes, and appends the new candles to the corresponding tables. + various timeframes, and upserts the new candles to the corresponding tables, + preventing data duplication. """ def __init__(self, log_level: str, coins: list, timeframes: dict): @@ -32,6 +33,62 @@ class Resampler: } self.resampling_status = self._load_existing_status() self.job_start_time = None + self._ensure_tables_exist() + + def _ensure_tables_exist(self): + """ + Ensures all resampled tables exist with a PRIMARY KEY on timestamp_ms. + Attempts to migrate existing tables if the schema is incorrect. + """ + with sqlite3.connect(self.db_path) as conn: + for coin in self.coins_to_process: + for tf_name in self.timeframes.keys(): + table_name = f"{coin}_{tf_name}" + cursor = conn.cursor() + cursor.execute(f"PRAGMA table_info('{table_name}')") + columns = cursor.fetchall() + if columns: + # --- FIX: Check for the correct PRIMARY KEY on timestamp_ms --- + pk_found = any(col[1] == 'timestamp_ms' and col[5] == 1 for col in columns) + if not pk_found: + logging.warning(f"Schema migration needed for table '{table_name}'.") + try: + conn.execute(f'ALTER TABLE "{table_name}" RENAME TO "{table_name}_old"') + self._create_resampled_table(conn, table_name) + # Copy data, ensuring to create the timestamp_ms + logging.info(f" -> Migrating data for '{table_name}'...") + old_df = pd.read_sql(f'SELECT * FROM "{table_name}_old"', conn, parse_dates=['datetime_utc']) + if not old_df.empty: + old_df['timestamp_ms'] = (old_df['datetime_utc'].astype('int64') // 10**6) + # Keep only unique timestamps, preserving the last entry + old_df.drop_duplicates(subset=['timestamp_ms'], keep='last', inplace=True) + old_df.to_sql(table_name, conn, if_exists='append', index=False) + logging.info(f" -> Data migration complete.") + conn.execute(f'DROP TABLE "{table_name}_old"') + conn.commit() + logging.info(f"Successfully migrated schema for '{table_name}'.") + except Exception as e: + logging.error(f"FATAL: Migration for '{table_name}' failed: {e}. Please delete 'market_data.db' and restart.") + sys.exit(1) + else: + self._create_resampled_table(conn, table_name) + logging.info("All resampled table schemas verified.") + + def _create_resampled_table(self, conn, table_name): + """Creates a new resampled table with the correct schema.""" + # --- FIX: Set PRIMARY KEY on timestamp_ms for performance and uniqueness --- + conn.execute(f''' + CREATE TABLE "{table_name}" ( + datetime_utc TEXT, + timestamp_ms INTEGER PRIMARY KEY, + open REAL, + high REAL, + low REAL, + close REAL, + volume REAL, + number_of_trades INTEGER + ) + ''') def _load_existing_status(self) -> dict: """Loads the existing status file if it exists, otherwise returns an empty dict.""" @@ -51,6 +108,14 @@ class Resampler: self.job_start_time = datetime.now(timezone.utc) logging.info(f"--- Resampling job started at {self.job_start_time.strftime('%Y-%m-%d %H:%M:%S %Z')} ---") + if '1m' in self.timeframes: + logging.debug("Ignoring '1m' timeframe as it is the source resolution.") + del self.timeframes['1m'] + + if not self.timeframes: + logging.warning("No timeframes to process after filtering. Exiting job.") + return + if not os.path.exists(self.db_path): logging.error(f"Database file '{self.db_path}' not found.") return @@ -61,37 +126,58 @@ class Resampler: logging.debug(f"Processing {len(self.coins_to_process)} coins...") for coin in self.coins_to_process: - source_table_name = f"{coin}_1m" logging.debug(f"--- Processing {coin} ---") try: - # Load the full 1m history once per coin - df_1m = pd.read_sql(f'SELECT * FROM "{source_table_name}"', conn, parse_dates=['datetime_utc']) - if df_1m.empty: - logging.warning(f"Source table '{source_table_name}' is empty. Skipping.") - continue - df_1m.set_index('datetime_utc', inplace=True) - for tf_name, tf_code in self.timeframes.items(): target_table_name = f"{coin}_{tf_name}" + source_table_name = f"{coin}_1m" logging.debug(f" Updating {tf_name} table...") - last_timestamp = self._get_last_timestamp(conn, target_table_name) + last_timestamp_ms = self._get_last_timestamp(conn, target_table_name) - # Get the new 1-minute data that needs to be processed - new_df_1m = df_1m[df_1m.index > last_timestamp] if last_timestamp else df_1m + query = f'SELECT * FROM "{source_table_name}"' + params = () + if last_timestamp_ms: + query += ' WHERE timestamp_ms >= ?' + # Go back one interval to rebuild the last (potentially partial) candle + try: + interval_delta_ms = pd.to_timedelta(tf_code).total_seconds() * 1000 + except ValueError: + # Fall back to a safe 32-day lookback for special timeframes + interval_delta_ms = timedelta(days=32).total_seconds() * 1000 + + query_start_ms = last_timestamp_ms - interval_delta_ms + params = (query_start_ms,) - if new_df_1m.empty: + df_1m = pd.read_sql(query, conn, params=params, parse_dates=['datetime_utc']) + + if df_1m.empty: logging.debug(f" -> No new 1-minute data for {tf_name}. Table is up to date.") continue - resampled_df = new_df_1m.resample(tf_code).agg(self.aggregation_logic) + df_1m.set_index('datetime_utc', inplace=True) + resampled_df = df_1m.resample(tf_code).agg(self.aggregation_logic) resampled_df.dropna(how='all', inplace=True) if not resampled_df.empty: - # Append the newly resampled data to the target table - resampled_df.to_sql(target_table_name, conn, if_exists='append', index=True) - logging.debug(f" -> Appended {len(resampled_df)} new candles to '{target_table_name}'.") + records_to_upsert = [] + for index, row in resampled_df.iterrows(): + records_to_upsert.append(( + index.strftime('%Y-%m-%d %H:%M:%S'), + int(index.timestamp() * 1000), # Generate timestamp_ms + row['open'], row['high'], row['low'], row['close'], + row['volume'], row['number_of_trades'] + )) + + cursor = conn.cursor() + cursor.executemany(f''' + INSERT OR REPLACE INTO "{target_table_name}" (datetime_utc, timestamp_ms, open, high, low, close, volume, number_of_trades) + VALUES (?, ?, ?, ?, ?, ?, ?, ?) + ''', records_to_upsert) + conn.commit() + + logging.debug(f" -> Upserted {len(resampled_df)} candles into '{target_table_name}'.") if coin not in self.resampling_status: self.resampling_status[coin] = {} total_candles = int(self._get_table_count(conn, target_table_name)) @@ -111,7 +197,6 @@ class Resampler: """Logs a summary of the total candles for each timeframe.""" logging.info("--- Resampling Job Summary ---") timeframe_totals = {} - # Iterate through coins, skipping metadata keys for coin, tfs in self.resampling_status.items(): if not isinstance(tfs, dict): continue for tf_name, tf_data in tfs.items(): @@ -129,9 +214,11 @@ class Resampler: logging.info(f" - {tf_name:<10}: {total:,} candles") def _get_last_timestamp(self, conn, table_name): - """Gets the timestamp of the last entry in a table.""" + """Gets the millisecond timestamp of the last entry in a table.""" try: - return pd.read_sql(f'SELECT MAX(datetime_utc) FROM "{table_name}"', conn).iloc[0, 0] + # --- FIX: Query for the integer timestamp_ms, not the text datetime_utc --- + timestamp_ms = pd.read_sql(f'SELECT MAX(timestamp_ms) FROM "{table_name}"', conn).iloc[0, 0] + return int(timestamp_ms) if pd.notna(timestamp_ms) else None except (pd.io.sql.DatabaseError, IndexError): return None @@ -151,7 +238,6 @@ class Resampler: self.resampling_status['job_start_time_utc'] = self.job_start_time.strftime('%Y-%m-%d %H:%M:%S') self.resampling_status['job_stop_time_utc'] = stop_time.strftime('%Y-%m-%d %H:%M:%S') - # Clean up old key if it exists from previous versions self.resampling_status.pop('last_completed_utc', None) try: @@ -167,14 +253,24 @@ def parse_timeframes(tf_strings: list) -> dict: tf_map = {} for tf_str in tf_strings: numeric_part = ''.join(filter(str.isdigit, tf_str)) - unit = ''.join(filter(str.isalpha, tf_str)).lower() + unit = ''.join(filter(str.isalpha, tf_str)) # Keep case for 'M' + key = tf_str code = '' - if unit == 'm': code = f"{numeric_part}min" - elif unit == 'w': code = f"{numeric_part}W" - elif unit in ['h', 'd']: code = f"{numeric_part}{unit}" - else: code = tf_str - tf_map[tf_str] = code + if unit == 'm': + code = f"{numeric_part}min" + elif unit.lower() == 'w': + code = f"{numeric_part}W-MON" + elif unit == 'M': + code = f"{numeric_part}MS" + key = f"{numeric_part}month" + elif unit.lower() in ['h', 'd']: + code = f"{numeric_part}{unit.lower()}" + else: + code = tf_str + logging.warning(f"Unrecognized timeframe unit in '{tf_str}'. Using as-is.") + + tf_map[key] = code return tf_map diff --git a/review.md b/review.md new file mode 100644 index 0000000..d0fe34c --- /dev/null +++ b/review.md @@ -0,0 +1,79 @@ +# Project Review and Recommendations + +This review provides an analysis of the current state of the automated trading bot project, proposes specific code improvements, and identifies files that appear to be unused or are one-off utilities that could be reorganized. + +The project is a well-structured, multi-process Python application for crypto trading. It has a clear separation of concerns between data fetching, strategy execution, and trade management. The use of `multiprocessing` and a centralized `main_app.py` orchestrator is a solid architectural choice. + +The following sections detail recommendations for improving configuration management, code structure, and robustness, along with a list of files recommended for cleanup. + +--- + +## Proposed Code Changes + +### 1. Centralize Configuration + +- **Issue:** Key configuration variables like `WATCHED_COINS` and `required_timeframes` are hardcoded in `main_app.py`. This makes them difficult to change without modifying the source code. +- **Proposal:** + - Create a central configuration file, e.g., `_data/config.json`. + - Move `WATCHED_COINS` and `required_timeframes` into this new file. + - Load this configuration in `main_app.py` at startup. +- **Benefit:** Decouples configuration from code, making the application more flexible and easier to manage. + +### 2. Refactor `main_app.py` for Clarity + +- **Issue:** `main_app.py` is long and handles multiple responsibilities: process orchestration, dashboard rendering, and data reading. +- **Proposal:** + - **Abstract Process Management:** The functions for running subprocesses (e.g., `run_live_candle_fetcher`, `run_resampler_job`) contain repetitive logic for logging, shutdown handling, and process looping. This could be abstracted into a generic `ProcessRunner` class. + - **Create a Dashboard Class:** The complex dashboard rendering logic could be moved into a separate `Dashboard` class to improve separation of concerns and make the main application loop cleaner. +- **Benefit:** Improves code readability, reduces duplication, and makes the application easier to maintain and extend. + +### 3. Improve Project Structure + +- **Issue:** The root directory is cluttered with numerous Python scripts, making it difficult to distinguish between core application files, utility scripts, and old/example files. +- **Proposal:** + - Create a `scripts/` directory and move all one-off utility and maintenance scripts into it. + - Consider creating a `src/` or `app/` directory to house the core application source code (`main_app.py`, `trade_executor.py`, etc.), separating it clearly from configuration, data, and documentation. +- **Benefit:** A cleaner, more organized project structure that is easier for new developers to understand. + +### 4. Enhance Robustness and Error Handling + +- **Issue:** The agent loading in `trade_executor.py` relies on discovering environment variables by a naming convention (`_AGENT_PK`). This is clever but can be brittle if environment variables are named incorrectly. +- **Proposal:** + - Explicitly define the agent names and their corresponding environment variable keys in the proposed `_data/config.json` file. The `trade_executor` would then load only the agents specified in the configuration. +- **Benefit:** Makes agent configuration more explicit and less prone to errors from stray environment variables. + +--- + +## Identified Unused/Utility Files + +The following files were identified as likely being unused by the core application, being obsolete, or serving as one-off utilities. It is recommended to **move them to a `scripts/` directory** or **delete them** if they are obsolete. + +### Obsolete / Old Versions: +- `data_fetcher_old.py` +- `market_old.py` +- `base_strategy.py` (The one in the root directory; the one in `strategies/` is used). + +### One-Off Utility Scripts (Recommend moving to `scripts/`): +- `!migrate_to_sqlite.py` +- `import_csv.py` +- `del_market_cap_tables.py` +- `fix_timestamps.py` +- `list_coins.py` +- `create_agent.py` + +### Examples / Unused Code: +- `basic_ws.py` (Appears to be an example file). +- `backtester.py` +- `strategy_sma_cross.py` (A strategy file in the root, not in the `strategies` folder). +- `strategy_template.py` + +### Standalone / Potentially Unused Core Files: +The following files seem to have their logic already integrated into the main multi-process application. They might be remnants of a previous architecture and may not be needed as standalone scripts. +- `address_monitor.py` +- `position_monitor.py` +- `trade_log.py` +- `wallet_data.py` +- `whale_tracker.py` + +### Data / Log Files (Recommend archiving or deleting): +- `hyperliquid_wallet_data_*.json` (These appear to be backups or logs). diff --git a/strategies/base_strategy.py b/strategies/base_strategy.py index e40452c..afe3ff6 100644 --- a/strategies/base_strategy.py +++ b/strategies/base_strategy.py @@ -5,36 +5,42 @@ import os import logging from datetime import datetime, timezone import sqlite3 +import multiprocessing +import time + +from logging_utils import setup_logging +from hyperliquid.info import Info +from hyperliquid.utils import constants class BaseStrategy(ABC): """ An abstract base class that defines the blueprint for all trading strategies. - It provides common functionality like loading data and saving status. + It provides common functionality like loading data, saving status, and state management. """ - def __init__(self, strategy_name: str, params: dict, log_level: str): + def __init__(self, strategy_name: str, params: dict, trade_signal_queue: multiprocessing.Queue = None, shared_status: dict = None): self.strategy_name = strategy_name self.params = params + self.trade_signal_queue = trade_signal_queue + # Optional multiprocessing.Manager().dict() to hold live status (avoids file IO) + self.shared_status = shared_status + self.coin = params.get("coin", "N/A") self.timeframe = params.get("timeframe", "N/A") self.db_path = os.path.join("_data", "market_data.db") self.status_file_path = os.path.join("_data", f"strategy_status_{self.strategy_name}.json") - - # --- ADDED: State variables required for status reporting --- + self.current_signal = "INIT" self.last_signal_change_utc = None self.signal_price = None - # This will be set up by the child class after it's initialized - # setup_logging(log_level, f"Strategy-{self.strategy_name}") - # logging.info(f"Initializing with parameters: {self.params}") + # Note: Logging is set up by the run_strategy function def load_data(self) -> pd.DataFrame: """Loads historical data for the configured coin and timeframe.""" table_name = f"{self.coin}_{self.timeframe}" - # Dynamically determine the number of candles needed based on all possible period parameters - periods = [v for k, v in self.params.items() if 'period' in k or '_ma' in k or 'slow' in k] + periods = [v for k, v in self.params.items() if 'period' in k or '_ma' in k or 'slow' in k or 'fast' in k] limit = max(periods) + 50 if periods else 500 try: @@ -51,10 +57,44 @@ class BaseStrategy(ABC): @abstractmethod def calculate_signals(self, df: pd.DataFrame) -> pd.DataFrame: - """ - The core logic of the strategy. Must be implemented by child classes. - """ + """The core logic of the strategy. Must be implemented by child classes.""" pass + + def calculate_signals_and_state(self, df: pd.DataFrame) -> bool: + """ + A wrapper that calls the strategy's signal calculation, determines + the last signal change, and returns True if the signal has changed. + """ + df_with_signals = self.calculate_signals(df) + df_with_signals.dropna(inplace=True) + if df_with_signals.empty: + return False + + df_with_signals['position_change'] = df_with_signals['signal'].diff() + + last_signal_int = df_with_signals['signal'].iloc[-1] + new_signal_str = "HOLD" + if last_signal_int == 1: new_signal_str = "BUY" + elif last_signal_int == -1: new_signal_str = "SELL" + + signal_changed = False + if self.current_signal == "INIT": + if new_signal_str == "BUY": self.current_signal = "INIT_BUY" + elif new_signal_str == "SELL": self.current_signal = "INIT_SELL" + else: self.current_signal = "HOLD" + signal_changed = True + elif new_signal_str != self.current_signal: + self.current_signal = new_signal_str + signal_changed = True + + if signal_changed: + last_change_series = df_with_signals[df_with_signals['position_change'] != 0] + if not last_change_series.empty: + last_change_row = last_change_series.iloc[-1] + self.last_signal_change_utc = last_change_row.name.tz_localize('UTC').isoformat() + self.signal_price = last_change_row['close'] + + return signal_changed def _save_status(self): """Saves the current strategy state to its JSON file.""" @@ -65,9 +105,62 @@ class BaseStrategy(ABC): "signal_price": self.signal_price, "last_checked_utc": datetime.now(timezone.utc).isoformat() } + # If a shared status dict is provided (Manager.dict()), update it instead of writing files try: - with open(self.status_file_path, 'w', encoding='utf-8') as f: - json.dump(status, f, indent=4) + if self.shared_status is not None: + try: + # store the status under the strategy name for easy lookup + self.shared_status[self.strategy_name] = status + except Exception: + # Manager proxies may not accept nested mutable objects consistently; assign a copy + self.shared_status[self.strategy_name] = dict(status) + else: + with open(self.status_file_path, 'w', encoding='utf-8') as f: + json.dump(status, f, indent=4) except IOError as e: logging.error(f"Failed to write status file for {self.strategy_name}: {e}") + def run_polling_loop(self): + """ + The default execution loop for polling-based strategies (e.g., SMAs). + """ + while True: + df = self.load_data() + if df.empty: + logging.warning("No data loaded. Waiting 1 minute...") + time.sleep(60) + continue + + signal_changed = self.calculate_signals_and_state(df.copy()) + self._save_status() + + if signal_changed or self.current_signal == "INIT_BUY" or self.current_signal == "INIT_SELL": + logging.warning(f"New signal detected: {self.current_signal}") + self.trade_signal_queue.put({ + "strategy_name": self.strategy_name, + "signal": self.current_signal, + "coin": self.coin, + "signal_price": self.signal_price, + "config": {"agent": self.params.get("agent"), "parameters": self.params} + }) + if self.current_signal == "INIT_BUY": self.current_signal = "BUY" + if self.current_signal == "INIT_SELL": self.current_signal = "SELL" + + logging.info(f"Current Signal: {self.current_signal}") + time.sleep(60) + + def run_event_loop(self): + """ + A placeholder for event-driven (WebSocket) strategies. + Child classes must override this. + """ + logging.error("run_event_loop() is not implemented for this strategy.") + time.sleep(3600) # Sleep for an hour to prevent rapid error loops + + def on_fill_message(self, message): + """ + Placeholder for the WebSocket callback. + Child classes must override this. + """ + pass + diff --git a/strategies/copy_trader_strategy.py b/strategies/copy_trader_strategy.py new file mode 100644 index 0000000..95443bb --- /dev/null +++ b/strategies/copy_trader_strategy.py @@ -0,0 +1,353 @@ +import logging +import time +import json +import os +from datetime import datetime, timezone +from hyperliquid.info import Info +from hyperliquid.utils import constants + +from strategies.base_strategy import BaseStrategy + +class CopyTraderStrategy(BaseStrategy): + """ + An event-driven strategy that monitors a target wallet address and + copies its trades for a specific set of allowed coins. + + This strategy is STATELESS. It translates a target's fill direction + (e.g., "Open Long") directly into an explicit signal + (e.g., "OPEN_LONG") for the PositionManager. + """ + def __init__(self, strategy_name: str, params: dict, trade_signal_queue, shared_status: dict = None): + # --- MODIFIED: Pass the correct queue to the parent --- + # The event-driven copy trader should send orders to the order_execution_queue + # We will assume the queue passed in is the correct one (as setup in main_app.py) + super().__init__(strategy_name, params, trade_signal_queue, shared_status) + + self.target_address = self.params.get("target_address", "").lower() + self.coins_to_copy = self.params.get("coins_to_copy", {}) + # Convert all coin keys to uppercase for consistency + self.coins_to_copy = {k.upper(): v for k, v in self.coins_to_copy.items()} + self.allowed_coins = list(self.coins_to_copy.keys()) + + if not self.target_address: + logging.error("No 'target_address' specified in parameters for copy trader.") + raise ValueError("target_address is required") + if not self.allowed_coins: + logging.warning("No 'coins_to_copy' configured. This strategy will not copy any trades.") + + self.info = None # Will be initialized in the run loop + + # --- REMOVED: All local state management --- + # self.position_state_file = ... + # self.current_positions = ... + + # --- MODIFIED: Check if shared_status is None before using it --- + if self.shared_status is None: + logging.warning("No shared_status dictionary provided. Initializing a new one.") + self.shared_status = {} + + self.current_signal = self.shared_status.get("current_signal", "WAIT") + self.signal_price = self.shared_status.get("signal_price") + self.last_signal_change_utc = self.shared_status.get("last_signal_change_utc") + + self.start_time_utc = datetime.now(timezone.utc) + logging.info(f"Strategy initialized. Ignoring all trades before {self.start_time_utc.isoformat()}") + + # --- REMOVED: _load_position_state --- + # --- REMOVED: _save_position_state --- + + def calculate_signals(self, df): + # This strategy is event-driven, so it does not use polling-based signal calculation. + pass + + def send_explicit_signal(self, signal: str, coin: str, price: float, trade_params: dict, size: float): + """Helper to send a formatted signal to the PositionManager.""" + config = { + # --- MODIFIED: Ensure agent is read from params --- + "agent": self.params.get("agent"), + "parameters": trade_params + } + + # --- MODIFIED: Use self.trade_signal_queue (which is the queue passed in) --- + self.trade_signal_queue.put({ + "strategy_name": self.strategy_name, + "signal": signal, # e.g., "OPEN_LONG", "CLOSE_SHORT" + "coin": coin, + "signal_price": price, + "config": config, + "size": size # Explicitly pass size (or leverage for leverage updates) + }) + logging.info(f"Explicit signal SENT: {signal} {coin} @ {price}, Size: {size}") + + def on_fill_message(self, message): + """ + This is the callback function that gets triggered by the WebSocket + every time the monitored address has an event. + """ + try: + # --- NEW: Add logging to see ALL messages --- + logging.debug(f"Received WebSocket message: {message}") + + channel = message.get("channel") + if channel not in ("user", "userFills", "userEvents"): + # --- NEW: Added debug logging --- + logging.debug(f"Ignoring message from unhandled channel: {channel}") + return + + data = message.get("data") + if not data: + # --- NEW: Added debug logging --- + logging.debug("Message received with no 'data' field. Ignoring.") + return + + # --- NEW: Check for user address FIRST --- + user_address = data.get("user", "").lower() + if not user_address: + logging.debug("Received message with 'data' but no 'user'. Ignoring.") + return + + # --- MODIFIED: Check for 'fills' vs. other event types --- + # This check is still valid for userFills + if "fills" not in data or not data.get("fills"): + # This is a userEvent, but not a fill (e.g., order placement, cancel, withdrawal) + event_type = data.get("type") # e.g., 'order', 'cancel', 'withdrawal' + if event_type: + logging.debug(f"Received non-fill user event: '{event_type}'. Ignoring.") + else: + logging.debug(f"Received 'data' message with no 'fills'. Ignoring.") + return + + # --- This line is now safe to run --- + if user_address != self.target_address: + # This shouldn't happen if the subscription is correct, but good to check + logging.warning(f"Received fill for wrong user: {user_address}") + return + + fills = data.get("fills") + logging.debug(f"Received {len(fills)} fill(s) for user {user_address}") + + for fill in fills: + # Check if the trade is new or historical + trade_time = datetime.fromtimestamp(fill['time'] / 1000, tz=timezone.utc) + if trade_time < self.start_time_utc: + logging.info(f"Ignoring stale/historical trade from {trade_time.isoformat()}") + continue + + coin = fill.get('coin').upper() + + if coin in self.allowed_coins: + price = float(fill.get('px')) + + # --- MODIFIED: Use the target's fill size --- + fill_size = float(fill.get('sz')) # Target's size + + if fill_size == 0: + logging.warning(f"Ignoring fill with size 0.") + continue + + # --- NEW: Get the fill direction --- + # "dir": "Open Long", "Close Long", "Open Short", "Close Short" + fill_direction = fill.get("dir") + + # --- NEW: Get startPosition to calculate flip sizes --- + start_pos_size = float(fill.get('startPosition', 0.0)) + + if not fill_direction: + logging.warning(f"Fill message missing 'dir'. Ignoring fill: {fill}") + continue + + # Get our strategy's configured leverage for this coin + coin_config = self.coins_to_copy.get(coin) + + # --- REMOVED: Check for coin_config.get("size") --- + # --- REMOVED: strategy_trade_size = coin_config.get("size") --- + + # Prepare config for the signal + trade_params = self.params.copy() + if coin_config: + trade_params.update(coin_config) + + # --- REMOVED: All stateful logic (current_local_pos, etc.) --- + + # --- MODIFIED: Expanded logic to handle flip directions --- + signal_sent = False + dashboard_signal = "" + + if fill_direction == "Open Long": + logging.warning(f"[{coin}] Target action: {fill_direction}. Sending signal: OPEN_LONG") + self.send_explicit_signal("OPEN_LONG", coin, price, trade_params, fill_size) + signal_sent = True + dashboard_signal = "OPEN_LONG" + + elif fill_direction == "Close Long": + logging.warning(f"[{coin}] Target action: {fill_direction}. Sending signal: CLOSE_LONG") + self.send_explicit_signal("CLOSE_LONG", coin, price, trade_params, fill_size) + signal_sent = True + dashboard_signal = "CLOSE_LONG" + + elif fill_direction == "Open Short": + logging.warning(f"[{coin}] Target action: {fill_direction}. Sending signal: OPEN_SHORT") + self.send_explicit_signal("OPEN_SHORT", coin, price, trade_params, fill_size) + signal_sent = True + dashboard_signal = "OPEN_SHORT" + + elif fill_direction == "Close Short": + logging.warning(f"[{coin}] Target action: {fill_direction}. Sending signal: CLOSE_SHORT") + self.send_explicit_signal("CLOSE_SHORT", coin, price, trade_params, fill_size) + signal_sent = True + dashboard_signal = "CLOSE_SHORT" + + elif fill_direction == "Short > Long": + logging.warning(f"[{coin}] Target action: {fill_direction}. Sending CLOSE_SHORT then OPEN_LONG.") + close_size = abs(start_pos_size) + open_size = fill_size - close_size + + if close_size > 0: + self.send_explicit_signal("CLOSE_SHORT", coin, price, trade_params, close_size) + + if open_size > 0: + self.send_explicit_signal("OPEN_LONG", coin, price, trade_params, open_size) + + signal_sent = True + dashboard_signal = "FLIP_TO_LONG" + + elif fill_direction == "Long > Short": + logging.warning(f"[{coin}] Target action: {fill_direction}. Sending CLOSE_LONG then OPEN_SHORT.") + close_size = abs(start_pos_size) + open_size = fill_size - close_size + + if close_size > 0: + self.send_explicit_signal("CLOSE_LONG", coin, price, trade_params, close_size) + + if open_size > 0: + self.send_explicit_signal("OPEN_SHORT", coin, price, trade_params, open_size) + + signal_sent = True + dashboard_signal = "FLIP_TO_SHORT" + + + if signal_sent: + # Update dashboard status + self.current_signal = dashboard_signal # Show the action + self.signal_price = price + self.last_signal_change_utc = trade_time.isoformat() + self.coin = coin # Update coin for dashboard + self.size = fill_size # Update size for dashboard + self._save_status() # For dashboard + + logging.info(f"Source trade logged: {json.dumps(fill)}") + else: + logging.info(f"[{coin}] Ignoring unhandled fill direction: {fill_direction}") + else: + logging.info(f"Ignoring fill for unmonitored coin: {coin}") + + except Exception as e: + logging.error(f"Error in on_fill_message: {e}", exc_info=True) + + def _connect_and_subscribe(self): + """ + Establishes a new WebSocket connection and subscribes to the userFills channel. + """ + try: + logging.info("Connecting to Hyperliquid WebSocket...") + self.info = Info(constants.MAINNET_API_URL, skip_ws=False) + + # --- MODIFIED: Reverted to 'userFills' as requested --- + subscription = {"type": "userFills", "user": self.target_address} + self.info.subscribe(subscription, self.on_fill_message) + logging.info(f"Subscribed to 'userFills' for target address: {self.target_address}") + + return True + except Exception as e: + logging.error(f"Failed to connect or subscribe: {e}") + self.info = None + return False + + def run_event_loop(self): + """ + This method overrides the default polling loop. It establishes a + persistent WebSocket connection and runs a watchdog to ensure + it stays connected. + """ + try: + if not self._connect_and_subscribe(): + # If connection fails on start, wait 60s before letting the process restart + time.sleep(60) + return + + # --- MODIFIED: Add a small delay to ensure Info object is ready for REST calls --- + logging.info("Connection established. Waiting 2 seconds for Info client to be ready...") + time.sleep(2) + # --- END MODIFICATION --- + + # --- NEW: Set initial leverage for all monitored coins --- + logging.info("Setting initial leverage for all monitored coins...") + try: + all_mids = self.info.all_mids() + for coin_key, coin_config in self.coins_to_copy.items(): + coin = coin_key.upper() + # Use a failsafe price of 1.0 if coin not in mids (e.g., new listing) + current_price = float(all_mids.get(coin, 1.0)) + + leverage_long = coin_config.get('leverage_long', 2) + leverage_short = coin_config.get('leverage_short', 2) + + # Prepare config for the signal + trade_params = self.params.copy() + trade_params.update(coin_config) + + # Send LONG leverage update + # The 'size' param is used to pass the leverage value for this signal type + self.send_explicit_signal("UPDATE_LEVERAGE_LONG", coin, current_price, trade_params, leverage_long) + + # Send SHORT leverage update + self.send_explicit_signal("UPDATE_LEVERAGE_SHORT", coin, current_price, trade_params, leverage_short) + + logging.info(f"Sent initial leverage signals for {coin} (Long: {leverage_long}x, Short: {leverage_short}x)") + + except Exception as e: + logging.error(f"Failed to set initial leverage: {e}", exc_info=True) + # --- END NEW LEVERAGE LOGIC --- + + # Save the initial "WAIT" status + self._save_status() + + while True: + try: + time.sleep(15) # Check the connection every 15 seconds + + if self.info is None or not self.info.ws_manager.is_alive(): + logging.error(f"WebSocket connection lost. Attempting to reconnect...") + + if self.info and self.info.ws_manager: + try: + self.info.ws_manager.stop() + except Exception as e: + logging.error(f"Error stopping old ws_manager: {e}") + + if not self._connect_and_subscribe(): + logging.error("Reconnect failed, will retry in 15s.") + else: + logging.info("Successfully reconnected to WebSocket.") + self._save_status() + else: + logging.debug("Watchdog check: WebSocket connection is active.") + + except Exception as e: + logging.error(f"An error occurred in the watchdog loop: {e}", exc_info=True) + + except KeyboardInterrupt: + # --- MODIFIED: No positions to close, just exit --- + logging.warning(f"Shutdown signal received. Exiting strategy '{self.strategy_name}'.") + + except Exception as e: + logging.error(f"An unhandled error occurred in run_event_loop: {e}", exc_info=True) + + finally: + if self.info and self.info.ws_manager and self.info.ws_manager.is_alive(): + try: + self.info.ws_manager.stop() + logging.info("WebSocket connection stopped.") + except Exception as e: + logging.error(f"Error stopping ws_manager on exit: {e}") + diff --git a/strategies/ma_cross_strategy.py b/strategies/ma_cross_strategy.py index 0002375..ff756a2 100644 --- a/strategies/ma_cross_strategy.py +++ b/strategies/ma_cross_strategy.py @@ -7,27 +7,22 @@ class MaCrossStrategy(BaseStrategy): A strategy based on a fast Simple Moving Average (SMA) crossing a slow SMA. """ - def calculate_signals(self, df: pd.DataFrame) -> pd.DataFrame: - # Support multiple naming conventions: some configs use 'fast'/'slow' - # while others use 'short_ma'/'long_ma'. Normalize here so both work. - fast_ma_period = self.params.get('short_ma') or self.params.get('fast') or 0 - slow_ma_period = self.params.get('long_ma') or self.params.get('slow') or 0 - - # If parameters are missing, return a neutral signal frame. - if not fast_ma_period or not slow_ma_period: - logging.warning(f"Missing MA period parameters (fast={fast_ma_period}, slow={slow_ma_period}).") - df['signal'] = 0 - return df + # --- FIX: Changed 3rd argument from log_level to trade_signal_queue --- + def __init__(self, strategy_name: str, params: dict, trade_signal_queue): + # --- FIX: Passed trade_signal_queue to the parent class --- + super().__init__(strategy_name, params, trade_signal_queue) + self.fast_ma_period = self.params.get('short_ma') or self.params.get('fast') or 0 + self.slow_ma_period = self.params.get('long_ma') or self.params.get('slow') or 0 - if len(df) < slow_ma_period: - logging.warning(f"Not enough data for MA periods {fast_ma_period}/{slow_ma_period}. Need {slow_ma_period}, have {len(df)}.") + def calculate_signals(self, df: pd.DataFrame) -> pd.DataFrame: + if not self.fast_ma_period or not self.slow_ma_period or len(df) < self.slow_ma_period: + logging.warning(f"Not enough data for MA periods.") df['signal'] = 0 return df - df['fast_sma'] = df['close'].rolling(window=fast_ma_period).mean() - df['slow_sma'] = df['close'].rolling(window=slow_ma_period).mean() + df['fast_sma'] = df['close'].rolling(window=self.fast_ma_period).mean() + df['slow_sma'] = df['close'].rolling(window=self.slow_ma_period).mean() - # Signal is 1 for Golden Cross (fast > slow), -1 for Death Cross df['signal'] = 0 df.loc[df['fast_sma'] > df['slow_sma'], 'signal'] = 1 df.loc[df['fast_sma'] < df['slow_sma'], 'signal'] = -1 diff --git a/strategies/single_sma_strategy.py b/strategies/single_sma_strategy.py index 52a1d33..a05f95e 100644 --- a/strategies/single_sma_strategy.py +++ b/strategies/single_sma_strategy.py @@ -6,17 +6,20 @@ class SingleSmaStrategy(BaseStrategy): """ A strategy based on the price crossing a single Simple Moving Average (SMA). """ + # --- FIX: Added trade_signal_queue to the constructor --- + def __init__(self, strategy_name: str, params: dict, trade_signal_queue): + # --- FIX: Passed trade_signal_queue to the parent class --- + super().__init__(strategy_name, params, trade_signal_queue) + self.sma_period = self.params.get('sma_period', 0) + def calculate_signals(self, df: pd.DataFrame) -> pd.DataFrame: - sma_period = self.params.get('sma_period', 0) - - if not sma_period or len(df) < sma_period: - logging.warning(f"Not enough data for SMA period {sma_period}. Need {sma_period}, have {len(df)}.") + if not self.sma_period or len(df) < self.sma_period: + logging.warning(f"Not enough data for SMA period {self.sma_period}.") df['signal'] = 0 return df - df['sma'] = df['close'].rolling(window=sma_period).mean() + df['sma'] = df['close'].rolling(window=self.sma_period).mean() - # Signal is 1 when price is above SMA, -1 when below df['signal'] = 0 df.loc[df['close'] > df['sma'], 'signal'] = 1 df.loc[df['close'] < df['sma'], 'signal'] = -1 diff --git a/trade_executor.py b/trade_executor.py index 35ac261..44c6e13 100644 --- a/trade_executor.py +++ b/trade_executor.py @@ -4,7 +4,9 @@ import os import sys import json import time +# --- REVERTED: Removed math import --- from datetime import datetime +import multiprocessing from eth_account import Account from hyperliquid.exchange import Exchange @@ -13,20 +15,20 @@ from hyperliquid.utils import constants from dotenv import load_dotenv from logging_utils import setup_logging -from trade_log import log_trade -# Load environment variables from a .env file load_dotenv() class TradeExecutor: """ - Monitors strategy signals and executes trades using a multi-agent, - multi-strategy position management system. Each strategy's position is - tracked independently. + Executes orders from a queue and, upon API success, + updates the shared 'opened_positions.json' state file. + It is the single source of truth for position state. """ - def __init__(self, log_level: str): - setup_logging(log_level, 'TradeExecutor') + def __init__(self, log_level: str, order_execution_queue: multiprocessing.Queue): + # Note: Logging is set up by the run_trade_executor function + + self.order_execution_queue = order_execution_queue self.vault_address = os.environ.get("MAIN_WALLET_ADDRESS") if not self.vault_address: @@ -39,21 +41,18 @@ class TradeExecutor: logging.error("No trading agents found in .env file.") sys.exit(1) - strategy_config_path = os.path.join("_data", "strategies.json") - try: - with open(strategy_config_path, 'r') as f: - self.strategy_configs = {name: config for name, config in json.load(f).items() if config.get("enabled")} - logging.info(f"Loaded {len(self.strategy_configs)} enabled strategies.") - except (FileNotFoundError, json.JSONDecodeError) as e: - logging.error(f"Could not load strategies from '{strategy_config_path}': {e}") - sys.exit(1) - - self.status_file_path = os.path.join("_logs", "trade_executor_status.json") - self.managed_positions_path = os.path.join("_data", "executor_managed_positions.json") - self.managed_positions = self._load_managed_positions() + # --- REVERTED: Removed asset_meta loading --- + # self.asset_meta = self._load_asset_metadata() + + # --- NEW: State management logic --- + self.opened_positions_file = os.path.join("_data", "opened_positions.json") + self.opened_positions = self._load_opened_positions() + + logging.info(f"Trade Executor started. Loaded {len(self.opened_positions)} positions.") + def _load_agents(self) -> dict: - """Discovers and initializes agents from environment variables.""" + # ... (omitted for brevity, this logic is correct and unchanged) ... exchanges = {} logging.info("Discovering agents from environment variables...") for env_var, private_key in os.environ.items(): @@ -71,130 +70,124 @@ class TradeExecutor: except Exception as e: logging.error(f"Failed to initialize agent '{agent_name}': {e}") return exchanges + + # --- REVERTED: Removed asset metadata loading --- + # def _load_asset_metadata(self) -> dict: ... - def _load_managed_positions(self) -> dict: - """Loads the state of which strategy manages which position.""" - if os.path.exists(self.managed_positions_path): - try: - with open(self.managed_positions_path, 'r') as f: - logging.info("Loading existing managed positions state.") - return json.load(f) - except (IOError, json.JSONDecodeError): - logging.warning("Could not read managed positions file. Starting fresh.") - return {} - - def _save_managed_positions(self): - """Saves the current state of managed positions.""" + # --- NEW: Position state save/load methods --- + def _load_opened_positions(self) -> dict: + """Loads the state of currently managed positions from a JSON file.""" + if not os.path.exists(self.opened_positions_file): + return {} try: - with open(self.managed_positions_path, 'w') as f: - json.dump(self.managed_positions, f, indent=4) - except IOError as e: - logging.error(f"Failed to save managed positions state: {e}") + with open(self.opened_positions_file, 'r', encoding='utf-8') as f: + return json.load(f) + except (json.JSONDecodeError, IOError) as e: + logging.error(f"Failed to read '{self.opened_positions_file}': {e}. Starting with empty state.", exc_info=True) + return {} - def _save_executor_status(self, perpetuals_state, spot_state, all_market_contexts): - """Saves the current balances and open positions to a live status file.""" - # This function is correct and does not need changes. - pass + def _save_opened_positions(self): + """Saves the current state of managed positions to a JSON file.""" + try: + with open(self.opened_positions_file, 'w', encoding='utf-8') as f: + json.dump(self.opened_positions, f, indent=4) + logging.debug(f"Successfully saved {len(self.opened_positions)} positions to '{self.opened_positions_file}'") + except IOError as e: + logging.error(f"Failed to write to '{self.opened_positions_file}': {e}", exc_info=True) + + # --- REVERTED: Removed tick rounding function --- + # def _round_to_tick(self, price, tick_size): ... def run(self): - """The main execution loop with advanced position management.""" - logging.info("Starting Trade Executor loop...") + """ + Main execution loop. Waits for an order and updates state on success. + """ + logging.info("Trade Executor started. Waiting for orders...") while True: try: - perpetuals_state = self.info.user_state(self.vault_address) - open_positions_api = {pos['position'].get('coin'): pos['position'] for pos in perpetuals_state.get('assetPositions', []) if float(pos.get('position', {}).get('szi', 0)) != 0} + order = self.order_execution_queue.get() + if not order: + continue + + logging.info(f"Received order: {order}") + + agent_name = order['agent'] + action = order['action'] + coin = order['coin'] + is_buy = order['is_buy'] + size = order['size'] + limit_px = order.get('limit_px') - for name, config in self.strategy_configs.items(): - coin = config['parameters'].get('coin') - size = config['parameters'].get('size') - # --- ADDED: Load leverage parameters from config --- - leverage_long = config['parameters'].get('leverage_long') - leverage_short = config['parameters'].get('leverage_short') - - status_file = os.path.join("_data", f"strategy_status_{name}.json") - if not os.path.exists(status_file): continue - with open(status_file, 'r') as f: status = json.load(f) - - desired_signal = status.get('current_signal') - current_position = self.managed_positions.get(name) - - agent_name = config.get("agent", "default").lower() - exchange_to_use = self.exchanges.get(agent_name) - if not exchange_to_use: - logging.error(f"[{name}] Agent '{agent_name}' not found. Skipping trade.") - continue + exchange_to_use = self.exchanges.get(agent_name) + if not exchange_to_use: + logging.error(f"Agent '{agent_name}' not found. Skipping order.") + continue - # --- State Machine Logic with Configurable Leverage --- - if desired_signal == "BUY": - if not current_position: - if not all([size, leverage_long]): - logging.error(f"[{name}] 'size' or 'leverage_long' not defined. Skipping.") - continue + response = None + + if action == "market_open" or action == "market_close": + reduce_only = (action == "market_close") + log_action = "MARKET CLOSE" if reduce_only else "MARKET OPEN" + logging.warning(f"ACTION: {log_action} {coin} {'BUY' if is_buy else 'SELL'} {size}") + + # --- REVERTED: Removed all slippage and rounding logic --- + # The raw limit_px from the order is now used directly + final_price = limit_px + logging.info(f"[{agent_name}] Using raw price for {coin}: {final_price}") + + order_type = {"limit": {"tif": "Ioc"}} + # --- REVERTED: Uses final_price (which is just limit_px) --- + response = exchange_to_use.order(coin, is_buy, size, final_price, order_type, reduce_only=reduce_only) + logging.info(f"Market order response: {response}") + + # --- NEW: STATE UPDATE ON SUCCESS --- + if response.get("status") == "ok": + response_data = response.get("response", {},).get("data", {}) + if response_data and "statuses" in response_data: + # Check if the order status contains an error + if "error" not in response_data["statuses"][0]: + position_key = order['position_key'] + if action == "market_open": + # Add to state + self.opened_positions[position_key] = { + "strategy": order['strategy'], + "coin": coin, + "side": "long" if is_buy else "short", + "open_time_utc": order['open_time_utc'], + "open_price": order['open_price'], + "amount": order['amount'], + # --- MODIFIED: Read leverage from the order --- + "leverage": order.get('leverage') + } + logging.info(f"Successfully opened position {position_key}. Saving state.") + elif action == "market_close": + # Remove from state + if position_key in self.opened_positions: + del self.opened_positions[position_key] + logging.info(f"Successfully closed position {position_key}. Saving state.") + else: + logging.warning(f"Received close confirmation for {position_key}, but it was not in state.") + + self._save_opened_positions() # Save state to disk - logging.warning(f"[{name}] ACTION: Open LONG for {coin} with {leverage_long}x leverage.") - exchange_to_use.update_leverage(int(leverage_long), coin) - exchange_to_use.market_open(coin, True, size, None, 0.01) - self.managed_positions[name] = {"coin": coin, "side": "long", "size": size} - log_trade(strategy=name, coin=coin, action="OPEN_LONG", price=status.get('signal_price', 0), size=size, signal=desired_signal) + else: + logging.error(f"API Error for {action}: {response_data['statuses'][0]['error']}") + else: + logging.error(f"Unexpected API response format: {response}") + else: + logging.error(f"API call failed, status: {response.get('status')}") - elif current_position['side'] == 'short': - if not all([size, leverage_long]): - logging.error(f"[{name}] 'size' or 'leverage_long' not defined. Skipping.") - continue - logging.warning(f"[{name}] ACTION: Close SHORT and open LONG for {coin} with {leverage_long}x leverage.") - exchange_to_use.update_leverage(int(leverage_long), coin) - exchange_to_use.market_open(coin, True, current_position['size'] + size, None, 0.01) - self.managed_positions[name] = {"coin": coin, "side": "long", "size": size} - log_trade(strategy=name, coin=coin, action="CLOSE_SHORT_&_REVERSE", price=status.get('signal_price', 0), size=size, signal=desired_signal) - - elif desired_signal == "SELL": - if not current_position: - if not all([size, leverage_short]): - logging.error(f"[{name}] 'size' or 'leverage_short' not defined. Skipping.") - continue - - logging.warning(f"[{name}] ACTION: Open SHORT for {coin} with {leverage_short}x leverage.") - exchange_to_use.update_leverage(int(leverage_short), coin) - exchange_to_use.market_open(coin, False, size, None, 0.01) - self.managed_positions[name] = {"coin": coin, "side": "short", "size": size} - log_trade(strategy=name, coin=coin, action="OPEN_SHORT", price=status.get('signal_price', 0), size=size, signal=desired_signal) - - elif current_position['side'] == 'long': - if not all([size, leverage_short]): - logging.error(f"[{name}] 'size' or 'leverage_short' not defined. Skipping.") - continue - - logging.warning(f"[{name}] ACTION: Close LONG and open SHORT for {coin} with {leverage_short}x leverage.") - exchange_to_use.update_leverage(int(leverage_short), coin) - exchange_to_use.market_open(coin, False, current_position['size'] + size, None, 0.01) - self.managed_positions[name] = {"coin": coin, "side": "short", "size": size} - log_trade(strategy=name, coin=coin, action="CLOSE_LONG_&_REVERSE", price=status.get('signal_price', 0), size=size, signal=desired_signal) - - elif desired_signal == "FLAT": - if current_position: - logging.warning(f"[{name}] ACTION: Close {current_position['side']} position for {coin}.") - is_buy = current_position['side'] == 'short' - exchange_to_use.market_open(coin, is_buy, current_position['size'], None, 0.01) - del self.managed_positions[name] - log_trade(strategy=name, coin=coin, action=f"CLOSE_{current_position['side'].upper()}", price=status.get('signal_price', 0), size=current_position['size'], signal=desired_signal) - - self._save_managed_positions() + elif action == "update_leverage": + leverage = int(size) + logging.warning(f"ACTION: UPDATE LEVERAGE {coin} to {leverage}x") + response = exchange_to_use.update_leverage(leverage, coin) + logging.info(f"Update leverage response: {response}") + + else: + logging.warning(f"Received unknown action: {action}") except Exception as e: - logging.error(f"An error occurred in the main executor loop: {e}") - - time.sleep(15) - - -if __name__ == "__main__": - parser = argparse.ArgumentParser(description="Run the Trade Executor.") - parser.add_argument("--log-level", default="normal", choices=['off', 'normal', 'debug']) - args = parser.parse_args() - - executor = TradeExecutor(log_level=args.log_level) - try: - executor.run() - except KeyboardInterrupt: - logging.info("Trade Executor stopped.") + logging.error(f"An error occurred in the main executor loop: {e}", exc_info=True) + time.sleep(1) diff --git a/wallet_data.py b/wallet_data.py new file mode 100644 index 0000000..0188724 --- /dev/null +++ b/wallet_data.py @@ -0,0 +1,652 @@ +#!/usr/bin/env python3 +""" +Hyperliquid Wallet Data Fetcher - FINAL Perfect Alignment +========================================================== +Complete Python script to pull all available data for a Hyperliquid wallet via API. + +Requirements: + pip install hyperliquid-python-sdk + +Usage: + python hyperliquid_wallet_data.py + +Example: + python hyperliquid_wallet_data.py 0xcd5051944f780a621ee62e39e493c489668acf4d +""" + +import sys +import json +from datetime import datetime, timedelta +from typing import Optional, Dict, Any +from hyperliquid.info import Info +from hyperliquid.utils import constants + + +class HyperliquidWalletAnalyzer: + """ + Comprehensive wallet data analyzer for Hyperliquid exchange. + Fetches all available information about a specific wallet address. + """ + + def __init__(self, wallet_address: str, use_testnet: bool = False): + """ + Initialize the analyzer with a wallet address. + + Args: + wallet_address: Ethereum-style address (0x...) + use_testnet: If True, use testnet instead of mainnet + """ + self.wallet_address = wallet_address + api_url = constants.TESTNET_API_URL if use_testnet else constants.MAINNET_API_URL + + # Initialize Info API (read-only, no private keys needed) + self.info = Info(api_url, skip_ws=True) + print(f"Initialized Hyperliquid API: {'Testnet' if use_testnet else 'Mainnet'}") + print(f"Target wallet: {wallet_address}\n") + + def print_position_details(self, position: Dict[str, Any], index: int): + """ + Print detailed information about a single position. + + Args: + position: Position data dictionary + index: Position number for display + """ + pos = position.get('position', {}) + + # Extract all position details + coin = pos.get('coin', 'Unknown') + size = float(pos.get('szi', 0)) + entry_px = float(pos.get('entryPx', 0)) + position_value = float(pos.get('positionValue', 0)) + unrealized_pnl = float(pos.get('unrealizedPnl', 0)) + return_on_equity = float(pos.get('returnOnEquity', 0)) + + # Leverage details + leverage = pos.get('leverage', {}) + leverage_type = leverage.get('type', 'unknown') if isinstance(leverage, dict) else 'cross' + leverage_value = leverage.get('value', 0) if isinstance(leverage, dict) else 0 + + # Margin and liquidation + margin_used = float(pos.get('marginUsed', 0)) + liquidation_px = pos.get('liquidationPx') + max_trade_szs = pos.get('maxTradeSzs', [0, 0]) + + # Cumulative funding + cumulative_funding = float(pos.get('cumFunding', {}).get('allTime', 0)) + + # Determine if long or short + side = "LONG šŸ“ˆ" if size > 0 else "SHORT šŸ“‰" + side_color = "šŸŸ¢" if size > 0 else "šŸ”“" + + # PnL color + pnl_symbol = "šŸŸ¢" if unrealized_pnl >= 0 else "šŸ”“" + pnl_sign = "+" if unrealized_pnl >= 0 else "" + + # ROE color + roe_symbol = "šŸŸ¢" if return_on_equity >= 0 else "šŸ”“" + roe_sign = "+" if return_on_equity >= 0 else "" + + print(f"\n{'='*80}") + print(f"POSITION #{index}: {coin} {side} {side_color}") + print(f"{'='*80}") + + print(f"\nšŸ“Š POSITION DETAILS:") + print(f" Size: {abs(size):.6f} {coin}") + print(f" Side: {side}") + print(f" Entry Price: ${entry_px:,.4f}") + print(f" Position Value: ${abs(position_value):,.2f}") + + print(f"\nšŸ’° PROFITABILITY:") + print(f" Unrealized PnL: {pnl_symbol} {pnl_sign}${unrealized_pnl:,.2f}") + print(f" Return on Equity: {roe_symbol} {roe_sign}{return_on_equity:.2%}") + print(f" Cumulative Funding: ${cumulative_funding:,.4f}") + + print(f"\nāš™ļø LEVERAGE & MARGIN:") + print(f" Leverage Type: {leverage_type.upper()}") + print(f" Leverage: {leverage_value}x") + print(f" Margin Used: ${margin_used:,.2f}") + + print(f"\nāš ļø RISK MANAGEMENT:") + if liquidation_px: + liquidation_px_float = float(liquidation_px) if liquidation_px else 0 + print(f" Liquidation Price: ${liquidation_px_float:,.4f}") + + # Calculate distance to liquidation + if entry_px > 0 and liquidation_px_float > 0: + if size > 0: # Long position + distance = ((entry_px - liquidation_px_float) / entry_px) * 100 + else: # Short position + distance = ((liquidation_px_float - entry_px) / entry_px) * 100 + + distance_symbol = "šŸŸ¢" if abs(distance) > 20 else "šŸŸ”" if abs(distance) > 10 else "šŸ”“" + print(f" Distance to Liq: {distance_symbol} {abs(distance):.2f}%") + else: + print(f" Liquidation Price: N/A (Cross margin)") + + if max_trade_szs and len(max_trade_szs) == 2: + print(f" Max Long Trade: {max_trade_szs[0]}") + print(f" Max Short Trade: {max_trade_szs[1]}") + + print(f"\n{'='*80}") + + def get_user_state(self) -> Dict[str, Any]: + """ + Get complete user state including positions and margin summary. + + Returns: + Dict containing: + - assetPositions: List of open perpetual positions + - marginSummary: Account value, margin used, withdrawable + - crossMarginSummary: Cross margin details + - withdrawable: Available balance to withdraw + """ + print("šŸ“Š Fetching User State (Perpetuals)...") + try: + data = self.info.user_state(self.wallet_address) + + if data: + margin_summary = data.get('marginSummary', {}) + positions = data.get('assetPositions', []) + + account_value = float(margin_summary.get('accountValue', 0)) + total_margin_used = float(margin_summary.get('totalMarginUsed', 0)) + total_ntl_pos = float(margin_summary.get('totalNtlPos', 0)) + total_raw_usd = float(margin_summary.get('totalRawUsd', 0)) + withdrawable = float(data.get('withdrawable', 0)) + + print(f" āœ“ Account Value: ${account_value:,.2f}") + print(f" āœ“ Total Margin Used: ${total_margin_used:,.2f}") + print(f" āœ“ Total Position Value: ${total_ntl_pos:,.2f}") + print(f" āœ“ Withdrawable: ${withdrawable:,.2f}") + print(f" āœ“ Open Positions: {len(positions)}") + + # Calculate margin utilization + if account_value > 0: + margin_util = (total_margin_used / account_value) * 100 + util_symbol = "šŸŸ¢" if margin_util < 50 else "šŸŸ”" if margin_util < 75 else "šŸ”“" + print(f" āœ“ Margin Utilization: {util_symbol} {margin_util:.2f}%") + + # Print detailed information for each position + if positions: + print(f"\n{'='*80}") + print(f"DETAILED POSITION BREAKDOWN ({len(positions)} positions)") + print(f"{'='*80}") + + for idx, position in enumerate(positions, 1): + self.print_position_details(position, idx) + + # Summary table with perfect alignment + self.print_positions_summary_table(positions) + + else: + print(" āš  No perpetual positions found") + + return data + except Exception as e: + print(f" āœ— Error: {e}") + return {} + + def print_positions_summary_table(self, positions: list): + """ + Print a summary table of all positions with perfectly aligned columns. + NO emojis in data cells - keeps them simple text only for perfect alignment. + + Args: + positions: List of position dictionaries + """ + print(f"\n{'='*130}") + print("POSITIONS SUMMARY TABLE") + print('='*130) + + # Print header + print("| Asset | Side | Size | Entry Price | Position Value | Unrealized PnL | ROE | Leverage |") + print("|----------|-------|-------------------|-------------------|-------------------|-------------------|------------|------------|") + + total_position_value = 0 + total_pnl = 0 + + for position in positions: + pos = position.get('position', {}) + + coin = pos.get('coin', 'Unknown') + size = float(pos.get('szi', 0)) + entry_px = float(pos.get('entryPx', 0)) + position_value = float(pos.get('positionValue', 0)) + unrealized_pnl = float(pos.get('unrealizedPnl', 0)) + return_on_equity = float(pos.get('returnOnEquity', 0)) + + # Get leverage + leverage = pos.get('leverage', {}) + leverage_value = leverage.get('value', 0) if isinstance(leverage, dict) else 0 + leverage_type = leverage.get('type', 'cross') if isinstance(leverage, dict) else 'cross' + + # Determine side - NO EMOJIS in data + side_text = "LONG" if size > 0 else "SHORT" + + # Format PnL and ROE with signs + pnl_sign = "+" if unrealized_pnl >= 0 else "" + roe_sign = "+" if return_on_equity >= 0 else "" + + # Accumulate totals + total_position_value += abs(position_value) + total_pnl += unrealized_pnl + + # Format all values as strings with proper width + asset_str = f"{coin[:8]:<8}" + side_str = f"{side_text:<5}" + size_str = f"{abs(size):>17,.4f}" + entry_str = f"${entry_px:>16,.2f}" + value_str = f"${abs(position_value):>16,.2f}" + pnl_str = f"{pnl_sign}${unrealized_pnl:>15,.2f}" + roe_str = f"{roe_sign}{return_on_equity:>9.2%}" + lev_str = f"{leverage_value}x {leverage_type[:4]}" + + # Print row with exact spacing + print(f"| {asset_str} | {side_str} | {size_str} | {entry_str} | {value_str} | {pnl_str} | {roe_str} | {lev_str:<10} |") + + # Separator before totals + print("|==========|=======|===================|===================|===================|===================|============|============|") + + # Total row + total_value_str = f"${total_position_value:>16,.2f}" + total_pnl_sign = "+" if total_pnl >= 0 else "" + total_pnl_str = f"{total_pnl_sign}${total_pnl:>15,.2f}" + + print(f"| TOTAL | | | | {total_value_str} | {total_pnl_str} | | |") + print('='*130 + '\n') + + def get_spot_state(self) -> Dict[str, Any]: + """ + Get spot trading state including token balances. + + Returns: + Dict containing: + - balances: List of spot token holdings + """ + print("\nšŸ’° Fetching Spot State...") + try: + data = self.info.spot_user_state(self.wallet_address) + + if data and data.get('balances'): + print(f" āœ“ Spot Holdings: {len(data['balances'])} tokens") + for balance in data['balances'][:5]: # Show first 5 + print(f" - {balance.get('coin', 'Unknown')}: {balance.get('total', 0)}") + else: + print(" āš  No spot holdings found") + + return data + except Exception as e: + print(f" āœ— Error: {e}") + return {} + + def get_open_orders(self) -> list: + """ + Get all open orders for the user. + + Returns: + List of open orders with details (price, size, side, etc.) + """ + print("\nšŸ“‹ Fetching Open Orders...") + try: + data = self.info.open_orders(self.wallet_address) + + if data: + print(f" āœ“ Open Orders: {len(data)}") + for order in data[:3]: # Show first 3 + coin = order.get('coin', 'Unknown') + side = order.get('side', 'Unknown') + size = order.get('sz', 0) + price = order.get('limitPx', 0) + print(f" - {coin} {side}: {size} @ ${price}") + else: + print(" āš  No open orders") + + return data + except Exception as e: + print(f" āœ— Error: {e}") + return [] + + def get_user_fills(self, limit: int = 100) -> list: + """ + Get recent trade fills (executions). + + Args: + limit: Maximum number of fills to retrieve (max 2000) + + Returns: + List of fills with execution details, PnL, timestamps + """ + print(f"\nšŸ“ˆ Fetching Recent Fills (last {limit})...") + try: + data = self.info.user_fills(self.wallet_address) + + if data: + fills = data[:limit] + print(f" āœ“ Total Fills Retrieved: {len(fills)}") + + # Show summary stats + total_pnl = sum(float(f.get('closedPnl', 0)) for f in fills if f.get('closedPnl')) + print(f" āœ“ Total Closed PnL: ${total_pnl:.2f}") + + # Show most recent + if fills: + recent = fills[0] + print(f" āœ“ Most Recent: {recent.get('coin')} {recent.get('side')} {recent.get('sz')} @ ${recent.get('px')}") + else: + print(" āš  No fills found") + + return data[:limit] if data else [] + except Exception as e: + print(f" āœ— Error: {e}") + return [] + + def get_user_fills_by_time(self, start_time: Optional[int] = None, + end_time: Optional[int] = None) -> list: + """ + Get fills within a specific time range. + + Args: + start_time: Start timestamp in milliseconds (default: 7 days ago) + end_time: End timestamp in milliseconds (default: now) + + Returns: + List of fills within the time range + """ + if not start_time: + start_time = int((datetime.now() - timedelta(days=7)).timestamp() * 1000) + if not end_time: + end_time = int(datetime.now().timestamp() * 1000) + + print(f"\nšŸ“… Fetching Fills by Time Range...") + print(f" From: {datetime.fromtimestamp(start_time/1000)}") + print(f" To: {datetime.fromtimestamp(end_time/1000)}") + + try: + data = self.info.user_fills_by_time(self.wallet_address, start_time, end_time) + + if data: + print(f" āœ“ Fills in Range: {len(data)}") + else: + print(" āš  No fills in this time range") + + return data + except Exception as e: + print(f" āœ— Error: {e}") + return [] + + def get_user_fees(self) -> Dict[str, Any]: + """ + Get user's fee schedule and trading volume. + + Returns: + Dict containing: + - feeSchedule: Fee rates by tier + - userCrossRate: User's current cross trading fee rate + - userAddRate: User's maker fee rate + - userWithdrawRate: Withdrawal fee rate + - dailyUserVlm: Daily trading volume + """ + print("\nšŸ’³ Fetching Fee Information...") + try: + data = self.info.user_fees(self.wallet_address) + + if data: + print(f" āœ“ Maker Fee: {data.get('userAddRate', 0)}%") + print(f" āœ“ Taker Fee: {data.get('userCrossRate', 0)}%") + print(f" āœ“ Daily Volume: ${data.get('dailyUserVlm', [0])[0] if data.get('dailyUserVlm') else 0}") + + return data + except Exception as e: + print(f" āœ— Error: {e}") + return {} + + def get_user_rate_limit(self) -> Dict[str, Any]: + """ + Get API rate limit information. + + Returns: + Dict containing: + - cumVlm: Cumulative trading volume + - nRequestsUsed: Number of requests used + - nRequestsCap: Request capacity + """ + print("\nā±ļø Fetching Rate Limit Info...") + try: + data = self.info.user_rate_limit(self.wallet_address) + + if data: + used = data.get('nRequestsUsed', 0) + cap = data.get('nRequestsCap', 0) + print(f" āœ“ API Requests: {used}/{cap}") + print(f" āœ“ Cumulative Volume: ${data.get('cumVlm', 0)}") + + return data + except Exception as e: + print(f" āœ— Error: {e}") + return {} + + def get_funding_history(self, coin: str, days: int = 7) -> list: + """ + Get funding rate history for a specific coin. + + Args: + coin: Asset symbol (e.g., 'BTC', 'ETH') + days: Number of days of history (default: 7) + + Returns: + List of funding rate entries + """ + end_time = int(datetime.now().timestamp() * 1000) + start_time = int((datetime.now() - timedelta(days=days)).timestamp() * 1000) + + print(f"\nšŸ“Š Fetching Funding History for {coin}...") + try: + data = self.info.funding_history(coin, start_time, end_time) + + if data: + print(f" āœ“ Funding Entries: {len(data)}") + if data: + latest = data[-1] + print(f" āœ“ Latest Rate: {latest.get('fundingRate', 0)}") + + return data + except Exception as e: + print(f" āœ— Error: {e}") + return [] + + def get_user_funding_history(self, days: int = 7) -> list: + """ + Get user's funding payments history. + + Args: + days: Number of days of history (default: 7) + + Returns: + List of funding payments + """ + end_time = int(datetime.now().timestamp() * 1000) + start_time = int((datetime.now() - timedelta(days=days)).timestamp() * 1000) + + print(f"\nšŸ’ø Fetching User Funding Payments (last {days} days)...") + try: + data = self.info.user_funding_history(self.wallet_address, start_time, end_time) + + if data: + print(f" āœ“ Funding Payments: {len(data)}") + total_funding = sum(float(f.get('usdc', 0)) for f in data) + print(f" āœ“ Total Funding P&L: ${total_funding:.2f}") + else: + print(" āš  No funding payments found") + + return data + except Exception as e: + print(f" āœ— Error: {e}") + return [] + + def get_user_non_funding_ledger_updates(self, days: int = 7) -> list: + """ + Get non-funding ledger updates (deposits, withdrawals, liquidations). + + Args: + days: Number of days of history (default: 7) + + Returns: + List of ledger updates + """ + end_time = int(datetime.now().timestamp() * 1000) + start_time = int((datetime.now() - timedelta(days=days)).timestamp() * 1000) + + print(f"\nšŸ“’ Fetching Ledger Updates (last {days} days)...") + try: + data = self.info.user_non_funding_ledger_updates(self.wallet_address, start_time, end_time) + + if data: + print(f" āœ“ Ledger Updates: {len(data)}") + # Categorize updates + deposits = [u for u in data if 'deposit' in str(u.get('delta', {})).lower()] + withdrawals = [u for u in data if 'withdraw' in str(u.get('delta', {})).lower()] + print(f" āœ“ Deposits: {len(deposits)}, Withdrawals: {len(withdrawals)}") + else: + print(" āš  No ledger updates found") + + return data + except Exception as e: + print(f" āœ— Error: {e}") + return [] + + def get_referral_state(self) -> Dict[str, Any]: + """ + Get referral program state for the user. + + Returns: + Dict with referral status and earnings + """ + print("\nšŸŽ Fetching Referral State...") + try: + data = self.info.query_referral_state(self.wallet_address) + + if data: + print(f" āœ“ Referral Code: {data.get('referralCode', 'N/A')}") + print(f" āœ“ Referees: {len(data.get('referees', []))}") + + return data + except Exception as e: + print(f" āœ— Error: {e}") + return {} + + def get_sub_accounts(self) -> list: + """ + Get list of sub-accounts for the user. + + Returns: + List of sub-account addresses + """ + print("\nšŸ‘„ Fetching Sub-Accounts...") + try: + data = self.info.query_sub_accounts(self.wallet_address) + + if data: + print(f" āœ“ Sub-Accounts: {len(data)}") + else: + print(" āš  No sub-accounts found") + + return data + except Exception as e: + print(f" āœ— Error: {e}") + return [] + + def fetch_all_data(self, save_to_file: bool = True) -> Dict[str, Any]: + """ + Fetch all available data for the wallet. + + Args: + save_to_file: If True, save results to JSON file + + Returns: + Dict containing all fetched data + """ + print("=" * 80) + print("HYPERLIQUID WALLET DATA FETCHER") + print("=" * 80) + + all_data = { + 'wallet_address': self.wallet_address, + 'timestamp': datetime.now().isoformat(), + 'data': {} + } + + # Fetch all data sections + all_data['data']['user_state'] = self.get_user_state() + all_data['data']['spot_state'] = self.get_spot_state() + all_data['data']['open_orders'] = self.get_open_orders() + all_data['data']['recent_fills'] = self.get_user_fills(limit=50) + all_data['data']['fills_last_7_days'] = self.get_user_fills_by_time() + all_data['data']['user_fees'] = self.get_user_fees() + all_data['data']['rate_limit'] = self.get_user_rate_limit() + all_data['data']['funding_payments'] = self.get_user_funding_history(days=7) + all_data['data']['ledger_updates'] = self.get_user_non_funding_ledger_updates(days=7) + all_data['data']['referral_state'] = self.get_referral_state() + all_data['data']['sub_accounts'] = self.get_sub_accounts() + + # Optional: Fetch funding history for positions + user_state = all_data['data']['user_state'] + if user_state and user_state.get('assetPositions'): + all_data['data']['funding_history'] = {} + for position in user_state['assetPositions'][:3]: # First 3 positions + coin = position.get('position', {}).get('coin') + if coin: + all_data['data']['funding_history'][coin] = self.get_funding_history(coin, days=7) + + print("\n" + "=" * 80) + print("DATA COLLECTION COMPLETE") + print("=" * 80) + + # Save to file + if save_to_file: + filename = f"hyperliquid_wallet_data_{self.wallet_address[:10]}_{datetime.now().strftime('%Y%m%d_%H%M%S')}.json" + with open(filename, 'w') as f: + json.dump(all_data, f, indent=2, default=str) + print(f"\nšŸ’¾ Data saved to: {filename}") + + return all_data + + +def main(): + """Main execution function.""" + if len(sys.argv) < 2: + print("Usage: python hyperliquid_wallet_data.py [--testnet]") + print("\nExample:") + print(" python hyperliquid_wallet_data.py 0xcd5051944f780a621ee62e39e493c489668acf4d") + sys.exit(1) + + wallet_address = sys.argv[1] + use_testnet = '--testnet' in sys.argv + + # Validate wallet address format + if not wallet_address.startswith('0x') or len(wallet_address) != 42: + print("āŒ Error: Invalid wallet address format") + print(" Address must be in format: 0x followed by 40 hexadecimal characters") + sys.exit(1) + + try: + analyzer = HyperliquidWalletAnalyzer(wallet_address, use_testnet=use_testnet) + data = analyzer.fetch_all_data(save_to_file=True) + + print("\nāœ… All data fetched successfully!") + print(f"\nšŸ“Š Summary:") + print(f" - Account Value: ${data['data']['user_state'].get('marginSummary', {}).get('accountValue', 0)}") + print(f" - Open Positions: {len(data['data']['user_state'].get('assetPositions', []))}") + print(f" - Spot Holdings: {len(data['data']['spot_state'].get('balances', []))}") + print(f" - Open Orders: {len(data['data']['open_orders'])}") + print(f" - Recent Fills: {len(data['data']['recent_fills'])}") + + except Exception as e: + print(f"\nāŒ Fatal Error: {e}") + import traceback + traceback.print_exc() + sys.exit(1) + + +if __name__ == "__main__": + main() \ No newline at end of file diff --git a/whale_tracker.py b/whale_tracker.py new file mode 100644 index 0000000..69fc29a --- /dev/null +++ b/whale_tracker.py @@ -0,0 +1,367 @@ +import json +import os +import time +import requests +import logging +import argparse +import sys +from datetime import datetime, timedelta + +# --- Configuration --- +# !! IMPORTANT: Update this to your actual Hyperliquid API endpoint !! +API_ENDPOINT = "https://api.hyperliquid.xyz/info" + +INPUT_FILE = os.path.join("_data", "wallets_to_track.json") +OUTPUT_FILE = os.path.join("_data", "wallets_info.json") +LOGS_DIR = "_logs" +LOG_FILE = os.path.join(LOGS_DIR, "whale_tracker.log") + +# Polling intervals (in seconds) +POLL_INTERVALS = { + 'core_data': 10, # 5-15s range + 'open_orders': 20, # 15-30s range + 'account_metrics': 180, # 1-5m range + 'ledger_updates': 600, # 5-15m range + 'save_data': 5, # How often to write to wallets_info.json + 'reload_wallets': 60 # Check for wallet list changes every 60s +} + +class HyperliquidAPI: + """ + Client to handle POST requests to the Hyperliquid info endpoint. + """ + def __init__(self, base_url): + self.base_url = base_url + self.session = requests.Session() + logging.info(f"API Client initialized for endpoint: {base_url}") + + def post_request(self, payload): + """ + Internal helper to send POST requests and handle errors. + """ + try: + response = self.session.post(self.base_url, json=payload, timeout=10) + response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) + return response.json() + except requests.exceptions.HTTPError as e: + logging.error(f"HTTP Error: {e.response.status_code} for {e.request.url}. Response: {e.response.text}") + except requests.exceptions.ConnectionError as e: + logging.error(f"Connection Error: {e}") + except requests.exceptions.Timeout: + logging.error(f"Request timed out for payload: {payload.get('type')}") + except json.JSONDecodeError: + logging.error(f"Failed to decode JSON response. Response text: {response.text if 'response' in locals() else 'No response text'}") + except Exception as e: + logging.error(f"An unexpected error occurred in post_request: {e}", exc_info=True) + return None + + def get_user_state(self, user_address: str): + payload = {"type": "clearinghouseState", "user": user_address} + return self.post_request(payload) + + def get_open_orders(self, user_address: str): + payload = {"type": "openOrders", "user": user_address} + return self.post_request(payload) + + def get_user_rate_limit(self, user_address: str): + payload = {"type": "userRateLimit", "user": user_address} + return self.post_request(payload) + + def get_user_ledger_updates(self, user_address: str, start_time_ms: int, end_time_ms: int): + payload = { + "type": "userNonFundingLedgerUpdates", + "user": user_address, + "startTime": start_time_ms, + "endTime": end_time_ms + } + return self.post_request(payload) + +class WalletTracker: + """ + Main class to track wallets, process data, and store results. + """ + def __init__(self, api_client, wallets_to_track): + self.api = api_client + self.wallets = wallets_to_track # This is the list of dicts + self.wallets_by_name = {w['name']: w for w in self.wallets} + self.wallets_data = { + wallet['name']: {"address": wallet['address']} for wallet in self.wallets + } + logging.info(f"WalletTracker initialized for {len(self.wallets)} wallets.") + + def reload_wallets(self): + """ + Checks the INPUT_FILE for changes and updates the tracked wallet list. + """ + logging.debug("Reloading wallet list...") + try: + with open(INPUT_FILE, 'r') as f: + new_wallets_list = json.load(f) + if not isinstance(new_wallets_list, list): + logging.warning(f"Failed to reload '{INPUT_FILE}': content is not a list.") + return + + new_wallets_by_name = {w['name']: w for w in new_wallets_list} + old_names = set(self.wallets_by_name.keys()) + new_names = set(new_wallets_by_name.keys()) + + added_names = new_names - old_names + removed_names = old_names - new_names + + if not added_names and not removed_names: + logging.debug("Wallet list is unchanged.") + return # No changes + + # Update internal wallet list + self.wallets = new_wallets_list + self.wallets_by_name = new_wallets_by_name + + # Add new wallets to wallets_data + for name in added_names: + self.wallets_data[name] = {"address": self.wallets_by_name[name]['address']} + logging.info(f"Added new wallet to track: {name}") + + # Remove old wallets from wallets_data + for name in removed_names: + if name in self.wallets_data: + del self.wallets_data[name] + logging.info(f"Removed wallet from tracking: {name}") + + logging.info(f"Wallet list reloaded. Tracking {len(self.wallets)} wallets.") + + except (FileNotFoundError, json.JSONDecodeError, ValueError) as e: + logging.error(f"Failed to reload and parse '{INPUT_FILE}': {e}") + except Exception as e: + logging.error(f"Unexpected error during wallet reload: {e}", exc_info=True) + + + def calculate_core_metrics(self, state_data: dict) -> dict: + """ + Performs calculations based on user_state data. + """ + if not state_data or 'crossMarginSummary' not in state_data: + logging.warning("Core state data is missing 'crossMarginSummary'.") + return {"raw_state": state_data} + + summary = state_data['crossMarginSummary'] + account_value = float(summary.get('accountValue', 0)) + margin_used = float(summary.get('totalMarginUsed', 0)) + + # Calculations + margin_utilization = (margin_used / account_value) if account_value > 0 else 0 + available_margin = account_value - margin_used + + total_position_value = 0 + if 'assetPositions' in state_data: + for pos in state_data.get('assetPositions', []): + try: + # Use 'value' for position value + pos_value_str = pos.get('position', {}).get('value', '0') + total_position_value += float(pos_value_str) + except (ValueError, TypeError): + logging.warning(f"Could not parse position value: {pos.get('position', {}).get('value')}") + continue + + portfolio_leverage = (total_position_value / account_value) if account_value > 0 else 0 + + # Return calculated metrics alongside raw data + return { + "raw_state": state_data, + "account_value": account_value, + "margin_used": margin_used, + "margin_utilization": margin_utilization, + "available_margin": available_margin, + "total_position_value": total_position_value, + "portfolio_leverage": portfolio_leverage + } + + def poll_core_data(self): + logging.debug("Polling Core Data...") + # Use self.wallets which is updated by reload_wallets + for wallet in self.wallets: + name = wallet['name'] + address = wallet['address'] + state_data = self.api.get_user_state(address) + if state_data: + calculated_data = self.calculate_core_metrics(state_data) + # Ensure wallet hasn't been removed by a concurrent reload + if name in self.wallets_data: + self.wallets_data[name]['core_state'] = calculated_data + time.sleep(0.1) # Avoid bursting requests + + def poll_open_orders(self): + logging.debug("Polling Open Orders...") + for wallet in self.wallets: + name = wallet['name'] + address = wallet['address'] + orders_data = self.api.get_open_orders(address) + if orders_data: + # TODO: Add calculations for 'pending_margin_required' if logic is available + if name in self.wallets_data: + self.wallets_data[name]['open_orders'] = {"raw_orders": orders_data} + time.sleep(0.1) + + def poll_account_metrics(self): + logging.debug("Polling Account Metrics...") + for wallet in self.wallets: + name = wallet['name'] + address = wallet['address'] + metrics_data = self.api.get_user_rate_limit(address) + if metrics_data: + if name in self.wallets_data: + self.wallets_data[name]['account_metrics'] = metrics_data + time.sleep(0.1) + + def poll_ledger_updates(self): + logging.debug("Polling Ledger Updates...") + end_time_ms = int(datetime.now().timestamp() * 1000) + start_time_ms = int((datetime.now() - timedelta(minutes=15)).timestamp() * 1000) + + for wallet in self.wallets: + name = wallet['name'] + address = wallet['address'] + ledger_data = self.api.get_user_ledger_updates(address, start_time_ms, end_time_ms) + if ledger_data: + if name in self.wallets_data: + self.wallets_data[name]['ledger_updates'] = ledger_data + time.sleep(0.1) + + def save_data_to_json(self): + """ + Atomically writes the current wallet data to the output JSON file. + (No longer needs cleaning logic) + """ + logging.debug(f"Saving data to {OUTPUT_FILE}...") + + temp_file = OUTPUT_FILE + ".tmp" + try: + # Save the data + with open(temp_file, 'w', encoding='utf-8') as f: + # self.wallets_data is automatically kept clean by reload_wallets + json.dump(self.wallets_data, f, indent=2) + # Atomic rename (move) + os.replace(temp_file, OUTPUT_FILE) + except (IOError, json.JSONDecodeError) as e: + logging.error(f"Failed to write wallet data to file: {e}") + except Exception as e: + logging.error(f"An unexpected error occurred during file save: {e}") + if os.path.exists(temp_file): + os.remove(temp_file) + +class WhaleTrackerRunner: + """ + Manages the polling loop using last-run timestamps instead of a complex scheduler. + """ + def __init__(self, api_client, wallets, shared_whale_data_dict=None): # Kept arg for compatibility + self.tracker = WalletTracker(api_client, wallets) + self.last_poll_times = {key: 0 for key in POLL_INTERVALS} + self.poll_intervals = POLL_INTERVALS + logging.info("WhaleTrackerRunner initialized to save to JSON file.") + + def update_shared_data(self): + """ + This function is no longer called by the run loop. + It's kept here to prevent errors if imported elsewhere, but is now unused. + """ + logging.debug("No shared dict, saving data to JSON file.") + self.tracker.save_data_to_json() + + + def run(self): + logging.info("Starting main polling loop...") + while True: + try: + now = time.time() + + if now - self.last_poll_times['reload_wallets'] > self.poll_intervals['reload_wallets']: + self.tracker.reload_wallets() + self.last_poll_times['reload_wallets'] = now + + if now - self.last_poll_times['core_data'] > self.poll_intervals['core_data']: + self.tracker.poll_core_data() + self.last_poll_times['core_data'] = now + + if now - self.last_poll_times['open_orders'] > self.poll_intervals['open_orders']: + self.tracker.poll_open_orders() + self.last_poll_times['open_orders'] = now + + if now - self.last_poll_times['account_metrics'] > self.poll_intervals['account_metrics']: + self.tracker.poll_account_metrics() + self.last_poll_times['account_metrics'] = now + + if now - self.last_poll_times['ledger_updates'] > self.poll_intervals['ledger_updates']: + self.tracker.poll_ledger_updates() + self.last_poll_times['ledger_updates'] = now + + if now - self.last_poll_times['save_data'] > self.poll_intervals['save_data']: + self.tracker.save_data_to_json() # <-- NEW + self.last_poll_times['save_data'] = now + + # Sleep for a short duration to prevent busy-waiting + time.sleep(1) + + except Exception as e: + logging.critical(f"Unhandled exception in main loop: {e}", exc_info=True) + time.sleep(10) + +def setup_logging(log_level_str: str, process_name: str): + """Configures logging for the script.""" + if not os.path.exists(LOGS_DIR): + try: + os.makedirs(LOGS_DIR) + except OSError as e: + print(f"Failed to create logs directory {LOGS_DIR}: {e}") + return + + level_map = { + 'debug': logging.DEBUG, + 'normal': logging.INFO, + 'off': logging.NOTSET + } + log_level = level_map.get(log_level_str.lower(), logging.INFO) + + if log_level == logging.NOTSET: + return + + handlers_list = [logging.FileHandler(LOG_FILE, mode='a')] + + if sys.stdout.isatty(): + handlers_list.append(logging.StreamHandler(sys.stdout)) + + logging.basicConfig( + level=log_level, + format=f"%(asctime)s.%(msecs)03d | {process_name:<20} | %(levelname)-8s | %(message)s", + datefmt='%Y-%m-%d %H:%M:%S', + handlers=handlers_list + ) + +if __name__ == "__main__": + parser = argparse.ArgumentParser(description="Hyperliquid Whale Tracker") + parser.add_argument("--log-level", default="normal", choices=['off', 'normal', 'debug']) + args = parser.parse_args() + + setup_logging(args.log_level, "WhaleTracker") + + # Load wallets to track + wallets_to_track = [] + try: + with open(INPUT_FILE, 'r') as f: + wallets_to_track = json.load(f) + if not isinstance(wallets_to_track, list) or not wallets_to_track: + raise ValueError(f"'{INPUT_FILE}' is empty or not a list.") + except (FileNotFoundError, json.JSONDecodeError, ValueError) as e: + logging.critical(f"Failed to load '{INPUT_FILE}': {e}. Exiting.") + sys.exit(1) + + # Initialize API client + api_client = HyperliquidAPI(base_url=API_ENDPOINT) + + # Initialize and run the tracker + runner = WhaleTrackerRunner(api_client, wallets_to_track, shared_whale_data_dict=None) + + try: + runner.run() + except KeyboardInterrupt: + logging.info("Whale Tracker shutting down.") + sys.exit(0) +