Merge remote-tracking branch 'origin/web_socket'

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).

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.

PROJECT_REVIEW_AND_PROPOSALS.md

@@ -0,0 +1 @@
+"# Comprehensive Project Review and Improvement Proposals" 

_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": {

_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"
+}

_data/coin_precision.json

@@ -101,6 +101,7 @@
     "MAV": 0,
     "MAVIA": 1,
     "ME": 1,
+    "MEGA": 0,
     "MELANIA": 1,
     "MEME": 0,
     "MERL": 0,

_data/executor_managed_positions.json

@@ -1,7 +0,0 @@
-{
-    "sma_cross_2": {
-        "coin": "BTC",
-        "side": "short",
-        "size": 0.0001
-    }
-}

_data/opened_positions.json

@@ -0,0 +1,11 @@
+{
+    "copy_trader_eth_ETH": {
+        "strategy": "copy_trader_eth",
+        "coin": "ETH",
+        "side": "long",
+        "open_time_utc": "2025-11-02T20:35:02.988272+00:00",
+        "open_price": 3854.9,
+        "amount": 0.0055,
+        "leverage": 3
+    }
+}

_data/strategies.json

@@ -1,12 +1,11 @@
 {
-    "sma_cross_eth_5m": {
+    "sma_cross_1": {
-        "enabled": true,
+        "enabled": false,
-        "script": "strategy_runner.py",
         "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": {
+       "sma_44d_btc": {
-        "enabled": true,
+        "enabled": false,
-        "script": "strategy_runner.py",
         "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
+                }
+            }
+        }
     }
 }
 

_data/strategy_state_copy_trader_eth.json

@@ -0,0 +1,7 @@
+{
+    "ETH": {
+        "side": "long",
+        "size": 0.018,
+        "entry": 3864.2
+    }
+}

_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"
+}

_data/strategy_status_ma_cross_btc.json

@@ -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"
-}

_data/strategy_status_sma_125d_btc.json

@@ -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"
-}

_data/strategy_status_sma_125d_eth.json

@@ -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"
-}

_data/strategy_status_sma_44d_btc.json

@@ -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"
-}

_data/strategy_status_sma_5m_eth.json

@@ -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"
-}

_data/strategy_status_sma_cross.json

@@ -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"
-}

_data/strategy_status_sma_cross_1.json

@@ -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"
-}

_data/strategy_status_sma_cross_eth_5m.json

@@ -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"
-}

_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
+    }
+  }
+}

_data/wallets_to_track.json

@@ -0,0 +1,7 @@
+[
+  {
+    "name": "Whale 1 (BTC Maxi)",
+    "address": "0xb83de012dba672c76a7dbbbf3e459cb59d7d6e36",
+    "tags": ["btc", "high_leverage"]
+  }
+]

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"

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

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()
+

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.")

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()

live_candle_fetcher.py

@@ -0,0 +1,238 @@
+import argparse
+import logging
+import os
+import sys
+import json
+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()
+

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.")
+

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"
+LIVE_CANDLE_FETCHER_SCRIPT = "live_candle_fetcher.py"
-MARKET_FEEDER_SCRIPT = "market.py"
-DATA_FETCHER_SCRIPT = "data_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")
+# --- REMOVED: Market Cap File ---
-MARKET_CAP_SUMMARY_FILE = os.path.join("_data", "market_cap_data.json")
 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():
+def run_live_candle_fetcher():
-    """Target function to run market.py and redirect its output to a log file."""
+    """Target function to run the live_candle_fetcher.py script in a resilient loop."""
-    log_file = os.path.join(LOGS_DIR, "market_feeder.log")
+    
-    while True:
+    # --- 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(
+                command = [sys.executable, LIVE_CANDLE_FETCHER_SCRIPT, "--coins"] + WATCHED_COINS + ["--log-level", "off"]
-                    [sys.executable, MARKET_FEEDER_SCRIPT, "--log-level", "off"], 
+                f.write(f"\n--- Starting {LIVE_CANDLE_FETCHER_SCRIPT} at {datetime.now()} ---\n")
-                    check=True, stdout=f, stderr=subprocess.STDOUT
+                
-                )
+                # 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)
-
+        
-
+        if shutdown_requested:
-def run_data_fetcher_job():
+            break # Exit outer loop
-    """Defines the job for the data fetcher, redirecting output to a log file."""
+            
-    log_file = os.path.join(LOGS_DIR, "data_fetcher.log")
+    print("[CandleFetcher] Live candle fetcher shutting down.")
-    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)
 
 
 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)
+    # Schedule to run every minute at the :01 second mark
-    while True:
+    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():
+# --- REMOVED: run_market_cap_fetcher_job function ---
-    """Defines the job for the market cap fetcher, redirecting output."""
+
-    log_file = os.path.join(LOGS_DIR, "market_cap_fetcher.log")
+# --- 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"]
+        sys.stdout = open(log_file_path, 'a', buffering=1)
-        with open(log_file, 'a') as f:
+        sys.stderr = sys.stdout
-            f.write(f"\n--- Starting {MARKET_CAP_FETCHER_SCRIPT} 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:
+        print(f"Failed to open log file for TradeExecutor: {e}")
-            f.write(f"\n--- SCHEDULER ERROR at {datetime.now()} ---\n")
-            f.write(f"Failed to run {MARKET_CAP_FETCHER_SCRIPT} job: {e}\n")
 
-
+    setup_logging('normal', f"TradeExecutor")
-def market_cap_fetcher_scheduler():
+    logging.info("\n--- Starting Trade Executor process ---")
-    """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)
     while True:
-        schedule.run_pending()
+        try:
-        time.sleep(60)
+            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):
+def run_strategy(strategy_name: str, config: dict, trade_signal_queue: multiprocessing.Queue):
-    """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")
+    This function BECOMES the strategy runner. It is executed as a separate
-    script_name = config['script']
+    process and pushes signals to the shared queue.
-    params_str = json.dumps(config['parameters'])
+    """
-    command = [sys.executable, script_name, "--name", strategy_name, "--params", params_str, "--log-level", "normal"]
+    # 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")
+                f.write(f"\n--- Starting Dashboard Data Fetcher at {datetime.now()} ---\n")
-                subprocess.run(command, check=True, stdout=f, stderr=subprocess.STDOUT)
+                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 = {}
+        # --- REMOVED: self.market_caps ---
-        self.last_db_update_info = "Initializing..."
         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."""
+        """Reads the latest prices directly from the shared memory dictionary."""
-        if os.path.exists(PRICE_DATA_FILE):
+        try:
-            try:
+            # --- FIX: Use .copy() for thread-safe iteration ---
-                with open(PRICE_DATA_FILE, 'r', encoding='utf-8') as f:
+            self.prices = self.shared_prices.copy()
-                    self.prices = json.load(f)
+        except Exception as e:
-            except (json.JSONDecodeError, IOError):
+            logging.debug(f"Could not read from shared prices dict: {e}")
-                logging.debug("Could not read price file.")
 
-    def read_market_caps(self):
+    # --- REMOVED: read_market_caps method ---
-        """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.")
 
     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_lines = ["--- Market Dashboard ---"]
-        left_table_width = 44
+        # --- MODIFIED: Adjusted width for new columns ---
-        left_table_lines.append("--- Market Dashboard ---")
+        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...")
+            # --- MODIFIED: Fetch all three price types ---
-            market_cap = self.market_caps.get(coin)
+            mid_price = self.prices.get(coin, "Loading...")
-            formatted_mc = format_market_cap(market_cap)
+            bid_price = self.prices.get(f"{coin}_bid", "Loading...")
-            left_table_lines.append(f"{i:<2} | {coin:^6} | {price:>10} | {formatted_mc:>15} |")
+            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_lines = ["--- Strategy Status ---"]
-        right_table_width = 154
+        # --- FIX: Adjusted table width after removing parameters ---
-        right_table_lines.append("--- Strategy Status ---")
+        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']}
+            # --- FIX: Read coin/size from status file first, fallback to config ---
-            params_str = ", ".join([f"{k}={v}" for k, v in other_params.items()])
+            coin = status.get('coin', config_params.get('coin', 'N/A'))
-
+            
-            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: 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', [])
+        # --- FIX: Correctly read and display open positions ---
-        spot_positions = self.open_positions.get('spot_account', {}).get('positions', [])
+        if not self.open_positions:
-
+            output_lines.append(f"{'No open positions.':^{pos_table_width}}")
-        if not perps_positions and not spot_positions:
-            output_lines.append("No open positions found.")
         else:
-            for pos in perps_positions:
+            for account, positions in self.open_positions.items():
-                # --- FIX: Safely handle potentially None values before formatting ---
+                if not positions:
-                try:
+                    continue
-                    pnl = float(pos.get('pnl', 0.0))
+                for coin, pos in positions.items():
-                    pnl_str = f"${pnl:,.2f}"
+                    try:
-                except (ValueError, TypeError):
+                        size_f = float(pos.get('size', 0))
-                    pnl_str = "Error"
+                        entry_f = float(pos.get('entry_price', 0))
-                
+                        mark_f = float(self.prices.get(coin, 0))
-                coin = pos.get('coin') or '-'
+                        pnl_f = (mark_f - entry_f) * size_f if size_f > 0 else (entry_f - mark_f) * abs(size_f)
-                size = pos.get('size') or '-'
+                        lev = pos.get('leverage', 1)
-                entry_price = pos.get('entry_price') or '-'
+                        
-                mark_price = pos.get('mark_price') or '-'
+                        size_str = f"{size_f:>{15}.5f}"
-                leverage = pos.get('leverage') or '-'
+                        entry_str = f"{entry_f:>{12}.2f}"
-                
+                        mark_str = f"{mark_f:>{12}.2f}"
-                output_lines.append(f"{'Perps':<10} | {coin:<6} | {size:>15} | {entry_price:>12} | {mark_price:>12} | {pnl_str:>15} | {leverage:>10} |")
+                        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()
+            # --- REMOVED: self.read_market_caps() ---
-            self.get_overall_db_status()
             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()
+    # --- FIX: Hardcoded timeframes ---
-    for name, config in strategy_configs.items():
+    required_timeframes = [
-        if config.get("enabled", False):
+        "3m", "5m", "15m", "30m", "1h", "2h", "4h", "8h", 
-            tf = config.get("parameters", {}).get("timeframe")
+        "12h", "1d", "3d", "1w", "1M", "148m", "37m"
-            if tf:
+    ]
-                required_timeframes.add(tf)
+    logging.info(f"Using fixed timeframes for resampler: {required_timeframes}")
     
-    if not required_timeframes:
+    with multiprocessing.Manager() as manager:
-        logging.warning("No timeframes required by any enabled strategy. Resampler will not run effectively.")
+        shared_prices = manager.dict()
+        # --- FIX: Create TWO queues ---
+        trade_signal_queue = manager.Queue()
+        order_execution_queue = manager.Queue()
 
-    
+        # --- REVERTED: All processes are daemon=True and in one dict ---
-    processes["Market Feeder"] = multiprocessing.Process(target=run_market_feeder, daemon=True)
+        
-    processes["Data Fetcher"] = multiprocessing.Process(target=data_fetcher_scheduler, daemon=True)
+        # --- FIX: Pass WATCHED_COINS to the start_live_feed process ---
-    processes["Resampler"] = multiprocessing.Process(target=resampler_scheduler, args=(list(required_timeframes),), daemon=True)
+        # --- MODIFICATION: Set log level back to 'off' ---
-    processes["Market Cap Fetcher"] = multiprocessing.Process(target=market_cap_fetcher_scheduler, daemon=True)
+        processes["Live Market Feed"] = multiprocessing.Process(
-    
+            target=start_live_feed, 
-    for name, config in strategy_configs.items():
+            args=(shared_prices, WATCHED_COINS, 'off'), 
-        if config.get("enabled", False):
+            daemon=True
-            if not os.path.exists(config['script']):
+        )
-                logging.error(f"Strategy script '{config['script']}' for strategy '{name}' not found. Skipping.")
+        processes["Live Candle Fetcher"] = multiprocessing.Process(target=run_live_candle_fetcher, daemon=True)
-                continue
+        processes["Resampler"] = multiprocessing.Process(target=resampler_scheduler, args=(list(required_timeframes),), daemon=True)
-            proc = multiprocessing.Process(target=run_strategy, args=(name, config), daemon=True)
+        # --- REMOVED: Market Cap Fetcher Process ---
-            processes[f"Strategy: {name}"] = proc
+        processes["Dashboard Data"] = multiprocessing.Process(target=run_dashboard_data_fetcher, daemon=True)
 
-    for name, proc in processes.items():
+        processes["Position Manager"] = multiprocessing.Process(
-        logging.info(f"Starting process '{name}'...")
+            target=run_position_manager, 
-        proc.start()
+            args=(trade_signal_queue, order_execution_queue),
-    
+            daemon=True
-    time.sleep(3)
+        )
+        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)
+        for name, proc in processes.items():
-    try:
+            logging.info(f"Starting process '{name}'...")
-        app.run()
+            proc.start()
-    except KeyboardInterrupt:
+        
-        logging.info("Shutting down...")
+        time.sleep(3)
-        for proc in processes.values():
+
-            if proc.is_alive(): proc.terminate()
+        app = MainApp(coins_to_watch=WATCHED_COINS, processes=processes, strategy_configs=strategy_configs, shared_prices=shared_prices)
-        for proc in processes.values():
+        try:
-            if proc.is_alive(): proc.join()
+            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)
 
+
+

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,
+    intelligently upserts it into the SQLite database for all coins.
-    aggregates stablecoins, and captures total market cap metrics.
     """
 
-    COIN_ID_MAP = {
+    def __init__(self, log_level: str):
-        "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):
         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):
-        """
+        # ... (This function is unchanged)
-        Queries the last record from each market cap table and saves a summary to a JSON file.
-        """
         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 upserts it for the current date."""
-        Fetches the current total market cap and saves 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()
-            
+            today_dt = pd.to_datetime(today_date)
-            cursor = conn.cursor()
+            today_ts = int(today_dt.timestamp() * 1000)
-            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
 
             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 = all_stablecoin_df.groupby('timestamp_ms').agg(
-        aggregated_df['datetime_utc'] = pd.to_datetime(aggregated_df['datetime_utc'])
+            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)
+            self._upsert_market_cap_data(conn, table_name, aggregated_df)
-            logging.info(f"Successfully saved {len(aggregated_df)} daily records to '{table_name}'.")
         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, is_timestamp_ms=True)
-        last_date_in_db = self._get_last_date_from_db(table_name, conn)
         
         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)
+            self._upsert_market_cap_data(conn, table_name, df)
-            logging.info(f"Successfully saved {len(df)} new daily market cap records for {coin_symbol}.")
         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:
+    def _get_last_date_from_db(self, table_name: str, conn, is_timestamp_ms: bool = False):
-        """Gets the most recent date from a market cap table as a pandas Timestamp."""
+        """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)
+            # --- FIX: Normalize all timestamps to the start of the day (00:00:00 UTC) ---
-            return df[['datetime_utc', 'market_cap']]
+            # 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()
 

position_logic/__init__.py

@@ -0,0 +1,2 @@
+# This file can be empty.
+# It tells Python that 'position_logic' is a directory containing modules.

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

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

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
+

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()

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
+                        query = f'SELECT * FROM "{source_table_name}"'
-                        new_df_1m = df_1m[df_1m.index > last_timestamp] if last_timestamp else df_1m
+                        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
+                            records_to_upsert = []
-                            resampled_df.to_sql(target_table_name, conn, if_exists='append', index=True)
+                            for index, row in resampled_df.iterrows():
-                            logging.debug(f"    -> Appended {len(resampled_df)} new candles to '{target_table_name}'.")
+                                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"
+        if unit == 'm': 
-        elif unit == 'w': code = f"{numeric_part}W"
+            code = f"{numeric_part}min"
-        elif unit in ['h', 'd']: code = f"{numeric_part}{unit}"
+        elif unit.lower() == 'w':
-        else: code = tf_str
+            code = f"{numeric_part}W-MON"
-        tf_map[tf_str] = code
+        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
 
 

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).

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
+        # Note: Logging is set up by the run_strategy function
-        # setup_logging(log_level, f"Strategy-{self.strategy_name}")
-        # logging.info(f"Initializing with parameters: {self.params}")
 
     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 or 'fast' in k]
-        periods = [v for k, v in self.params.items() if 'period' in k or '_ma' in k or 'slow' 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:
+            if self.shared_status is not None:
-                json.dump(status, f, indent=4)
+                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
+

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}")
+

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:
+    # --- FIX: Changed 3rd argument from log_level to trade_signal_queue ---
-        # Support multiple naming conventions: some configs use 'fast'/'slow'
+    def __init__(self, strategy_name: str, params: dict, trade_signal_queue):
-        # while others use 'short_ma'/'long_ma'. Normalize here so both work.
+        # --- FIX: Passed trade_signal_queue to the parent class ---
-        fast_ma_period = self.params.get('short_ma') or self.params.get('fast') or 0
+        super().__init__(strategy_name, params, trade_signal_queue)
-        slow_ma_period = self.params.get('long_ma') or self.params.get('slow') or 0
+        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 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
 
-        if len(df) < slow_ma_period:
+    def calculate_signals(self, df: pd.DataFrame) -> pd.DataFrame:
-            logging.warning(f"Not enough data for MA periods {fast_ma_period}/{slow_ma_period}. Need {slow_ma_period}, have {len(df)}.")
+        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['fast_sma'] = df['close'].rolling(window=self.fast_ma_period).mean()
-        df['slow_sma'] = df['close'].rolling(window=slow_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

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 self.sma_period or len(df) < self.sma_period:
-        
+            logging.warning(f"Not enough data for SMA period {self.sma_period}.")
-        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)}.")
             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

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,
+    Executes orders from a queue and, upon API success,
-    multi-strategy position management system. Each strategy's position is
+    updates the shared 'opened_positions.json' state file.
-    tracked independently.
+    It is the single source of truth for position state.
     """
 
-    def __init__(self, log_level: str):
+    def __init__(self, log_level: str, order_execution_queue: multiprocessing.Queue):
-        setup_logging(log_level, 'TradeExecutor')
+        # 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")
+        # --- REVERTED: Removed asset_meta loading ---
-        try:
+        # self.asset_meta = self._load_asset_metadata()
-            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")}
+        # --- NEW: State management logic ---
-            logging.info(f"Loaded {len(self.strategy_configs)} enabled strategies.")
+        self.opened_positions_file = os.path.join("_data", "opened_positions.json")
-        except (FileNotFoundError, json.JSONDecodeError) as e:
+        self.opened_positions = self._load_opened_positions()
-            logging.error(f"Could not load strategies from '{strategy_config_path}': {e}")
+        
-            sys.exit(1)
+        logging.info(f"Trade Executor started. Loaded {len(self.opened_positions)} positions.")
-            
+
-        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()
 
     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:
+    # --- NEW: Position state save/load methods ---
-        """Loads the state of which strategy manages which position."""
+    def _load_opened_positions(self) -> dict:
-        if os.path.exists(self.managed_positions_path):
+        """Loads the state of currently managed positions from a JSON file."""
-            try:
+        if not os.path.exists(self.opened_positions_file):
-                with open(self.managed_positions_path, 'r') as f:
+            return {}
-                    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."""
         try:
-            with open(self.managed_positions_path, 'w') as f:
+            with open(self.opened_positions_file, 'r', encoding='utf-8') as f:
-                json.dump(self.managed_positions, f, indent=4)
+                return json.load(f)
-        except IOError as e:
+        except (json.JSONDecodeError, IOError) as e:
-            logging.error(f"Failed to save managed positions state: {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):
+    def _save_opened_positions(self):
-        """Saves the current balances and open positions to a live status file."""
+        """Saves the current state of managed positions to a JSON file."""
-        # This function is correct and does not need changes.
+        try:
-        pass
+            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)
+                order = self.order_execution_queue.get()
-                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}
+                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():
+                exchange_to_use = self.exchanges.get(agent_name)
-                    coin = config['parameters'].get('coin')
+                if not exchange_to_use:
-                    size = config['parameters'].get('size')
+                    logging.error(f"Agent '{agent_name}' not found. Skipping order.")
-                    # --- ADDED: Load leverage parameters from config ---
+                    continue
-                    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
 
-                    # --- State Machine Logic with Configurable Leverage ---
+                response = None
-                    if desired_signal == "BUY":
+                
-                        if not current_position:
+                if action == "market_open" or action == "market_close":
-                            if not all([size, leverage_long]):
+                    reduce_only = (action == "market_close")
-                                logging.error(f"[{name}] 'size' or 'leverage_long' not defined. Skipping.")
+                    log_action = "MARKET CLOSE" if reduce_only else "MARKET OPEN"
-                                continue
+                    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.")
+                            else:
-                            exchange_to_use.update_leverage(int(leverage_long), coin)
+                                logging.error(f"API Error for {action}: {response_data['statuses'][0]['error']}")
-                            exchange_to_use.market_open(coin, True, size, None, 0.01)
+                        else:
-                            self.managed_positions[name] = {"coin": coin, "side": "long", "size": size}
+                            logging.error(f"Unexpected API response format: {response}")
-                            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 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.")
+                elif action == "update_leverage":
-                            exchange_to_use.update_leverage(int(leverage_long), coin)
+                    leverage = int(size) 
-                            exchange_to_use.market_open(coin, True, current_position['size'] + size, None, 0.01)
+                    logging.warning(f"ACTION: UPDATE LEVERAGE {coin} to {leverage}x")
-                            self.managed_positions[name] = {"coin": coin, "side": "long", "size": size}
+                    response = exchange_to_use.update_leverage(leverage, coin)
-                            log_trade(strategy=name, coin=coin, action="CLOSE_SHORT_&_REVERSE", price=status.get('signal_price', 0), size=size, signal=desired_signal)
+                    logging.info(f"Update leverage response: {response}")
-                        
+                
-                    elif desired_signal == "SELL":
+                else:
-                        if not current_position:
+                    logging.warning(f"Received unknown action: {action}")
-                            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()
 
             except Exception as e:
-                logging.error(f"An error occurred in the main executor loop: {e}")
+                logging.error(f"An error occurred in the main executor loop: {e}", exc_info=True)
-
+                time.sleep(1)
-            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.")
 

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 <wallet_address>
+    
+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 📈" if size > 0 else "SHORT 📉"
+        side_color = "🟢" if size > 0 else "🔴"
+        
+        # PnL color
+        pnl_symbol = "🟢" if unrealized_pnl >= 0 else "🔴"
+        pnl_sign = "+" if unrealized_pnl >= 0 else ""
+        
+        # ROE color
+        roe_symbol = "🟢" if return_on_equity >= 0 else "🔴"
+        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"\n📊 POSITION DETAILS:")
+        print(f"   Size:                {abs(size):.6f} {coin}")
+        print(f"   Side:                {side}")
+        print(f"   Entry Price:         ${entry_px:,.4f}")
+        print(f"   Position Value:      ${abs(position_value):,.2f}")
+        
+        print(f"\n💰 PROFITABILITY:")
+        print(f"   Unrealized PnL:      {pnl_symbol} {pnl_sign}${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"\n⚙️ LEVERAGE & MARGIN:")
+        print(f"   Leverage Type:       {leverage_type.upper()}")
+        print(f"   Leverage:            {leverage_value}x")
+        print(f"   Margin Used:         ${margin_used:,.2f}")
+        
+        print(f"\n⚠️ 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 = "🟢" if abs(distance) > 20 else "🟡" if abs(distance) > 10 else "🔴"
+                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("📊 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"   ✓ Account Value: ${account_value:,.2f}")
+                print(f"   ✓ Total Margin Used: ${total_margin_used:,.2f}")
+                print(f"   ✓ Total Position Value: ${total_ntl_pos:,.2f}")
+                print(f"   ✓ Withdrawable: ${withdrawable:,.2f}")
+                print(f"   ✓ Open Positions: {len(positions)}")
+                
+                # Calculate margin utilization
+                if account_value > 0:
+                    margin_util = (total_margin_used / account_value) * 100
+                    util_symbol = "🟢" if margin_util < 50 else "🟡" if margin_util < 75 else "🔴"
+                    print(f"   ✓ 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("   ⚠ No perpetual positions found")
+            
+            return data
+        except Exception as e:
+            print(f"   ✗ 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("\n💰 Fetching Spot State...")
+        try:
+            data = self.info.spot_user_state(self.wallet_address)
+            
+            if data and data.get('balances'):
+                print(f"   ✓ 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("   ⚠ No spot holdings found")
+            
+            return data
+        except Exception as e:
+            print(f"   ✗ 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("\n📋 Fetching Open Orders...")
+        try:
+            data = self.info.open_orders(self.wallet_address)
+            
+            if data:
+                print(f"   ✓ 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("   ⚠ No open orders")
+            
+            return data
+        except Exception as e:
+            print(f"   ✗ 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"\n📈 Fetching Recent Fills (last {limit})...")
+        try:
+            data = self.info.user_fills(self.wallet_address)
+            
+            if data:
+                fills = data[:limit]
+                print(f"   ✓ 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"   ✓ Total Closed PnL: ${total_pnl:.2f}")
+                
+                # Show most recent
+                if fills:
+                    recent = fills[0]
+                    print(f"   ✓ Most Recent: {recent.get('coin')} {recent.get('side')} {recent.get('sz')} @ ${recent.get('px')}")
+            else:
+                print("   ⚠ No fills found")
+            
+            return data[:limit] if data else []
+        except Exception as e:
+            print(f"   ✗ 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"\n📅 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"   ✓ Fills in Range: {len(data)}")
+            else:
+                print("   ⚠ No fills in this time range")
+            
+            return data
+        except Exception as e:
+            print(f"   ✗ 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("\n💳 Fetching Fee Information...")
+        try:
+            data = self.info.user_fees(self.wallet_address)
+            
+            if data:
+                print(f"   ✓ Maker Fee: {data.get('userAddRate', 0)}%")
+                print(f"   ✓ Taker Fee: {data.get('userCrossRate', 0)}%")
+                print(f"   ✓ Daily Volume: ${data.get('dailyUserVlm', [0])[0] if data.get('dailyUserVlm') else 0}")
+            
+            return data
+        except Exception as e:
+            print(f"   ✗ 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("\n⏱️ 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"   ✓ API Requests: {used}/{cap}")
+                print(f"   ✓ Cumulative Volume: ${data.get('cumVlm', 0)}")
+            
+            return data
+        except Exception as e:
+            print(f"   ✗ 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"\n📊 Fetching Funding History for {coin}...")
+        try:
+            data = self.info.funding_history(coin, start_time, end_time)
+            
+            if data:
+                print(f"   ✓ Funding Entries: {len(data)}")
+                if data:
+                    latest = data[-1]
+                    print(f"   ✓ Latest Rate: {latest.get('fundingRate', 0)}")
+            
+            return data
+        except Exception as e:
+            print(f"   ✗ 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"\n💸 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"   ✓ Funding Payments: {len(data)}")
+                total_funding = sum(float(f.get('usdc', 0)) for f in data)
+                print(f"   ✓ Total Funding P&L: ${total_funding:.2f}")
+            else:
+                print("   ⚠ No funding payments found")
+            
+            return data
+        except Exception as e:
+            print(f"   ✗ 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"\n📒 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"   ✓ 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"   ✓ Deposits: {len(deposits)}, Withdrawals: {len(withdrawals)}")
+            else:
+                print("   ⚠ No ledger updates found")
+            
+            return data
+        except Exception as e:
+            print(f"   ✗ 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("\n🎁 Fetching Referral State...")
+        try:
+            data = self.info.query_referral_state(self.wallet_address)
+            
+            if data:
+                print(f"   ✓ Referral Code: {data.get('referralCode', 'N/A')}")
+                print(f"   ✓ Referees: {len(data.get('referees', []))}")
+            
+            return data
+        except Exception as e:
+            print(f"   ✗ Error: {e}")
+            return {}
+    
+    def get_sub_accounts(self) -> list:
+        """
+        Get list of sub-accounts for the user.
+        
+        Returns:
+            List of sub-account addresses
+        """
+        print("\n👥 Fetching Sub-Accounts...")
+        try:
+            data = self.info.query_sub_accounts(self.wallet_address)
+            
+            if data:
+                print(f"   ✓ Sub-Accounts: {len(data)}")
+            else:
+                print("   ⚠ No sub-accounts found")
+            
+            return data
+        except Exception as e:
+            print(f"   ✗ 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"\n💾 Data saved to: {filename}")
+        
+        return all_data
+
+
+def main():
+    """Main execution function."""
+    if len(sys.argv) < 2:
+        print("Usage: python hyperliquid_wallet_data.py <wallet_address> [--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("❌ 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("\n✅ All data fetched successfully!")
+        print(f"\n📊 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"\n❌ Fatal Error: {e}")
+        import traceback
+        traceback.print_exc()
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()

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)
+