execution and training fixes
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Dobromir Popov
164
debug/test_fixed_issues.py
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164
debug/test_fixed_issues.py
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#!/usr/bin/env python3
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"""
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Test script to verify that both model prediction and trading statistics issues are fixed
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"""
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import sys
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import os
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sys.path.append(os.path.join(os.path.dirname(__file__), '..'))
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from core.orchestrator import TradingOrchestrator
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from core.data_provider import DataProvider
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from core.trading_executor import TradingExecutor
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import asyncio
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import logging
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# Set up logging
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logging.basicConfig(level=logging.INFO)
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logger = logging.getLogger(__name__)
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async def test_model_predictions():
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"""Test that model predictions are working correctly"""
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logger.info("=" * 60)
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logger.info("TESTING MODEL PREDICTIONS")
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logger.info("=" * 60)
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# Initialize components
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data_provider = DataProvider()
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orchestrator = TradingOrchestrator(data_provider)
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# Check model registration
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logger.info("1. Checking model registration...")
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models = orchestrator.model_registry.get_all_models()
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logger.info(f" Registered models: {list(models.keys()) if models else 'None'}")
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# Test making a decision
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logger.info("2. Testing trading decision generation...")
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decision = await orchestrator.make_trading_decision('ETH/USDT')
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if decision:
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logger.info(f" ✅ Decision generated: {decision.action} (confidence: {decision.confidence:.3f})")
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logger.info(f" ✅ Reasoning: {decision.reasoning}")
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return True
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else:
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logger.error(" ❌ No decision generated")
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return False
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def test_trading_statistics():
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"""Test that trading statistics calculations are working correctly"""
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logger.info("=" * 60)
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logger.info("TESTING TRADING STATISTICS")
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logger.info("=" * 60)
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# Initialize trading executor
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trading_executor = TradingExecutor()
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# Check if we have any trades
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trade_history = trading_executor.get_trade_history()
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logger.info(f"1. Current trade history: {len(trade_history)} trades")
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# Get daily stats
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daily_stats = trading_executor.get_daily_stats()
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logger.info("2. Daily statistics from trading executor:")
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logger.info(f" Total trades: {daily_stats.get('total_trades', 0)}")
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logger.info(f" Winning trades: {daily_stats.get('winning_trades', 0)}")
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logger.info(f" Losing trades: {daily_stats.get('losing_trades', 0)}")
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logger.info(f" Win rate: {daily_stats.get('win_rate', 0.0) * 100:.1f}%")
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logger.info(f" Avg winning trade: ${daily_stats.get('avg_winning_trade', 0.0):.2f}")
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logger.info(f" Avg losing trade: ${daily_stats.get('avg_losing_trade', 0.0):.2f}")
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logger.info(f" Total P&L: ${daily_stats.get('total_pnl', 0.0):.2f}")
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# Simulate some trades if we don't have any
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if daily_stats.get('total_trades', 0) == 0:
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logger.info("3. No trades found - simulating some test trades...")
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# Add some mock trades to the trade history
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from core.trading_executor import TradeRecord
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from datetime import datetime
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# Add a winning trade
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winning_trade = TradeRecord(
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symbol='ETH/USDT',
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side='LONG',
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quantity=0.01,
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entry_price=2500.0,
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exit_price=2550.0,
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entry_time=datetime.now(),
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exit_time=datetime.now(),
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pnl=0.50, # $0.50 profit
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fees=0.01,
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confidence=0.8
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)
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trading_executor.trade_history.append(winning_trade)
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# Add a losing trade
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losing_trade = TradeRecord(
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symbol='ETH/USDT',
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side='LONG',
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quantity=0.01,
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entry_price=2500.0,
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exit_price=2480.0,
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entry_time=datetime.now(),
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exit_time=datetime.now(),
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pnl=-0.20, # $0.20 loss
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fees=0.01,
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confidence=0.7
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)
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trading_executor.trade_history.append(losing_trade)
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# Get updated stats
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daily_stats = trading_executor.get_daily_stats()
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logger.info(" Updated statistics after adding test trades:")
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logger.info(f" Total trades: {daily_stats.get('total_trades', 0)}")
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logger.info(f" Winning trades: {daily_stats.get('winning_trades', 0)}")
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logger.info(f" Losing trades: {daily_stats.get('losing_trades', 0)}")
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logger.info(f" Win rate: {daily_stats.get('win_rate', 0.0) * 100:.1f}%")
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logger.info(f" Avg winning trade: ${daily_stats.get('avg_winning_trade', 0.0):.2f}")
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logger.info(f" Avg losing trade: ${daily_stats.get('avg_losing_trade', 0.0):.2f}")
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logger.info(f" Total P&L: ${daily_stats.get('total_pnl', 0.0):.2f}")
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# Verify calculations
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expected_win_rate = 1/2 # 1 win out of 2 trades = 50%
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expected_avg_win = 0.50
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expected_avg_loss = -0.20
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actual_win_rate = daily_stats.get('win_rate', 0.0)
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actual_avg_win = daily_stats.get('avg_winning_trade', 0.0)
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actual_avg_loss = daily_stats.get('avg_losing_trade', 0.0)
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logger.info("4. Verifying calculations:")
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logger.info(f" Win rate: Expected {expected_win_rate*100:.1f}%, Got {actual_win_rate*100:.1f}% ✅" if abs(actual_win_rate - expected_win_rate) < 0.01 else f" Win rate: Expected {expected_win_rate*100:.1f}%, Got {actual_win_rate*100:.1f}% ❌")
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logger.info(f" Avg win: Expected ${expected_avg_win:.2f}, Got ${actual_avg_win:.2f} ✅" if abs(actual_avg_win - expected_avg_win) < 0.01 else f" Avg win: Expected ${expected_avg_win:.2f}, Got ${actual_avg_win:.2f} ❌")
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logger.info(f" Avg loss: Expected ${expected_avg_loss:.2f}, Got ${actual_avg_loss:.2f} ✅" if abs(actual_avg_loss - expected_avg_loss) < 0.01 else f" Avg loss: Expected ${expected_avg_loss:.2f}, Got ${actual_avg_loss:.2f} ❌")
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return True
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return True
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async def main():
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"""Run all tests"""
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logger.info("🚀 STARTING COMPREHENSIVE FIXES TEST")
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logger.info("Testing both model prediction fixes and trading statistics fixes")
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# Test model predictions
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prediction_success = await test_model_predictions()
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# Test trading statistics
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stats_success = test_trading_statistics()
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logger.info("=" * 60)
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logger.info("TEST SUMMARY")
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logger.info("=" * 60)
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logger.info(f"Model Predictions: {'✅ FIXED' if prediction_success else '❌ STILL BROKEN'}")
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logger.info(f"Trading Statistics: {'✅ FIXED' if stats_success else '❌ STILL BROKEN'}")
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if prediction_success and stats_success:
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logger.info("🎉 ALL ISSUES FIXED! The system should now work correctly.")
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else:
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logger.error("❌ Some issues remain. Check the logs above for details.")
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if __name__ == "__main__":
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asyncio.run(main())
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