Files
gogo2/run_realtime_rl_cob_trader.py
2025-06-24 19:07:42 +03:00

324 lines
13 KiB
Python

#!/usr/bin/env python3
"""
Real-time RL COB Trader Launcher
Launch script for the real-time reinforcement learning trader that:
1. Uses COB data for training a 1B parameter model
2. Performs inference every 200ms
3. Accumulates confident signals for trade execution
4. Trains continuously in real-time based on outcomes
This script provides a complete trading system integration.
"""
import asyncio
import logging
import signal
import sys
import json
import os
from datetime import datetime
from typing import Dict, Any, Optional
# Local imports
from core.realtime_rl_cob_trader import RealtimeRLCOBTrader
from core.trading_executor import TradingExecutor
from core.config import load_config
# Configure logging
logging.basicConfig(
level=logging.INFO,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
handlers=[
logging.FileHandler('logs/realtime_rl_cob_trader.log'),
logging.StreamHandler(sys.stdout)
]
)
logger = logging.getLogger(__name__)
class RealtimeRLCOBTraderLauncher:
"""
Launcher for Real-time RL COB Trader system
"""
def __init__(self, config_path: str = "config.yaml"):
"""Initialize launcher with configuration"""
self.config_path = config_path
self.config = load_config(config_path)
self.trader: Optional[RealtimeRLCOBTrader] = None
self.trading_executor: Optional[TradingExecutor] = None
self.running = False
# Setup signal handlers for graceful shutdown
signal.signal(signal.SIGINT, self._signal_handler)
signal.signal(signal.SIGTERM, self._signal_handler)
logger.info("RealtimeRLCOBTraderLauncher initialized")
def _signal_handler(self, signum, frame):
"""Handle shutdown signals"""
logger.info(f"Received signal {signum}, initiating graceful shutdown...")
self.running = False
async def start(self):
"""Start the real-time RL COB trading system"""
try:
logger.info("=" * 60)
logger.info("REAL-TIME RL COB TRADER SYSTEM STARTING")
logger.info("=" * 60)
# Initialize trading executor
await self._initialize_trading_executor()
# Initialize RL trader
await self._initialize_rl_trader()
# Start the trading system
await self._start_trading_system()
# Run main loop
await self._run_main_loop()
except Exception as e:
logger.error(f"Critical error in trader launcher: {e}")
raise
finally:
await self.stop()
async def _initialize_trading_executor(self):
"""Initialize the trading executor"""
logger.info("Initializing Trading Executor...")
# Get trading configuration
trading_config = self.config.get('trading', {})
mexc_config = self.config.get('mexc', {})
# Determine if we should run in simulation mode
simulation_mode = mexc_config.get('simulation_mode', True)
if simulation_mode:
logger.info("Running in SIMULATION mode - no real trades will be executed")
else:
logger.warning("Running in LIVE TRADING mode - real money at risk!")
# Add safety confirmation for live trading
confirmation = input("Type 'CONFIRM_LIVE_TRADING' to proceed with live trading: ")
if confirmation != 'CONFIRM_LIVE_TRADING':
logger.info("Live trading not confirmed, switching to simulation mode")
simulation_mode = True
# Initialize trading executor
self.trading_executor = TradingExecutor(self.config_path)
logger.info(f"Trading Executor initialized in {'SIMULATION' if simulation_mode else 'LIVE'} mode")
async def _initialize_rl_trader(self):
"""Initialize the RL trader"""
logger.info("Initializing Real-time RL COB Trader...")
# Get RL configuration
rl_config = self.config.get('realtime_rl', {})
# Trading symbols
symbols = rl_config.get('symbols', ['BTC/USDT', 'ETH/USDT'])
# RL parameters
inference_interval_ms = rl_config.get('inference_interval_ms', 200)
min_confidence_threshold = rl_config.get('min_confidence_threshold', 0.7)
required_confident_predictions = rl_config.get('required_confident_predictions', 3)
model_checkpoint_dir = rl_config.get('model_checkpoint_dir', 'models/realtime_rl_cob')
# Initialize RL trader
if self.trading_executor is None:
raise RuntimeError("Trading executor not initialized")
self.trader = RealtimeRLCOBTrader(
symbols=symbols,
trading_executor=self.trading_executor,
model_checkpoint_dir=model_checkpoint_dir,
inference_interval_ms=inference_interval_ms,
min_confidence_threshold=min_confidence_threshold,
required_confident_predictions=required_confident_predictions
)
logger.info(f"RL Trader initialized for symbols: {symbols}")
logger.info(f"Inference interval: {inference_interval_ms}ms")
logger.info(f"Confidence threshold: {min_confidence_threshold}")
logger.info(f"Required predictions: {required_confident_predictions}")
async def _start_trading_system(self):
"""Start the complete trading system"""
logger.info("Starting Real-time RL COB Trading System...")
# Start RL trader (this will start COB integration internally)
if self.trader is None:
raise RuntimeError("RL trader not initialized")
await self.trader.start()
self.running = True
logger.info("✅ Real-time RL COB Trading System started successfully!")
logger.info("🔥 1B parameter model training and inference active")
logger.info("📊 COB data streaming and processing")
logger.info("🎯 Signal accumulation and trade execution ready")
logger.info("⚡ Real-time training on prediction outcomes")
async def _run_main_loop(self):
"""Main monitoring and statistics loop"""
logger.info("Starting main monitoring loop...")
last_stats_time = datetime.now()
stats_interval = 60 # Print stats every 60 seconds
while self.running:
try:
# Sleep for a bit
await asyncio.sleep(10)
# Print periodic statistics
current_time = datetime.now()
if (current_time - last_stats_time).total_seconds() >= stats_interval:
await self._print_performance_stats()
last_stats_time = current_time
except asyncio.CancelledError:
break
except Exception as e:
logger.error(f"Error in main loop: {e}")
await asyncio.sleep(5)
logger.info("Main monitoring loop stopped")
async def _print_performance_stats(self):
"""Print comprehensive performance statistics"""
try:
if not self.trader:
return
stats = self.trader.get_performance_stats()
logger.info("=" * 80)
logger.info("🔥 REAL-TIME RL COB TRADER PERFORMANCE STATISTICS")
logger.info("=" * 80)
# Model information
logger.info("📊 Model Information:")
for symbol, model_info in stats.get('model_info', {}).items():
total_params = model_info.get('total_parameters', 0)
logger.info(f" {symbol}: {total_params:,} parameters ({total_params/1e9:.2f}B)")
# Training statistics
logger.info("\n🧠 Training Statistics:")
for symbol, training_stats in stats.get('training_stats', {}).items():
total_preds = training_stats.get('total_predictions', 0)
successful_preds = training_stats.get('successful_predictions', 0)
success_rate = (successful_preds / max(1, total_preds)) * 100
avg_loss = training_stats.get('average_loss', 0.0)
training_steps = training_stats.get('total_training_steps', 0)
last_training = training_stats.get('last_training_time')
logger.info(f" {symbol}:")
logger.info(f" Predictions: {total_preds} (Success: {success_rate:.1f}%)")
logger.info(f" Training Steps: {training_steps}")
logger.info(f" Average Loss: {avg_loss:.6f}")
if last_training:
logger.info(f" Last Training: {last_training}")
# Inference statistics
logger.info("\n⚡ Inference Statistics:")
for symbol, inference_stats in stats.get('inference_stats', {}).items():
total_inferences = inference_stats.get('total_inferences', 0)
avg_time = inference_stats.get('average_inference_time_ms', 0.0)
last_inference = inference_stats.get('last_inference_time')
logger.info(f" {symbol}:")
logger.info(f" Total Inferences: {total_inferences}")
logger.info(f" Average Time: {avg_time:.1f}ms")
if last_inference:
logger.info(f" Last Inference: {last_inference}")
# Signal statistics
logger.info("\n🎯 Signal Accumulation:")
for symbol, signal_stats in stats.get('signal_stats', {}).items():
current_signals = signal_stats.get('current_signals', 0)
confidence_sum = signal_stats.get('confidence_sum', 0.0)
success_rate = signal_stats.get('success_rate', 0.0) * 100
logger.info(f" {symbol}:")
logger.info(f" Current Signals: {current_signals}")
logger.info(f" Confidence Sum: {confidence_sum:.2f}")
logger.info(f" Historical Success Rate: {success_rate:.1f}%")
# Trading executor statistics
if self.trading_executor:
positions = self.trading_executor.get_positions()
trade_history = self.trading_executor.get_trade_history()
logger.info("\n💰 Trading Statistics:")
logger.info(f" Active Positions: {len(positions)}")
logger.info(f" Total Trades: {len(trade_history)}")
if trade_history:
# Calculate P&L statistics
total_pnl = sum(trade.pnl for trade in trade_history)
profitable_trades = sum(1 for trade in trade_history if trade.pnl > 0)
win_rate = (profitable_trades / len(trade_history)) * 100
logger.info(f" Total P&L: ${total_pnl:.2f}")
logger.info(f" Win Rate: {win_rate:.1f}%")
# Show active positions
if positions:
logger.info("\n📍 Active Positions:")
for symbol, position in positions.items():
logger.info(f" {symbol}: {position.side} {position.quantity:.6f} @ ${position.entry_price:.2f}")
logger.info("=" * 80)
except Exception as e:
logger.error(f"Error printing performance stats: {e}")
async def stop(self):
"""Stop the trading system gracefully"""
if not self.running:
return
logger.info("Stopping Real-time RL COB Trading System...")
self.running = False
# Stop RL trader
if self.trader:
await self.trader.stop()
logger.info("✅ RL Trader stopped")
# Print final statistics
if self.trader:
logger.info("\n📊 Final Performance Summary:")
await self._print_performance_stats()
logger.info("Real-time RL COB Trading System stopped successfully")
async def main():
"""Main entry point"""
try:
# Create logs directory if it doesn't exist
os.makedirs('logs', exist_ok=True)
# Initialize and start launcher
launcher = RealtimeRLCOBTraderLauncher()
await launcher.start()
except KeyboardInterrupt:
logger.info("Received keyboard interrupt, shutting down...")
except Exception as e:
logger.error(f"Critical error: {e}")
raise
if __name__ == "__main__":
# Set event loop policy for Windows compatibility
if hasattr(asyncio, 'WindowsProactorEventLoopPolicy'):
asyncio.set_event_loop_policy(asyncio.WindowsProactorEventLoopPolicy())
asyncio.run(main())