#!/usr/bin/env python3
"""
Clean Main Entry Point for Enhanced Trading Dashboard

This is the main entry point that safely launches the clean dashboard
with proper error handling and optimized settings.
"""

import os
import sys
import logging
import argparse
from typing import Optional

# Add project root to path
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))

# Import core components
try:
    from core.config import setup_logging
    from core.data_provider import DataProvider
    from core.orchestrator import TradingOrchestrator
    from core.trading_executor import TradingExecutor
    from web.clean_dashboard import create_clean_dashboard
except ImportError as e:
    print(f"Error importing core modules: {e}")
    sys.exit(1)

logger = logging.getLogger(__name__)

def create_safe_orchestrator() -> Optional[TradingOrchestrator]:
    """Create orchestrator with safe CNN model handling"""
    try:
        # Create orchestrator with basic configuration (uses correct constructor parameters)
        orchestrator = TradingOrchestrator(
            enhanced_rl_training=False  # Disable problematic training initially
        )
        
        logger.info("Trading orchestrator created successfully")
        return orchestrator
        
    except Exception as e:
        logger.error(f"Error creating orchestrator: {e}")
        logger.info("Continuing without orchestrator - dashboard will run in view-only mode")
        return None

def create_safe_trading_executor() -> Optional[TradingExecutor]:
    """Create trading executor with safe configuration"""
    try:
        # TradingExecutor only accepts config_path parameter
        trading_executor = TradingExecutor(config_path="config.yaml")
        
        logger.info("Trading executor created successfully")
        return trading_executor
        
    except Exception as e:
        logger.error(f"Error creating trading executor: {e}")
        logger.info("Continuing without trading executor - dashboard will be view-only")
        return None

def main():
    """Main entry point for clean dashboard"""
    parser = argparse.ArgumentParser(description='Enhanced Trading Dashboard')
    parser.add_argument('--port', type=int, default=8050, help='Dashboard port (default: 8050)')
    parser.add_argument('--host', type=str, default='127.0.0.1', help='Dashboard host (default: 127.0.0.1)')
    parser.add_argument('--debug', action='store_true', help='Enable debug mode')
    parser.add_argument('--no-training', action='store_true', help='Disable ML training for stability')
    
    args = parser.parse_args()
    
    # Setup logging
    try:
        setup_logging()
        logger.info("================================================================================")
        logger.info("CLEAN ENHANCED TRADING DASHBOARD")
        logger.info("================================================================================")
        logger.info(f"Starting on http://{args.host}:{args.port}")
        logger.info("Features: Real-time Charts, Trading Interface, Model Monitoring")
        logger.info("================================================================================")
    except Exception as e:
        print(f"Error setting up logging: {e}")
        # Continue without logging setup
    
    # Set environment variables for optimization
    os.environ['ENABLE_REALTIME_CHARTS'] = '1'
    if not args.no_training:
        os.environ['ENABLE_NN_MODELS'] = '1'
    
    try:
        # Create data provider
        logger.info("Initializing data provider...")
        data_provider = DataProvider(symbols=['ETH/USDT', 'BTC/USDT'])
        
        # Create orchestrator (with safe CNN handling)
        logger.info("Initializing trading orchestrator...")
        orchestrator = create_safe_orchestrator()
        
        # Create trading executor
        logger.info("Initializing trading executor...")
        trading_executor = create_safe_trading_executor()
        
        # Create and run dashboard
        logger.info("Creating clean dashboard...")
        dashboard = create_clean_dashboard(
            data_provider=data_provider,
            orchestrator=orchestrator,
            trading_executor=trading_executor
        )
        
        # Start the dashboard server
        logger.info(f"Starting dashboard server on http://{args.host}:{args.port}")
        dashboard.run_server(
            host=args.host,
            port=args.port,
            debug=args.debug
        )
        
    except KeyboardInterrupt:
        logger.info("Dashboard stopped by user")
    except Exception as e:
        logger.error(f"Error running dashboard: {e}")
        
        # Try to provide helpful error message
        if "model.fit" in str(e) or "CNN" in str(e):
            logger.error("CNN model training error detected. Try running with --no-training flag")
            logger.error("Command: python main_clean.py --no-training")
        
        sys.exit(1)
    finally:
        logger.info("Clean dashboard shutdown complete")

if __name__ == '__main__':
    main()