from ETF_Portal.services.data_service import DataService
import logging
import json

# Set up logging
logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
)
logger = logging.getLogger(__name__)

def test_data_fetching():
    # Initialize service
    service = DataService()
    
    # Test portfolio
    portfolio = ['MSTY', 'FEPI', 'JEPI', 'VTI', 'VOO']
    
    for ticker in portfolio:
        print(f"\nTesting {ticker}:")
        print("=" * 50)
        
        try:
            # Get ETF data
            data = service.get_etf_data(ticker)
            
            # Print data source
            if data.get('is_estimated'):
                print("\nData Source: High Yield Estimates")
            elif 'info' in data and data['info']:
                print("\nData Source: FMP API")
            else:
                print("\nData Source: yfinance")
            
            # Print data structure
            print("\nData Structure:")
            for key, value in data.items():
                if isinstance(value, dict):
                    print(f"{key}: {len(value)} items")
                    if key == 'info' and value:
                        print("  Sample info fields:")
                        for k, v in list(value.items())[:5]:
                            print(f"    {k}: {v}")
                else:
                    print(f"{key}: {value}")
            
            # Print key metrics
            print("\nKey Metrics:")
            print(f"Volatility: {data.get('volatility', 'N/A')}")
            print(f"Max Drawdown: {data.get('max_drawdown', 'N/A')}")
            print(f"Sharpe Ratio: {data.get('sharpe_ratio', 'N/A')}")
            print(f"Sortino Ratio: {data.get('sortino_ratio', 'N/A')}")
            print(f"Dividend Trend: {data.get('dividend_trend', 'N/A')}")
            print(f"ETF Age: {data.get('age_years', 'N/A')} years")
            print(f"Is New ETF: {data.get('is_new', 'N/A')}")
            print(f"Is Estimated: {data.get('is_estimated', 'N/A')}")
            
            # Save raw data for inspection
            with open(f"{ticker}_data.json", 'w') as f:
                json.dump(data, f, indent=2)
            print(f"\nRaw data saved to {ticker}_data.json")
            
        except Exception as e:
            logger.error(f"Error testing {ticker}: {str(e)}")
            raise

if __name__ == "__main__":
    test_data_fetching()