import asyncio
import logging
import os
import sys

# Add src to path
sys.path.append(os.path.join(os.path.dirname(__file__), '..'))

from src.data_collector.database import DatabaseManager
from src.data_collector.custom_timeframe_generator import CustomTimeframeGenerator

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

async def main():
    logger.info("Starting custom timeframe generation...")
    
    # DB connection settings from env or defaults
    db_host = os.getenv('DB_HOST', 'localhost')
    db_port = int(os.getenv('DB_PORT', 5432))
    db_name = os.getenv('DB_NAME', 'btc_data')
    db_user = os.getenv('DB_USER', 'btc_bot')
    db_password = os.getenv('DB_PASSWORD', '')
    
    db = DatabaseManager(
        host=db_host,
        port=db_port,
        database=db_name,
        user=db_user,
        password=db_password
    )
    
    await db.connect()
    
    try:
        generator = CustomTimeframeGenerator(db)
        await generator.initialize()
        
        # Generate 37m from 1m
        logger.info("Generating 37m candles from 1m data...")
        count_37m = await generator.generate_historical('37m')
        logger.info(f"Generated {count_37m} candles for 37m")
        
        # Generate 148m from 37m
        # Note: 148m generation relies on 37m data existing
        logger.info("Generating 148m candles from 37m data...")
        count_148m = await generator.generate_historical('148m')
        logger.info(f"Generated {count_148m} candles for 148m")
        
        logger.info("Done!")
        
    except Exception as e:
        logger.error(f"Error generating custom timeframes: {e}")
        import traceback
        traceback.print_exc()
    finally:
        await db.disconnect()

if __name__ == "__main__":
    asyncio.run(main())