#!/usr/bin/env python3
"""
Basic Usage Example for Market Trends Scraper

This script demonstrates how to use the Market Trends Scraper
to collect and analyze pricing data from e-commerce websites.
"""

import sys
from pathlib import Path

# Add src directory to Python path
sys.path.insert(0, str(Path(__file__).resolve().parent.parent / "src"))

from config_manager import ConfigManager
from scraper import MarketTrendsScraper
from logger import setup_logger


def main():
    """Main function demonstrating basic scraper usage."""
    
    # Setup logging
    setup_logger(verbose=True)
    
    # Initialize configuration manager
    config_manager = ConfigManager("../config/sample_config.yaml")
    
    # Load configuration
    try:
        config = config_manager.load_config()
        print("✓ Configuration loaded successfully")
    except Exception as e:
        print(f"✗ Failed to load configuration: {str(e)}")
        return 1
    
    # Initialize scraper
    try:
        scraper = MarketTrendsScraper(config, headless=True)
        print("✓ Scraper initialized successfully")
    except Exception as e:
        print(f"✗ Failed to initialize scraper: {str(e)}")
        return 1
    
    try:
        # Scrape market trends data
        print("\n🔍 Scraping market trends data...")
        data = scraper.scrape_market_trends()
        print(f"✓ Scraped {len(data)} product records")
        
        if not data:
            print("⚠ No data was scraped. Check your configuration and selectors.")
            return 0
        
        # Save scraped data
        output_file = "../data/example_output.csv"
        scraper.save_data(data, output_file)
        print(f"✓ Data saved to {output_file}")
        
        # Analyze trends
        print("\n📊 Analyzing market trends...")
        analysis = scraper.analyze_trends(data)
        print("✓ Trend analysis completed")
        
        # Save analysis results
        analysis_file = "../data/example_analysis.json"
        scraper.save_analysis(analysis, analysis_file)
        print(f"✓ Analysis saved to {analysis_file}")
        
        # Print summary
        print("\n📋 Summary:")
        print(f"  - Total products: {analysis.get('total_products', 0)}")
        
        if 'price_analysis' in analysis:
            price_analysis = analysis['price_analysis']
            print(f"  - Average price: ${price_analysis.get('average_price', 0):.2f}")
            print(f"  - Price range: ${price_analysis.get('min_price', 0):.2f} - ${price_analysis.get('max_price', 0):.2f}")
        
        if 'sources' in analysis:
            print("  - Products by source:")
            for source, count in analysis['sources'].items():
                print(f"    * {source}: {count} products")
        
        print("\n✅ Market trends analysis completed successfully!")
        return 0
        
    except Exception as e:
        print(f"✗ Error during scraping: {str(e)}")
        return 1
    
    finally:
        # Close scraper
        scraper.close()


if __name__ == "__main__":
    sys.exit(main())