Initial commit: Market Trends Scraper

examples/basic_usage.py

@@ -0,0 +1,97 @@
+#!/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())