Complete refactoring of the search module for robustness and reliability:
**New Architecture:**
- Modular parser system with specialized parsers for each major site
- Factory pattern for automatic parser selection
- Generic fallback parser for sites without specific implementation
**Specialized Parsers:**
- ✅ Amazon.fr - Robust parser with multiple fallback selectors
- Handles sponsored products, Prime eligibility, ratings, reviews
- Based on proven amazon_scraper_v2.py implementation
- ✅ Cdiscount.com - Optimized for Cdiscount's HTML structure
- ✅ Fnac.com - Handles Fnac's picture elements and article structure
- ✅ Darty.com - Specialized for electronics retailer
- ✅ Boulanger.com - Optimized for Boulanger's product cards
**Key Features:**
- Multiple fallback selectors for each element (title, price, image)
- Proper price parsing for French format (1 234,56 €)
- Rating and review count extraction
- Stock status detection
- Image URL extraction with multiple attribute fallbacks
- Query filtering to ensure relevant results
**Benefits:**
- Much more robust than previous generic parsing
- Easier to maintain (one parser per site)
- Easily extensible (add new parser for new site)
- Better error handling and logging
- Higher success rate for product extraction
**Updated Services:**
- improved_search_service.py now uses ParserFactory
- Legacy _parse_results marked as deprecated
- Conversion layer between ProductResult and SearchResult
This implements the Amazon France model across all major sites
for consistent, reliable product search results.
- Improved image extraction with multiple strategies (src, data-src, srcset, picture elements)
- Filter out placeholder and 1x1 pixel images
- Don't replace real images with non-existent screenshots
- Screenshots would need FastAPI static serving which is unnecessary
Claude
Michael