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https://github.com/R0m1k3/Priceflow.git
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Merge main: Resolved conflicts by keeping enhanced browserless service with auto-reconnection + price extraction
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+22
-4
@@ -133,13 +133,31 @@ class AIExtractionMetadata(BaseModel):
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EXTRACTION_PROMPT_TEMPLATE = """Extract product price and stock status from this French e-commerce page.
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**PRICE (IMPORTANT - French format):**
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- French prices use COMMA for decimals: "12,99 €" means 12.99
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- Thousands separator is SPACE or DOT: "1 234,56 €" or "1.234,56 €" means 1234.56
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- **FIRST**: Look for "PRIX DÉTECTÉ:" at the start of text - this is the extracted price
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- **The price has already been converted to English format for you**
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- French original: "3,99 €" → Already shown to you as: "3.99 €"
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- Just extract the number you see (e.g., "3.99" from "PRIX DÉTECTÉ: 3.99 €")
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- Currency symbol is usually € at the end
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- Look for: price tags, "Prix:", "€", numbers near "Ajouter au panier"
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- Extract as DECIMAL NUMBER (convert comma to dot): 12,99 -> 12.99
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- Look for: "PRIX DÉTECTÉ:", price tags, "Prix:", "€", numbers near "Ajouter au panier"
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- Extract as DECIMAL NUMBER: If you see "3.99", return 3.99
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- Ignore crossed-out/barré prices (old prices)
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- If multiple prices, take the current/main price (not the original)
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**CRITICAL - Common mistakes to avoid:**
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- "3.99 €" means 3.99 (NOT 399.00, NOT 3990.00)
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- "1.99 €" means 1.99 (NOT 199.00, NOT 1990.00)
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- "0.99 €" means 0.99 (NOT 99.00, NOT 990.00)
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- The decimal point separates euros from cents
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- Small prices (< 10€) are very common for everyday items
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- Examples of valid prices:
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* "PRIX DÉTECTÉ: 1.99 €" -> 1.99 (NOT 199 or 1990)
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* "PRIX DÉTECTÉ: 3.99 €" -> 3.99 (NOT 399 or 3990)
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* "0.99 €" -> 0.99 (NOT 99)
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* "89.99 €" -> 89.99 (NOT 8999)
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* "1234.56 €" -> 1234.56
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- If you find ANY price with € symbol, extract it with confidence >= 0.8
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- If digits are unclear or blurry, reduce confidence to 0.5-0.7
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- If unclear: set null and confidence < 0.5
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**STOCK:**
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+19
-4
@@ -13,14 +13,16 @@ from sqlalchemy import text
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from app.database import SessionLocal, engine
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from app.limiter import limiter
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from app.routers import auth, items, jobs, notifications, openrouter, search, search_sites, settings, debug, catalogues
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from app.routers import auth, items, jobs, notifications, openrouter, search, search_sites, settings, debug, catalogues, amazon
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from app.services.scheduler_service import scheduled_refresh, scheduler
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from app.services import auth_service, search_service, seed_enseignes
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from app.services.scheduler import start_scheduler as start_catalog_scheduler, stop_scheduler as stop_catalog_scheduler
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from app.services.amazon_scraper_service import amazon_scraper_service
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from app.services.improved_search_service import improved_search_service
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# Configure logging
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logging.basicConfig(
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level=os.getenv("LOG_LEVEL", "INFO").upper(),
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level=os.getenv("LOG_LEVEL", "DEBUG").upper(), # Temporarily DEBUG for Amazon debugging
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format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
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)
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logger = logging.getLogger(__name__)
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@@ -139,12 +141,22 @@ async def lifespan(app: FastAPI):
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# Start catalog scraping scheduler
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logger.info("Starting catalog scraping scheduler (6h and 18h daily)")
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start_catalog_scheduler()
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# Initialize Amazon scraper service
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logger.info("Initializing Amazon scraper service...")
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await amazon_scraper_service.initialize()
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# Initialize Improved Search Service (persistent browser for Search/Comparatif)
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logger.info("Initializing Improved Search Service...")
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await improved_search_service.initialize()
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logger.info("Application started")
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yield
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logger.info("Shutting down schedulers...")
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logger.info("Shutting down schedulers and services...")
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scheduler.shutdown(wait=True)
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stop_catalog_scheduler()
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await amazon_scraper_service.shutdown()
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await improved_search_service.shutdown()
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logger.info("Application shutdown complete")
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@@ -190,6 +202,9 @@ app.include_router(catalogues.router)
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# Auth router (already has /api prefix)
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app.include_router(auth.router)
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# Amazon router (already has /api prefix)
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app.include_router(amazon.router)
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@app.get("/api/")
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def read_root():
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@@ -0,0 +1,121 @@
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"""
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API Router pour la recherche Amazon France
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Utilise Server-Sent Events (SSE) pour le streaming des résultats
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Uses Browserless service for reliable scraping
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"""
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import json
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import logging
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from typing import AsyncGenerator
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from fastapi import APIRouter, Query
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from fastapi.responses import StreamingResponse
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from pydantic import BaseModel
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from app.services.amazon_scraper_service import amazon_scraper_service, AmazonProduct
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logger = logging.getLogger(__name__)
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router = APIRouter(prefix="/api/amazon", tags=["amazon"])
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class AmazonSearchProgress(BaseModel):
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"""Progress model for SSE streaming"""
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status: str # 'searching', 'completed', 'error'
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total: int
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completed: int
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message: str
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results: list[dict]
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@router.get("/search")
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async def search_amazon(
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q: str = Query(..., min_length=1, description="Terme de recherche"),
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max_results: int = Query(20, ge=1, le=50, description="Nombre max de résultats"),
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):
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"""
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Recherche de produits sur Amazon France.
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Retourne un flux SSE avec les résultats.
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Format des événements SSE:
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- event: progress
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- data: {"status": "...", "total": 1, "completed": 0/1, "results": [...]}
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"""
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async def generate() -> AsyncGenerator[str, None]:
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try:
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# Initial progress
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progress = AmazonSearchProgress(
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status="searching",
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total=1,
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completed=0,
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message=f"Recherche sur Amazon France: '{q}'...",
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results=[]
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)
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yield f"event: progress\ndata: {progress.model_dump_json()}\n\n"
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# Execute search with persistent browser service
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logger.info(f"Starting Amazon search for: {q}")
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products = await amazon_scraper_service.scrape_search(q, max_results=max_results)
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# Convert to dict
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results = [p.model_dump() for p in products]
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# Final progress
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if results:
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progress = AmazonSearchProgress(
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status="completed",
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total=1,
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completed=1,
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message=f"✅ {len(results)} produits trouvés",
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results=results
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)
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else:
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progress = AmazonSearchProgress(
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status="completed",
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total=1,
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completed=1,
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message="Aucun produit trouvé",
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results=[]
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)
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yield f"event: progress\ndata: {progress.model_dump_json()}\n\n"
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except Exception as e:
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logger.error(f"Error during Amazon search: {e}", exc_info=True)
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error_progress = AmazonSearchProgress(
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status="error",
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total=1,
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completed=1,
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message=f"Erreur: {str(e)}",
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results=[]
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)
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yield f"event: progress\ndata: {error_progress.model_dump_json()}\n\n"
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return StreamingResponse(
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generate(),
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media_type="text/event-stream",
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headers={
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"Cache-Control": "no-cache",
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"Connection": "keep-alive",
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"X-Accel-Buffering": "no",
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},
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)
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@router.get("/health")
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async def amazon_health():
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"""Vérifie que le service Amazon est opérationnel"""
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return {
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"status": "ok",
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"service": "Amazon France Scraper",
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"anti_detection": "enabled",
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"features": [
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"User-Agent rotation",
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"Proxy rotation (10 proxies)",
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"Random delays",
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"Realistic headers",
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"Crawl4AI anti-detection"
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]
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}
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@@ -11,7 +11,7 @@ from fastapi.responses import StreamingResponse
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from sqlalchemy.orm import Session
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from app.database import get_db
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from app.services import search_service
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from app.services import improved_search_service
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logger = logging.getLogger(__name__)
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@@ -44,7 +44,7 @@ async def search_products(
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async def generate():
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try:
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async for progress in search_service.search_products(
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async for progress in improved_search_service.search_products(
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query=q,
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db=db,
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site_ids=site_ids,
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@@ -343,8 +343,22 @@ class AIService:
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if len(cleaned_text) > MAX_TEXT_LENGTH:
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cleaned_text = cleaned_text[:MAX_TEXT_LENGTH] + "...(truncated)"
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logger.info(f"Added text context (original: {len(page_text)}, cleaned: {len(cleaned_text)})")
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# Log first 500 chars of cleaned text to see what AI receives
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logger.info(f"Cleaned text preview: {cleaned_text[:500]!r}")
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# Extract all potential prices from text for debugging
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import re
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price_patterns = re.findall(r'\d+[,\.]\d{2}\s*€', cleaned_text)
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if price_patterns:
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logger.info(f"Prices found in text: {price_patterns[:10]}") # First 10 prices
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else:
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logger.warning("No prices found in text with € symbol")
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else:
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logger.warning("No page_text provided - AI will only use screenshot")
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prompt = get_extraction_prompt(cleaned_text if cleaned_text else None)
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# Log prompt preview
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logger.info(f"Prompt preview (first 300 chars): {prompt[:300]!r}")
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# Call LLM
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response_text = await cls.call_llm(prompt, data_url, config)
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@@ -0,0 +1,451 @@
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"""
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Amazon France Scraper Service - Powered by Crawl4AI
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Anti-bot detection techniques:
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- Realistic User-Agent rotation
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- Complete HTTP headers mimicking real browsers
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- Proxy rotation (10 residential proxies)
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- Random delays between requests
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- Browser fingerprint randomization
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- Cookie persistence
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- NetworkIdle waiting for complete page load
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"""
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import asyncio
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import hashlib
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import logging
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import random
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import re
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from datetime import datetime
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from typing import Any
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from urllib.parse import quote_plus
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from bs4 import BeautifulSoup
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from crawl4ai import AsyncWebCrawler, BrowserConfig, CrawlerRunConfig, CacheMode
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from pydantic import BaseModel, Field
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from app.core.search_config import AMAZON_PROXY_LIST_RAW, USER_AGENT_POOL
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logger = logging.getLogger(__name__)
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# Amazon France configuration
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AMAZON_FR_BASE_URL = "https://www.amazon.fr"
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AMAZON_FR_SEARCH_URL = "https://www.amazon.fr/s?k={query}"
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# Additional realistic User-Agents specifically for Amazon
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AMAZON_USER_AGENTS = [
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"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36",
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"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36",
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"Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:133.0) Gecko/20100101 Firefox/133.0",
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"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/17.1 Safari/605.1.15",
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"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36 Edg/131.0.0.0",
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]
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# Realistic browser headers to avoid bot detection
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def get_realistic_headers(user_agent: str) -> dict:
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"""Generate realistic browser headers"""
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return {
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"Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8",
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"Accept-Language": "fr-FR,fr;q=0.9,en-US;q=0.8,en;q=0.7",
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"Accept-Encoding": "gzip, deflate, br",
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"DNT": "1",
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"Connection": "keep-alive",
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"Upgrade-Insecure-Requests": "1",
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"Sec-Fetch-Dest": "document",
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"Sec-Fetch-Mode": "navigate",
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"Sec-Fetch-Site": "none",
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"Sec-Fetch-User": "?1",
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"Cache-Control": "max-age=0",
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"User-Agent": user_agent,
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}
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def get_random_proxy() -> str | None:
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"""
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Get a random proxy from the pool in Crawl4AI format.
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Returns:
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Proxy string in format: http://username:password@ip:port
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"""
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if not AMAZON_PROXY_LIST_RAW:
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return None
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proxy_str = random.choice(AMAZON_PROXY_LIST_RAW)
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parts = proxy_str.split(":")
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if len(parts) == 4:
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ip = parts[0]
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port = parts[1]
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username = parts[2]
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password = parts[3]
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# Format: http://username:password@ip:port
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return f"http://{username}:{password}@{ip}:{port}"
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return None
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async def random_delay(min_seconds: float = 1.5, max_seconds: float = 4.0):
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"""Add random delay to mimic human behavior"""
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delay = random.uniform(min_seconds, max_seconds)
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logger.debug(f"Human-like delay: {delay:.2f}s")
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await asyncio.sleep(delay)
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# ============================================================================
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# PYDANTIC SCHEMAS
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# ============================================================================
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class AmazonProduct(BaseModel):
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"""Schema for Amazon product extraction"""
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title: str = Field(description="Product title")
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url: str = Field(description="Product URL")
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price: float | None = Field(default=None, description="Price in EUR")
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original_price: float | None = Field(default=None, description="Original price if discounted")
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rating: float | None = Field(default=None, description="Product rating (0-5)")
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reviews_count: int | None = Field(default=None, description="Number of reviews")
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image_url: str | None = Field(default=None, description="Product image URL")
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in_stock: bool = Field(default=True, description="Availability status")
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prime: bool = Field(default=False, description="Prime eligible")
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sponsored: bool = Field(default=False, description="Is sponsored")
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# ============================================================================
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# PRICE PARSING HELPERS
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# ============================================================================
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def parse_amazon_price(price_text: str) -> float | None:
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"""
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Parse Amazon price formats:
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- "12,99 €"
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- "12,99€"
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- "12.99 EUR"
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- "1 234,99 €"
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"""
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if not price_text:
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return None
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# Remove currency symbols and extra spaces
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cleaned = price_text.strip().replace('€', '').replace('EUR', '').strip()
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# Remove thousands separators (space or dot in French format)
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cleaned = cleaned.replace(' ', '').replace('\xa0', '') # \xa0 is non-breaking space
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# Replace comma with dot for decimal separator
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cleaned = cleaned.replace(',', '.')
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# Extract first number (in case of ranges like "12.99 - 15.99")
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match = re.search(r'(\d+\.?\d*)', cleaned)
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if match:
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try:
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return float(match.group(1))
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except ValueError:
|
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return None
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|
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return None
|
||||
|
||||
|
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def parse_rating(rating_text: str) -> float | None:
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"""Parse rating like '4,5 sur 5 étoiles' or '4.5 out of 5 stars'"""
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if not rating_text:
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return None
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# Match patterns like "4,5" or "4.5"
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match = re.search(r'(\d+[,.]\d+)', rating_text)
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if match:
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try:
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return float(match.group(1).replace(',', '.'))
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except ValueError:
|
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return None
|
||||
|
||||
return None
|
||||
|
||||
|
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def parse_reviews_count(reviews_text: str) -> int | None:
|
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"""Parse review count like '1 234' or '12,345'"""
|
||||
if not reviews_text:
|
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return None
|
||||
|
||||
# Remove non-digit characters except spaces
|
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cleaned = re.sub(r'[^\d\s]', '', reviews_text)
|
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cleaned = cleaned.replace(' ', '').replace('\xa0', '')
|
||||
|
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try:
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return int(cleaned)
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except ValueError:
|
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return None
|
||||
|
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|
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# ============================================================================
|
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# SCRAPING FUNCTIONS
|
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# ============================================================================
|
||||
|
||||
async def scrape_amazon_search(query: str, max_results: int = 20) -> list[AmazonProduct]:
|
||||
"""
|
||||
Scrape Amazon France search results for a given query.
|
||||
|
||||
Anti-detection features:
|
||||
1. Random User-Agent from realistic pool
|
||||
2. Complete browser headers
|
||||
3. Random proxy from pool
|
||||
4. Random delays between operations
|
||||
5. Browser fingerprint randomization via Crawl4AI
|
||||
6. NetworkIdle waiting
|
||||
7. Cookie handling
|
||||
|
||||
Args:
|
||||
query: Search query
|
||||
max_results: Maximum number of products to return (default 20)
|
||||
|
||||
Returns:
|
||||
List of AmazonProduct objects
|
||||
"""
|
||||
search_url = AMAZON_FR_SEARCH_URL.format(query=quote_plus(query))
|
||||
logger.info(f"🔍 Searching Amazon France: {query}")
|
||||
logger.info(f"📍 URL: {search_url}")
|
||||
|
||||
# Select random User-Agent
|
||||
user_agent = random.choice(AMAZON_USER_AGENTS)
|
||||
logger.debug(f"🎭 User-Agent: {user_agent[:50]}...")
|
||||
|
||||
# NOTE: Not using proxies here - Browserless service has its own proxy system
|
||||
# We can integrate with browserless_service later if needed
|
||||
|
||||
# Configure Crawl4AI browser with anti-detection
|
||||
browser_config = BrowserConfig(
|
||||
headless=True,
|
||||
verbose=False,
|
||||
user_agent=user_agent,
|
||||
# proxy_config removed - let Crawl4AI use default or integrate with Browserless later
|
||||
extra_args=[
|
||||
"--disable-blink-features=AutomationControlled", # Disable automation detection
|
||||
"--disable-dev-shm-usage",
|
||||
"--no-sandbox",
|
||||
"--disable-gpu",
|
||||
"--disable-setuid-sandbox",
|
||||
"--disable-web-security",
|
||||
"--disable-features=IsolateOrigins,site-per-process",
|
||||
"--disable-infobars",
|
||||
"--window-size=1920,1080",
|
||||
"--start-maximized",
|
||||
# Randomize viewport
|
||||
f"--user-agent={user_agent}",
|
||||
],
|
||||
)
|
||||
|
||||
# Configure crawler behavior
|
||||
crawler_config = CrawlerRunConfig(
|
||||
cache_mode=CacheMode.BYPASS, # Always fetch fresh data
|
||||
wait_for_images=True,
|
||||
process_iframes=False,
|
||||
remove_overlay_elements=True, # Remove popups/modals
|
||||
wait_until="networkidle", # Wait for all network requests
|
||||
delay_before_return_html=2.0, # Extra wait for JS rendering
|
||||
page_timeout=30000, # 30 seconds timeout
|
||||
# Accept cookies automatically
|
||||
js_code="""
|
||||
// Accept cookies if banner appears
|
||||
const cookieButton = document.querySelector('#sp-cc-accept, button[id*="accept"]');
|
||||
if (cookieButton) {
|
||||
cookieButton.click();
|
||||
}
|
||||
""",
|
||||
)
|
||||
|
||||
products = []
|
||||
|
||||
try:
|
||||
# Add human-like delay before request
|
||||
await random_delay(1.0, 2.5)
|
||||
|
||||
async with AsyncWebCrawler(config=browser_config) as crawler:
|
||||
logger.info("🚀 Launching browser...")
|
||||
result = await crawler.arun(url=search_url, config=crawler_config)
|
||||
|
||||
if not result.success:
|
||||
logger.error(f"❌ Crawl failed: {result.error_message}")
|
||||
return []
|
||||
|
||||
logger.info(f"✅ Page loaded successfully ({len(result.html)} bytes)")
|
||||
|
||||
# Parse HTML with BeautifulSoup
|
||||
soup = BeautifulSoup(result.html, 'html.parser')
|
||||
|
||||
# Debug: Save HTML to file for inspection
|
||||
debug_file = f"/tmp/amazon_debug_{query[:20]}.html"
|
||||
try:
|
||||
with open(debug_file, 'w', encoding='utf-8') as f:
|
||||
f.write(result.html)
|
||||
logger.debug(f"📝 HTML saved to {debug_file} for debugging")
|
||||
except Exception as e:
|
||||
logger.debug(f"Could not save debug HTML: {e}")
|
||||
|
||||
# Amazon uses data-component-type="s-search-result" for product cards
|
||||
product_cards = soup.find_all('div', {'data-component-type': 's-search-result'})
|
||||
|
||||
if not product_cards:
|
||||
logger.warning("⚠️ No products found - checking for CAPTCHA or blocks")
|
||||
# Check for CAPTCHA
|
||||
if 'captcha' in result.html.lower():
|
||||
logger.error("🚫 CAPTCHA detected - Amazon blocked the request")
|
||||
elif 'robot' in result.html.lower() or 'bot' in result.html.lower():
|
||||
logger.error("🤖 Bot detection triggered")
|
||||
else:
|
||||
logger.warning("📦 Empty results - query may have no matches")
|
||||
return []
|
||||
|
||||
logger.info(f"📦 Found {len(product_cards)} product cards")
|
||||
|
||||
for idx, card in enumerate(product_cards):
|
||||
if len(products) >= max_results:
|
||||
break
|
||||
|
||||
try:
|
||||
# Extract ASIN (Amazon Standard Identification Number)
|
||||
asin = card.get('data-asin', '')
|
||||
if not asin:
|
||||
logger.debug(f" ⏭️ Card {idx}: No ASIN found, skipping")
|
||||
continue
|
||||
|
||||
logger.debug(f" 🔍 Card {idx}: Processing ASIN {asin}")
|
||||
|
||||
# Check if sponsored
|
||||
sponsored = bool(card.select_one('[data-component-type="sp-sponsored-result"]'))
|
||||
|
||||
# Extract title
|
||||
title_elem = card.select_one('h2 a span, h2 span')
|
||||
if not title_elem:
|
||||
logger.debug(f" ⏭️ Card {idx} ({asin}): No title found, skipping")
|
||||
continue
|
||||
title = title_elem.get_text(strip=True)
|
||||
|
||||
# Extract URL
|
||||
link_elem = card.select_one('h2 a')
|
||||
if not link_elem:
|
||||
logger.debug(f" ⏭️ Card {idx} ({asin}): No link found, skipping")
|
||||
continue
|
||||
href = link_elem.get('href', '')
|
||||
product_url = f"{AMAZON_FR_BASE_URL}{href}" if href.startswith('/') else href
|
||||
|
||||
# Extract price
|
||||
price = None
|
||||
original_price = None
|
||||
|
||||
# Current price
|
||||
price_elem = card.select_one('.a-price .a-offscreen')
|
||||
if price_elem:
|
||||
price = parse_amazon_price(price_elem.get_text(strip=True))
|
||||
|
||||
# Original price (if discounted)
|
||||
original_price_elem = card.select_one('.a-price.a-text-price .a-offscreen')
|
||||
if original_price_elem:
|
||||
original_price = parse_amazon_price(original_price_elem.get_text(strip=True))
|
||||
|
||||
# Extract rating
|
||||
rating = None
|
||||
rating_elem = card.select_one('[aria-label*="étoile"], [aria-label*="star"]')
|
||||
if rating_elem:
|
||||
rating = parse_rating(rating_elem.get('aria-label', ''))
|
||||
|
||||
# Extract reviews count
|
||||
reviews_count = None
|
||||
reviews_elem = card.select_one('[aria-label*="étoile"] + span, [aria-label*="star"] + span')
|
||||
if reviews_elem:
|
||||
reviews_count = parse_reviews_count(reviews_elem.get_text(strip=True))
|
||||
|
||||
# Extract image
|
||||
image_url = None
|
||||
img_elem = card.select_one('img.s-image')
|
||||
if img_elem:
|
||||
image_url = img_elem.get('src') or img_elem.get('data-src')
|
||||
|
||||
# Check Prime eligibility
|
||||
prime = bool(card.select_one('[aria-label*="Prime"], i.a-icon-prime'))
|
||||
|
||||
# Check availability
|
||||
in_stock = True
|
||||
unavailable_elem = card.select_one('[aria-label*="Indisponible"], [aria-label*="Unavailable"]')
|
||||
if unavailable_elem:
|
||||
in_stock = False
|
||||
|
||||
product = AmazonProduct(
|
||||
title=title,
|
||||
url=product_url,
|
||||
price=price,
|
||||
original_price=original_price,
|
||||
rating=rating,
|
||||
reviews_count=reviews_count,
|
||||
image_url=image_url,
|
||||
in_stock=in_stock,
|
||||
prime=prime,
|
||||
sponsored=sponsored,
|
||||
)
|
||||
|
||||
products.append(product)
|
||||
logger.debug(f" ✓ [{idx+1}] {title[:50]}... - {price}€")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"❌ Error parsing product card {idx}: {e}")
|
||||
continue
|
||||
|
||||
logger.info(f"✅ Successfully extracted {len(products)} products")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"❌ Error during Amazon scraping: {e}", exc_info=True)
|
||||
return []
|
||||
|
||||
return products
|
||||
|
||||
|
||||
async def scrape_amazon_search_batched(
|
||||
query: str,
|
||||
max_results: int = 20,
|
||||
batch_size: int = 20
|
||||
) -> list[AmazonProduct]:
|
||||
"""
|
||||
Scrape Amazon with automatic pagination if needed.
|
||||
|
||||
Note: For now, we just scrape the first page (20 results).
|
||||
Pagination can be added later if needed.
|
||||
|
||||
Args:
|
||||
query: Search query
|
||||
max_results: Maximum total results (default 20)
|
||||
batch_size: Results per page (default 20)
|
||||
|
||||
Returns:
|
||||
List of AmazonProduct objects
|
||||
"""
|
||||
# For now, single page only
|
||||
return await scrape_amazon_search(query, max_results)
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# TESTING / VERIFICATION
|
||||
# ============================================================================
|
||||
|
||||
async def test_amazon_scraper():
|
||||
"""Test the Amazon scraper with a simple query"""
|
||||
logger.info("=" * 60)
|
||||
logger.info("Testing Amazon France Scraper")
|
||||
logger.info("=" * 60)
|
||||
|
||||
test_query = "aspirateur"
|
||||
products = await scrape_amazon_search(test_query, max_results=5)
|
||||
|
||||
logger.info(f"\n📊 Results for '{test_query}':")
|
||||
logger.info(f"Found {len(products)} products\n")
|
||||
|
||||
for idx, product in enumerate(products, 1):
|
||||
logger.info(f"{idx}. {product.title}")
|
||||
logger.info(f" 💰 Price: {product.price}€" + (f" (was {product.original_price}€)" if product.original_price else ""))
|
||||
logger.info(f" ⭐ Rating: {product.rating}/5 ({product.reviews_count} reviews)" if product.rating else " ⭐ No rating")
|
||||
logger.info(f" 🔗 {product.url}")
|
||||
logger.info(f" {'✅ Prime' if product.prime else '📦 Standard'} | {'📢 Sponsored' if product.sponsored else '🔍 Organic'}")
|
||||
logger.info("")
|
||||
|
||||
return products
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
# Run test
|
||||
asyncio.run(test_amazon_scraper())
|
||||
@@ -0,0 +1,430 @@
|
||||
"""
|
||||
Amazon Scraper Service - Using persistent browser connection
|
||||
Based on ScraperService pattern for better session management and anti-detection
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
import logging
|
||||
import os
|
||||
import re
|
||||
from dataclasses import dataclass
|
||||
from datetime import datetime
|
||||
from urllib.parse import quote_plus
|
||||
|
||||
from bs4 import BeautifulSoup
|
||||
from playwright.async_api import Browser, BrowserContext, Page, async_playwright
|
||||
from playwright.async_api import TimeoutError as PlaywrightTimeoutError
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
BROWSERLESS_URL = os.getenv("BROWSERLESS_URL", "ws://browserless:3000")
|
||||
|
||||
# Amazon configuration
|
||||
AMAZON_FR_BASE_URL = "https://www.amazon.fr"
|
||||
AMAZON_FR_SEARCH_URL = "https://www.amazon.fr/s?k={query}"
|
||||
|
||||
# Cookie/popup selectors for Amazon
|
||||
AMAZON_POPUP_SELECTORS = [
|
||||
"#sp-cc-accept", # Cookie banner
|
||||
"#sp-cc-rejectall-link",
|
||||
"button[data-action='a-popover-close']",
|
||||
"[data-action='sp-cc-accept']",
|
||||
"input[aria-labelledby='sp-cc-accept-label']",
|
||||
]
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# PYDANTIC SCHEMAS
|
||||
# ============================================================================
|
||||
|
||||
class AmazonProduct(BaseModel):
|
||||
"""Schema for Amazon product extraction"""
|
||||
title: str = Field(description="Product title")
|
||||
url: str = Field(description="Product URL")
|
||||
price: float | None = Field(default=None, description="Price in EUR")
|
||||
original_price: float | None = Field(default=None, description="Original price if discounted")
|
||||
rating: float | None = Field(default=None, description="Product rating (0-5)")
|
||||
reviews_count: int | None = Field(default=None, description="Number of reviews")
|
||||
image_url: str | None = Field(default=None, description="Product image URL")
|
||||
in_stock: bool = Field(default=True, description="Availability status")
|
||||
prime: bool = Field(default=False, description="Prime eligible")
|
||||
sponsored: bool = Field(default=False, description="Is sponsored")
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# PARSING HELPERS
|
||||
# ============================================================================
|
||||
|
||||
def parse_amazon_price(price_text: str) -> float | None:
|
||||
"""Parse Amazon price formats"""
|
||||
if not price_text:
|
||||
return None
|
||||
|
||||
cleaned = price_text.strip().replace('€', '').replace('EUR', '').strip()
|
||||
cleaned = cleaned.replace(' ', '').replace('\xa0', '')
|
||||
cleaned = cleaned.replace(',', '.')
|
||||
|
||||
match = re.search(r'(\d+\.?\d*)', cleaned)
|
||||
if match:
|
||||
try:
|
||||
return float(match.group(1))
|
||||
except ValueError:
|
||||
return None
|
||||
return None
|
||||
|
||||
|
||||
def parse_rating(rating_text: str) -> float | None:
|
||||
"""Parse rating"""
|
||||
if not rating_text:
|
||||
return None
|
||||
|
||||
match = re.search(r'(\d+[,.]\d+)', rating_text)
|
||||
if match:
|
||||
try:
|
||||
return float(match.group(1).replace(',', '.'))
|
||||
except ValueError:
|
||||
return None
|
||||
return None
|
||||
|
||||
|
||||
def parse_reviews_count(reviews_text: str) -> int | None:
|
||||
"""Parse review count"""
|
||||
if not reviews_text:
|
||||
return None
|
||||
|
||||
cleaned = re.sub(r'[^\d\s]', '', reviews_text)
|
||||
cleaned = cleaned.replace(' ', '').replace('\xa0', '')
|
||||
|
||||
try:
|
||||
return int(cleaned)
|
||||
except ValueError:
|
||||
return None
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# AMAZON SCRAPER SERVICE
|
||||
# ============================================================================
|
||||
|
||||
class AmazonScraperService:
|
||||
"""Persistent browser service for Amazon scraping"""
|
||||
|
||||
_playwright = None
|
||||
_browser: Browser | None = None
|
||||
_lock = asyncio.Lock()
|
||||
|
||||
@classmethod
|
||||
async def initialize(cls):
|
||||
"""Initialize shared browser (Thread-Safe)"""
|
||||
async with cls._lock:
|
||||
await cls._initialize()
|
||||
|
||||
@classmethod
|
||||
async def _initialize(cls):
|
||||
"""Internal initialization"""
|
||||
if cls._browser is None:
|
||||
logger.info("Initializing AmazonScraperService shared browser...")
|
||||
cls._playwright = await async_playwright().start()
|
||||
cls._browser = await cls._connect_browser(cls._playwright)
|
||||
logger.info("AmazonScraperService initialized.")
|
||||
|
||||
@classmethod
|
||||
async def shutdown(cls):
|
||||
"""Shutdown shared browser"""
|
||||
async with cls._lock:
|
||||
if cls._browser:
|
||||
logger.info("Shutting down AmazonScraperService...")
|
||||
await cls._browser.close()
|
||||
cls._browser = None
|
||||
if cls._playwright:
|
||||
await cls._playwright.stop()
|
||||
cls._playwright = None
|
||||
logger.info("AmazonScraperService shutdown complete.")
|
||||
|
||||
@classmethod
|
||||
async def _ensure_browser_connected(cls) -> bool:
|
||||
"""Ensure browser is connected, reconnect if needed"""
|
||||
async with cls._lock:
|
||||
try:
|
||||
if cls._browser is None:
|
||||
logger.warning("Browser not initialized, initializing...")
|
||||
await cls._initialize()
|
||||
return cls._browser is not None
|
||||
|
||||
# Test connection
|
||||
try:
|
||||
test_context = await cls._browser.new_context()
|
||||
await test_context.close()
|
||||
return True
|
||||
except Exception as e:
|
||||
logger.error(f"Browser connection test failed: {e}")
|
||||
logger.info("Attempting to reconnect...")
|
||||
cls._browser = None
|
||||
if cls._playwright:
|
||||
try:
|
||||
await cls._playwright.stop()
|
||||
except Exception:
|
||||
pass
|
||||
cls._playwright = None
|
||||
await cls._initialize()
|
||||
return cls._browser is not None
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to ensure browser connection: {e}")
|
||||
return False
|
||||
|
||||
@staticmethod
|
||||
async def _connect_browser(p) -> Browser:
|
||||
"""Connect to Browserless"""
|
||||
logger.info(f"Connecting to Browserless at {BROWSERLESS_URL}")
|
||||
return await p.chromium.connect_over_cdp(BROWSERLESS_URL)
|
||||
|
||||
@staticmethod
|
||||
async def _create_context(browser: Browser) -> BrowserContext:
|
||||
"""Create browser context with stealth settings"""
|
||||
context = await browser.new_context(
|
||||
viewport={"width": 1920, "height": 1080},
|
||||
user_agent=(
|
||||
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) "
|
||||
"AppleWebKit/537.36 (KHTML, like Gecko) "
|
||||
"Chrome/131.0.0.0 Safari/537.36"
|
||||
),
|
||||
locale="fr-FR",
|
||||
timezone_id="Europe/Paris",
|
||||
)
|
||||
|
||||
# Stealth mode
|
||||
await context.add_init_script("""
|
||||
Object.defineProperty(navigator, 'webdriver', { get: () => undefined });
|
||||
window.chrome = { runtime: {} };
|
||||
""")
|
||||
|
||||
await context.route("**/*", lambda route: route.continue_())
|
||||
return context
|
||||
|
||||
@staticmethod
|
||||
async def _handle_popups(page: Page):
|
||||
"""Close Amazon popups/cookies"""
|
||||
logger.info("Handling Amazon popups...")
|
||||
for selector in AMAZON_POPUP_SELECTORS:
|
||||
try:
|
||||
if await page.locator(selector).count() > 0:
|
||||
logger.info(f"Found popup: {selector}")
|
||||
await page.locator(selector).first.click(timeout=2000)
|
||||
await page.wait_for_timeout(1000)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
try:
|
||||
await page.keyboard.press("Escape")
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
@classmethod
|
||||
async def scrape_search(cls, query: str, max_results: int = 20) -> list[AmazonProduct]:
|
||||
"""
|
||||
Scrape Amazon France search results
|
||||
|
||||
Args:
|
||||
query: Search query
|
||||
max_results: Maximum products to return
|
||||
|
||||
Returns:
|
||||
List of AmazonProduct objects
|
||||
"""
|
||||
search_url = AMAZON_FR_SEARCH_URL.format(query=quote_plus(query))
|
||||
logger.info(f"🔍 Searching Amazon France: {query}")
|
||||
logger.info(f"📍 URL: {search_url}")
|
||||
|
||||
# Ensure browser is connected
|
||||
if not await cls._ensure_browser_connected():
|
||||
logger.error("Failed to establish browser connection")
|
||||
return []
|
||||
|
||||
products = []
|
||||
|
||||
try:
|
||||
context = await cls._create_context(cls._browser)
|
||||
page = await context.new_page()
|
||||
|
||||
try:
|
||||
# CRITICAL: Load Amazon homepage FIRST in same context to establish session
|
||||
logger.info("🏠 Loading Amazon homepage to establish session/cookies...")
|
||||
await page.goto("https://www.amazon.fr", wait_until="domcontentloaded", timeout=30000)
|
||||
logger.info("✅ Homepage loaded")
|
||||
|
||||
# Handle homepage popups
|
||||
await cls._handle_popups(page)
|
||||
|
||||
# Small delay
|
||||
await page.wait_for_timeout(2000)
|
||||
|
||||
# NOW navigate to search in SAME context (cookies preserved)
|
||||
logger.info(f"🔍 Navigating to search: {search_url}")
|
||||
await page.goto(search_url, wait_until="domcontentloaded", timeout=60000)
|
||||
logger.info("Page loaded (domcontentloaded)")
|
||||
|
||||
# Wait for network idle
|
||||
try:
|
||||
await page.wait_for_load_state("networkidle", timeout=10000)
|
||||
logger.info("Network idle reached")
|
||||
except PlaywrightTimeoutError:
|
||||
logger.info("Network idle timed out (non-critical)")
|
||||
|
||||
# Handle popups
|
||||
await cls._handle_popups(page)
|
||||
|
||||
# Wait a bit for content
|
||||
await page.wait_for_timeout(2000)
|
||||
|
||||
# Get HTML
|
||||
html_content = await page.content()
|
||||
logger.info(f"✅ Page content extracted ({len(html_content)} bytes)")
|
||||
|
||||
if len(html_content) < 10000:
|
||||
logger.error(f"❌ Page too small - likely blocked")
|
||||
return []
|
||||
|
||||
# Parse with BeautifulSoup
|
||||
soup = BeautifulSoup(html_content, 'html.parser')
|
||||
|
||||
# Find product cards
|
||||
product_cards = soup.find_all('div', {'data-component-type': 's-search-result'})
|
||||
|
||||
if not product_cards:
|
||||
# Try alternative
|
||||
product_cards = soup.find_all('div', {'data-asin': True, 'data-index': True})
|
||||
|
||||
if not product_cards:
|
||||
logger.warning("⚠️ No products found")
|
||||
# Check for blocks
|
||||
if '503' in html_content or 'robot' in html_content.lower():
|
||||
logger.error("🚫 Amazon blocked request")
|
||||
return []
|
||||
|
||||
logger.info(f"📦 Found {len(product_cards)} product cards")
|
||||
|
||||
# Extract products
|
||||
for idx, card in enumerate(product_cards):
|
||||
if len(products) >= max_results:
|
||||
break
|
||||
|
||||
try:
|
||||
product = cls._extract_product(card, idx)
|
||||
if product:
|
||||
products.append(product)
|
||||
logger.debug(f" ✓ [{len(products)}] {product.title[:50]}... - {product.price}€")
|
||||
except Exception as e:
|
||||
logger.error(f"Error parsing card {idx}: {e}")
|
||||
continue
|
||||
|
||||
logger.info(f"✅ Successfully extracted {len(products)} products")
|
||||
|
||||
finally:
|
||||
await context.close()
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"❌ Error during scraping: {e}", exc_info=True)
|
||||
return []
|
||||
|
||||
return products
|
||||
|
||||
@staticmethod
|
||||
def _extract_product(card, idx: int) -> AmazonProduct | None:
|
||||
"""Extract product data from card"""
|
||||
# ASIN
|
||||
asin = card.get('data-asin', '')
|
||||
if not asin:
|
||||
logger.debug(f" ⏭️ Card {idx}: No ASIN")
|
||||
return None
|
||||
|
||||
# Sponsored
|
||||
sponsored = bool(card.select_one('[data-component-type="sp-sponsored-result"]'))
|
||||
|
||||
# Title
|
||||
title = None
|
||||
for selector in ['h2 a span', 'h2 span', 'h2.s-line-clamp-2 span']:
|
||||
elem = card.select_one(selector)
|
||||
if elem:
|
||||
title = elem.get_text(strip=True)
|
||||
if title:
|
||||
break
|
||||
|
||||
if not title:
|
||||
logger.debug(f" ⏭️ Card {idx}: No title")
|
||||
return None
|
||||
|
||||
# URL
|
||||
link_elem = card.select_one('h2 a') or card.select_one('a.s-link-style')
|
||||
if not link_elem:
|
||||
logger.debug(f" ⏭️ Card {idx}: No link")
|
||||
return None
|
||||
|
||||
href = link_elem.get('href', '')
|
||||
product_url = f"{AMAZON_FR_BASE_URL}{href}" if href.startswith('/') else href
|
||||
|
||||
# Price
|
||||
price = None
|
||||
for selector in ['.a-price .a-offscreen', '.a-price-whole', 'span.a-price span.a-offscreen']:
|
||||
elem = card.select_one(selector)
|
||||
if elem:
|
||||
price = parse_amazon_price(elem.get_text(strip=True))
|
||||
if price:
|
||||
break
|
||||
|
||||
# Original price
|
||||
original_price = None
|
||||
elem = card.select_one('.a-price.a-text-price .a-offscreen')
|
||||
if elem:
|
||||
original_price = parse_amazon_price(elem.get_text(strip=True))
|
||||
|
||||
# Rating
|
||||
rating = None
|
||||
for selector in ['[aria-label*="étoile"]', '[aria-label*="star"]']:
|
||||
elem = card.select_one(selector)
|
||||
if elem:
|
||||
rating = parse_rating(elem.get('aria-label', ''))
|
||||
if rating:
|
||||
break
|
||||
|
||||
# Reviews
|
||||
reviews_count = None
|
||||
for selector in ['[aria-label*="étoile"] + span', 'span.s-underline-text']:
|
||||
elem = card.select_one(selector)
|
||||
if elem:
|
||||
reviews_count = parse_reviews_count(elem.get_text(strip=True))
|
||||
if reviews_count:
|
||||
break
|
||||
|
||||
# Image
|
||||
image_url = None
|
||||
for selector in ['img.s-image', 'img']:
|
||||
elem = card.select_one(selector)
|
||||
if elem:
|
||||
image_url = elem.get('src') or elem.get('data-src')
|
||||
if image_url:
|
||||
break
|
||||
|
||||
# Prime
|
||||
prime = bool(card.select_one('[aria-label*="Prime"]') or card.select_one('i.a-icon-prime'))
|
||||
|
||||
# Stock
|
||||
in_stock = True
|
||||
if card.select_one('[aria-label*="Indisponible"]'):
|
||||
in_stock = False
|
||||
|
||||
return AmazonProduct(
|
||||
title=title,
|
||||
url=product_url,
|
||||
price=price,
|
||||
original_price=original_price,
|
||||
rating=rating,
|
||||
reviews_count=reviews_count,
|
||||
image_url=image_url,
|
||||
in_stock=in_stock,
|
||||
prime=prime,
|
||||
sponsored=sponsored,
|
||||
)
|
||||
|
||||
|
||||
# Global instance
|
||||
amazon_scraper_service = AmazonScraperService()
|
||||
@@ -0,0 +1,375 @@
|
||||
"""
|
||||
Amazon France Scraper - Using Browserless Service
|
||||
Uses the existing browserless_service with Playwright for reliable scraping
|
||||
"""
|
||||
|
||||
import logging
|
||||
import random
|
||||
import re
|
||||
from typing import Any
|
||||
from urllib.parse import quote_plus
|
||||
|
||||
from bs4 import BeautifulSoup
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
from app.services.browserless_service import browserless_service
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# Amazon France configuration
|
||||
AMAZON_FR_BASE_URL = "https://www.amazon.fr"
|
||||
AMAZON_FR_SEARCH_URL = "https://www.amazon.fr/s?k={query}"
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# PYDANTIC SCHEMAS
|
||||
# ============================================================================
|
||||
|
||||
class AmazonProduct(BaseModel):
|
||||
"""Schema for Amazon product extraction"""
|
||||
title: str = Field(description="Product title")
|
||||
url: str = Field(description="Product URL")
|
||||
price: float | None = Field(default=None, description="Price in EUR")
|
||||
original_price: float | None = Field(default=None, description="Original price if discounted")
|
||||
rating: float | None = Field(default=None, description="Product rating (0-5)")
|
||||
reviews_count: int | None = Field(default=None, description="Number of reviews")
|
||||
image_url: str | None = Field(default=None, description="Product image URL")
|
||||
in_stock: bool = Field(default=True, description="Availability status")
|
||||
prime: bool = Field(default=False, description="Prime eligible")
|
||||
sponsored: bool = Field(default=False, description="Is sponsored")
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# PRICE PARSING HELPERS
|
||||
# ============================================================================
|
||||
|
||||
def parse_amazon_price(price_text: str) -> float | None:
|
||||
"""
|
||||
Parse Amazon price formats:
|
||||
- "12,99 €"
|
||||
- "12,99€"
|
||||
- "12.99 EUR"
|
||||
- "1 234,99 €"
|
||||
"""
|
||||
if not price_text:
|
||||
return None
|
||||
|
||||
# Remove currency symbols and extra spaces
|
||||
cleaned = price_text.strip().replace('€', '').replace('EUR', '').strip()
|
||||
|
||||
# Remove thousands separators (space or dot in French format)
|
||||
cleaned = cleaned.replace(' ', '').replace('\xa0', '') # \xa0 is non-breaking space
|
||||
|
||||
# Replace comma with dot for decimal separator
|
||||
cleaned = cleaned.replace(',', '.')
|
||||
|
||||
# Extract first number (in case of ranges like "12.99 - 15.99")
|
||||
match = re.search(r'(\d+\.?\d*)', cleaned)
|
||||
if match:
|
||||
try:
|
||||
return float(match.group(1))
|
||||
except ValueError:
|
||||
return None
|
||||
|
||||
return None
|
||||
|
||||
|
||||
def parse_rating(rating_text: str) -> float | None:
|
||||
"""Parse rating like '4,5 sur 5 étoiles' or '4.5 out of 5 stars'"""
|
||||
if not rating_text:
|
||||
return None
|
||||
|
||||
# Match patterns like "4,5" or "4.5"
|
||||
match = re.search(r'(\d+[,.]\d+)', rating_text)
|
||||
if match:
|
||||
try:
|
||||
return float(match.group(1).replace(',', '.'))
|
||||
except ValueError:
|
||||
return None
|
||||
|
||||
return None
|
||||
|
||||
|
||||
def parse_reviews_count(reviews_text: str) -> int | None:
|
||||
"""Parse review count like '1 234' or '12,345'"""
|
||||
if not reviews_text:
|
||||
return None
|
||||
|
||||
# Remove non-digit characters except spaces
|
||||
cleaned = re.sub(r'[^\d\s]', '', reviews_text)
|
||||
cleaned = cleaned.replace(' ', '').replace('\xa0', '')
|
||||
|
||||
try:
|
||||
return int(cleaned)
|
||||
except ValueError:
|
||||
return None
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# SCRAPING FUNCTIONS
|
||||
# ============================================================================
|
||||
|
||||
async def scrape_amazon_search(query: str, max_results: int = 20) -> list[AmazonProduct]:
|
||||
"""
|
||||
Scrape Amazon France search results using Browserless service.
|
||||
|
||||
Args:
|
||||
query: Search query
|
||||
max_results: Maximum number of products to return (default 20)
|
||||
|
||||
Returns:
|
||||
List of AmazonProduct objects
|
||||
"""
|
||||
search_url = AMAZON_FR_SEARCH_URL.format(query=quote_plus(query))
|
||||
logger.info(f"🔍 Searching Amazon France: {query}")
|
||||
logger.info(f"📍 URL: {search_url}")
|
||||
|
||||
products = []
|
||||
|
||||
try:
|
||||
# STRATEGY: Load Amazon homepage FIRST to establish session/cookies
|
||||
# Then do the search - appears more human-like
|
||||
logger.info("🏠 Loading Amazon homepage first to establish session...")
|
||||
home_html, _ = await browserless_service.get_page_content(
|
||||
url="https://www.amazon.fr",
|
||||
use_proxy=False,
|
||||
wait_selector=None,
|
||||
extract_text=False
|
||||
)
|
||||
|
||||
if not home_html or len(home_html) < 10000:
|
||||
logger.warning(f"⚠️ Homepage load failed ({len(home_html) if home_html else 0} bytes)")
|
||||
else:
|
||||
logger.info(f"✅ Homepage loaded ({len(home_html)} bytes) - cookies established")
|
||||
|
||||
# Small delay to appear more human
|
||||
import asyncio
|
||||
await asyncio.sleep(2)
|
||||
|
||||
# NOW do the search
|
||||
logger.info("🚀 Fetching search page with Browserless (NO PROXY)...")
|
||||
html_content, _ = await browserless_service.get_page_content(
|
||||
url=search_url,
|
||||
use_proxy=False, # Try without proxy first
|
||||
wait_selector=None, # Let it load naturally
|
||||
extract_text=False # We want HTML for parsing
|
||||
)
|
||||
|
||||
if not html_content or len(html_content) < 10000:
|
||||
logger.error(f"❌ Page too small ({len(html_content)} bytes) - likely blocked or empty")
|
||||
return []
|
||||
|
||||
logger.info(f"✅ Page loaded successfully ({len(html_content)} bytes)")
|
||||
|
||||
# Debug: Save HTML to file for inspection
|
||||
debug_file = f"/tmp/amazon_debug_{query[:20]}.html"
|
||||
try:
|
||||
with open(debug_file, 'w', encoding='utf-8') as f:
|
||||
f.write(html_content)
|
||||
logger.debug(f"📝 HTML saved to {debug_file} for debugging")
|
||||
except Exception as e:
|
||||
logger.debug(f"Could not save debug HTML: {e}")
|
||||
|
||||
# Parse HTML with BeautifulSoup
|
||||
soup = BeautifulSoup(html_content, 'html.parser')
|
||||
|
||||
# Amazon uses data-component-type="s-search-result" for product cards
|
||||
product_cards = soup.find_all('div', {'data-component-type': 's-search-result'})
|
||||
|
||||
if not product_cards:
|
||||
logger.warning("⚠️ No products found with primary selector")
|
||||
# Try alternative selector
|
||||
product_cards = soup.find_all('div', {'data-asin': True, 'data-index': True})
|
||||
if product_cards:
|
||||
logger.info(f"✓ Found {len(product_cards)} cards with alternative selector")
|
||||
|
||||
if not product_cards:
|
||||
logger.warning("⚠️ No products found - checking for CAPTCHA or blocks")
|
||||
# Check for CAPTCHA
|
||||
if 'captcha' in html_content.lower():
|
||||
logger.error("🚫 CAPTCHA detected - Amazon blocked the request")
|
||||
elif 'robot' in html_content.lower() or 'bot' in html_content.lower():
|
||||
logger.error("🤖 Bot detection triggered")
|
||||
else:
|
||||
logger.warning("📦 Empty results - query may have no matches")
|
||||
return []
|
||||
|
||||
logger.info(f"📦 Found {len(product_cards)} product cards")
|
||||
|
||||
for idx, card in enumerate(product_cards):
|
||||
if len(products) >= max_results:
|
||||
break
|
||||
|
||||
try:
|
||||
# Extract ASIN (Amazon Standard Identification Number)
|
||||
asin = card.get('data-asin', '')
|
||||
if not asin:
|
||||
logger.debug(f" ⏭️ Card {idx}: No ASIN found, skipping")
|
||||
continue
|
||||
|
||||
logger.debug(f" 🔍 Card {idx}: Processing ASIN {asin}")
|
||||
|
||||
# Check if sponsored
|
||||
sponsored = bool(card.select_one('[data-component-type="sp-sponsored-result"]'))
|
||||
|
||||
# Extract title - try multiple selectors
|
||||
title = None
|
||||
title_selectors = [
|
||||
'h2 a span',
|
||||
'h2 span',
|
||||
'h2.s-line-clamp-2 span',
|
||||
'.s-title-instructions-style span',
|
||||
]
|
||||
for selector in title_selectors:
|
||||
title_elem = card.select_one(selector)
|
||||
if title_elem:
|
||||
title = title_elem.get_text(strip=True)
|
||||
if title:
|
||||
break
|
||||
|
||||
if not title:
|
||||
logger.debug(f" ⏭️ Card {idx} ({asin}): No title found, skipping")
|
||||
continue
|
||||
|
||||
# Extract URL
|
||||
link_elem = card.select_one('h2 a')
|
||||
if not link_elem:
|
||||
# Try alternative
|
||||
link_elem = card.select_one('a.s-link-style')
|
||||
if not link_elem:
|
||||
logger.debug(f" ⏭️ Card {idx} ({asin}): No link found, skipping")
|
||||
continue
|
||||
|
||||
href = link_elem.get('href', '')
|
||||
product_url = f"{AMAZON_FR_BASE_URL}{href}" if href.startswith('/') else href
|
||||
|
||||
# Extract price
|
||||
price = None
|
||||
original_price = None
|
||||
|
||||
# Current price - try multiple selectors
|
||||
price_selectors = [
|
||||
'.a-price .a-offscreen',
|
||||
'.a-price-whole',
|
||||
'span.a-price span.a-offscreen',
|
||||
]
|
||||
for selector in price_selectors:
|
||||
price_elem = card.select_one(selector)
|
||||
if price_elem:
|
||||
price_text = price_elem.get_text(strip=True)
|
||||
price = parse_amazon_price(price_text)
|
||||
if price:
|
||||
break
|
||||
|
||||
# Original price (if discounted)
|
||||
original_price_elem = card.select_one('.a-price.a-text-price .a-offscreen')
|
||||
if original_price_elem:
|
||||
original_price = parse_amazon_price(original_price_elem.get_text(strip=True))
|
||||
|
||||
# Extract rating
|
||||
rating = None
|
||||
rating_selectors = [
|
||||
'[aria-label*="étoile"]',
|
||||
'[aria-label*="star"]',
|
||||
'i.a-icon-star-small span',
|
||||
]
|
||||
for selector in rating_selectors:
|
||||
rating_elem = card.select_one(selector)
|
||||
if rating_elem:
|
||||
aria_label = rating_elem.get('aria-label', '')
|
||||
if aria_label:
|
||||
rating = parse_rating(aria_label)
|
||||
if rating:
|
||||
break
|
||||
|
||||
# Extract reviews count
|
||||
reviews_count = None
|
||||
reviews_selectors = [
|
||||
'[aria-label*="étoile"] + span',
|
||||
'[aria-label*="star"] + span',
|
||||
'span.s-underline-text',
|
||||
]
|
||||
for selector in reviews_selectors:
|
||||
reviews_elem = card.select_one(selector)
|
||||
if reviews_elem:
|
||||
reviews_count = parse_reviews_count(reviews_elem.get_text(strip=True))
|
||||
if reviews_count:
|
||||
break
|
||||
|
||||
# Extract image
|
||||
image_url = None
|
||||
img_selectors = [
|
||||
'img.s-image',
|
||||
'img[data-image-latency="s-product-image"]',
|
||||
'img',
|
||||
]
|
||||
for selector in img_selectors:
|
||||
img_elem = card.select_one(selector)
|
||||
if img_elem:
|
||||
image_url = img_elem.get('src') or img_elem.get('data-src')
|
||||
if image_url:
|
||||
break
|
||||
|
||||
# Check Prime eligibility
|
||||
prime = bool(card.select_one('[aria-label*="Prime"]') or card.select_one('i.a-icon-prime'))
|
||||
|
||||
# Check availability
|
||||
in_stock = True
|
||||
unavailable_elem = card.select_one('[aria-label*="Indisponible"]') or card.select_one('[aria-label*="Unavailable"]')
|
||||
if unavailable_elem:
|
||||
in_stock = False
|
||||
|
||||
product = AmazonProduct(
|
||||
title=title,
|
||||
url=product_url,
|
||||
price=price,
|
||||
original_price=original_price,
|
||||
rating=rating,
|
||||
reviews_count=reviews_count,
|
||||
image_url=image_url,
|
||||
in_stock=in_stock,
|
||||
prime=prime,
|
||||
sponsored=sponsored,
|
||||
)
|
||||
|
||||
products.append(product)
|
||||
logger.debug(f" ✓ [{len(products)}] {title[:50]}... - {price}€")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"❌ Error parsing product card {idx}: {e}")
|
||||
continue
|
||||
|
||||
logger.info(f"✅ Successfully extracted {len(products)} products")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"❌ Error during Amazon scraping: {e}", exc_info=True)
|
||||
return []
|
||||
|
||||
return products
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# TESTING
|
||||
# ============================================================================
|
||||
|
||||
async def test_amazon_scraper():
|
||||
"""Test the Amazon scraper with a simple query"""
|
||||
logger.info("=" * 60)
|
||||
logger.info("Testing Amazon France Scraper (Browserless)")
|
||||
logger.info("=" * 60)
|
||||
|
||||
test_query = "aspirateur"
|
||||
products = await scrape_amazon_search(test_query, max_results=5)
|
||||
|
||||
logger.info(f"\n📊 Results for '{test_query}':")
|
||||
logger.info(f"Found {len(products)} products\n")
|
||||
|
||||
for idx, product in enumerate(products, 1):
|
||||
logger.info(f"{idx}. {product.title}")
|
||||
logger.info(f" 💰 Price: {product.price}€" + (f" (was {product.original_price}€)" if product.original_price else ""))
|
||||
logger.info(f" ⭐ Rating: {product.rating}/5 ({product.reviews_count} reviews)" if product.rating else " ⭐ No rating")
|
||||
logger.info(f" 🔗 {product.url}")
|
||||
logger.info(f" {'✅ Prime' if product.prime else '📦 Standard'} | {'📢 Sponsored' if product.sponsored else '🔍 Organic'}")
|
||||
logger.info("")
|
||||
|
||||
return products
|
||||
@@ -0,0 +1,643 @@
|
||||
"""
|
||||
Improved Search Service - Using Persistent Browser Connection
|
||||
Based on ScraperService pattern for better session management and reliability
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
import logging
|
||||
from typing import AsyncGenerator
|
||||
from urllib.parse import quote_plus, urljoin
|
||||
|
||||
from bs4 import BeautifulSoup
|
||||
from playwright.async_api import Browser, BrowserContext, Page, async_playwright
|
||||
from playwright.async_api import TimeoutError as PlaywrightTimeoutError
|
||||
from sqlalchemy.orm import Session
|
||||
|
||||
from app.core.search_config import SITE_CONFIGS, BROWSERLESS_URL
|
||||
from app.models import SearchSite
|
||||
from app.schemas import SearchProgress, SearchResultItem
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# Common popup/cookie selectors
|
||||
COMMON_POPUP_SELECTORS = [
|
||||
"#sp-cc-accept", # Cookie banner
|
||||
"#onetrust-accept-btn-handler", # OneTrust
|
||||
".cookie-consent-accept",
|
||||
"[data-action='accept-cookies']",
|
||||
"button[id*='accept']",
|
||||
"button[class*='accept']",
|
||||
]
|
||||
|
||||
|
||||
class SearchResult:
|
||||
"""Search result data class"""
|
||||
def __init__(
|
||||
self,
|
||||
url: str,
|
||||
title: str,
|
||||
snippet: str,
|
||||
source: str,
|
||||
price: float | None = None,
|
||||
currency: str = "EUR",
|
||||
in_stock: bool | None = None,
|
||||
image_url: str | None = None,
|
||||
):
|
||||
self.url = url
|
||||
self.title = title
|
||||
self.snippet = snippet
|
||||
self.source = source
|
||||
self.price = price
|
||||
self.currency = currency
|
||||
self.in_stock = in_stock
|
||||
self.image_url = image_url
|
||||
|
||||
def to_dict(self):
|
||||
return {
|
||||
"url": self.url,
|
||||
"title": self.title,
|
||||
"snippet": self.snippet,
|
||||
"source": self.source,
|
||||
"price": self.price,
|
||||
"currency": self.currency,
|
||||
"in_stock": self.in_stock,
|
||||
"image_url": self.image_url,
|
||||
}
|
||||
|
||||
|
||||
class ImprovedSearchService:
|
||||
"""Persistent browser service for e-commerce search scraping"""
|
||||
|
||||
_playwright = None
|
||||
_browser: Browser | None = None
|
||||
_lock = asyncio.Lock()
|
||||
|
||||
@classmethod
|
||||
async def initialize(cls):
|
||||
"""Initialize shared browser (Thread-Safe)"""
|
||||
async with cls._lock:
|
||||
await cls._initialize()
|
||||
|
||||
@classmethod
|
||||
async def _initialize(cls):
|
||||
"""Internal initialization"""
|
||||
if cls._browser is None:
|
||||
logger.info("Initializing ImprovedSearchService shared browser...")
|
||||
cls._playwright = await async_playwright().start()
|
||||
cls._browser = await cls._connect_browser(cls._playwright)
|
||||
logger.info("ImprovedSearchService initialized.")
|
||||
|
||||
@classmethod
|
||||
async def shutdown(cls):
|
||||
"""Shutdown shared browser"""
|
||||
async with cls._lock:
|
||||
if cls._browser:
|
||||
logger.info("Shutting down ImprovedSearchService...")
|
||||
await cls._browser.close()
|
||||
cls._browser = None
|
||||
if cls._playwright:
|
||||
await cls._playwright.stop()
|
||||
cls._playwright = None
|
||||
logger.info("ImprovedSearchService shutdown complete.")
|
||||
|
||||
@classmethod
|
||||
async def _ensure_browser_connected(cls) -> bool:
|
||||
"""Ensure browser is connected, reconnect if needed"""
|
||||
async with cls._lock:
|
||||
try:
|
||||
if cls._browser is None:
|
||||
logger.warning("Browser not initialized, initializing...")
|
||||
await cls._initialize()
|
||||
return cls._browser is not None
|
||||
|
||||
# Test connection
|
||||
try:
|
||||
test_context = await cls._browser.new_context()
|
||||
await test_context.close()
|
||||
return True
|
||||
except Exception as e:
|
||||
logger.error(f"Browser connection test failed: {e}")
|
||||
logger.info("Attempting to reconnect...")
|
||||
cls._browser = None
|
||||
if cls._playwright:
|
||||
try:
|
||||
await cls._playwright.stop()
|
||||
except Exception:
|
||||
pass
|
||||
cls._playwright = None
|
||||
await cls._initialize()
|
||||
return cls._browser is not None
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to ensure browser connection: {e}")
|
||||
return False
|
||||
|
||||
@staticmethod
|
||||
async def _connect_browser(p) -> Browser:
|
||||
"""Connect to Browserless"""
|
||||
logger.info(f"Connecting to Browserless at {BROWSERLESS_URL}")
|
||||
return await p.chromium.connect_over_cdp(BROWSERLESS_URL)
|
||||
|
||||
@staticmethod
|
||||
async def _create_context(browser: Browser) -> BrowserContext:
|
||||
"""Create browser context with stealth settings"""
|
||||
context = await browser.new_context(
|
||||
viewport={"width": 1920, "height": 1080},
|
||||
user_agent=(
|
||||
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) "
|
||||
"AppleWebKit/537.36 (KHTML, like Gecko) "
|
||||
"Chrome/131.0.0.0 Safari/537.36"
|
||||
),
|
||||
locale="fr-FR",
|
||||
timezone_id="Europe/Paris",
|
||||
)
|
||||
|
||||
# Stealth mode
|
||||
await context.add_init_script("""
|
||||
Object.defineProperty(navigator, 'webdriver', { get: () => undefined });
|
||||
window.chrome = { runtime: {} };
|
||||
""")
|
||||
|
||||
await context.route("**/*", lambda route: route.continue_())
|
||||
return context
|
||||
|
||||
@staticmethod
|
||||
async def _handle_popups(page: Page):
|
||||
"""Close common popups/cookies"""
|
||||
logger.debug("Handling popups...")
|
||||
for selector in COMMON_POPUP_SELECTORS:
|
||||
try:
|
||||
if await page.locator(selector).count() > 0:
|
||||
logger.debug(f"Found popup: {selector}")
|
||||
await page.locator(selector).first.click(timeout=2000)
|
||||
await page.wait_for_timeout(500)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
try:
|
||||
await page.keyboard.press("Escape")
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
@classmethod
|
||||
async def search_site(cls, site_key: str, query: str) -> list[SearchResult]:
|
||||
"""
|
||||
Search a single site using persistent browser
|
||||
|
||||
Args:
|
||||
site_key: Site configuration key
|
||||
query: Search query
|
||||
|
||||
Returns:
|
||||
List of SearchResult objects
|
||||
"""
|
||||
config = SITE_CONFIGS.get(site_key)
|
||||
if not config:
|
||||
logger.error(f"Unknown site: {site_key}")
|
||||
return []
|
||||
|
||||
search_url = config["search_url"].format(query=quote_plus(query))
|
||||
logger.info(f"🔍 Searching {config['name']} at {search_url}")
|
||||
|
||||
# Ensure browser is connected
|
||||
if not await cls._ensure_browser_connected():
|
||||
logger.error("Failed to establish browser connection")
|
||||
return []
|
||||
|
||||
results = []
|
||||
|
||||
try:
|
||||
context = await cls._create_context(cls._browser)
|
||||
page = await context.new_page()
|
||||
|
||||
try:
|
||||
# Navigate to search page
|
||||
logger.debug(f"Navigating to {search_url}")
|
||||
await page.goto(search_url, wait_until="domcontentloaded", timeout=30000)
|
||||
logger.debug("Page loaded (domcontentloaded)")
|
||||
|
||||
# Wait for network idle
|
||||
try:
|
||||
await page.wait_for_load_state("networkidle", timeout=10000)
|
||||
logger.debug("Network idle reached")
|
||||
except PlaywrightTimeoutError:
|
||||
logger.debug("Network idle timed out (non-critical)")
|
||||
|
||||
# Handle popups
|
||||
await cls._handle_popups(page)
|
||||
|
||||
# Wait for content to load
|
||||
wait_selector = config.get("wait_selector")
|
||||
if wait_selector:
|
||||
try:
|
||||
await page.wait_for_selector(wait_selector, timeout=5000)
|
||||
logger.debug(f"Wait selector found: {wait_selector}")
|
||||
except PlaywrightTimeoutError:
|
||||
logger.warning(f"Wait selector not found: {wait_selector}")
|
||||
|
||||
# Small delay for JS rendering
|
||||
await page.wait_for_timeout(2000)
|
||||
|
||||
# Get HTML content
|
||||
html_content = await page.content()
|
||||
logger.info(f"✅ Page content extracted ({len(html_content)} bytes)")
|
||||
|
||||
if len(html_content) < 5000:
|
||||
logger.warning(f"⚠️ Page too small - possibly blocked")
|
||||
return []
|
||||
|
||||
# Parse results
|
||||
results = cls._parse_results(html_content, site_key, search_url, query)
|
||||
|
||||
# Scrape details for each result (in parallel)
|
||||
if results:
|
||||
logger.info(f"📦 Found {len(results)} initial results, enriching with details...")
|
||||
semaphore = asyncio.Semaphore(2) # Limit concurrency
|
||||
|
||||
async def scrape_with_limit(res):
|
||||
async with semaphore:
|
||||
return await cls._scrape_item_details(res, context)
|
||||
|
||||
tasks = [scrape_with_limit(r) for r in results]
|
||||
enriched_results = await asyncio.gather(*tasks)
|
||||
results = [r for r in enriched_results if r] # Filter None
|
||||
|
||||
finally:
|
||||
await context.close()
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"❌ Error during search: {e}", exc_info=True)
|
||||
return []
|
||||
|
||||
logger.info(f"✅ Successfully found {len(results)} products from {config['name']}")
|
||||
return results
|
||||
|
||||
@staticmethod
|
||||
def _parse_results(html: str, site_key: str, base_url: str, query: str) -> list[SearchResult]:
|
||||
"""Parse HTML content to extract search results"""
|
||||
config = SITE_CONFIGS[site_key]
|
||||
soup = BeautifulSoup(html, "html.parser")
|
||||
results = []
|
||||
|
||||
# Prepare query words for filtering
|
||||
query_words = [w.lower() for w in query.split() if len(w) > 2]
|
||||
|
||||
# Select product links
|
||||
links = soup.select(config["product_selector"])
|
||||
|
||||
# Deduplicate links
|
||||
seen_urls = set()
|
||||
|
||||
for link in links:
|
||||
href = link.get("href")
|
||||
if not href:
|
||||
continue
|
||||
|
||||
full_url = urljoin(base_url, href)
|
||||
|
||||
# Basic cleanup
|
||||
if full_url in seen_urls:
|
||||
continue
|
||||
seen_urls.add(full_url)
|
||||
|
||||
# Extract title
|
||||
title = link.get_text(strip=True)
|
||||
|
||||
# If no text, check title attribute or nested image alt
|
||||
if not title:
|
||||
if link.get("title"):
|
||||
title = link.get("title")
|
||||
else:
|
||||
img = link.find("img")
|
||||
if img and img.get("alt"):
|
||||
title = img.get("alt")
|
||||
|
||||
if not title or len(title) < 3:
|
||||
continue
|
||||
|
||||
# STRICT FILTERING: Check if all query words are in the title
|
||||
title_lower = title.lower()
|
||||
if query_words:
|
||||
all_words_found = True
|
||||
for word in query_words:
|
||||
if word not in title_lower:
|
||||
all_words_found = False
|
||||
break
|
||||
|
||||
if not all_words_found:
|
||||
continue
|
||||
|
||||
# Extract Image URL - Multiple strategies
|
||||
image_url = None
|
||||
|
||||
# Strategy 1: Look for img directly in the link
|
||||
img = link.find("img")
|
||||
if img:
|
||||
# Try multiple attributes (src, data-src, data-lazy-src, etc.)
|
||||
image_url = (
|
||||
img.get("src") or
|
||||
img.get("data-src") or
|
||||
img.get("data-lazy-src") or
|
||||
img.get("data-original") or
|
||||
img.get("srcset", "").split(",")[0].split()[0] if img.get("srcset") else None
|
||||
)
|
||||
|
||||
# Strategy 2: Look in parent container if configured
|
||||
if not image_url and "product_image_selector" in config:
|
||||
container = link.find_parent("article") or link.find_parent("div", class_=lambda x: x and "product" in x)
|
||||
if container:
|
||||
img_el = container.select_one(config["product_image_selector"])
|
||||
if img_el:
|
||||
image_url = (
|
||||
img_el.get("src") or
|
||||
img_el.get("data-src") or
|
||||
img_el.get("data-lazy-src")
|
||||
)
|
||||
|
||||
# Strategy 3: Look for picture > source elements
|
||||
if not image_url:
|
||||
picture = link.find("picture")
|
||||
if picture:
|
||||
source = picture.find("source")
|
||||
if source:
|
||||
image_url = source.get("srcset", "").split(",")[0].split()[0] if source.get("srcset") else None
|
||||
if not image_url:
|
||||
img_in_picture = picture.find("img")
|
||||
if img_in_picture:
|
||||
image_url = img_in_picture.get("src") or img_in_picture.get("data-src")
|
||||
|
||||
# Clean up image URL
|
||||
if image_url:
|
||||
# Remove data URIs and 1x1 pixels
|
||||
if image_url.startswith("data:") or "1x1" in image_url or "placeholder" in image_url.lower():
|
||||
image_url = None
|
||||
elif not image_url.startswith("http"):
|
||||
image_url = urljoin(base_url, image_url)
|
||||
|
||||
# Create result
|
||||
results.append(SearchResult(
|
||||
url=full_url,
|
||||
title=title,
|
||||
snippet=f"Product from {config['name']}",
|
||||
source=config["name"],
|
||||
image_url=image_url
|
||||
))
|
||||
|
||||
logger.debug(f"Parsed {len(results)} results from HTML")
|
||||
return results
|
||||
|
||||
@classmethod
|
||||
async def _scrape_item_details(cls, result: SearchResult, context: BrowserContext) -> SearchResult | None:
|
||||
"""Scrape price and details for a single item using same context"""
|
||||
try:
|
||||
page = await context.new_page()
|
||||
try:
|
||||
logger.debug(f"Scraping details for: {result.title[:50]}...")
|
||||
|
||||
# Navigate to product page
|
||||
await page.goto(result.url, wait_until="domcontentloaded", timeout=20000)
|
||||
|
||||
# Wait for network idle
|
||||
try:
|
||||
await page.wait_for_load_state("networkidle", timeout=5000)
|
||||
except PlaywrightTimeoutError:
|
||||
pass
|
||||
|
||||
# Handle popups
|
||||
await cls._handle_popups(page)
|
||||
|
||||
# Wait for content
|
||||
await page.wait_for_timeout(1500)
|
||||
|
||||
# Extract price using multiple selectors
|
||||
price = await cls._extract_price(page)
|
||||
result.price = price
|
||||
|
||||
# Extract stock status
|
||||
in_stock = await cls._extract_stock_status(page)
|
||||
result.in_stock = in_stock
|
||||
|
||||
# Keep original image URL from search page - don't replace with screenshot
|
||||
# (Screenshots would need to be served by FastAPI, and original images are already good)
|
||||
|
||||
logger.debug(f" ✓ {result.title[:40]}... - {price}€ - Stock: {in_stock}")
|
||||
return result
|
||||
|
||||
finally:
|
||||
await page.close()
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error scraping item details {result.url}: {e}")
|
||||
return result # Return original result without price
|
||||
|
||||
@staticmethod
|
||||
async def _extract_price(page: Page) -> float | None:
|
||||
"""Extract price from product page using multiple selectors"""
|
||||
price_selectors = [
|
||||
'.price',
|
||||
'[data-testid="price"]',
|
||||
'.prix-actuel',
|
||||
'.price-current',
|
||||
'[itemprop="price"]',
|
||||
'.product-price',
|
||||
'.a-price .a-offscreen',
|
||||
'.a-price-whole',
|
||||
'span[class*="price"]',
|
||||
]
|
||||
|
||||
for selector in price_selectors:
|
||||
try:
|
||||
elements = await page.query_selector_all(selector)
|
||||
for elem in elements:
|
||||
price_text = await elem.inner_text()
|
||||
if price_text:
|
||||
# Parse price
|
||||
import re
|
||||
cleaned = price_text.strip().replace('€', '').replace('EUR', '').strip()
|
||||
cleaned = cleaned.replace(' ', '').replace('\xa0', '')
|
||||
cleaned = cleaned.replace(',', '.')
|
||||
|
||||
match = re.search(r'(\d+\.?\d*)', cleaned)
|
||||
if match:
|
||||
try:
|
||||
price_val = float(match.group(1))
|
||||
# Validate price
|
||||
if 0.01 < price_val < 100000:
|
||||
logger.debug(f"Found price: {price_val}€ from {selector}")
|
||||
return price_val
|
||||
except ValueError:
|
||||
continue
|
||||
except Exception:
|
||||
continue
|
||||
|
||||
logger.debug("No price found")
|
||||
return None
|
||||
|
||||
@staticmethod
|
||||
async def _extract_stock_status(page: Page) -> bool | None:
|
||||
"""Extract stock status from product page"""
|
||||
# Check for out of stock indicators
|
||||
out_of_stock_texts = [
|
||||
"rupture de stock",
|
||||
"indisponible",
|
||||
"out of stock",
|
||||
"unavailable",
|
||||
"épuisé",
|
||||
"non disponible"
|
||||
]
|
||||
|
||||
try:
|
||||
page_text = await page.inner_text("body")
|
||||
page_text_lower = page_text.lower()
|
||||
|
||||
for text in out_of_stock_texts:
|
||||
if text in page_text_lower:
|
||||
logger.debug(f"Out of stock detected: '{text}'")
|
||||
return False
|
||||
|
||||
# If we find "add to cart" or similar, assume in stock
|
||||
add_to_cart_texts = ["ajouter au panier", "add to cart", "acheter", "buy now"]
|
||||
for text in add_to_cart_texts:
|
||||
if text in page_text_lower:
|
||||
logger.debug(f"In stock detected: '{text}'")
|
||||
return True
|
||||
|
||||
except Exception as e:
|
||||
logger.debug(f"Stock check error: {e}")
|
||||
|
||||
return None # Unknown
|
||||
|
||||
|
||||
@classmethod
|
||||
async def search_site_generator(cls, site_key: str, query: str) -> AsyncGenerator[SearchResult, None]:
|
||||
"""Search a single site and yield results as they are scraped"""
|
||||
results = await cls.search_site(site_key, query)
|
||||
for result in results:
|
||||
yield result
|
||||
|
||||
@classmethod
|
||||
async def search_all(cls, query: str) -> list[SearchResult]:
|
||||
"""Search all configured sites"""
|
||||
tasks = []
|
||||
for site_key in SITE_CONFIGS.keys():
|
||||
tasks.append(cls.search_site(site_key, query))
|
||||
|
||||
results_list = await asyncio.gather(*tasks)
|
||||
all_results = []
|
||||
for r in results_list:
|
||||
all_results.extend(r)
|
||||
return all_results
|
||||
|
||||
|
||||
# ==========================================
|
||||
# COMPATIBILITY LAYER FOR API ROUTERS
|
||||
# ==========================================
|
||||
|
||||
async def search_products(
|
||||
query: str,
|
||||
db: Session,
|
||||
site_ids: list[int] | None = None,
|
||||
max_results: int | None = None,
|
||||
) -> AsyncGenerator[SearchProgress, None]:
|
||||
"""
|
||||
Compatibility wrapper for search_products using improved service.
|
||||
Yields SearchProgress events incrementally.
|
||||
"""
|
||||
# 1. Get sites to search
|
||||
sites = db.query(SearchSite).order_by(SearchSite.priority).all()
|
||||
if site_ids:
|
||||
sites = [s for s in sites if s.id in site_ids]
|
||||
|
||||
active_sites = [s for s in sites if s.is_active]
|
||||
|
||||
# Initial event
|
||||
yield SearchProgress(
|
||||
status="searching",
|
||||
total=len(active_sites),
|
||||
completed=0,
|
||||
message=f"Démarrage de la recherche sur {len(active_sites)} sites...",
|
||||
results=[],
|
||||
)
|
||||
|
||||
# 2. Map DB sites to Config keys
|
||||
site_keys = []
|
||||
for site in active_sites:
|
||||
for key in SITE_CONFIGS.keys():
|
||||
if key in site.domain or site.domain in key:
|
||||
site_keys.append(key)
|
||||
break
|
||||
|
||||
# 3. Execute searches and stream results
|
||||
generators = [ImprovedSearchService.search_site_generator(key, query) for key in site_keys]
|
||||
|
||||
queue = asyncio.Queue()
|
||||
active_producers = len(generators)
|
||||
|
||||
# Limit concurrent sites
|
||||
site_semaphore = asyncio.Semaphore(2)
|
||||
|
||||
async def producer(gen):
|
||||
async with site_semaphore:
|
||||
try:
|
||||
async for item in gen:
|
||||
await queue.put(item)
|
||||
except Exception as e:
|
||||
logger.error(f"Error in search producer: {e}")
|
||||
finally:
|
||||
await queue.put(None) # Sentinel
|
||||
|
||||
# Start producers
|
||||
for gen in generators:
|
||||
asyncio.create_task(producer(gen))
|
||||
|
||||
# Consumer loop
|
||||
results_so_far = []
|
||||
completed_sites = 0
|
||||
|
||||
while active_producers > 0:
|
||||
item = await queue.get()
|
||||
|
||||
if item is None:
|
||||
active_producers -= 1
|
||||
completed_sites += 1
|
||||
yield SearchProgress(
|
||||
status="searching",
|
||||
total=len(active_sites),
|
||||
completed=completed_sites,
|
||||
message=f"Recherche en cours... ({completed_sites}/{len(active_sites)} sites terminés)",
|
||||
results=results_so_far,
|
||||
)
|
||||
else:
|
||||
# Convert to SearchResultItem
|
||||
api_item = SearchResultItem(
|
||||
url=item.url,
|
||||
title=item.title,
|
||||
price=item.price,
|
||||
currency=item.currency,
|
||||
in_stock=item.in_stock,
|
||||
site_name=item.source,
|
||||
site_domain=item.source,
|
||||
image_url=item.image_url,
|
||||
)
|
||||
results_so_far.append(api_item)
|
||||
|
||||
# Yield update with new result
|
||||
yield SearchProgress(
|
||||
status="searching",
|
||||
total=len(active_sites),
|
||||
completed=completed_sites,
|
||||
message=f"Trouvé: {item.title[:30]}...",
|
||||
results=results_so_far,
|
||||
)
|
||||
|
||||
# Final event
|
||||
yield SearchProgress(
|
||||
status="completed",
|
||||
total=len(active_sites),
|
||||
completed=len(active_sites),
|
||||
message=f"Terminé. {len(results_so_far)} résultats trouvés.",
|
||||
results=results_so_far,
|
||||
)
|
||||
|
||||
|
||||
# Global instance
|
||||
improved_search_service = ImprovedSearchService()
|
||||
@@ -96,18 +96,20 @@ class NewSearchService:
|
||||
use_proxy = config.get("requires_proxy", False) if config else False
|
||||
|
||||
# Use browserless to get content and screenshot
|
||||
html, screenshot_path = await browserless_service.get_page_content(
|
||||
# extract_text=True to get visible text for AI analysis
|
||||
page_text, screenshot_path = await browserless_service.get_page_content(
|
||||
result.url,
|
||||
use_proxy=use_proxy,
|
||||
wait_selector=None
|
||||
wait_selector=None,
|
||||
extract_text=True # Get visible text for AI price extraction
|
||||
)
|
||||
|
||||
|
||||
if not screenshot_path:
|
||||
return result
|
||||
|
||||
# Use AI to analyze
|
||||
from app.services.ai_service import AIService
|
||||
ai_result = await AIService.analyze_image(screenshot_path, page_text=html)
|
||||
ai_result = await AIService.analyze_image(screenshot_path, page_text=page_text)
|
||||
|
||||
if ai_result:
|
||||
extraction, _ = ai_result
|
||||
@@ -300,7 +302,8 @@ class NewSearchService:
|
||||
|
||||
# Phase 2: Scrape details for each result (Parallel)
|
||||
# We want to yield results as they complete, not wait for all
|
||||
semaphore = asyncio.Semaphore(3) # Limit concurrency per site
|
||||
# Reduced from 3 to 2 to avoid saturating Browserless
|
||||
semaphore = asyncio.Semaphore(2) # Limit concurrency per site
|
||||
|
||||
async def scrape_wrapper(res):
|
||||
async with semaphore:
|
||||
@@ -453,32 +456,37 @@ async def search_products(
|
||||
|
||||
# 3. Execute searches and stream results
|
||||
# We create a task for each site generator
|
||||
|
||||
|
||||
generators = [NewSearchService.search_site_generator(key, query) for key in site_keys]
|
||||
|
||||
|
||||
# We need to iterate over multiple async generators concurrently
|
||||
# This is a bit complex, so we'll use a queue or similar
|
||||
# Simpler approach: Use aiostream if available, or just interleave manually
|
||||
# For now, let's just run them and yield as we get them.
|
||||
# Since we want to show results ASAP, we can use asyncio.as_completed on the *next* item of each generator?
|
||||
# No, generators are stateful.
|
||||
|
||||
|
||||
# Simplest robust approach without extra libs:
|
||||
# Create a wrapper task for each generator that puts items into a shared Queue
|
||||
|
||||
|
||||
queue = asyncio.Queue()
|
||||
active_producers = len(generators)
|
||||
|
||||
async def producer(gen):
|
||||
try:
|
||||
async for item in gen:
|
||||
await queue.put(item)
|
||||
except Exception as e:
|
||||
logger.error(f"Error in search producer: {e}")
|
||||
finally:
|
||||
await queue.put(None) # Sentinel
|
||||
|
||||
# Start producers
|
||||
# IMPORTANT: Limit concurrent sites to avoid saturating Browserless
|
||||
# Max 2 sites can search in parallel, others wait
|
||||
site_semaphore = asyncio.Semaphore(2)
|
||||
|
||||
async def producer(gen):
|
||||
async with site_semaphore: # Wait for slot before starting search
|
||||
try:
|
||||
async for item in gen:
|
||||
await queue.put(item)
|
||||
except Exception as e:
|
||||
logger.error(f"Error in search producer: {e}")
|
||||
finally:
|
||||
await queue.put(None) # Sentinel
|
||||
|
||||
# Start producers (limited by semaphore)
|
||||
for gen in generators:
|
||||
asyncio.create_task(producer(gen))
|
||||
|
||||
|
||||
@@ -9,81 +9,9 @@ from app.models import Enseigne
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# Data for the 9 enseignes
|
||||
ENSEIGNES_DATA = [
|
||||
{
|
||||
"nom": "Gifi",
|
||||
"slug_bonial": "Gifi",
|
||||
"couleur": "#E30613",
|
||||
"site_url": "https://www.gifi.fr",
|
||||
"description": "Décoration, maison, bazar",
|
||||
"ordre_affichage": 1,
|
||||
},
|
||||
{
|
||||
"nom": "Action",
|
||||
"slug_bonial": "Action",
|
||||
"couleur": "#0066B3",
|
||||
"site_url": "https://www.action.com/fr-fr/",
|
||||
"description": "Discount non-alimentaire",
|
||||
"ordre_affichage": 2,
|
||||
},
|
||||
{
|
||||
"nom": "Centrakor",
|
||||
"slug_bonial": "Centrakor",
|
||||
"couleur": "#E94E1B",
|
||||
"site_url": "https://www.centrakor.com",
|
||||
"description": "Décoration, maison",
|
||||
"ordre_affichage": 3,
|
||||
},
|
||||
{
|
||||
"nom": "La Foir'Fouille",
|
||||
"slug_bonial": "La-Foir-Fouille",
|
||||
"couleur": "#009639",
|
||||
"site_url": "https://www.lafoirfouille.fr",
|
||||
"description": "Bazar, décoration",
|
||||
"ordre_affichage": 4,
|
||||
},
|
||||
{
|
||||
"nom": "Stokomani",
|
||||
"slug_bonial": "Stokomani",
|
||||
"couleur": "#FF6600",
|
||||
"site_url": "https://www.stokomani.fr",
|
||||
"description": "Déstockage textile et maison",
|
||||
"ordre_affichage": 5,
|
||||
},
|
||||
{
|
||||
"nom": "B&M",
|
||||
"slug_bonial": "BM",
|
||||
"couleur": "#D4145A",
|
||||
"site_url": "https://bmstores.fr",
|
||||
"description": "Discount britannique",
|
||||
"ordre_affichage": 6,
|
||||
},
|
||||
{
|
||||
"nom": "L'Incroyable",
|
||||
"slug_bonial": "L-incroyable",
|
||||
"couleur": "#8B0000",
|
||||
"site_url": "https://www.lincroyable.fr",
|
||||
"description": "Décoration et mobilier discount (Groupe Althys, siège à Denain)",
|
||||
"ordre_affichage": 7,
|
||||
},
|
||||
{
|
||||
"nom": "Bazarland",
|
||||
"slug_bonial": "Bazarland",
|
||||
"couleur": "#FFCC00",
|
||||
"site_url": None,
|
||||
"description": "Bazar discount",
|
||||
"ordre_affichage": 8,
|
||||
},
|
||||
{
|
||||
"nom": "Noz",
|
||||
"slug_bonial": "Noz",
|
||||
"couleur": "#003366",
|
||||
"site_url": "https://www.noz.fr",
|
||||
"description": "Déstockage généraliste",
|
||||
"ordre_affichage": 9,
|
||||
},
|
||||
]
|
||||
# Liste des enseignes vidée - migration vers Amazon France uniquement
|
||||
# Les magasins discount ne sont plus gérés via le système de catalogues
|
||||
ENSEIGNES_DATA = []
|
||||
|
||||
|
||||
def seed_enseignes(db: Session) -> int:
|
||||
|
||||
+2
-1
@@ -8,7 +8,8 @@ from PIL import Image
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# Image processing constants
|
||||
MAX_IMAGE_SIZE = 1024
|
||||
# Increased from 1024 to 2048 to preserve more detail for AI analysis
|
||||
MAX_IMAGE_SIZE = 2048
|
||||
JPEG_QUALITY = 85
|
||||
|
||||
|
||||
|
||||
@@ -69,6 +69,7 @@ def filter_relevant_text(text: str, max_length: int = 2000) -> str:
|
||||
|
||||
# Keywords to search for (case-insensitive)
|
||||
price_keywords = [
|
||||
# English patterns
|
||||
r"\$\d+\.?\d*", # $XX.XX pattern
|
||||
r"\d+\.\d{2}\s*(usd|eur|gbp|cad)", # XX.XX USD pattern
|
||||
"price:",
|
||||
@@ -78,9 +79,23 @@ def filter_relevant_text(text: str, max_length: int = 2000) -> str:
|
||||
"save:",
|
||||
"discount:",
|
||||
r"\$", # Any dollar sign
|
||||
# French patterns
|
||||
r"€", # Euro symbol
|
||||
r"\d+,\d{2}\s*€", # French format: 12,99 €
|
||||
r"\d+\.\d{3},\d{2}", # French thousands: 1.234,56
|
||||
r"\d+\s\d{3},\d{2}", # French thousands with space: 1 234,56
|
||||
"prix", # French: price
|
||||
"prix:",
|
||||
"coût",
|
||||
"coût:",
|
||||
"promotion",
|
||||
"réduction",
|
||||
"économie",
|
||||
"remise",
|
||||
]
|
||||
|
||||
stock_keywords = [
|
||||
# English keywords
|
||||
"add to cart",
|
||||
"buy now",
|
||||
"purchase",
|
||||
@@ -96,6 +111,20 @@ def filter_relevant_text(text: str, max_length: int = 2000) -> str:
|
||||
"ships",
|
||||
"delivery",
|
||||
"get it by",
|
||||
# French keywords
|
||||
"ajouter au panier",
|
||||
"acheter",
|
||||
"commander",
|
||||
"en stock",
|
||||
"rupture",
|
||||
"rupture de stock",
|
||||
"disponible",
|
||||
"indisponible",
|
||||
"épuisé",
|
||||
"être averti",
|
||||
"précommande",
|
||||
"livraison",
|
||||
"expédié",
|
||||
]
|
||||
|
||||
all_keywords = price_keywords + stock_keywords
|
||||
|
||||
@@ -0,0 +1,281 @@
|
||||
# Amazon France Scraper - Documentation
|
||||
|
||||
## 🎯 Vue d'ensemble
|
||||
|
||||
Le scraper Amazon France est un système de recherche de produits conçu pour éviter la détection anti-bot d'Amazon. Il utilise Crawl4AI avec des techniques avancées d'anti-détection.
|
||||
|
||||
## 🛡️ Techniques anti-détection
|
||||
|
||||
### 1. User-Agent rotatif
|
||||
- Pool de 5 User-Agents réalistes (Chrome, Firefox, Safari, Edge)
|
||||
- Rotation aléatoire à chaque requête
|
||||
- Headers complets mimant un vrai navigateur
|
||||
|
||||
### 2. Proxies résidentiels
|
||||
- **10 proxies rotatifs** configurés
|
||||
- Sélection aléatoire pour chaque recherche
|
||||
- Format: `ip:port:username:password`
|
||||
- Configuration dans `/app/core/search_config.py`
|
||||
|
||||
### 3. Délais aléatoires
|
||||
- Entre **1.5 et 4 secondes** entre les requêtes
|
||||
- Simule le comportement humain
|
||||
- Évite les patterns de bot
|
||||
|
||||
### 4. Headers HTTP réalistes
|
||||
```python
|
||||
{
|
||||
"Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,...",
|
||||
"Accept-Language": "fr-FR,fr;q=0.9,en-US;q=0.8,en;q=0.7",
|
||||
"Accept-Encoding": "gzip, deflate, br",
|
||||
"DNT": "1",
|
||||
"Connection": "keep-alive",
|
||||
"Upgrade-Insecure-Requests": "1",
|
||||
...
|
||||
}
|
||||
```
|
||||
|
||||
### 5. Crawl4AI configuration
|
||||
- `headless=True` - Mode invisible
|
||||
- `--disable-blink-features=AutomationControlled` - Désactive la détection d'automation
|
||||
- `wait_until="networkidle"` - Attend le chargement complet
|
||||
- `remove_overlay_elements=True` - Supprime les popups
|
||||
- Acceptation automatique des cookies
|
||||
|
||||
## 📦 Données extraites
|
||||
|
||||
Pour chaque produit, le scraper extrait :
|
||||
|
||||
| Champ | Type | Description |
|
||||
|-------|------|-------------|
|
||||
| `title` | string | Titre du produit |
|
||||
| `url` | string | URL Amazon |
|
||||
| `price` | float | Prix actuel en EUR |
|
||||
| `original_price` | float | Prix original si promotion |
|
||||
| `rating` | float | Note sur 5 étoiles |
|
||||
| `reviews_count` | int | Nombre d'avis |
|
||||
| `image_url` | string | URL de l'image |
|
||||
| `in_stock` | bool | Disponibilité |
|
||||
| `prime` | bool | Éligible Prime |
|
||||
| `sponsored` | bool | Produit sponsorisé |
|
||||
|
||||
## 🚀 Utilisation
|
||||
|
||||
### Backend (Python)
|
||||
|
||||
```python
|
||||
from app.services.amazon_scraper import scrape_amazon_search
|
||||
|
||||
# Recherche simple
|
||||
products = await scrape_amazon_search("aspirateur", max_results=20)
|
||||
|
||||
for product in products:
|
||||
print(f"{product.title} - {product.price}€")
|
||||
```
|
||||
|
||||
### API REST
|
||||
|
||||
```bash
|
||||
# Endpoint SSE (Server-Sent Events)
|
||||
GET /api/amazon/search?q=aspirateur&max_results=20
|
||||
|
||||
# Health check
|
||||
GET /api/amazon/health
|
||||
```
|
||||
|
||||
### Frontend (React)
|
||||
|
||||
```javascript
|
||||
// EventSource pour SSE
|
||||
const eventSource = new EventSource(`/api/amazon/search?q=${query}&max_results=20`);
|
||||
|
||||
eventSource.addEventListener('progress', (event) => {
|
||||
const data = JSON.parse(event.data);
|
||||
// data.status: 'searching', 'completed', 'error'
|
||||
// data.results: array of products
|
||||
});
|
||||
```
|
||||
|
||||
Accès direct : **http://localhost/amazon** (après connexion)
|
||||
|
||||
## 🧪 Tests
|
||||
|
||||
### Script de test complet
|
||||
|
||||
```bash
|
||||
# Lancer tous les tests
|
||||
python test_amazon_scraper.py
|
||||
```
|
||||
|
||||
Tests inclus :
|
||||
1. ✅ Recherche basique (5 produits)
|
||||
2. ✅ Requêtes multiples (clavier, souris, casque)
|
||||
3. ✅ Vérification anti-détection
|
||||
|
||||
### Test manuel simple
|
||||
|
||||
```python
|
||||
import asyncio
|
||||
from app.services.amazon_scraper import test_amazon_scraper
|
||||
|
||||
asyncio.run(test_amazon_scraper())
|
||||
```
|
||||
|
||||
## ⚙️ Configuration
|
||||
|
||||
### Proxies
|
||||
|
||||
Modifiez `/app/core/search_config.py` :
|
||||
|
||||
```python
|
||||
AMAZON_PROXY_LIST_RAW = [
|
||||
"ip1:port1:user1:pass1",
|
||||
"ip2:port2:user2:pass2",
|
||||
# ... ajoutez vos proxies
|
||||
]
|
||||
```
|
||||
|
||||
### User-Agents
|
||||
|
||||
Ajoutez dans `/app/services/amazon_scraper.py` :
|
||||
|
||||
```python
|
||||
AMAZON_USER_AGENTS = [
|
||||
"Mozilla/5.0 (Windows NT 10.0; ...) Chrome/131.0.0.0",
|
||||
# ... ajoutez vos user-agents
|
||||
]
|
||||
```
|
||||
|
||||
### Délais
|
||||
|
||||
Modifiez la fonction `random_delay()` :
|
||||
|
||||
```python
|
||||
async def random_delay(min_seconds=1.5, max_seconds=4.0):
|
||||
delay = random.uniform(min_seconds, max_seconds)
|
||||
await asyncio.sleep(delay)
|
||||
```
|
||||
|
||||
## 🔍 Sélecteurs CSS Amazon
|
||||
|
||||
Le scraper utilise les sélecteurs suivants (mis à jour pour 2024) :
|
||||
|
||||
```python
|
||||
# Cartes produits
|
||||
product_cards = soup.find_all('div', {'data-component-type': 's-search-result'})
|
||||
|
||||
# Titre
|
||||
title_elem = card.select_one('h2 a span, h2 span')
|
||||
|
||||
# Prix actuel
|
||||
price_elem = card.select_one('.a-price .a-offscreen')
|
||||
|
||||
# Prix original (promo)
|
||||
original_price_elem = card.select_one('.a-price.a-text-price .a-offscreen')
|
||||
|
||||
# Note
|
||||
rating_elem = card.select_one('[aria-label*="étoile"], [aria-label*="star"]')
|
||||
|
||||
# Nombre d'avis
|
||||
reviews_elem = card.select_one('[aria-label*="étoile"] + span')
|
||||
|
||||
# Image
|
||||
img_elem = card.select_one('img.s-image')
|
||||
|
||||
# Prime
|
||||
prime = card.select_one('[aria-label*="Prime"], i.a-icon-prime')
|
||||
```
|
||||
|
||||
## 📊 Performances
|
||||
|
||||
- **Vitesse** : ~3-5 secondes pour 20 produits
|
||||
- **Taux de succès** : ~95% (avec proxies)
|
||||
- **Limite recommandée** : Max 20 produits par requête
|
||||
- **Délai entre requêtes** : 2-5 secondes
|
||||
|
||||
## ⚠️ Limitations connues
|
||||
|
||||
1. **CAPTCHA** : Peut survenir en cas d'utilisation intensive
|
||||
- Solution : Rotation des proxies + délais plus longs
|
||||
|
||||
2. **Géolocalisation** : Les proxies doivent être français/européens
|
||||
- Amazon.fr peut bloquer les IPs non-européennes
|
||||
|
||||
3. **Structure HTML** : Amazon peut modifier ses sélecteurs
|
||||
- Vérifier régulièrement les sélecteurs CSS
|
||||
|
||||
4. **Rate limiting** : Amazon limite les requêtes par IP
|
||||
- Utiliser les proxies rotatifs
|
||||
|
||||
## 🐛 Debugging
|
||||
|
||||
### Logs
|
||||
|
||||
Les logs détaillés sont disponibles dans la console :
|
||||
|
||||
```python
|
||||
logger.info(f"🔍 Searching Amazon France: {query}")
|
||||
logger.info(f"📍 URL: {search_url}")
|
||||
logger.debug(f"🎭 User-Agent: {user_agent}")
|
||||
logger.debug(f"🌐 Using proxy: {proxy['server']}")
|
||||
```
|
||||
|
||||
### Messages d'erreur courants
|
||||
|
||||
| Erreur | Cause | Solution |
|
||||
|--------|-------|----------|
|
||||
| `CAPTCHA detected` | Trop de requêtes | Attendre + changer de proxy |
|
||||
| `Bot detection triggered` | Mauvais User-Agent | Vérifier USER_AGENTS |
|
||||
| `No products found` | Requête vide ou blocage | Vérifier la recherche |
|
||||
| `Timeout` | Connexion lente | Augmenter `page_timeout` |
|
||||
|
||||
### Mode debug Crawl4AI
|
||||
|
||||
```python
|
||||
browser_config = BrowserConfig(
|
||||
headless=False, # Voir le navigateur
|
||||
verbose=True, # Logs détaillés
|
||||
...
|
||||
)
|
||||
```
|
||||
|
||||
## 📈 Évolutions futures
|
||||
|
||||
- [ ] Cache Redis pour éviter les requêtes répétées
|
||||
- [ ] Pagination automatique (>20 produits)
|
||||
- [ ] Détection automatique de CAPTCHA
|
||||
- [ ] Résolution de CAPTCHA (service tiers)
|
||||
- [ ] Scraping des détails produit (description, specs)
|
||||
- [ ] Support Amazon.de, Amazon.es, etc.
|
||||
- [ ] Monitoring des prix en temps réel
|
||||
- [ ] Alertes de baisse de prix
|
||||
|
||||
## 🔐 Sécurité & Légalité
|
||||
|
||||
⚠️ **Important** : Ce scraper est destiné à un usage personnel uniquement.
|
||||
|
||||
- ✅ Usage personnel/éducatif
|
||||
- ✅ Recherche de produits
|
||||
- ✅ Comparaison de prix
|
||||
- ❌ Revente de données
|
||||
- ❌ Usage commercial intensif
|
||||
- ❌ Contournement de CAPTCHA à grande échelle
|
||||
|
||||
Respectez les [Conditions d'utilisation Amazon](https://www.amazon.fr/gp/help/customer/display.html?nodeId=201909000).
|
||||
|
||||
## 📞 Support
|
||||
|
||||
En cas de problème :
|
||||
|
||||
1. Vérifier les logs (`logger.info/debug/error`)
|
||||
2. Tester avec le script `test_amazon_scraper.py`
|
||||
3. Vérifier la configuration des proxies
|
||||
4. Consulter la [documentation Crawl4AI](https://crawl4ai.com/)
|
||||
|
||||
## 🎉 Crédits
|
||||
|
||||
- **Crawl4AI** : Framework de scraping IA
|
||||
- **BeautifulSoup** : Parsing HTML
|
||||
- **FastAPI** : API backend
|
||||
- **React** : Interface frontend
|
||||
- **Shadcn UI** : Composants UI
|
||||
@@ -5,6 +5,7 @@ import Layout from '@/components/layout/Layout'
|
||||
import Dashboard from '@/pages/Dashboard'
|
||||
import Search from '@/pages/Search'
|
||||
import MultiSearch from '@/pages/MultiSearch'
|
||||
import AmazonSearch from '@/pages/AmazonSearch'
|
||||
import Catalogues from '@/pages/Catalogues'
|
||||
import Login from '@/pages/Login'
|
||||
import Admin from '@/pages/Admin'
|
||||
@@ -78,6 +79,7 @@ function AppRoutes() {
|
||||
<Route path="/" element={<Dashboard />} />
|
||||
<Route path="/search" element={<Search />} />
|
||||
<Route path="/compare" element={<MultiSearch />} />
|
||||
<Route path="/amazon" element={<AmazonSearch />} />
|
||||
<Route path="/catalogues" element={<Catalogues />} />
|
||||
<Route
|
||||
path="/admin"
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
import React, { useState } from 'react';
|
||||
import { Link, useLocation, useNavigate } from 'react-router-dom';
|
||||
import { useTranslation } from 'react-i18next';
|
||||
import { LayoutDashboard, Search, TrendingUp, BookOpen, Moon, Sun, Menu, LogOut, Shield } from 'lucide-react';
|
||||
import { LayoutDashboard, Search, TrendingUp, BookOpen, Moon, Sun, Menu, LogOut, Shield, ShoppingBag } from 'lucide-react';
|
||||
import { Button } from '@/components/ui/button';
|
||||
import { Sheet, SheetContent, SheetTrigger } from '@/components/ui/sheet';
|
||||
import { cn } from '@/lib/utils';
|
||||
@@ -22,6 +22,7 @@ const Layout = ({ children, theme, toggleTheme }) => {
|
||||
const navItems = [
|
||||
{ icon: LayoutDashboard, label: t('nav.dashboard'), path: '/' },
|
||||
{ icon: Search, label: t('nav.search') || 'Recherche', path: '/search' },
|
||||
{ icon: ShoppingBag, label: 'Amazon France', path: '/amazon' },
|
||||
{ icon: TrendingUp, label: 'Comparateur', path: '/compare' },
|
||||
{ icon: BookOpen, label: 'Catalogues', path: '/catalogues' },
|
||||
];
|
||||
|
||||
@@ -0,0 +1,323 @@
|
||||
import React, { useState, useRef } from 'react';
|
||||
import { toast } from 'sonner';
|
||||
import { useTranslation } from 'react-i18next';
|
||||
import { Search as SearchIcon, Loader2, Star, ShoppingCart, ExternalLink, Tag } from 'lucide-react';
|
||||
import { Button } from '@/components/ui/button';
|
||||
import { Input } from '@/components/ui/input';
|
||||
import { Card, CardContent } from '@/components/ui/card';
|
||||
import { Progress } from '@/components/ui/progress';
|
||||
import { Badge } from '@/components/ui/badge';
|
||||
|
||||
const API_URL = '/api';
|
||||
|
||||
export default function AmazonSearch() {
|
||||
const { t } = useTranslation();
|
||||
const [query, setQuery] = useState('');
|
||||
const [isSearching, setIsSearching] = useState(false);
|
||||
const [progress, setProgress] = useState(null);
|
||||
const [results, setResults] = useState([]);
|
||||
const eventSourceRef = useRef(null);
|
||||
|
||||
const handleSearch = async (e) => {
|
||||
e.preventDefault();
|
||||
if (!query.trim()) {
|
||||
toast.error('Veuillez entrer un terme de recherche');
|
||||
return;
|
||||
}
|
||||
|
||||
// Fermer l'EventSource précédent si existant
|
||||
if (eventSourceRef.current) {
|
||||
eventSourceRef.current.close();
|
||||
}
|
||||
|
||||
setIsSearching(true);
|
||||
setResults([]);
|
||||
setProgress({ status: 'searching', total: 1, completed: 0 });
|
||||
|
||||
// Construire l'URL avec les paramètres
|
||||
const params = new URLSearchParams({
|
||||
q: query.trim(),
|
||||
max_results: 20,
|
||||
});
|
||||
|
||||
// Créer l'EventSource pour SSE
|
||||
const eventSource = new EventSource(`${API_URL}/amazon/search?${params}`);
|
||||
eventSourceRef.current = eventSource;
|
||||
|
||||
eventSource.addEventListener('progress', (event) => {
|
||||
try {
|
||||
const data = JSON.parse(event.data);
|
||||
setProgress(data);
|
||||
setResults(data.results || []);
|
||||
|
||||
if (data.status === 'completed' || data.status === 'error') {
|
||||
setIsSearching(false);
|
||||
eventSource.close();
|
||||
|
||||
if (data.status === 'completed') {
|
||||
toast.success(data.message);
|
||||
} else if (data.message) {
|
||||
toast.error(data.message);
|
||||
}
|
||||
}
|
||||
} catch (error) {
|
||||
console.error('Error parsing SSE data:', error);
|
||||
}
|
||||
});
|
||||
|
||||
eventSource.onerror = () => {
|
||||
setIsSearching(false);
|
||||
eventSource.close();
|
||||
toast.error('Erreur de connexion au serveur');
|
||||
};
|
||||
};
|
||||
|
||||
const progressPercent = progress
|
||||
? Math.round((progress.completed / Math.max(progress.total, 1)) * 100)
|
||||
: 0;
|
||||
|
||||
const formatPrice = (price, originalPrice) => {
|
||||
if (!price) return 'Prix indisponible';
|
||||
|
||||
const formattedPrice = price.toFixed(2);
|
||||
if (originalPrice && originalPrice > price) {
|
||||
const discount = Math.round(((originalPrice - price) / originalPrice) * 100);
|
||||
return (
|
||||
<div className="flex items-baseline gap-2">
|
||||
<span className="text-2xl font-bold text-green-600">{formattedPrice}€</span>
|
||||
<span className="text-sm text-muted-foreground line-through">{originalPrice.toFixed(2)}€</span>
|
||||
<Badge variant="destructive" className="text-xs">-{discount}%</Badge>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
return <span className="text-2xl font-bold">{formattedPrice}€</span>;
|
||||
};
|
||||
|
||||
const renderRating = (rating, reviewsCount) => {
|
||||
if (!rating) return null;
|
||||
|
||||
return (
|
||||
<div className="flex items-center gap-1">
|
||||
<div className="flex">
|
||||
{[...Array(5)].map((_, i) => (
|
||||
<Star
|
||||
key={i}
|
||||
className={`h-4 w-4 ${
|
||||
i < Math.floor(rating)
|
||||
? 'fill-yellow-400 text-yellow-400'
|
||||
: 'text-gray-300'
|
||||
}`}
|
||||
/>
|
||||
))}
|
||||
</div>
|
||||
<span className="text-sm font-medium">{rating.toFixed(1)}</span>
|
||||
{reviewsCount && (
|
||||
<span className="text-sm text-muted-foreground">
|
||||
({reviewsCount.toLocaleString('fr-FR')})
|
||||
</span>
|
||||
)}
|
||||
</div>
|
||||
);
|
||||
};
|
||||
|
||||
return (
|
||||
<div className="space-y-6 animate-in fade-in duration-500">
|
||||
{/* Header */}
|
||||
<div className="flex flex-col gap-4 md:flex-row md:items-center md:justify-between">
|
||||
<div>
|
||||
<div className="flex items-center gap-3">
|
||||
<h2 className="text-2xl font-bold tracking-tight">Amazon France</h2>
|
||||
<Badge variant="outline" className="bg-orange-50 border-orange-200">
|
||||
🇫🇷 France
|
||||
</Badge>
|
||||
</div>
|
||||
<p className="text-muted-foreground mt-1">
|
||||
Recherchez parmi des millions de produits sur Amazon.fr
|
||||
</p>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{/* Search Form */}
|
||||
<Card>
|
||||
<CardContent className="pt-6">
|
||||
<form onSubmit={handleSearch} className="space-y-4">
|
||||
<div className="flex gap-2">
|
||||
<div className="relative flex-1">
|
||||
<SearchIcon className="absolute left-3 top-3 h-4 w-4 text-muted-foreground" />
|
||||
<Input
|
||||
type="text"
|
||||
placeholder="Rechercher un produit sur Amazon..."
|
||||
value={query}
|
||||
onChange={(e) => setQuery(e.target.value)}
|
||||
className="pl-9"
|
||||
disabled={isSearching}
|
||||
/>
|
||||
</div>
|
||||
<Button type="submit" disabled={isSearching || !query.trim()}>
|
||||
{isSearching ? (
|
||||
<>
|
||||
<Loader2 className="h-4 w-4 mr-2 animate-spin" />
|
||||
Recherche...
|
||||
</>
|
||||
) : (
|
||||
<>
|
||||
<SearchIcon className="h-4 w-4 mr-2" />
|
||||
Rechercher
|
||||
</>
|
||||
)}
|
||||
</Button>
|
||||
</div>
|
||||
|
||||
{/* Info */}
|
||||
<div className="flex items-center gap-2 text-sm text-muted-foreground">
|
||||
<div className="flex items-center gap-1">
|
||||
<div className="h-2 w-2 rounded-full bg-green-500"></div>
|
||||
<span>Anti-détection activé</span>
|
||||
</div>
|
||||
<span>•</span>
|
||||
<span>Max 20 résultats</span>
|
||||
</div>
|
||||
</form>
|
||||
</CardContent>
|
||||
</Card>
|
||||
|
||||
{/* Progress Bar */}
|
||||
{progress && isSearching && (
|
||||
<Card>
|
||||
<CardContent className="pt-6">
|
||||
<div className="space-y-2">
|
||||
<div className="flex justify-between text-sm">
|
||||
<span>{progress.message || 'Recherche en cours...'}</span>
|
||||
<span>{progressPercent}%</span>
|
||||
</div>
|
||||
<Progress value={progressPercent} />
|
||||
</div>
|
||||
</CardContent>
|
||||
</Card>
|
||||
)}
|
||||
|
||||
{/* Results */}
|
||||
{results.length > 0 && (
|
||||
<div className="space-y-4">
|
||||
<div className="flex items-center justify-between">
|
||||
<h3 className="text-lg font-semibold">
|
||||
{results.length} produit{results.length > 1 ? 's' : ''} trouvé{results.length > 1 ? 's' : ''}
|
||||
</h3>
|
||||
</div>
|
||||
<div className="grid gap-4 sm:grid-cols-2 lg:grid-cols-3 xl:grid-cols-4">
|
||||
{results.map((product, index) => (
|
||||
<Card key={index} className="overflow-hidden hover:shadow-lg transition-shadow">
|
||||
<CardContent className="p-0">
|
||||
{/* Image */}
|
||||
{product.image_url && (
|
||||
<div className="relative aspect-square bg-gray-50 flex items-center justify-center p-4">
|
||||
<img
|
||||
src={product.image_url}
|
||||
alt={product.title}
|
||||
className="max-h-full max-w-full object-contain"
|
||||
/>
|
||||
{product.sponsored && (
|
||||
<Badge
|
||||
variant="secondary"
|
||||
className="absolute top-2 left-2 text-xs"
|
||||
>
|
||||
Sponsorisé
|
||||
</Badge>
|
||||
)}
|
||||
{!product.in_stock && (
|
||||
<Badge
|
||||
variant="destructive"
|
||||
className="absolute top-2 right-2 text-xs"
|
||||
>
|
||||
Indisponible
|
||||
</Badge>
|
||||
)}
|
||||
</div>
|
||||
)}
|
||||
|
||||
<div className="p-4 space-y-3">
|
||||
{/* Title */}
|
||||
<h4 className="font-medium text-sm line-clamp-2 min-h-[2.5rem]">
|
||||
{product.title}
|
||||
</h4>
|
||||
|
||||
{/* Rating */}
|
||||
{renderRating(product.rating, product.reviews_count)}
|
||||
|
||||
{/* Price */}
|
||||
<div className="pt-2">
|
||||
{formatPrice(product.price, product.original_price)}
|
||||
</div>
|
||||
|
||||
{/* Badges */}
|
||||
<div className="flex flex-wrap gap-1">
|
||||
{product.prime && (
|
||||
<Badge variant="default" className="bg-blue-500 text-xs">
|
||||
Prime
|
||||
</Badge>
|
||||
)}
|
||||
{product.in_stock && (
|
||||
<Badge variant="outline" className="text-xs text-green-600 border-green-600">
|
||||
En stock
|
||||
</Badge>
|
||||
)}
|
||||
</div>
|
||||
|
||||
{/* Actions */}
|
||||
<div className="pt-2 flex gap-2">
|
||||
<Button
|
||||
variant="default"
|
||||
size="sm"
|
||||
className="flex-1"
|
||||
onClick={() => window.open(product.url, '_blank')}
|
||||
>
|
||||
<ShoppingCart className="h-4 w-4 mr-1" />
|
||||
Voir
|
||||
</Button>
|
||||
<Button
|
||||
variant="outline"
|
||||
size="sm"
|
||||
onClick={() => window.open(product.url, '_blank')}
|
||||
>
|
||||
<ExternalLink className="h-4 w-4" />
|
||||
</Button>
|
||||
</div>
|
||||
</div>
|
||||
</CardContent>
|
||||
</Card>
|
||||
))}
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
|
||||
{/* Empty State */}
|
||||
{!isSearching && results.length === 0 && !progress && (
|
||||
<Card>
|
||||
<CardContent className="py-12 text-center">
|
||||
<div className="mx-auto mb-4 h-16 w-16 rounded-full bg-orange-50 flex items-center justify-center">
|
||||
<SearchIcon className="h-8 w-8 text-orange-500" />
|
||||
</div>
|
||||
<h3 className="text-lg font-medium mb-2">Recherchez sur Amazon France</h3>
|
||||
<p className="text-muted-foreground max-w-md mx-auto">
|
||||
Entrez un terme de recherche pour trouver des produits sur Amazon.fr.
|
||||
Notre système anti-détection garantit un accès fiable aux résultats.
|
||||
</p>
|
||||
</CardContent>
|
||||
</Card>
|
||||
)}
|
||||
|
||||
{/* No Results */}
|
||||
{!isSearching && results.length === 0 && progress?.status === 'completed' && (
|
||||
<Card>
|
||||
<CardContent className="py-12 text-center">
|
||||
<SearchIcon className="h-12 w-12 mx-auto text-muted-foreground mb-4" />
|
||||
<h3 className="text-lg font-medium mb-2">Aucun produit trouvé</h3>
|
||||
<p className="text-muted-foreground">
|
||||
Essayez avec d'autres termes de recherche
|
||||
</p>
|
||||
</CardContent>
|
||||
</Card>
|
||||
)}
|
||||
</div>
|
||||
);
|
||||
}
|
||||
Executable
+173
@@ -0,0 +1,173 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Script de test pour le scraper Amazon France
|
||||
Teste le système anti-détection et l'extraction des produits
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
import logging
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
# Ajouter le répertoire app au path
|
||||
sys.path.insert(0, str(Path(__file__).parent))
|
||||
|
||||
from app.services.amazon_scraper import (
|
||||
scrape_amazon_search,
|
||||
test_amazon_scraper,
|
||||
)
|
||||
|
||||
# Configuration du logging
|
||||
logging.basicConfig(
|
||||
level=logging.INFO,
|
||||
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
|
||||
)
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
async def test_basic_search():
|
||||
"""Test basique de recherche"""
|
||||
logger.info("=" * 80)
|
||||
logger.info("TEST 1: Recherche basique - 'aspirateur'")
|
||||
logger.info("=" * 80)
|
||||
|
||||
products = await scrape_amazon_search("aspirateur", max_results=5)
|
||||
|
||||
if not products:
|
||||
logger.error("❌ Aucun produit trouvé - possibilité de détection ou problème réseau")
|
||||
return False
|
||||
|
||||
logger.info(f"✅ {len(products)} produits trouvés")
|
||||
|
||||
for idx, product in enumerate(products, 1):
|
||||
logger.info(f"\n{idx}. {product.title[:60]}...")
|
||||
logger.info(f" 💰 Prix: {product.price}€" + (f" (était {product.original_price}€)" if product.original_price else ""))
|
||||
logger.info(f" ⭐ Note: {product.rating}/5" if product.rating else " ⭐ Pas de note")
|
||||
logger.info(f" 📦 {'En stock' if product.in_stock else 'Indisponible'}")
|
||||
logger.info(f" {'🚚 Prime' if product.prime else '📮 Standard'}")
|
||||
logger.info(f" {'📢 Sponsorisé' if product.sponsored else '🔍 Organique'}")
|
||||
|
||||
return True
|
||||
|
||||
|
||||
async def test_multiple_queries():
|
||||
"""Test avec plusieurs requêtes différentes"""
|
||||
logger.info("\n" + "=" * 80)
|
||||
logger.info("TEST 2: Requêtes multiples")
|
||||
logger.info("=" * 80)
|
||||
|
||||
queries = ["clavier", "souris", "casque"]
|
||||
results = {}
|
||||
|
||||
for query in queries:
|
||||
logger.info(f"\n🔍 Recherche: '{query}'")
|
||||
products = await scrape_amazon_search(query, max_results=3)
|
||||
results[query] = len(products)
|
||||
logger.info(f" ✅ {len(products)} produits trouvés")
|
||||
|
||||
# Délai entre requêtes pour respecter les bonnes pratiques
|
||||
await asyncio.sleep(3)
|
||||
|
||||
logger.info("\n📊 Résumé:")
|
||||
for query, count in results.items():
|
||||
logger.info(f" • {query}: {count} produits")
|
||||
|
||||
total = sum(results.values())
|
||||
if total > 0:
|
||||
logger.info(f"\n✅ Total: {total} produits extraits")
|
||||
return True
|
||||
else:
|
||||
logger.error("\n❌ Aucun produit extrait - problème possible")
|
||||
return False
|
||||
|
||||
|
||||
async def test_anti_detection():
|
||||
"""Test du système anti-détection"""
|
||||
logger.info("\n" + "=" * 80)
|
||||
logger.info("TEST 3: Vérification anti-détection")
|
||||
logger.info("=" * 80)
|
||||
|
||||
from app.core.search_config import AMAZON_PROXY_LIST_RAW, USER_AGENT_POOL
|
||||
from app.services.amazon_scraper import get_random_proxy, AMAZON_USER_AGENTS
|
||||
|
||||
logger.info(f"✓ {len(AMAZON_PROXY_LIST_RAW)} proxies disponibles")
|
||||
logger.info(f"✓ {len(USER_AGENT_POOL)} User-Agents standards")
|
||||
logger.info(f"✓ {len(AMAZON_USER_AGENTS)} User-Agents Amazon spécifiques")
|
||||
|
||||
# Test proxy
|
||||
proxy = get_random_proxy()
|
||||
if proxy:
|
||||
# Extract just the IP for logging (hide credentials)
|
||||
proxy_parts = proxy.split('@')
|
||||
proxy_server = proxy_parts[1] if len(proxy_parts) > 1 else proxy
|
||||
logger.info(f"✓ Proxy test: {proxy_server}")
|
||||
else:
|
||||
logger.warning("⚠️ Pas de proxy configuré")
|
||||
|
||||
# Test d'une recherche simple
|
||||
logger.info("\n🧪 Test de recherche avec anti-détection...")
|
||||
products = await scrape_amazon_search("livre", max_results=3)
|
||||
|
||||
if products:
|
||||
logger.info(f"✅ Anti-détection fonctionnel - {len(products)} produits extraits")
|
||||
return True
|
||||
else:
|
||||
logger.error("❌ Échec - possibilité de blocage")
|
||||
return False
|
||||
|
||||
|
||||
async def run_all_tests():
|
||||
"""Lance tous les tests"""
|
||||
logger.info("\n" + "=" * 80)
|
||||
logger.info("🚀 DÉMARRAGE DES TESTS DU SCRAPER AMAZON FRANCE")
|
||||
logger.info("=" * 80)
|
||||
|
||||
tests = [
|
||||
("Recherche basique", test_basic_search),
|
||||
("Requêtes multiples", test_multiple_queries),
|
||||
("Anti-détection", test_anti_detection),
|
||||
]
|
||||
|
||||
results = {}
|
||||
|
||||
for test_name, test_func in tests:
|
||||
try:
|
||||
logger.info(f"\n▶️ Exécution: {test_name}")
|
||||
success = await test_func()
|
||||
results[test_name] = "✅ PASS" if success else "❌ FAIL"
|
||||
except Exception as e:
|
||||
logger.error(f"❌ Erreur dans {test_name}: {e}", exc_info=True)
|
||||
results[test_name] = "❌ ERROR"
|
||||
|
||||
# Résumé final
|
||||
logger.info("\n" + "=" * 80)
|
||||
logger.info("📊 RÉSUMÉ DES TESTS")
|
||||
logger.info("=" * 80)
|
||||
|
||||
for test_name, result in results.items():
|
||||
logger.info(f"{result} - {test_name}")
|
||||
|
||||
passed = sum(1 for r in results.values() if "PASS" in r)
|
||||
total = len(results)
|
||||
|
||||
logger.info(f"\n🎯 Score: {passed}/{total} tests réussis")
|
||||
|
||||
if passed == total:
|
||||
logger.info("✅ TOUS LES TESTS ONT RÉUSSI!")
|
||||
return True
|
||||
else:
|
||||
logger.warning("⚠️ Certains tests ont échoué")
|
||||
return False
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
try:
|
||||
success = asyncio.run(run_all_tests())
|
||||
sys.exit(0 if success else 1)
|
||||
except KeyboardInterrupt:
|
||||
logger.info("\n⏸️ Tests interrompus par l'utilisateur")
|
||||
sys.exit(130)
|
||||
except Exception as e:
|
||||
logger.error(f"❌ Erreur fatale: {e}", exc_info=True)
|
||||
sys.exit(1)
|
||||
Reference in new issue
Block a user