Merge pull request #146 from R0m1k3/claude/amazon-france-search-page-01KmPqbdPCqxWXxEoFw9jgFo

Claude/amazon france search page 01 km pqbd p cqx w xx eo fw9jg fo
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LogiFlow authored and GitHub committed 2025-11-30 01:53:59 +01:00
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@@ -13,7 +13,7 @@ from sqlalchemy import text
from app.database import SessionLocal, engine
from app.limiter import limiter
from app.routers import auth, items, jobs, notifications, openrouter, search, search_sites, settings, debug, catalogues
from app.routers import auth, items, jobs, notifications, openrouter, search, search_sites, settings, debug, catalogues, amazon
from app.services.scheduler_service import scheduled_refresh, scheduler
from app.services import auth_service, search_service, seed_enseignes
from app.services.scheduler import start_scheduler as start_catalog_scheduler, stop_scheduler as stop_catalog_scheduler
@@ -190,6 +190,9 @@ app.include_router(catalogues.router)
# Auth router (already has /api prefix)
app.include_router(auth.router)
# Amazon router (already has /api prefix)
app.include_router(amazon.router)
@app.get("/api/")
def read_root():
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"""
API Router pour la recherche Amazon France
Utilise Server-Sent Events (SSE) pour le streaming des résultats
"""
import json
import logging
from typing import AsyncGenerator
from fastapi import APIRouter, Query
from fastapi.responses import StreamingResponse
from pydantic import BaseModel
from app.services.amazon_scraper import scrape_amazon_search, AmazonProduct
logger = logging.getLogger(__name__)
router = APIRouter(prefix="/api/amazon", tags=["amazon"])
class AmazonSearchProgress(BaseModel):
"""Progress model for SSE streaming"""
status: str # 'searching', 'completed', 'error'
total: int
completed: int
message: str
results: list[dict]
@router.get("/search")
async def search_amazon(
q: str = Query(..., min_length=1, description="Terme de recherche"),
max_results: int = Query(20, ge=1, le=50, description="Nombre max de résultats"),
):
"""
Recherche de produits sur Amazon France.
Retourne un flux SSE avec les résultats.
Format des événements SSE:
- event: progress
- data: {"status": "...", "total": 1, "completed": 0/1, "results": [...]}
"""
async def generate() -> AsyncGenerator[str, None]:
try:
# Initial progress
progress = AmazonSearchProgress(
status="searching",
total=1,
completed=0,
message=f"Recherche sur Amazon France: '{q}'...",
results=[]
)
yield f"event: progress\ndata: {progress.model_dump_json()}\n\n"
# Execute search
logger.info(f"Starting Amazon search for: {q}")
products = await scrape_amazon_search(q, max_results=max_results)
# Convert to dict
results = [p.model_dump() for p in products]
# Final progress
if results:
progress = AmazonSearchProgress(
status="completed",
total=1,
completed=1,
message=f"✅ {len(results)} produits trouvés",
results=results
)
else:
progress = AmazonSearchProgress(
status="completed",
total=1,
completed=1,
message="Aucun produit trouvé",
results=[]
)
yield f"event: progress\ndata: {progress.model_dump_json()}\n\n"
except Exception as e:
logger.error(f"Error during Amazon search: {e}", exc_info=True)
error_progress = AmazonSearchProgress(
status="error",
total=1,
completed=1,
message=f"Erreur: {str(e)}",
results=[]
)
yield f"event: progress\ndata: {error_progress.model_dump_json()}\n\n"
return StreamingResponse(
generate(),
media_type="text/event-stream",
headers={
"Cache-Control": "no-cache",
"Connection": "keep-alive",
"X-Accel-Buffering": "no",
},
)
@router.get("/health")
async def amazon_health():
"""Vérifie que le service Amazon est opérationnel"""
return {
"status": "ok",
"service": "Amazon France Scraper",
"anti_detection": "enabled",
"features": [
"User-Agent rotation",
"Proxy rotation (10 proxies)",
"Random delays",
"Realistic headers",
"Crawl4AI anti-detection"
]
}
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"""
Amazon France Scraper Service - Powered by Crawl4AI
Anti-bot detection techniques:
- Realistic User-Agent rotation
- Complete HTTP headers mimicking real browsers
- Proxy rotation (10 residential proxies)
- Random delays between requests
- Browser fingerprint randomization
- Cookie persistence
- NetworkIdle waiting for complete page load
"""
import asyncio
import hashlib
import logging
import random
import re
from datetime import datetime
from typing import Any
from urllib.parse import quote_plus
from bs4 import BeautifulSoup
from crawl4ai import AsyncWebCrawler, BrowserConfig, CrawlerRunConfig, CacheMode
from pydantic import BaseModel, Field
from app.core.search_config import AMAZON_PROXY_LIST_RAW, USER_AGENT_POOL
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}"
# Additional realistic User-Agents specifically for Amazon
AMAZON_USER_AGENTS = [
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36",
"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",
"Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:133.0) Gecko/20100101 Firefox/133.0",
"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",
"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",
]
# Realistic browser headers to avoid bot detection
def get_realistic_headers(user_agent: str) -> dict:
"""Generate realistic browser headers"""
return {
"Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8",
"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",
"Sec-Fetch-Dest": "document",
"Sec-Fetch-Mode": "navigate",
"Sec-Fetch-Site": "none",
"Sec-Fetch-User": "?1",
"Cache-Control": "max-age=0",
"User-Agent": user_agent,
}
def get_random_proxy() -> dict | None:
"""Get a random proxy from the pool"""
if not AMAZON_PROXY_LIST_RAW:
return None
proxy_str = random.choice(AMAZON_PROXY_LIST_RAW)
parts = proxy_str.split(":")
if len(parts) == 4:
return {
"server": f"http://{parts[0]}:{parts[1]}",
"username": parts[2],
"password": parts[3]
}
return None
async def random_delay(min_seconds: float = 1.5, max_seconds: float = 4.0):
"""Add random delay to mimic human behavior"""
delay = random.uniform(min_seconds, max_seconds)
logger.debug(f"Human-like delay: {delay:.2f}s")
await asyncio.sleep(delay)
# ============================================================================
# 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 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]}...")
# Select random proxy
proxy = get_random_proxy()
if proxy:
logger.debug(f"🌐 Using proxy: {proxy['server']}")
else:
logger.warning("⚠️ No proxy available - may face rate limiting")
# Configure Crawl4AI browser with anti-detection
browser_config = BrowserConfig(
headless=True,
verbose=False,
user_agent=user_agent,
proxy=proxy,
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')
# 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:
continue
# 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:
continue
title = title_elem.get_text(strip=True)
# Extract URL
link_elem = card.select_one('h2 a')
if not link_elem:
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())
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@@ -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:
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# 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
+2
View File
@@ -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"
+2 -1
View File
@@ -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' },
];
+323
View File
@@ -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>
);
}
+170
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@@ -0,0 +1,170 @@
#!/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:
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)