Merge pull request #249 from R0m1k3/antigravity

Antigravity

app/services/scheduler_service.py

@@ -220,28 +220,56 @@ async def process_item_check(item_id: int):
         # Check for notifications
         if item_data["notification_channel"] and extraction.price:
             channel = item_data["notification_channel"]
+            logger.info(f"📢 Notification check for item {item_id}: old_price={old_price}, new_price={extraction.price}, target_price={item_data['target_price']}")
             
-            # 1. Target Price Reached
-            if item_data["target_price"] and extraction.price <= item_data["target_price"]:
-                # Only notify if we haven't already notified for this price (or if price dropped further)
-                # For simplicity, we notify if current price <= target. 
-                # Ideally we should check if we already notified recently, but let's keep it simple.
-                if not old_price or old_price > item_data["target_price"]:
-                    await NotificationService.send_notification(
-                        channel,
-                        title=f"🎯 Prix cible atteint : {item_data['name']}",
-                        body=f"Le prix de {item_data['name']} est passé à {extraction.price}€ (Cible: {item_data['target_price']}€)\n{item_data['url']}"
-                    )
+            notification_sent = False
             
-            # 2. Price Drop
-            elif old_price and extraction.price < old_price:
-                drop_percent = (old_price - extraction.price) / old_price * 100
-                if drop_percent >= 5:  # Notify only for significant drops (> 5%)
+            # CASE 1: Target price is set -> notify only when target is reached
+            if item_data["target_price"]:
+                if extraction.price <= item_data["target_price"]:
+                    # Only notify if we haven't already notified for this price
+                    if not old_price or old_price > item_data["target_price"]:
+                        logger.info(f"✅ Target price reached for {item_data['name']}: {extraction.price}€ <= {item_data['target_price']}€")
+                        await NotificationService.send_notification(
+                            channel,
+                            title=f"🎯 Prix cible atteint : {item_data['name']}",
+                            body=f"Le prix de {item_data['name']} est passé à {extraction.price}€ (Cible: {item_data['target_price']}€)\n{item_data['url']}"
+                        )
+                        notification_sent = True
+                else:
+                    logger.info(f"ℹ️ Price {extraction.price}€ not yet at target {item_data['target_price']}€")
+            
+            # CASE 2: No target price -> notify on ANY price drop
+            else:
+                if old_price and extraction.price < old_price:
+                    drop_percent = (old_price - extraction.price) / old_price * 100
+                    logger.info(f"📉 Price drop detected for {item_data['name']}: {drop_percent:.1f}%")
                     await NotificationService.send_notification(
                         channel,
                         title=f"📉 Baisse de prix : {item_data['name']}",
                         body=f"Le prix de {item_data['name']} a baissé de {drop_percent:.1f}% !\nNouveau prix : {extraction.price}€ (Ancien: {old_price}€)\n{item_data['url']}"
                     )
+                    notification_sent = True
+                
+                # Also notify on significant price increases (>= 5%)
+                elif old_price and extraction.price > old_price:
+                    increase_percent = (extraction.price - old_price) / old_price * 100
+                    if increase_percent >= 5:
+                        logger.info(f"📈 Price increase detected for {item_data['name']}: {increase_percent:.1f}%")
+                        await NotificationService.send_notification(
+                            channel,
+                            title=f"📈 Hausse de prix : {item_data['name']}",
+                            body=f"Le prix de {item_data['name']} a augmenté de {increase_percent:.1f}%.\nNouveau prix : {extraction.price}€ (Ancien: {old_price}€)\n{item_data['url']}"
+                        )
+                        notification_sent = True
+            
+            if not notification_sent:
+                logger.info(f"ℹ️ No notification triggered for item {item_id} (no significant change)")
+        else:
+            if not item_data["notification_channel"]:
+                logger.debug(f"⚠️ Item {item_id} has no notification channel assigned.")
+            if not extraction.price:
+                logger.debug(f"⚠️ Item {item_id} has no extracted price.")
 
 
 

app/services/tracking_scraper_service.py

@@ -23,7 +23,7 @@ POPUP_SELECTORS = [
     "button:has-text('No thanks')",
     "a:has-text('No, thanks')",
     "div[role='dialog'] button[aria-label='Close']",
-    # Amazon Interstitials (Added for robustness)
+    # Amazon Interstitials & Cookies
     "button:has-text('Continuer les achats')",
     "span:has-text('Continuer les achats')",
     "a:has-text('Continuer les achats')",
@@ -32,13 +32,17 @@ POPUP_SELECTORS = [
     "span.a-button-inner > input.a-button-input[type='submit']",
     "form:has-text('Continuer les achats') input[type='submit']",
     "[aria-labelledby='continue-shopping-label']",
+    "#sp-cc-accept",
+    "#sp-cc-rejectall-link",
+    "button[data-action='a-popover-close']",
+    "[data-action='sp-cc-accept']",
+    "input[aria-labelledby='sp-cc-accept-label']",
     # Didomi / Gifi
     "#didomi-notice-agree-button",
     "button[id='didomi-notice-agree-button']",
     "span:has-text('Accepter & Fermer')",
     "button:has-text('Accepter & Fermer')",
     # Common banners
-    "#sp-cc-accept",
     "#onetrust-accept-btn-handler",
     ".cookie-consent-accept",
     "[data-action='accept-cookies']",
@@ -148,6 +152,10 @@ class ScraperService:
             return None, "", url, ""
 
         try:
+            # SPECIALIZED AMAZON HANDLING
+            if "amazon" in url:
+                return await ScraperService._scrape_amazon_specific(url, item_id, config, return_html)
+
             context = await ScraperService._create_context(ScraperService._browser, url)
             page = await context.new_page()
 
@@ -222,6 +230,103 @@ class ScraperService:
             logger.error(f"Error scraping {url}: {e}")
             return None, "", url, ""
 
+    @staticmethod
+    async def _scrape_amazon_specific(
+        url: str,
+        item_id: int | None,
+        config: ScrapeConfig,
+        return_html: bool
+    ) -> tuple[str | None, str, str, str]:
+        """
+        Specialized scraping flow for Amazon to avoid bot detection and ensure good screenshots.
+        Strategy:
+        1. Emulate human visiting homepage first
+        2. Navigate to product
+        3. Aggressively handle popups
+        4. Wait for main image to be visible
+        """
+        logger.info(f"🛒 Starting specialized Amazon scrape for: {url}")
+        
+        # Determine base domain
+        from urllib.parse import urlparse
+        parsed = urlparse(url)
+        base_domain = f"{parsed.scheme}://{parsed.netloc}"
+        
+        context = await ScraperService._create_context(ScraperService._browser, url)
+        page = await context.new_page()
+        
+        try:
+            # 1. Warm-up: Visit Homepage to get cookies/session
+            try:
+                logger.info(f"🏠 Visiting {base_domain} to establish authentic session...")
+                await page.goto(base_domain, wait_until="domcontentloaded", timeout=30000)
+                await asyncio.sleep(2)
+                await ScraperService._handle_popups(page)
+            except Exception as e:
+                logger.warning(f"Homepage warm-up failed (continuing anyway): {e}")
+
+            # 2. Navigate to Product
+            logger.info(f"➡️ Navigating to product page: {url}")
+            await page.goto(url, wait_until="domcontentloaded", timeout=60000)
+            
+            final_url = page.url
+            try:
+                page_title = await page.title()
+            except:
+                page_title = "Amazon Product"
+
+            # 3. Check for Bot Detection / CAPTCHA
+            content_check = await page.content()
+            if "Type the characters you see in this image" in content_check or "Saisissez les caractères que vous voyez" in content_check:
+                logger.error("🚫 Amazon CAPTCHA detected!")
+                # Attempt refresh once
+                logger.info("Retrying with refresh...")
+                await page.reload()
+                await asyncio.sleep(3)
+
+            # 4. Handle Popups & Location Selectors
+            await ScraperService._handle_popups(page)
+            
+            # Dismiss "Change Address" or specific Amazon location modals if any
+            try:
+                await page.evaluate("document.getElementById('nav-main')?.classList.remove('nav-progressive-attribute')")
+            except: pass
+
+            # 5. Wait for Main Image (Critical for screenshot)
+            logger.info("🖼️ Waiting for product image...")
+            try:
+                # Main image container on desktop
+                await page.wait_for_selector(
+                    "#imgTagWrapperId, #landingImage, #main-image-container, .imgTagWrapper", 
+                    timeout=10000
+                )
+            except Exception as e:
+                logger.warning(f"Could not find main image container: {e}")
+
+            # 6. Smart User Behavior (Scroll to trigger lazy loading)
+            if config.smart_scroll:
+                await ScraperService._smart_scroll(page, config.scroll_pixels)
+                # Scroll back up to header for good screenshot
+                await page.evaluate("window.scrollTo(0, 0)")
+                await asyncio.sleep(1)
+
+            # 7. Extract Data
+            if return_html:
+                content_data = await page.content()
+            else:
+                content_data = await ScraperService._extract_text(page, config.text_length)
+                
+            # 8. Screenshot
+            screenshot_path = await ScraperService._take_screenshot(page, url, item_id)
+            
+            return screenshot_path, content_data, final_url, page_title
+
+        except Exception as e:
+            logger.error(f"❌ Amazon specific scrape failed: {e}")
+            return None, "", url, ""
+        finally:
+            await context.close()
+
     @staticmethod
     async def _connect_browser(p) -> Browser:
         logger.info(f"Connecting to Browserless at {BROWSERLESS_URL}")