feat(scraping): enhance job scraping with session persistence and feedback system

- Add config module for spoof data management
- Implement session persistence to reuse authenticated sessions
- Add feedback system to track success rates and adjust fingerprinting
- Improve job link collection with pagination and scroll detection
- Separate verified/unverified job listings into different folders
- Enhance error handling for CAPTCHA and Cloudflare challenges

config.py

@@ -0,0 +1,39 @@
+
+import os
+import json
+
+
+def load_spoof_config():
+    """Load spoof data from JSON config file. Falls back to defaults if missing."""
+    config_path = os.path.join(os.path.dirname(__file__), "spoof_config.json")
+    
+    if os.path.exists(config_path):
+        with open(config_path, "r", encoding="utf-8") as f:
+            return json.load(f)
+    else:
+        # Generate default config file on first run
+        default_config = {
+            "renderers": {
+                "windows": [
+                    "ANGLE (Intel, Intel(R) UHD Graphics 630 (0x00003E9B) Direct3D11 vs_5_0 ps_5_0, D3D11)",
+                    "ANGLE (Intel, Intel(R) UHD Graphics (0x00009A49) Direct3D11 vs_5_0 ps_5_0, D3D11)",
+                    "ANGLE (Intel(R) Iris(TM) Graphics 540 Direct3D11 vs_5_0 ps_5_0)",
+                    "ANGLE (Intel, Intel(R) UHD Graphics 620 (0x00005916) Direct3D11 vs_5_0 ps_5_0, D3D11)",
+                    "ANGLE (Intel, Intel(R) HD Graphics 530 (0x0000191B) Direct3D11 vs_5_0 ps_5_0, D3D11)",
+                    "ANGLE (Intel, Intel(R) UHD Graphics 600 (0x00003180) Direct3D11 vs_5_0 ps_5_0, D3D11)",
+                    "ANGLE (Intel, Intel(R) Iris(R) Xe Graphics (0x00009A49) Direct3D11 vs_5_0 ps_5_0, D3D11)",
+                ],
+                "macos": [
+                    "Intel HD Graphics 530 OpenGL Engine",
+                    "Intel Iris Graphics 6100 OpenGL Engine",
+                    "Intel UHD Graphics 630 OpenGL Engine",
+                    "Intel HD Graphics 4000 OpenGL Engine",
+                    "Intel Iris Pro OpenGL Engine",
+                    "Intel UHD Graphics 617 OpenGL Engine",
+                ]
+            },
+            "vendors": ["Intel Inc.", "Intel", "Intel Corporation"]
+        }
+        with open(config_path, "w", encoding="utf-8") as f:
+            json.dump(default_config, f, indent=2)
+        return default_config

job_scraper.py

@@ -1,4 +1,5 @@
 
+
 import asyncio
 import random
 import sqlite3
@@ -114,24 +115,22 @@ class LinkedInJobScraper:
                 pass
             return "N/A"
 
-        # Try multiple strategies for each field
+        title = await get_text("h1.t-24")
-        title = await get_text("h1.t-24")  # LinkedIn
         if title == "N/A":
-            title = await get_text("h1, h2")  # External
+            title = await get_text("h1, h2")
 
-        company = await get_text("a.app-aware-link[href*='/company/']")  # LinkedIn
+        company = await get_text("a.app-aware-link[href*='/company/']")
         if company == "N/A":
-            company = await get_text("div.org, .company, [class*='company']")  # External
+            company = await get_text("div.org, .company, [class*='company']")
 
-        location = await get_text("span[class*='location']")  # LinkedIn
+        location = await get_text("span[class*='location']")
         if location == "N/A":
             location = await get_text(".location, [class*='location']")
 
-        description = await get_text("div[class*='description__text']")  # LinkedIn
+        description = await get_text("div[class*='description__text']")
         if description == "N/A":
             description = await get_text(".job-desc, .description, main, body")
 
-        # Workplace & salary — LinkedIn only (external may not have)
         workplace = await get_text("span.job-workplace-type") or "N/A"
         salary = await get_text("span.salary") or "N/A"
 
@@ -145,19 +144,39 @@ class LinkedInJobScraper:
             "url": page.url
         }
 
-    async def _save_to_markdown(self, job_data: Dict, keyword: str):
+    async def _save_to_markdown(self, job_data: Dict, keyword: str, verified: bool=True):
-        os.makedirs("linkedin_jobs", exist_ok=True)
+        """Save to appropriate folder using job ID to avoid duplication"""
-        clean_keyword = keyword.replace(" ", "_")
+        folder = "linkedin_jobs" if verified else "linkedin_jobs_unverified"
-        filename = f"linkedin_{clean_keyword}_{datetime.now().strftime('%Y%m%d_%H%M%S')}.md"
+        os.makedirs(folder, exist_ok=True)
-        filepath = os.path.join("linkedin_jobs", filename)
         
+        # Extract job ID from URL for LinkedIn jobs
+        url = job_data.get("url", "")
+        if "/jobs/view/" in url:
+            try:
+                job_id = url.split("/view/")[1].split("/")[0]
+            except:
+                job_id = "unknown"
+        else:
+            # For external jobs, use a hash of the URL (first 12 chars)
+            import hashlib
+            job_id = hashlib.md5(url.encode()).hexdigest()[:12]
+        
+        clean_keyword = keyword.replace(" ", "_")
+        filename = f"linkedin_{clean_keyword}_job_{job_id}.md"
+        filepath = os.path.join(folder, filename)
+        
+        # Only save if file doesn't already exist (idempotent)
+        if os.path.exists(filepath):
+            print(f"  📝 Skipping duplicate Markdown file: {filename}")
+            return
+
         with open(filepath, "w", encoding="utf-8") as f:
             f.write(f"# {job_data['title']}\n\n")
             f.write(f"- **Company**: {job_data['company']}\n")
             f.write(f"- **Location**: {job_data['location']}\n")
             f.write(f"- **Workplace**: {job_data['workplace_type']}\n")
             f.write(f"- **Salary**: {job_data['salary']}\n")
-            f.write(f"- **URL**: <{job_data['url']}>\n\n")
+            f.write(f"- **URL**: <{url}>\n\n")
             f.write(f"## Description\n\n{job_data['description']}\n")
 
     async def _save_to_db(self, job_data: Dict, keyword: str):
@@ -208,59 +227,176 @@ class LinkedInJobScraper:
             await context.add_init_script(spoof_script)
 
             page = await context.new_page()
-            
+
-            if credentials:
+            session_loaded = await self.engine.load_session(context)
-                print("🔐 Attempting LinkedIn login...")
+            login_successful = False
-                if not await self._login(page, credentials):
+
+            if session_loaded:
+                print("🔁 Using saved session — verifying login...")
+                await page.goto("https://www.linkedin.com/feed/", timeout=60000)
+                if "feed" in page.url and "login" not in page.url:
+                    print("✅ Session still valid.")
+                    login_successful = True
+                else:
+                    print("⚠️ Saved session expired — re-authenticating.")
+                    session_loaded = False
+
+            if not session_loaded and credentials:
+                print("🔐 Performing fresh login...")
+                login_successful = await self._login(page, credentials)
+                if login_successful:
+                    await self.engine.save_session(context)
+                else:
                     print("❌ Login failed. Exiting.")
                     await browser.close()
+                    self.engine.report_outcome("block")
                     return
-            else:
+            elif not credentials:
                 print("ℹ️ No credentials — proceeding as guest.")
+                login_successful = True
+            else:
+                pass
+
+            await page.wait_for_load_state("load", timeout=60000)
+            print("✅ Post-login page fully loaded. Starting search...")
+
+            if await self.engine._detect_cloudflare(page):
+                print("☁️ Cloudflare detected on initial load.")
+                if not await self.engine._handle_cloudflare(page):
+                    print("❌ Cloudflare could not be resolved.")
+                    await browser.close()
+                    self.engine.report_outcome("cloudflare")
+                    return
 
             print(f"🔍 Searching for: {search_keywords}")
             await page.goto(search_url, wait_until='load', timeout=60000)
             await asyncio.sleep(random.uniform(4.0, 6.0) * self.human_speed)
 
+            if await self.engine._detect_cloudflare(page):
+                print("☁️ Cloudflare detected on search page.")
+                if not await self.engine._handle_cloudflare(page):
+                    await browser.close()
+                    self.engine.report_outcome("cloudflare")
+                    return
+
             scraped_count = 0
             all_job_links = []
+            seen_job_ids = set()
 
-            # Collect job links
+            # ← NEW: Scroll once to reveal pagination (if any)
-            for page_num in range(1, max_pages + 1):
+            print("🔄 Scrolling to bottom to reveal pagination controls...")
-                print(f"📄 Collecting job links from page {page_num}/{max_pages}")
+            await page.evaluate("window.scrollTo(0, document.body.scrollHeight)")
-                for _ in range(50):
+            await asyncio.sleep(random.uniform(3.0, 5.0) * self.human_speed)
-                    links = await page.query_selector_all("a[href*='/jobs/view/']")
+
-                    if links:
+            # Check if pagination exists
-                        for link in links:
+            pagination_exists = await page.query_selector("button[aria-label='Next']")
-                            href = await link.get_attribute("href")
+            if pagination_exists:
-                            if href and href not in all_job_links:
+                print("⏭️ Pagination detected. Using page navigation.")
+                current_page = 1
+                while current_page <= max_pages:
+                    print(f"📄 Processing page {current_page}/{max_pages}")
+                    
+                    # Collect job links on current page
+                    current_links = await page.query_selector_all("a[href*='/jobs/view/']")
+                    new_jobs = 0
+                    for link in current_links:
+                        href = await link.get_attribute("href")
+                        if href:
+                            job_id = href.split("/view/")[-1].split("/")[0] if "/view/" in href else href
+                            if job_id and job_id not in seen_job_ids:
+                                seen_job_ids.add(job_id)
                                 all_job_links.append(href)
-                        break
+                                new_jobs += 1
-                    await asyncio.sleep(1)
+                    
-                print(f"   ➕ Found {len(links) if 'links' in locals() else 0} new job links.")
+                    print(f"   ➕ Found {new_jobs} new job(s) on page {current_page} (total: {len(all_job_links)})")
-                
+
-                if page_num < max_pages:
+                    # Try to go to next page
-                    next_btn = await page.query_selector("button[aria-label='Next']")
+                    if current_page < max_pages:
-                    if next_btn and await next_btn.is_enabled():
+                        next_btn = await page.query_selector("button[aria-label='Next']")
-                        await self._human_click(page, next_btn)
+                        if next_btn and await next_btn.is_enabled():
-                        await asyncio.sleep(4 * self.human_speed)
+                            await self._human_click(page, next_btn)
+                            await asyncio.sleep(random.uniform(4.0, 6.0) * self.human_speed)
+                            # Wait for URL to change or new content
+                            try:
+                                await page.wait_for_function("() => window.location.href.includes('start=')", timeout=30000)
+                            except:
+                                pass
+                        else:
+                            print("🔚 'Next' button not available — stopping pagination.")
+                            break
+                    current_page += 1
+
+            else:
+                print("🔄 No pagination found. Falling back to infinite scroll...")
+                last_height = await page.evaluate("document.body.scrollHeight")
+                no_new_jobs_count = 0
+                max_no_new = 3
+
+                while no_new_jobs_count < max_no_new:
+                    await page.evaluate("window.scrollTo(0, document.body.scrollHeight)")
+                    await asyncio.sleep(random.uniform(3.0, 5.0) * self.human_speed)
+
+                    current_links = await page.query_selector_all("a[href*='/jobs/view/']")
+                    new_jobs_found = 0
+
+                    for link in current_links:
+                        href = await link.get_attribute("href")
+                        if href:
+                            job_id = href.split("/view/")[-1].split("/")[0] if "/view/" in href else href
+                            if job_id and job_id not in seen_job_ids:
+                                seen_job_ids.add(job_id)
+                                all_job_links.append(href)
+                                new_jobs_found += 1
+
+                    print(f"   ➕ Found {new_jobs_found} new job(s) (total: {len(all_job_links)})")
+
+                    new_height = await page.evaluate("document.body.scrollHeight")
+                    if new_height == last_height:
+                        no_new_jobs_count += 1
                     else:
-                        print("🔚 No next page.")
+                        no_new_jobs_count = 0
+                        last_height = new_height
+
+                    if new_jobs_found == 0 and no_new_jobs_count >= 1:
+                        print("🔚 No new jobs loaded. Stopping scroll.")
                         break
 
-            # Process each job
+            print(f"✅ Collected {len(all_job_links)} unique job links.")
+
+            # ← Rest of job processing loop unchanged
+            scraped_count = 0
             for idx, href in enumerate(all_job_links):
                 try:
                     full_url = href if href.startswith("http") else f"https://www.linkedin.com{href}"
-                    print(f"  → Opening job {idx+1}: {full_url}")
+                    print(f"  → Opening job {idx+1}/{len(all_job_links)}: {full_url}")
                     await page.goto(full_url, wait_until='load', timeout=60000)
                     await asyncio.sleep(3 * self.human_speed)
 
-                    if not await page.query_selector("h1.t-24"):
+                    is_cloudflare = await self.engine._detect_cloudflare(page)
-                        print(f"    ⚠️ Invalid job page, skipping.")
+                    page_content = await page.content()
-                        continue
+                    has_captcha_text = "captcha" in page_content.lower()
+                    captcha_present = is_cloudflare or has_captcha_text
+
+                    title_element = await page.query_selector("h1.t-24")
+                    job_data_accessible = title_element is not None
+
+                    if captcha_present:
+                        if job_data_accessible:
+                            print("  ⚠️ CAPTCHA detected, but job data is accessible. Proceeding in stealth mode...")
+                            await self.engine._avoid_captcha(page)
+                        else:
+                            print("  ⚠️ CAPTCHA detected and job data blocked. Attempting recovery...")
+                            if not await self.engine._solve_captcha_fallback(page):
+                                print("  ❌ CAPTCHA recovery failed. Skipping job.")
+                                continue
+                            title_element = await page.query_selector("h1.t-24")
+                            if not title_element:
+                                print("  ❌ Job data still unavailable after CAPTCHA handling. Skipping.")
+                                continue
+
+                    if not captcha_present:
+                        await self.engine._avoid_captcha(page)
 
-                    # Find and click the main "Apply" button
                     apply_btn = None
                     apply_selectors = [
                         "button[aria-label*='Apply']",
@@ -273,36 +409,83 @@ class LinkedInJobScraper:
                         if apply_btn:
                             break
 
-                    if not apply_btn:
+                    job_data = None
-                        print(f"    ⚠️ No 'Apply' button found, skipping.")
+                    final_url = full_url
-                        continue
 
-                    # Click "Apply"
+                    if apply_btn:
-                    print(f"  → Clicking 'Apply' / 'Easy Apply' button...")
+                        print("  → Clicking 'Apply' / 'Easy Apply' button...")
-                    await self._human_click(page, apply_btn, wait_after=False)
+                        
-                    await asyncio.sleep(4 * self.human_speed)  # Wait for next page/form to load
+                        page_waiter = asyncio.create_task(context.wait_for_event("page"))
+                        await self._human_click(page, apply_btn, wait_after=False)
+                        
+                        external_page = None
+                        try:
+                            external_page = await asyncio.wait_for(page_waiter, timeout=5.0)
+                            print("  🌐 External job site opened in new tab.")
+                            await external_page.wait_for_load_state("load", timeout=30000)
+                            await asyncio.sleep(2 * self.human_speed)
+                            await self.engine._human_like_scroll(external_page)
+                            await asyncio.sleep(2 * self.human_speed)
+                            
+                            job_data = await self._extract_job_details(external_page)
+                            final_url = external_page.url
+                            
+                            if not external_page.is_closed():
+                                await external_page.close()
+                                
+                        except asyncio.TimeoutError:
+                            print("  🖥️ No external tab — scraping LinkedIn job page.")
+                            await page.wait_for_timeout(2000)
+                            try:
+                                await page.wait_for_selector("div.jobs-apply-button--fixed, div.jobs-easy-apply-modal", timeout=8000)
+                            except:
+                                pass
+                            await self.engine._human_like_scroll(page)
+                            await asyncio.sleep(2 * self.human_speed)
+                            job_data = await self._extract_job_details(page)
+                            final_url = page.url
+                    else:
+                        print("    ⚠️ No 'Apply' button found — scraping job details directly.")
+                        await self.engine._human_like_scroll(page)
+                        await asyncio.sleep(2 * self.human_speed)
+                        job_data = await self._extract_job_details(page)
+                        final_url = page.url
 
-                    # Now scrape WHATEVER page is displayed (Easy Apply form OR external site)
+                    job_data["url"] = final_url
-                    job_data = await self._extract_job_details(page)
-                    if job_data["title"] == "N/A" and "linkedin.com" in page.url:
-                        # On LinkedIn but no title → likely Easy Apply form; use job ID as title
-                        job_id = full_url.split("/")[-2] if "/jobs/view/" in full_url else "unknown"
-                        job_data["title"] = f"Easy Apply Job - ID {job_id}"
                     
-                    await self._save_to_db(job_data, search_keywords)
+                    if job_data["title"] == "N/A" and "linkedin.com" in final_url:
-                    await self._save_to_markdown(job_data, search_keywords)
+                        job_id = final_url.split("/")[-2] if "/jobs/view/" in final_url else "unknown"
-                    scraped_count += 1
+                        job_data["title"] = f"Easy Apply Job - ID {job_id}"
-                    domain = "LinkedIn (Easy Apply)" if "linkedin.com" in page.url else "External Site"
+
-                    print(f"  ✅ Scraped ({domain}): {job_data['title'][:50]}...")
+                    is_meaningful = (
+                        job_data["title"] != "N/A" or
+                        job_data["company"] != "N/A" or
+                        (job_data["description"] != "N/A" and len(job_data["description"]) > 20)
+                    )
+
+                    if is_meaningful:
+                        await self._save_to_db(job_data, search_keywords)
+                        await self._save_to_markdown(job_data, search_keywords, verified=True)
+                        scraped_count += 1
+                        print(f"  ✅ Scraped (verified): {job_data['title'][:50]}...")
+                    else:
+                        await self._save_to_markdown(job_data, search_keywords, verified=False)
+                        print(f"  🟡 Scraped (unverified): {final_url} — low-quality data")
 
                 except Exception as e:
                     print(f"    ⚠️ Failed on job {idx+1}: {str(e)[:100]}")
+                    continue
                 
                 finally:
-                    # Return to search results
                     print("  ↩️ Returning to LinkedIn search results...")
                     await page.goto(search_url, timeout=60000)
                     await asyncio.sleep(4 * self.human_speed)
 
             await browser.close()
-            print(f"✅ Completed! Scraped {scraped_count} job pages (internal + external) for '{search_keywords}'.")
+            
+            if scraped_count > 0:
+                self.engine.report_outcome("success")
+                print(f"✅ Completed! Saved {scraped_count} verified + additional unverified jobs for '{search_keywords}'.")
+            else:
+                self.engine.report_outcome("captcha")
+                print("⚠️ No verified jobs scraped — check 'linkedin_jobs_unverified' for raw outputs.")

linkedin_main.py

@@ -10,13 +10,13 @@ async def main():
         target_os="windows",
         db_path="job_listings.db",
         markdown_path="job_listings.md",
-        search_keywords="Accountant",
+        search_keywords="Data Anaylst" 
     )
 
-    scraper = LinkedInJobScraper(engine, human_speed=1.2)
+    scraper = LinkedInJobScraper(engine, human_speed=1.6)
 
     await scraper.scrape_jobs(
-        search_keywords="Accountant",  # ← Your search terms
+        search_keywords="Data Anaylst",  # ← Your search terms
         max_pages=3,
         credentials={
             "email": os.getenv("SCRAPING_USERNAME"),

scraping_engine.py

@@ -1,12 +1,15 @@
+
 # scraping_engine.py
 
 import asyncio
 import hashlib
 import random
 import os
+import json
 from typing import List, Optional, Dict
 from browserforge.fingerprints import FingerprintGenerator
 from dotenv import load_dotenv
+from config import load_spoof_config
 
 # Load environment variables
 load_dotenv()
@@ -27,7 +30,6 @@ class FingerprintScrapingEngine:
         if target_os not in ['windows', 'macos']:
             raise ValueError("operating_system must be 'windows' or 'macos'")
 
-        # Load credentials from .env if not provided
         if login_credentials is None:
             username = os.getenv("SCRAPING_USERNAME")
             password = os.getenv("SCRAPING_PASSWORD")
@@ -47,37 +49,99 @@ class FingerprintScrapingEngine:
         )
         
         self.num_variations = num_variations
-        self.common_renderers = {
+        
-            'windows': [
+        # Load spoof config
-                "ANGLE (Intel, Intel(R) UHD Graphics 630 (0x00003E9B) Direct3D11 vs_5_0 ps_5_0, D3D11)",
+        spoof_config = load_spoof_config()
-                "ANGLE (Intel, Intel(R) UHD Graphics (0x00009A49) Direct3D11 vs_5_0 ps_5_0, D3D11)",
+        self.common_renderers = spoof_config["renderers"]
-                "ANGLE (Intel(R) Iris(TM) Graphics 540 Direct3D11 vs_5_0 ps_5_0)",
+        self.common_vendors = spoof_config["vendors"]
-                "ANGLE (Intel, Intel(R) UHD Graphics 620 (0x00005916) Direct3D11 vs_5_0 ps_5_0, D3D11)",
+
-                "ANGLE (Intel, Intel(R) HD Graphics 530 (0x0000191B) Direct3D11 vs_5_0 ps_5_0, D3D11)",
+        # Feedback system
-                "ANGLE (Intel, Intel(R) UHD Graphics 600 (0x00003180) Direct3D11 vs_5_0 ps_5_0, D3D11)",
+        self.feedback_file = f"feedback_{seed}.json"
-                "ANGLE (Intel, Intel(R) Iris(R) Xe Graphics (0x00009A49) Direct3D11 vs_5_0 ps_5_0, D3D11)",
+        self.feedback = self._load_feedback()
-            ],
+
-            'macos': [
+        # ← NEW: Session persistence paths
-                "Intel HD Graphics 530 OpenGL Engine",
+        self.session_dir = "browser_sessions"
-                "Intel Iris Graphics 6100 OpenGL Engine",
+        os.makedirs(self.session_dir, exist_ok=True)
-                "Intel UHD Graphics 630 OpenGL Engine",
+        self.session_path = os.path.join(self.session_dir, f"{seed}_session.json")
-                "Intel HD Graphics 4000 OpenGL Engine",
+
-                "Intel Iris Pro OpenGL Engine",
+    def _load_feedback(self):
-                "Intel UHD Graphics 617 OpenGL Engine",
+        if os.path.exists(self.feedback_file):
-            ]
+            try:
-        }
+                with open(self.feedback_file, "r") as f:
-        self.common_vendors = ["Intel Inc.", "Intel", "Intel Corporation"]
+                    data = json.load(f)
+                    data.setdefault("success_rate", 1.0)
+                    data.setdefault("captcha_count", 0)
+                    data.setdefault("cloudflare_count", 0)
+                    return data
+            except:
+                pass
+        return {"success_rate": 1.0, "captcha_count": 0, "cloudflare_count": 0}
+
+    def save_feedback(self):
+        with open(self.feedback_file, "w") as f:
+            json.dump(self.feedback, f)
+
+    def report_outcome(self, outcome: str):
+        if outcome == "success":
+            self.feedback["success_rate"] = min(1.0, self.feedback["success_rate"] + 0.1)
+        else:
+            self.feedback["success_rate"] = max(0.1, self.feedback["success_rate"] - 0.2)
+            if outcome == "captcha":
+                self.feedback["captcha_count"] += 1
+            elif outcome == "cloudflare":
+                self.feedback["cloudflare_count"] += 1
+        self.save_feedback()
+
+    # ← NEW: Save browser context (cookies + localStorage)
+    async def save_session(self, context):
+        """Save authenticated session to disk tied to seed"""
+        try:
+            storage = await context.storage_state()
+            with open(self.session_path, "w", encoding="utf-8") as f:
+                json.dump(storage, f, indent=2)
+            print(f"💾 Session saved for seed '{self.seed}'")
+        except Exception as e:
+            print(f"⚠️ Failed to save session: {e}")
+
+    # ← NEW: Load session if exists
+    async def load_session(self, context):
+        """Restore session if available"""
+        if os.path.exists(self.session_path):
+            try:
+                with open(self.session_path, "r", encoding="utf-8") as f:
+                    storage = json.load(f)
+                await context.add_cookies(storage.get("cookies", []))
+                # Note: Playwright doesn't support localStorage restore via API directly,
+                # but cookies are the main auth carrier (e.g., li_at on LinkedIn)
+                print(f"🔁 Reusing session for seed '{self.seed}'")
+                return True
+            except Exception as e:
+                print(f"⚠️ Failed to load session: {e}")
+                # Optionally delete corrupted session
+                if os.path.exists(self.session_path):
+                    os.remove(self.session_path)
+        return False
 
     def _select_profile(self):
         seed_hash = int(hashlib.sha256(self.seed.encode()).hexdigest(), 16)
         random.seed(seed_hash)
         profile = self.fingerprint_generator.generate()
-        profile.navigator.hardwareConcurrency = random.choice([4, 8, 12, 16])
+        concurrency_options = [4, 8, 12, 16]
-        profile.navigator.deviceMemory = random.choice([4, 8])
+        memory_options = [4, 8]
+        if self.feedback["success_rate"] < 0.5:
+            concurrency_options = [8, 4]
+            memory_options = [8]
+        profile.navigator.hardwareConcurrency = random.choice(concurrency_options)
+        profile.navigator.deviceMemory = random.choice(memory_options)
         return profile
 
     def _get_spoof_script(self, renderer: str, vendor: str):
         seed_hash = int(hashlib.sha256(self.seed.encode()).hexdigest(), 16)
+        if self.feedback["captcha_count"] > 2:
+            noise_factor = seed_hash % 100000000 + 100000000
+        else:
+            noise_factor = seed_hash % 100000000
+
         return f"""
         (function() {{
             const originalGetContext = HTMLCanvasElement.prototype.getContext;
@@ -113,7 +177,7 @@ class FingerprintScrapingEngine:
                 if (ctx) {{
                     const imageData = ctx.getImageData(0, 0, this.width, this.height);
                     for (let i = 0; i < imageData.data.length; i += 4) {{
-                        const noise = (Math.sin({seed_hash % 100000000} + i) * 0.5 + 0.5) * 2 - 1;
+                        const noise = (Math.sin({noise_factor} + i) * 0.5 + 0.5) * 2 - 1;
                         imageData.data[i] = Math.min(255, Math.max(0, imageData.data[i] + noise));
                         imageData.data[i+1] = Math.min(255, Math.max(0, imageData.data[i+1] + noise));
                         imageData.data[i+2] = Math.min(255, Math.max(0, imageData.data[i+2] + noise));
@@ -184,7 +248,6 @@ class FingerprintScrapingEngine:
             pass
         
     async def _detect_cloudflare(self, page) -> bool:
-        """Detect Cloudflare challenge pages"""
         content = await page.content()
         return (
             "#cf-chl" in content or
@@ -193,7 +256,6 @@ class FingerprintScrapingEngine:
         )
 
     async def _handle_cloudflare(self, page, max_retries: int = 3):
-        """Wait for Cloudflare to resolve"""
         for i in range(max_retries):
             if not await self._detect_cloudflare(page):
                 return True