Major refactoring to eliminate memory leaks and enable high-scale crawling: - **Smart 3-Tier Browser Pool**: - Permanent browser (always-ready default config) - Hot pool (configs used 3+ times, longer TTL) - Cold pool (new/rare configs, short TTL) - Auto-promotion: cold → hot after 3 uses - 100% pool reuse achieved in tests - **Container-Aware Memory Detection**: - Read cgroup v1/v2 memory limits (not host metrics) - Accurate memory pressure detection in Docker - Memory-based browser creation blocking - **Adaptive Janitor**: - Dynamic cleanup intervals (10s/30s/60s based on memory) - Tiered TTLs: cold 30-300s, hot 120-600s - Aggressive cleanup at high memory pressure - **Unified Pool Usage**: - All endpoints now use pool (/html, /screenshot, /pdf, /execute_js, /md, /llm) - Fixed config signature mismatch (permanent browser matches endpoints) - get_default_browser_config() helper for consistency - **Configuration**: - Reduced idle_ttl: 1800s → 300s (30min → 5min) - Fixed port: 11234 → 11235 (match Gunicorn) **Performance Results** (from stress tests): - Memory: 10x reduction (500-700MB × N → 270MB permanent) - Latency: 30-50x faster (<100ms pool hits vs 3-5s startup) - Reuse: 100% for default config, 60%+ for variants - Capacity: 100+ concurrent requests (vs ~20 before) - Leak: 0 MB/cycle (stable across tests) **Test Infrastructure**: - 7-phase sequential test suite (tests/) - Docker stats integration + log analysis - Pool promotion verification - Memory leak detection - Full endpoint coverage Fixes memory issues reported in production deployments.
230 lines
7.6 KiB
Python
Executable File
230 lines
7.6 KiB
Python
Executable File
#!/usr/bin/env python3
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"""
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Test 3: Pool Validation - Permanent Browser Reuse
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- Tests /html endpoint (should use permanent browser)
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- Monitors container logs for pool hit markers
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- Validates browser reuse rate
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- Checks memory after browser creation
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"""
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import asyncio
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import time
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import docker
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import httpx
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from threading import Thread, Event
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# Config
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IMAGE = "crawl4ai-local:latest"
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CONTAINER_NAME = "crawl4ai-test"
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PORT = 11235
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REQUESTS = 30
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# Stats tracking
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stats_history = []
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stop_monitoring = Event()
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def monitor_stats(container):
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"""Background stats collector."""
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for stat in container.stats(decode=True, stream=True):
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if stop_monitoring.is_set():
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break
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try:
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mem_usage = stat['memory_stats'].get('usage', 0) / (1024 * 1024)
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stats_history.append({
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'timestamp': time.time(),
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'memory_mb': mem_usage,
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})
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except:
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pass
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time.sleep(0.5)
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def count_log_markers(container):
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"""Extract pool usage markers from logs."""
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logs = container.logs().decode('utf-8')
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permanent_hits = logs.count("🔥 Using permanent browser")
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hot_hits = logs.count("♨️ Using hot pool browser")
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cold_hits = logs.count("❄️ Using cold pool browser")
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new_created = logs.count("🆕 Creating new browser")
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return {
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'permanent_hits': permanent_hits,
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'hot_hits': hot_hits,
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'cold_hits': cold_hits,
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'new_created': new_created,
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'total_hits': permanent_hits + hot_hits + cold_hits
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}
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async def test_endpoint(url: str, count: int):
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"""Hit endpoint multiple times."""
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results = []
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async with httpx.AsyncClient(timeout=60.0) as client:
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for i in range(count):
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start = time.time()
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try:
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resp = await client.post(url, json={"url": "https://httpbin.org/html"})
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elapsed = (time.time() - start) * 1000
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results.append({
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"success": resp.status_code == 200,
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"latency_ms": elapsed,
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})
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if (i + 1) % 10 == 0:
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print(f" [{i+1}/{count}] ✓ {resp.status_code} - {elapsed:.0f}ms")
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except Exception as e:
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results.append({"success": False, "error": str(e)})
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print(f" [{i+1}/{count}] ✗ Error: {e}")
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return results
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def start_container(client, image: str, name: str, port: int):
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"""Start container."""
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try:
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old = client.containers.get(name)
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print(f"🧹 Stopping existing container...")
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old.stop()
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old.remove()
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except docker.errors.NotFound:
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pass
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print(f"🚀 Starting container...")
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container = client.containers.run(
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image,
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name=name,
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ports={f"{port}/tcp": port},
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detach=True,
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shm_size="1g",
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mem_limit="4g",
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)
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print(f"⏳ Waiting for health...")
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for _ in range(30):
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time.sleep(1)
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container.reload()
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if container.status == "running":
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try:
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import requests
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resp = requests.get(f"http://localhost:{port}/health", timeout=2)
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if resp.status_code == 200:
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print(f"✅ Container healthy!")
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return container
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except:
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pass
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raise TimeoutError("Container failed to start")
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def stop_container(container):
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"""Stop container."""
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print(f"🛑 Stopping container...")
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container.stop()
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container.remove()
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async def main():
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print("="*60)
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print("TEST 3: Pool Validation - Permanent Browser Reuse")
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print("="*60)
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client = docker.from_env()
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container = None
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monitor_thread = None
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try:
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# Start container
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container = start_container(client, IMAGE, CONTAINER_NAME, PORT)
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# Wait for permanent browser initialization
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print(f"\n⏳ Waiting for permanent browser init (3s)...")
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await asyncio.sleep(3)
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# Start stats monitoring
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print(f"📊 Starting stats monitor...")
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stop_monitoring.clear()
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stats_history.clear()
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monitor_thread = Thread(target=monitor_stats, args=(container,), daemon=True)
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monitor_thread.start()
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await asyncio.sleep(1)
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baseline_mem = stats_history[-1]['memory_mb'] if stats_history else 0
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print(f"📏 Baseline (with permanent browser): {baseline_mem:.1f} MB")
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# Test /html endpoint (uses permanent browser for default config)
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print(f"\n🔄 Running {REQUESTS} requests to /html...")
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url = f"http://localhost:{PORT}/html"
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results = await test_endpoint(url, REQUESTS)
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# Wait a bit
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await asyncio.sleep(1)
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# Stop monitoring
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stop_monitoring.set()
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if monitor_thread:
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monitor_thread.join(timeout=2)
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# Analyze logs for pool markers
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print(f"\n📋 Analyzing pool usage...")
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pool_stats = count_log_markers(container)
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# Calculate request stats
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successes = sum(1 for r in results if r.get("success"))
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success_rate = (successes / len(results)) * 100
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latencies = [r["latency_ms"] for r in results if "latency_ms" in r]
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avg_latency = sum(latencies) / len(latencies) if latencies else 0
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# Memory stats
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memory_samples = [s['memory_mb'] for s in stats_history]
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peak_mem = max(memory_samples) if memory_samples else 0
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final_mem = memory_samples[-1] if memory_samples else 0
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mem_delta = final_mem - baseline_mem
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# Calculate reuse rate
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total_requests = len(results)
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total_pool_hits = pool_stats['total_hits']
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reuse_rate = (total_pool_hits / total_requests * 100) if total_requests > 0 else 0
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# Print results
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print(f"\n{'='*60}")
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print(f"RESULTS:")
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print(f" Success Rate: {success_rate:.1f}% ({successes}/{len(results)})")
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print(f" Avg Latency: {avg_latency:.0f}ms")
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print(f"\n Pool Stats:")
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print(f" 🔥 Permanent Hits: {pool_stats['permanent_hits']}")
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print(f" ♨️ Hot Pool Hits: {pool_stats['hot_hits']}")
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print(f" ❄️ Cold Pool Hits: {pool_stats['cold_hits']}")
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print(f" 🆕 New Created: {pool_stats['new_created']}")
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print(f" 📊 Reuse Rate: {reuse_rate:.1f}%")
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print(f"\n Memory Stats:")
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print(f" Baseline: {baseline_mem:.1f} MB")
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print(f" Peak: {peak_mem:.1f} MB")
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print(f" Final: {final_mem:.1f} MB")
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print(f" Delta: {mem_delta:+.1f} MB")
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print(f"{'='*60}")
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# Pass/Fail
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passed = True
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if success_rate < 100:
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print(f"❌ FAIL: Success rate {success_rate:.1f}% < 100%")
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passed = False
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if reuse_rate < 80:
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print(f"❌ FAIL: Reuse rate {reuse_rate:.1f}% < 80% (expected high permanent browser usage)")
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passed = False
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if pool_stats['permanent_hits'] < (total_requests * 0.8):
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print(f"⚠️ WARNING: Only {pool_stats['permanent_hits']} permanent hits out of {total_requests} requests")
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if mem_delta > 200:
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print(f"⚠️ WARNING: Memory grew by {mem_delta:.1f} MB (possible browser leak)")
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if passed:
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print(f"✅ TEST PASSED")
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return 0
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else:
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return 1
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except Exception as e:
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print(f"\n❌ TEST ERROR: {e}")
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import traceback
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traceback.print_exc()
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return 1
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finally:
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stop_monitoring.set()
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if container:
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stop_container(container)
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if __name__ == "__main__":
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exit_code = asyncio.run(main())
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exit(exit_code)
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