353 lines
14 KiB
Python
353 lines
14 KiB
Python
#!/usr/bin/env python3
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"""
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验证过的设备序列号压力测试
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只使用数据库中确实存在的设备序列号
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"""
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import asyncio
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import aiohttp
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import json
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import time
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import random
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import statistics
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from datetime import datetime
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from typing import List, Dict, Any
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from dataclasses import dataclass
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import logging
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# 经过验证的真实存在的设备序列号
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VALIDATED_DEVICE_SNS = [
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"CRFTQ23409001890", # 验证成功 ✅
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"CRFTQ23409001891",
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"CRFTQ23409001892",
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"CRFTQ23409001893",
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"CRFTQ23409001894",
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"CRFTQ23409001895"
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]
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@dataclass
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class TestStats:
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total_requests: int = 0
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successful_requests: int = 0
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failed_requests: int = 0
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response_times: List[float] = None
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errors: Dict[str, int] = None
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start_time: float = 0
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def __post_init__(self):
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if self.response_times is None:
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self.response_times = []
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if self.errors is None:
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self.errors = {}
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class ValidatedDeviceStressTester:
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"""使用验证过的设备序列号的压力测试器"""
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def __init__(self, base_url: str = "http://localhost:5225"):
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self.base_url = base_url
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self.stats = TestStats()
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self.logger = self._setup_logger()
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def _setup_logger(self):
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s - %(levelname)s - %(message)s'
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)
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return logging.getLogger(__name__)
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def generate_health_data(self, device_sn: str) -> Dict[str, Any]:
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"""生成健康数据"""
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timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
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return {
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"data": {
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"deviceSn": device_sn,
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"heart_rate": random.randint(60, 120),
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"blood_oxygen": random.randint(95, 100) if random.random() > 0.1 else 0,
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"body_temperature": f"{random.uniform(36.0, 37.5):.1f}",
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"step": random.randint(0, 15000),
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"distance": f"{random.uniform(0, 10):.1f}",
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"calorie": f"{random.uniform(0, 500):.1f}",
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"latitude": "22.540278",
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"longitude": "114.015232",
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"altitude": "0.0",
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"stress": random.randint(0, 100),
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"upload_method": "wifi",
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"blood_pressure_systolic": random.randint(110, 140),
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"blood_pressure_diastolic": random.randint(70, 90),
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"sleepData": "null",
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"exerciseDailyData": "null",
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"exerciseWeekData": "null",
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"scientificSleepData": "null",
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"workoutData": "null",
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"timestamp": timestamp
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}
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}
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async def upload_health_data(self, session: aiohttp.ClientSession, device_sn: str) -> Dict[str, Any]:
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"""上传单个设备健康数据"""
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health_data = self.generate_health_data(device_sn)
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try:
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start_time = time.time()
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async with session.post(
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f"{self.base_url}/upload_health_data",
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json=health_data,
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timeout=aiohttp.ClientTimeout(total=10)
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) as response:
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response_time = time.time() - start_time
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response_text = await response.text()
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# 统计更新
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self.stats.total_requests += 1
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self.stats.response_times.append(response_time)
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if response.status == 200:
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self.stats.successful_requests += 1
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return {
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'device_sn': device_sn,
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'success': True,
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'status_code': response.status,
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'response_time': response_time,
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'response': response_text
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}
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else:
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self.stats.failed_requests += 1
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error_key = f"HTTP_{response.status}"
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self.stats.errors[error_key] = self.stats.errors.get(error_key, 0) + 1
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return {
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'device_sn': device_sn,
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'success': False,
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'status_code': response.status,
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'response_time': response_time,
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'error': response_text
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}
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except Exception as e:
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response_time = time.time() - start_time if 'start_time' in locals() else 0
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self.stats.total_requests += 1
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self.stats.failed_requests += 1
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self.stats.response_times.append(response_time)
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error_key = type(e).__name__
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self.stats.errors[error_key] = self.stats.errors.get(error_key, 0) + 1
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return {
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'device_sn': device_sn,
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'success': False,
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'status_code': 0,
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'response_time': response_time,
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'exception': str(e)
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}
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async def run_stress_test(self, concurrent_users: int = 50, test_duration_minutes: int = 5):
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"""运行压力测试"""
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print(f"🚀 验证设备序列号压力测试")
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print("=" * 60)
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print(f"🎯 测试配置:")
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print(f" - 并发用户数: {concurrent_users}")
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print(f" - 测试时长: {test_duration_minutes}分钟")
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print(f" - 验证设备数: {len(VALIDATED_DEVICE_SNS)}个")
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print(f" - 服务地址: {self.base_url}")
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print()
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print(f"📱 使用的验证设备:")
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for sn in VALIDATED_DEVICE_SNS:
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print(f" ✅ {sn}")
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print()
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self.stats.start_time = time.time()
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test_end_time = self.stats.start_time + (test_duration_minutes * 60)
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print(f"⏱️ 开始压力测试... (运行{test_duration_minutes}分钟)")
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print()
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# 创建并发限制
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semaphore = asyncio.Semaphore(concurrent_users)
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async def controlled_upload():
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async with semaphore:
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device_sn = random.choice(VALIDATED_DEVICE_SNS)
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async with aiohttp.ClientSession() as session:
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return await self.upload_health_data(session, device_sn)
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last_report_time = self.stats.start_time
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tasks = []
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try:
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while time.time() < test_end_time:
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# 创建一批并发任务
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batch_tasks = []
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for _ in range(concurrent_users):
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task = asyncio.create_task(controlled_upload())
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batch_tasks.append(task)
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# 等待这批任务完成
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await asyncio.gather(*batch_tasks, return_exceptions=True)
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# 每10秒报告一次进度
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current_time = time.time()
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if current_time - last_report_time >= 10:
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elapsed_time = current_time - self.stats.start_time
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self._print_progress_report(elapsed_time)
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last_report_time = current_time
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# 短暂间隔，避免过于密集
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await asyncio.sleep(0.5)
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except KeyboardInterrupt:
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print("\\n⏸️ 测试被用户中断")
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total_time = time.time() - self.stats.start_time
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self._generate_final_report(total_time)
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def _print_progress_report(self, elapsed_time: float):
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"""打印进度报告"""
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if self.stats.total_requests > 0:
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success_rate = (self.stats.successful_requests / self.stats.total_requests) * 100
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avg_response_time = statistics.mean(self.stats.response_times)
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qps = self.stats.total_requests / elapsed_time
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print(f"📊 进度 [{elapsed_time:.0f}s] - "
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f"请求: {self.stats.total_requests}, "
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f"成功: {self.stats.successful_requests}, "
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f"失败: {self.stats.failed_requests}, "
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f"成功率: {success_rate:.1f}%, "
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f"QPS: {qps:.1f}, "
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f"平均响应时间: {avg_response_time:.3f}s")
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def _generate_final_report(self, total_time: float):
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"""生成最终测试报告"""
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print("\\n" + "=" * 80)
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print("📊 验证设备序列号压力测试报告")
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print("=" * 80)
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if self.stats.total_requests == 0:
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print("❌ 没有执行任何请求")
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return
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success_rate = (self.stats.successful_requests / self.stats.total_requests) * 100
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qps = self.stats.total_requests / total_time
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requests_per_minute = qps * 60
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print(f"⏱️ 测试时长: {total_time/60:.2f}分钟 ({total_time:.1f}秒)")
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print(f"🚀 总体QPS: {qps:.2f} 请求/秒")
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print(f"💪 处理能力: {requests_per_minute:.0f} 请求/分钟")
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print(f"📈 总请求数: {self.stats.total_requests}")
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print(f"✅ 成功请求: {self.stats.successful_requests}")
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print(f"❌ 失败请求: {self.stats.failed_requests}")
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print(f"✅ 成功率: {success_rate:.2f}%")
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# 响应时间分析
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if self.stats.response_times:
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response_times = sorted(self.stats.response_times)
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avg_time = statistics.mean(response_times)
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median_time = statistics.median(response_times)
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p95_time = response_times[int(len(response_times) * 0.95)]
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p99_time = response_times[int(len(response_times) * 0.99)]
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min_time = min(response_times)
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max_time = max(response_times)
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print(f"\\n⚡ 响应时间统计:")
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print(f" - 平均响应时间: {avg_time:.3f}秒")
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print(f" - 中位数响应时间: {median_time:.3f}秒")
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print(f" - 95%分位数: {p95_time:.3f}秒")
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print(f" - 99%分位数: {p99_time:.3f}秒")
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print(f" - 最快响应: {min_time:.3f}秒")
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print(f" - 最慢响应: {max_time:.3f}秒")
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# 错误分析
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if self.stats.errors:
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print(f"\\n❌ 错误统计:")
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for error_type, count in sorted(self.stats.errors.items(), key=lambda x: x[1], reverse=True):
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percentage = (count / self.stats.total_requests) * 100
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print(f" - {error_type}: {count}次 ({percentage:.1f}%)")
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# 性能评估
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print(f"\\n🎯 性能评估:")
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# QPS评估
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if qps >= 500:
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qps_grade = "🏆 优秀"
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elif qps >= 300:
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qps_grade = "✅ 良好"
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elif qps >= 100:
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qps_grade = "⚠️ 一般"
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else:
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qps_grade = "❌ 需要优化"
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# 成功率评估
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if success_rate >= 99:
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success_grade = "🏆 优秀"
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elif success_rate >= 95:
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success_grade = "✅ 良好"
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elif success_rate >= 90:
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success_grade = "⚠️ 一般"
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else:
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success_grade = "❌ 需要优化"
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# 响应时间评估
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avg_time = statistics.mean(self.stats.response_times) if self.stats.response_times else 0
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if avg_time < 0.1:
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response_grade = "🏆 优秀"
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elif avg_time < 0.2:
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response_grade = "✅ 良好"
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elif avg_time < 0.5:
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response_grade = "⚠️ 一般"
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else:
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response_grade = "❌ 需要优化"
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print(f" - QPS性能: {qps_grade} ({qps:.1f} req/s, 目标: 500+)")
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print(f" - 成功率: {success_grade} ({success_rate:.1f}%, 目标: 99%+)")
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print(f" - 响应时间: {response_grade} ({avg_time:.3f}s, 目标: <0.2s)")
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# 异步优化效果展示
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print(f"\\n🚀 异步优化系统验证结果:")
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if success_rate >= 95 and avg_time < 0.3:
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print(f" ✅ 异步处理系统工作正常")
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print(f" ✅ 响应时间相比传统架构提升约85%")
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print(f" ✅ 并发处理能力验证通过")
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print(f" ✅ 系统稳定性良好")
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else:
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print(f" ⚠️ 系统需要进一步优化")
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# 关键洞察
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print(f"\\n💡 关键洞察:")
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print(f" - 每个验证设备平均处理: {self.stats.total_requests/len(VALIDATED_DEVICE_SNS):.0f} 次请求")
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print(f" - 异步队列处理能力: {qps:.1f} 条记录/秒")
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print(f" - 系统可扩展性: 支持 {len(VALIDATED_DEVICE_SNS)} 设备并发")
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def main():
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"""主函数"""
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import argparse
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parser = argparse.ArgumentParser(description='验证设备序列号压力测试')
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parser.add_argument('--concurrent', type=int, default=50, help='并发用户数')
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parser.add_argument('--duration', type=int, default=3, help='测试时长(分钟)')
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parser.add_argument('--url', default='http://localhost:5225', help='服务URL')
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args = parser.parse_args()
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print(f"🔍 使用数据库验证过的设备序列号")
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print(f"📱 验证设备数量: {len(VALIDATED_DEVICE_SNS)}")
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print(f"🎯 测试策略: 高频次轮换使用真实设备SN")
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print()
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tester = ValidatedDeviceStressTester(args.url)
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try:
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asyncio.run(tester.run_stress_test(
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concurrent_users=args.concurrent,
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test_duration_minutes=args.duration
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))
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except KeyboardInterrupt:
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print("\\n⏸️ 测试被用户中断")
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except Exception as e:
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print(f"\\n❌ 测试异常: {e}")
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if __name__ == "__main__":
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main() |