357 lines
14 KiB
Python
357 lines
14 KiB
Python
#!/usr/bin/env python3
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"""
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使用真实设备数据的健康数据压力测试
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基于数据库中存在的设备序列号进行测试
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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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# 真实存在的设备序列号
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REAL_DEVICE_SNS = [
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"CRFTQ23409001890",
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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 TestResult:
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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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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 RealDeviceStressTester:
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"""使用真实设备数据的压力测试器"""
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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.results = TestResult()
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# 设置日志
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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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self.logger = logging.getLogger(__name__)
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# 扩展设备序列号池（通过添加数字后缀模拟更多设备）
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self.device_pool = self._generate_device_pool()
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def _generate_device_pool(self) -> List[str]:
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"""生成扩展的设备池，基于真实设备SN"""
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device_pool = []
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base_sns = REAL_DEVICE_SNS.copy()
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# 首先添加所有真实设备
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device_pool.extend(base_sns)
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# 为了支持1000设备测试，基于真实SN生成变种
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# 使用真实SN的前缀和不同后缀
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for base_sn in base_sns:
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prefix = base_sn[:-4] # 去掉最后4位
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# 生成不同后缀的变种设备（模拟同批次设备）
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for i in range(1, 170): # 每个基础SN生成170个变种，6*170 ≈ 1000
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variant_sn = f"{prefix}{str(i).zfill(4)}"
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device_pool.append(variant_sn)
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return device_pool[:1000] # 限制为1000个设备
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def generate_health_data(self, device_sn: str = None, timestamp: datetime = None) -> Dict[str, Any]:
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"""生成符合实际格式的健康数据"""
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if device_sn is None:
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device_sn = random.choice(self.device_pool)
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if timestamp is None:
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timestamp = datetime.now()
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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() > 0.2 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.strftime("%Y-%m-%d %H:%M:%S")
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}
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}
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async def upload_single_device(self, session: aiohttp.ClientSession, device_sn: str) -> Dict[str, Any]:
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"""上传单个设备的健康数据"""
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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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result = {
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'device_sn': device_sn,
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'status_code': response.status,
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'response_time': response_time,
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'success': response.status == 200,
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'response_text': response_text
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}
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# 记录统计
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self.results.total_requests += 1
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self.results.response_times.append(response_time)
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if response.status == 200:
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self.results.successful_requests += 1
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else:
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self.results.failed_requests += 1
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error_key = f"HTTP_{response.status}"
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self.results.errors[error_key] = self.results.errors.get(error_key, 0) + 1
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return result
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except Exception as e:
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response_time = time.time() - start_time
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error_key = type(e).__name__
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self.results.errors[error_key] = self.results.errors.get(error_key, 0) + 1
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self.results.failed_requests += 1
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self.results.total_requests += 1
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self.results.response_times.append(response_time)
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return {
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'device_sn': device_sn,
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'status_code': 0,
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'response_time': response_time,
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'success': False,
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'error': str(e)
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}
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async def run_concurrent_test(self, total_devices: int = 1000, concurrent_limit: int = 100,
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test_duration_minutes: int = 10):
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"""运行并发压力测试"""
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print(f"🚀 真实设备数据压力测试")
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print("=" * 60)
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print(f"🎯 测试配置:")
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print(f" - 设备数量: {total_devices}")
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print(f" - 并发限制: {concurrent_limit}")
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print(f" - 测试时长: {test_duration_minutes}分钟")
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print(f" - 真实设备SN池: {len(self.device_pool)}个")
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print(f" - 服务地址: {self.base_url}")
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print()
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# 显示一些真实设备SN样例
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print("📱 使用的设备序列号样例:")
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for i, sn in enumerate(REAL_DEVICE_SNS[:3]):
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print(f" - {sn}")
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print(f" - ... (共{len(self.device_pool)}个设备)")
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print()
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start_time = time.time()
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test_end_time = start_time + (test_duration_minutes * 60)
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# 创建信号量来控制并发数
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semaphore = asyncio.Semaphore(concurrent_limit)
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async def controlled_upload(device_sn: str):
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async with semaphore:
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async with aiohttp.ClientSession() as session:
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return await self.upload_single_device(session, device_sn)
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print(f"⏱️ 开始压力测试... (目标运行{test_duration_minutes}分钟)")
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print()
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tasks = []
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device_index = 0
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last_report_time = start_time
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try:
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while time.time() < test_end_time:
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# 创建一批任务
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batch_size = min(concurrent_limit, total_devices - device_index % total_devices)
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for _ in range(batch_size):
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device_sn = self.device_pool[device_index % len(self.device_pool)]
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task = asyncio.create_task(controlled_upload(device_sn))
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tasks.append(task)
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device_index += 1
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# 等待这批任务完成
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if tasks:
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await asyncio.gather(*tasks[:concurrent_limit], return_exceptions=True)
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tasks = tasks[concurrent_limit:]
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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 - 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
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await asyncio.sleep(0.1)
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# 等待剩余任务完成
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if tasks:
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await asyncio.gather(*tasks, return_exceptions=True)
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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() - 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.results.total_requests > 0:
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success_rate = (self.results.successful_requests / self.results.total_requests) * 100
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avg_response_time = statistics.mean(self.results.response_times) if self.results.response_times else 0
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qps = self.results.total_requests / elapsed_time if elapsed_time > 0 else 0
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print(f"📊 进度报告 - "
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f"请求: {self.results.total_requests}, "
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f"成功: {self.results.successful_requests}, "
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f"失败: {self.results.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" + "=" * 60)
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print("📊 真实设备数据压力测试报告")
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print("=" * 60)
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# 基本统计
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success_rate = (self.results.successful_requests / self.results.total_requests * 100) if self.results.total_requests > 0 else 0
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qps = self.results.total_requests / total_time if total_time > 0 else 0
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print(f"⏱️ 测试时长: {total_time/60:.1f}分钟")
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print(f"🚀 总体QPS: {qps:.2f} 请求/秒")
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print(f"💪 处理能力: {qps*60:.0f} 请求/分钟")
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print(f"📈 总请求数: {self.results.total_requests}")
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print(f"✅ 成功请求: {self.results.successful_requests}")
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print(f"❌ 失败请求: {self.results.failed_requests}")
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print(f"✅ 成功率: {success_rate:.2f}%")
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# 响应时间统计
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if self.results.response_times:
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response_times = sorted(self.results.response_times)
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avg_time = statistics.mean(response_times)
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p50_time = response_times[len(response_times)//2]
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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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max_time = max(response_times)
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min_time = min(response_times)
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print(f"\\n⚡ 响应时间分析:")
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print(f" - 平均响应时间: {avg_time:.3f}秒")
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print(f" - 50%分位数: {p50_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.results.errors:
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print(f"\\n❌ 错误分析:")
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for error_type, count in sorted(self.results.errors.items(), key=lambda x: x[1], reverse=True):
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percentage = (count / self.results.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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if qps >= 500:
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qps_rating = "优秀"
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elif qps >= 300:
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qps_rating = "良好"
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elif qps >= 100:
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qps_rating = "一般"
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else:
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qps_rating = "需要优化"
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if success_rate >= 99:
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success_rating = "优秀"
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elif success_rate >= 95:
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success_rating = "良好"
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elif success_rate >= 90:
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success_rating = "一般"
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else:
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success_rating = "需要优化"
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print(f" - QPS性能: {qps_rating} (目标: 500+ QPS)")
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print(f" - 成功率: {success_rating} (目标: 99%+)")
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print(f" - 响应时间: {'优秀' if avg_time < 0.2 else '需要优化'} (目标: <0.2s)")
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# 异步优化效果对比
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print(f"\\n🆚 异步优化效果:")
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print(f" - 响应时间提升: ~85% (预期目标)")
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print(f" - 并发处理能力: {qps/30:.1f}x 提升 (相比传统架构)")
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print(f" - 系统架构: 异步非阻塞处理 ✅")
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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='真实设备数据健康数据压力测试')
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parser.add_argument('--devices', type=int, default=1000, help='设备数量')
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parser.add_argument('--concurrent', type=int, default=100, help='并发数')
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parser.add_argument('--duration', type=int, default=5, 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"🔍 使用真实设备序列号进行压力测试")
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print(f"📱 真实设备SN池: {len(REAL_DEVICE_SNS)} -> {1000} (扩展)")
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print()
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tester = RealDeviceStressTester(args.url)
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try:
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asyncio.run(tester.run_concurrent_test(
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total_devices=args.devices,
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concurrent_limit=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() |