"""
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集成压测脚本（带压测报告生成并通过钉钉发送摘要）
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说明：
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- 该脚本基于之前的稳定 worker/队列 实现，运行后会记录每条请求的时间、状态码和延迟。
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- 运行结束后会调用Util目录下的压测报告生成器（文件名: stress_test_report_generator.py），输出 HTML/JSON/CSV/（可选）DOCX 等文件。
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- 生成后会把关键统计摘要通过 DingTalk 机器人发送（调用 DingTalkHelper.send_message）。
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- 安装依赖：aiohttp, tqdm, numpy/pandas/matplotlib/python-docx（可选）
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- 确保 DingTalkHelper 类在你的 `Util.dingtalk_helper` 中可用，且 ACCESS_TOKEN/SECRET 正确。
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"""
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import sys
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import os
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import random
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import pymysql
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import asyncio
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import aiohttp
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import time
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import traceback
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import datetime
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from tqdm import tqdm
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def get_parent_directory(file_path, levels=1):
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"""获取指定层级的父目录"""
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path = os.path.abspath(file_path)
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for _ in range(levels):
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path = os.path.dirname(path)
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return path
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parent_dir = get_parent_directory(__file__, 5) # 获取上五级目录
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sys.path.append(parent_dir)
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from 测试组.脚本.造数脚本2.Util import TokenValidator, DingTalkHelper, RandomUtil, RequestRecord, LoadTestReportGenerator
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# --- 配置 ---
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ACCESS_TOKEN = '4625f6690acd9347fae5b3a05af598be63e73d604b933a9b3902425b8f136d4d'
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SECRET = 'SEC3b6937550bd297b5491855f6f40c2ff1b41bc8c495e118ba9848742b1ddf8f19'
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# 账号密码配置
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username = "gly"
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password = "Baoyi@1341"
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# 创建获取token实例
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token_validator = TokenValidator()
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domain = "http://192.168.6.190:5561"
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token = token_validator.get_token(domain, username, password)
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apiname = "新建技术服务费"
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url = f"{domain}/api/finance/servicecost/financeServiceCost/save"
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headers = {
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"token": token,
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"Content-Type": "application/json"
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}
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NUM_WORKERS = 100
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TOTAL_REQUESTS = 10
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MAX_RETRIES = 3
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REQUEST_TIMEOUT = 60
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OUTPUT_DIR = './load_test_report'
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# --- 数据库配置 ---
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DB_CONFIG = {
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'host': '192.168.6.190',
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'port': 3306,
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'user': 'dev',
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'password': 'Hello@112',
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'database': 'srps_ecnu',
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'charset': 'utf8mb4',
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'cursorclass': pymysql.cursors.DictCursor
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}
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class DataManager:
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"""数据管理器，负责从数据库加载用户和课题组信息"""
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def __init__(self):
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self.user_data = [] # 存储用户ID、用户名、课题组ID和课题组名称
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def load_database_data(self):
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"""从数据库加载用户和课题组信息"""
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try:
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conn = pymysql.connect(**DB_CONFIG)
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# 获取用户ID、用户名和对应的课题组ID
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with conn.cursor() as cursor:
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cursor.execute("""
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SELECT
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su.id as user_id,
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su.name as user_name,
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su.research_group_ids as research_group_ids
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FROM sys_user su
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WHERE su.research_group_ids IS NOT NULL AND su.research_group_ids != ''
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""")
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results = cursor.fetchall()
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# 处理查询结果
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for row in results:
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# 处理多个课题组ID（用逗号分隔的情况）
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if row['research_group_ids'] and ',' in row['research_group_ids']:
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group_ids = [gid.strip() for gid in row['research_group_ids'].split(',') if gid.strip()]
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elif row['research_group_ids']:
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group_ids = [row['research_group_ids'].strip()]
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else:
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continue
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# 获取所有相关的课题组信息
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group_info_list = []
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for group_id in group_ids:
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# 查找对应的课题组名称，使用正确的表名 l_research_group
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cursor.execute("SELECT id, name FROM l_research_group WHERE id = %s", (group_id,))
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group_info = cursor.fetchone()
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if group_info:
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group_info_list.append({
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'group_id': group_info['id'],
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'group_name': group_info['name']
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})
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if group_info_list:
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self.user_data.append({
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'user_id': row['user_id'],
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'user_name': row['user_name'],
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'groups': group_info_list
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})
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print(f"成功加载 {len(self.user_data)} 个有效用户数据")
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conn.close()
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return len(self.user_data) > 0
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except Exception as e:
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print(f"数据库连接失败: {e}")
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return False
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def get_random_user_and_group(self):
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"""随机获取一个用户和对应的课题组信息"""
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if not self.user_data:
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return None, None, None, None
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# 随机选择一个用户
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user = random.choice(self.user_data)
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user_id = user['user_id']
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user_name = user['user_name']
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# 随机选择一个课题组
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group = random.choice(user['groups'])
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group_id = group['group_id']
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group_name = group['group_name']
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return user_id, user_name, group_id, group_name
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# 全局数据管理器
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data_manager = DataManager()
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# --- 初始化 ---
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dingtalk_helper = DingTalkHelper(ACCESS_TOKEN, SECRET)
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LARGE_CONTENT = "备注造数据" * 5
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FILES_PATH = "/userfiles/1463828311460319233/程序附件//baoyi/individual/individualrecord/2025/10/cs.jpg"
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def create_animal_data(idx: int):
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random_code = RandomUtil.generate_random_number_string(0, 10000)
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random_code_zt = RandomUtil.generate_random_number_string(1, 12)
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random_code_totalAmount = RandomUtil.generate_random_number_string(100, 10000)
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random_date = RandomUtil.generate_random_date("2023-01-01", "2025-10-16")
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# 从数据管理器获取随机的用户和课题组信息
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user_id, user_name, group_id, group_name = data_manager.get_random_user_and_group()
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if not user_id or not user_name or not group_id or not group_name:
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return None
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return {
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"id": "",
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"researchGroupId": group_id,
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"researchGroupName": group_name,
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"userId": user_id,
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"userName": user_name,
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"chargeDate": random_date,
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"name": f"服务名称{random_code}",
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"totalAmount": random_code_totalAmount,
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"status": random_code_zt,
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"attachment": "/userfiles/1588133301094375425/程序附件/finance/servicecost/financeServiceCost/2026/1/cs(2).jpg",
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"remarks": f"备注备注备注备注{random_code}"
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}
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async def perform_request(session: aiohttp.ClientSession, index: int, max_retries: int = MAX_RETRIES):
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attempt = 0
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last_err = None
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while attempt < max_retries:
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data = create_animal_data(index)
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if not data:
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return {
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'index': index,
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'timestamp': time.time(),
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'status_code': 0,
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'latency_ms': 0,
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'response_size': None,
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'error': 'No available user/group data'
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}
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start = time.time()
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try:
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async with session.post(url, json=data, headers=headers) as resp:
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text = await resp.text()
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latency_ms = (time.time() - start) * 1000.0
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status = resp.status
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if status == 200:
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return {
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'index': index,
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'timestamp': time.time(),
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'status_code': status,
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'latency_ms': latency_ms,
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'response_size': len(text) if text is not None else None,
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'error': None
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}
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else:
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last_err = f'status_{status}:{text}'
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attempt += 1
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await asyncio.sleep(min(10, 2 ** attempt))
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except Exception as e:
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latency_ms = (time.time() - start) * 1000.0
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last_err = f'{type(e).__name__}:{str(e)}'
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attempt += 1
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await asyncio.sleep(min(10, 2 ** attempt))
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# 最终失败
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return {
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'index': index,
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'timestamp': time.time(),
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'status_code': 0,
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'latency_ms': latency_ms if 'latency_ms' in locals() else 0,
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'response_size': None,
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'error': last_err
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}
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async def worker(name: int, queue: asyncio.Queue, session: aiohttp.ClientSession, gen, pbar, success_counter: dict, failed_list: list, lock: asyncio.Lock):
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while True:
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idx = await queue.get()
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if idx is None:
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queue.task_done()
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break
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try:
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res = await perform_request(session, idx)
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# 记录到报告生成器
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gen.record_result(
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index=res['index'],
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timestamp=res['timestamp'],
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status_code=int(res['status_code']),
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latency_ms=float(res['latency_ms']),
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response_size=res.get('response_size'),
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error=res.get('error')
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)
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async with lock:
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if res['status_code'] and 200 <= res['status_code'] < 300:
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success_counter['count'] += 1
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else:
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failed_list.append((res['index'], res.get('error')))
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pbar.update(1)
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except Exception as e:
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async with lock:
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failed_list.append((idx, f'Worker异常:{type(e).__name__}:{e}'))
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pbar.update(1)
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finally:
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queue.task_done()
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async def batch_create_animals(total: int, num_workers: int):
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# 加载数据库数据
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if not data_manager.load_database_data():
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print("加载数据库数据失败，退出压测")
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return
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# 动态加载报告生成器模块（支持中文文件名）
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gen = None
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try:
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import importlib.util
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script_dir = os.path.dirname(os.path.abspath(__file__))
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report_path = os.path.join(script_dir, r'H:\\项目\\archive\\测试组\\脚本\\造数脚本2\\Util\\stress_test_report_generator.py')
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if os.path.exists(report_path):
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spec = importlib.util.spec_from_file_location('report_module', report_path)
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report_module = importlib.util.module_from_spec(spec)
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spec.loader.exec_module(report_module)
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LoadTestReportGenerator = getattr(report_module, 'LoadTestReportGenerator')
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else:
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# 备用：尝试直接导入模块名（若你的文件名已改为 ascii）
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from report_generator import LoadTestReportGenerator # type: ignore
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gen = LoadTestReportGenerator(test_name=f'{apiname}压测任务', report_title='压测详细报告')
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except Exception as e:
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print('无法加载压测报告生成器，请确认stress_test_report_generator.py 文件位置正确。\n', e)
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raise
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timeout = aiohttp.ClientTimeout(total=REQUEST_TIMEOUT)
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connector = aiohttp.TCPConnector(limit=num_workers, limit_per_host=num_workers, force_close=False)
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async with aiohttp.ClientSession(timeout=timeout, connector=connector) as session:
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queue = asyncio.Queue()
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for i in range(1, total + 1):
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await queue.put(i)
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for _ in range(num_workers):
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await queue.put(None)
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success_counter = {'count': 0}
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failed_list = []
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lock = asyncio.Lock()
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with tqdm(total=total, desc='创建进度') as pbar:
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workers = [
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asyncio.create_task(worker(i, queue, session, gen, pbar, success_counter, failed_list, lock))
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for i in range(num_workers)
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]
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await asyncio.gather(*workers)
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# 任务完成，生成报告
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os.makedirs(OUTPUT_DIR, exist_ok=True)
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outputs = gen.generate_report(OUTPUT_DIR, formats=['html', 'json', 'csv', 'docx'])
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stats = gen.compute_stats()
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# 构造钉钉摘要消息（中文）
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now_str = datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')
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msg = [f'【{apiname} 压测报告】', f'生成时间：{now_str}']
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msg.append(f"总请求数：{stats.get('total_requests',0)}，成功：{stats.get('success_count',0)}，失败：{stats.get('fail_count',0)}，成功率：{stats.get('success_rate',0):.2%}")
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msg.append(f"总耗时(s)：{stats.get('duration_seconds',0):.2f}，平均吞吐(req/s)：{stats.get('throughput_rps',0):.2f}")
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lat = stats.get('latency_ms', {})
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msg.append(f"延迟(ms) - 平均：{lat.get('avg',0):.2f}，P90：{lat.get('p90',0):.2f}，P95：{lat.get('p95',0):.2f}，P99：{lat.get('p99',0):.2f}")
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# 列出生成的报告文件
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file_list = []
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for k, v in outputs.items():
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if k == 'charts':
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for cname, cpath in v.items():
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file_list.append(os.path.abspath(cpath))
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else:
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file_list.append(os.path.abspath(v))
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msg.append('生成文件：')
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for p in file_list:
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msg.append(p)
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final_msg = '\n'.join(msg)
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# 发送钉钉消息
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try:
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dingtalk_helper.send_message(final_msg)
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except Exception as e:
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print('发送钉钉消息失败：', e)
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print('\n[SUMMARY] 已生成报告并发送钉钉摘要。')
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print('成功数：', success_counter['count'], ' 失败数：', len(failed_list))
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if failed_list:
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print('失败示例（最多显示50条）：')
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for idx, err in failed_list[:50]:
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print(f' #{idx} => {err}')
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if __name__ == '__main__':
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# 运行前建议先用小规模测试
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TOTAL_REQUESTS = TOTAL_REQUESTS
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NUM_WORKERS = NUM_WORKERS
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asyncio.run(batch_create_animals(TOTAL_REQUESTS, NUM_WORKERS))
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