"""
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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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# 将上一级目录加入模块搜索路径
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sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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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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from Util.random_util import RandomUtil
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from Util.dingtalk_helper import DingTalkHelper
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# --- 配置 ---
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ACCESS_TOKEN = '4625f6690acd9347fae5b3a05af598be63e73d604b933a9b3902425b8f136d4d'
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SECRET = 'SEC3b6937550bd297b5491855f6f40c2ff1b41bc8c495e118ba9848742b1ddf8f19'
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apiname = "个体信息"
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url = "http://192.168.6.168:5534/api/individual/individualrecord/individualRecord/save"
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headers = {
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"token": "eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJleHAiOjE3NjA2Nzk1MDksInVzZXJuYW1lIjoiZ2x5In0.aApZ-cXC_pIw6gdPZHg3TlsgZIaCPRrmlMDM3-zEhtg",
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"Content-Type": "application/json"
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}
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NUM_WORKERS = 10
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TOTAL_REQUESTS = 100
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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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# --- 初始化 ---
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dingtalk_helper = DingTalkHelper(ACCESS_TOKEN, SECRET)
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LARGE_CONTENT = "备注压测中" * 10
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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_grade = RandomUtil.generate_random_number_string(1, 2)
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random_code_sex = RandomUtil.generate_random_number_string(1, 2)
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random_date = RandomUtil.generate_random_date("2023-01-01", "2025-10-16")
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return {
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"individualExperimentRecordDTOList": [
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{
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"fileUrl": "",
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"id": "",
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"individualId": "",
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"experimentDate": random_date,
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"name": "3",
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"otherName": "",
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"remarks": "",
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"ultrasoundScanDate": "",
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"pregnancyStatus": "",
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"otherSituation": ""
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},
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{
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"fileUrl": "",
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"id": "",
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"individualId": "",
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"experimentDate": random_date,
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"name": "5",
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"otherName": "",
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"remarks": "",
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"ultrasoundScanDate": "",
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"pregnancyStatus": "",
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"otherSituation": ""
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}
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],
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"id": "",
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"rfid": "random_code",
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"code": f"hyb压测模拟万人新建动物信息{random_code}",
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"variety": "食蟹猴",
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"birthDate": f"{random_date} 00:00:00",
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"deathDate": "",
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"grade": random_code_grade,
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"gender": random_code_sex,
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"father": {"id": ""},
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"mother": {"id": ""},
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"birthPlace": "",
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"room": {"id": "", "name": ""},
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"cage": {"id": "", "code": ""},
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"status": "5,2",
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"weight": "",
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"weightUnit": "",
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"weightUnitValue": "",
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"researchGroup": {"id": "1491301397488844801"},
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"isConfirmBirth": "1",
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"birthYear": "2025",
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"weightDate": "",
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"remarks": LARGE_CONTENT,
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"relevanceId": "",
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"version": "",
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"transferTime": "",
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"transferRemarks": "",
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"transferList": [],
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"otherVariety": "",
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"varietyType": "",
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"animalSource": "1",
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"enterTime": f"{random_date} 00:00:00",
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"animalModel": "",
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"project": {"id": "1825457771270230018"},
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"projectManager": {"id": "1810602921408172033"},
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"reminderTime": random_date,
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"reminderUser": {"id": "1463828311460319233"},
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"fileUrl": FILES_PATH,
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"groupChagneDate": random_date,
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"infantId": "",
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"statusStr": "5,2"
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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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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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# 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, 'H:\\项目\\造数脚本\\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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