337 lines
13 KiB
Python
337 lines
13 KiB
Python
from pathlib import Path
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import traceback
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import requests
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import json
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import time
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from datetime import datetime
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from tqdm import tqdm
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import pandas as pd
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import os
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#+
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# f6_module = F6_module()
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#
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# # 1.向服务器发送请求登录
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# username = "13799889725"
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# password = "Lc1234"
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# store_name = "禹城榕桦"
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module = 1
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#
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# res = f6_module.login_in(username, password, store_name)
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# # cookies = requests.utils.dict_from_cookiejar(res.cookies)
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cookies = {
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'memberSESSIONID': '639e52b2-1260-47a9-8d0b-d0cd41054738',
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'erpLanguage': 'zh-CN',
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'tmall': 'false',
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'Hm_lvt_25f5e7a3a5dbb293d7dd35d5f1be8d0a': '1776909170,1776923216,1777270359,1777277857',
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'HMACCOUNT': 'A6A0585E8C70051D',
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'unp': '16023446149142708289',
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'un': '16023446149142708289',
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'_up': '-NillNN-qyBEJ--t3vnSknvoOF1_z_KJtMsE13I-XuVaVvnDr5DQjaZJ9Q3d-WrAAGgt60MgQHajHWBHMKKxj0CuWypi1JgKCFP1EPEk-HbqE_QQq4Ml3wcK_PBRv-ZNHu3M-GTf3pqyEXOur-lciO8Yl1bLPBtmrEj90x3BhsH6PGY.',
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'sensorsdata2015jssdkcross': '%7B%22distinct_id%22%3A%2216023446149142708289%22%2C%22first_id%22%3A%2219b6df76a22f46-04a98afdd2a11d8-4c657b58-1327104-19b6df76a2312c7%22%2C%22props%22%3A%7B%22%24latest_traffic_source_type%22%3A%22%E7%9B%B4%E6%8E%A5%E6%B5%81%E9%87%8F%22%2C%22%24latest_search_keyword%22%3A%22%E6%9C%AA%E5%8F%96%E5%88%B0%E5%80%BC_%E7%9B%B4%E6%8E%A5%E6%89%93%E5%BC%80%22%2C%22%24latest_referrer%22%3A%22%22%7D%2C%22%24device_id%22%3A%2219b6df76a22f46-04a98afdd2a11d8-4c657b58-1327104-19b6df76a2312c7%22%7D',
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'prodOrg': '16070511835941490720',
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'Hm_lpvt_25f5e7a3a5dbb293d7dd35d5f1be8d0a': '1777428810',
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}
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print("cookies loaded")
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request_results = []
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script_dir = Path(__file__).resolve().parent
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output_base = script_dir / f"请求结果_{datetime.now():%Y%m%d_%H%M%S}"
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df = pd.read_excel(fr"C:\Users\hp_z66\Desktop\客户信息.xlsx",sheet_name="客户信息").astype(str)
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if module == 1: # 客户信息删除
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# --- 初始化日志列表 ---
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delete_logs = [] # 删除操作日志
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query_logs = [] # 查询日志
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# --- 1. 数据准备 ---
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df['手机号码'] = df['手机号码'].astype(str).str.strip().str.replace('.0$', '', regex=True)
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df['手机号码'].dropna(inplace=True)
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# 将需要删除的手机号转为集合，查询速度更快
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phones_to_delete = set(df['手机号码'].values)
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print(f"待删除手机号数量: {len(phones_to_delete)}")
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# --- 2. 分页查询所有客户 ---
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base_url = "https://yunxiu.f6car.cn/member/customer/listForPermission"
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id_own_org = "16070511835941490720"
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page_size = 100
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page_no = 1
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all_customers = []
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print("正在获取所有客户数据...")
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while True:
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params = {
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"idOwnOrg": id_own_org,
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"pageSize": page_size,
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"pageNo": page_no
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}
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try:
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res = requests.get(base_url, params=params, cookies=cookies)
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query_log = {
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"ts": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
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"module": module,
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"action": "customer_list_page",
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"url": res.url,
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"page_no": page_no
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}
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query_log["status_code"] = getattr(res, "status_code", None)
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query_log["ok"] = getattr(res, "ok", None)
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data = res.json()
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query_log["response_json"] = json.dumps(data, ensure_ascii=False)
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request_results.append(query_log)
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query_logs.append(query_log)
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# 获取当前页的数据列表
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page_data = data.get('data', {}).get('data', [])
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# 如果当前页没有数据了，说明已经取完，跳出循环
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if not page_data:
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print(f"第 {page_no} 页没有数据了，获取完毕。")
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break
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all_customers.extend(page_data)
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print(f"已获取第 {page_no} 页，共 {len(page_data)} 条数据。累计获取: {len(all_customers)} 条")
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page_no += 1
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time.sleep(0.5)
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except Exception as e:
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print(f"获取第 {page_no} 页数据时出错: {e}")
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error_log = {
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"ts": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
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"module": module,
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"action": "customer_list_error",
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"page_no": page_no,
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"error": str(e)
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}
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query_logs.append(error_log)
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break
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# --- 3. 遍历所有客户并执行删除 ---
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print(f"开始处理删除操作，共需检查 {len(all_customers)} 个客户...")
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success_count = 0
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failed_count = 0
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for item in tqdm(all_customers):
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try:
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idCustomer = item['idCustomer']
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phone = item['cellPhone']
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phone_clean = str(phone).strip().replace('.0', '')
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# 检查手机号是否在待删除列表中
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if phone_clean in phones_to_delete:
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print(f"\n正在删除: {phone_clean}")
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url = f"https://yunxiu.f6car.cn/member/customer/{idCustomer}"
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# 记录删除开始
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delete_log = {
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"ts": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
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"module": module,
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"action": "customer_delete",
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"url": url,
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"idCustomer": idCustomer,
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"cellPhone": phone_clean,
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}
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res = requests.delete(url, cookies=cookies)
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delete_log["status_code"] = getattr(res, "status_code", None)
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delete_log["ok"] = getattr(res, "ok", None)
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# 解析响应
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try:
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response_data = res.json()
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delete_log["response_json"] = json.dumps(response_data, ensure_ascii=False)
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delete_log["response_code"] = response_data.get('code', '')
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delete_log["response_msg"] = response_data.get('msg', '')
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except Exception:
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delete_log["response_text"] = res.text
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delete_log["response_code"] = ''
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delete_log["response_msg"] = '响应解析失败'
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# 判断删除是否成功
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if res.ok and delete_log.get("response_code") == 200:
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delete_log["delete_status"] = "成功"
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success_count += 1
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print(f"✓ 成功删除: {phone_clean}")
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else:
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delete_log["delete_status"] = "失败"
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failed_count += 1
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print(f"✗ 删除失败: {phone_clean}")
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request_results.append(delete_log)
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delete_logs.append(delete_log)
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# 打印详细结果
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try:
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print(response_data)
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except:
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print(res.text[:200]) # 只打印前200个字符
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time.sleep(3)
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except Exception as e:
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# 记录异常情况
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error_log = {
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"ts": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
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"module": module,
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"action": "customer_delete_error",
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"idCustomer": item.get('idCustomer', '未知'),
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"cellPhone": phone_clean if 'phone_clean' in locals() else item.get('cellPhone', '未知'),
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"error": str(e),
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"delete_status": "异常"
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}
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delete_logs.append(error_log)
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failed_count += 1
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print(f"处理客户 {item.get('idCustomer', '未知')} 时出错: {e}")
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# --- 4. 保存日志到Excel文件 ---
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print("\n正在保存日志文件...")
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# 创建日志目录
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log_dir = "delete_logs"
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if not os.path.exists(log_dir):
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os.makedirs(log_dir)
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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# 保存删除操作日志
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if delete_logs:
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df_delete_logs = pd.DataFrame(delete_logs)
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# 选择要保存的列（可根据需要调整）
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columns_to_save = [
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"ts", "action", "idCustomer", "cellPhone",
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"delete_status", "status_code", "ok",
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"response_code", "response_msg", "error"
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]
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# 只保存存在的列
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existing_columns = [col for col in columns_to_save if col in df_delete_logs.columns]
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df_delete_logs = df_delete_logs[existing_columns]
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delete_log_file = f"{log_dir}/删除操作日志_{timestamp}.xlsx"
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df_delete_logs.to_excel(delete_log_file, index=False, engine='openpyxl')
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print(f"删除操作日志已保存到: {delete_log_file}")
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# 保存查询日志
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if query_logs:
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df_query_logs = pd.DataFrame(query_logs)
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query_log_file = f"{log_dir}/查询日志_{timestamp}.xlsx"
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df_query_logs.to_excel(query_log_file, index=False, engine='openpyxl')
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print(f"查询日志已保存到: {query_log_file}")
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# 保存汇总信息
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summary_data = {
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"项目": ["待删除手机号数量", "查询到的客户总数", "实际执行删除数", "删除成功", "删除失败", "执行时间"],
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"数值": [
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len(phones_to_delete),
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len(all_customers),
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success_count + failed_count,
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success_count,
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failed_count,
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datetime.now().strftime("%Y-%m-%d %H:%M:%S")
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]
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}
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df_summary = pd.DataFrame(summary_data)
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summary_file = f"{log_dir}/删除汇总_{timestamp}.xlsx"
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df_summary.to_excel(summary_file, index=False, engine='openpyxl')
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print(f"删除汇总已保存到: {summary_file}")
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# 打印最终统计
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print("\n" + "=" * 50)
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print("删除操作完成！")
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print(f"待删除手机号: {len(phones_to_delete)} 个")
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print(f"查询到客户总数: {len(all_customers)} 个")
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print(f"实际执行删除: {success_count + failed_count} 次")
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print(f"删除成功: {success_count} 个")
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print(f"删除失败/异常: {failed_count} 个")
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print(f"日志文件保存在: {log_dir}/ 目录下")
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print("=" * 50)
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if module == 2: # 客户车辆信息删除
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for index, row in tqdm(df.iterrows(), total=len(df)):
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car_number = row['车牌号']
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car_Id = row["carId"]
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customerId = row["customerId"]
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try:
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# print("删除：", car_number)
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url = f"https://yunxiu.f6car.cn/member/car/deleteCar/{car_Id}/{customerId}"
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# url = f"https://yunxiu.f6car.cn/macan/coupon/car/batchRemove?customerId={customerId}&carId={carId}&operateOrgId={operateOrgId}" # 删除客户车辆信息url
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res = requests.delete(url, cookies=cookies) # 客户车辆信息删除
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row = {
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"ts": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
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"module": module,
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"action": "car_delete",
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"url": url,
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"car_number": car_number,
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"carId": car_Id,
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"customerId": customerId,
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}
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row["status_code"] = getattr(res, "status_code", None)
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row["ok"] = getattr(res, "ok", None)
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try:
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row["response_json"] = json.dumps(res.json(), ensure_ascii=False)
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except Exception:
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try:
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row["response_text"] = res.text
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except Exception:
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row["response_text"] = None
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request_results.append(row)
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print("delete——", res.json(), customerId, car_Id)
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now = datetime.now()
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if now.hour >= 20:
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time.sleep(1)
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else:
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time.sleep(3)
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except:
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res_tmp = locals().get("res")
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row = {
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"ts": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
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"module": module,
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"action": "car_delete",
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"url": locals().get("url"),
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"car_number": car_number,
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"carId": car_Id,
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"customerId": customerId,
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"error": "删除失败",
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"traceback": traceback.format_exc(),
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}
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if res_tmp is not None:
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row["status_code"] = getattr(res_tmp, "status_code", None)
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row["ok"] = getattr(res_tmp, "ok", None)
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try:
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row["response_json"] = json.dumps(res_tmp.json(), ensure_ascii=False)
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except Exception:
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try:
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row["response_text"] = res_tmp.text
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except Exception:
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row["response_text"] = None
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request_results.append(row)
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try:
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print("删除失败：", res_tmp.json(), customerId, car_Id)
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except Exception:
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print("删除失败：", getattr(res_tmp, "text", None), customerId, car_Id)
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continue
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if request_results:
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df_out = pd.DataFrame(request_results)
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df_out.to_csv(f"{output_base}.csv", index=False, encoding="utf-8-sig")
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with open(f"{output_base}.jsonl", "w", encoding="utf-8") as f:
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for row in request_results:
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f.write(json.dumps(row, ensure_ascii=False) + "\n")
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try:
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df_out.to_excel(f"{output_base}.xlsx", index=False)
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except Exception:
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pass
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