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2025-08-12 13:43:10 +08:00
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back_ground_module/Exception_Task.py
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import datetime
import os
import time
import requests
from api import API
import re
from back_ground_module import CommonModule
import pandas as pd
from log_config import configure_task_logger, configure_error_task_logger
api_instance = API()
common_module = CommonModule()
# start_time = datetime.datetime.now()
# 获取已经配置好的常规日志记录器
logger = configure_task_logger()
# 获取已经配置好的错误任务日志记录器
error_task_logger = configure_error_task_logger()
class NewExceptionTask:
"""
SaaS异常回访
"""
def __init__(self):
self.get_feature_usage = None
self.saas_create_time = None
self.index = None
self.date_one = None
self.data_yichang_S = None
self.date_list = None
self.Smart_detection = None
self.service_remind = None
self.NGV_data_list = None
self.permissions_table = None
self.staff_id_list = None
self.json_list = []
self.policy_recognition = None
self.widget_list = None
self.private_domain = None
self.public_domain = None
self.public_domain_list = None
self.different_industries = None
self.different_industries_list = None
self.groupnotification = None
def calculate_date_one(self, start_offset=0):
"""
计算从当前日期（或指定偏移量的日期）开始，往前遍历遇到date_list中日期的次数。
参数:
- start_offset: 从当前日期起始的天数偏移量，默认为0（即今天）。负数表示过去，正数表示未来。
返回:
- date_one: 遍历到date_list中日期的次数。
"""
jdy_date = datetime.datetime.now().strftime("%Y-%m-%d")
jdy_start_time = datetime.datetime.now().strftime("%Y-%m-%d ")
# 设置起始日期
now_time = datetime.datetime.now() + datetime.timedelta(days=start_offset)
# 初始化计数器
date_one = 1
print("当前日期：", now_time.strftime("%Y-%m-%d"))
# 检查起始日期是否在date_list中
if now_time.strftime("%Y-%m-%d") in self.date_list:
date_one = 0
print("开始次数：", date_one)
else:
# 遍历日期
for i in range(1, 10):
new_date = now_time + datetime.timedelta(days=-i)
new_date_str = new_date.strftime("%Y-%m-%d")
print("遍历日期：", new_date_str)
if new_date_str in self.date_list:
date_one += 1
print("节假日期：", new_date_str)
else:
break
print("遍历次数：", date_one)
return date_one
@staticmethod
def download_url_content(url, save_path):
"""
下载指定 URL 的内容并保存到本地文件。
:param url: 要下载内容的 URL
:param save_path: 保存文件的路径
"""
try:
# 发送 GET 请求以获取内容
response = requests.get(url, stream=True)
response.raise_for_status() # 如果响应状态码不是 200，抛出异常
# 确保保存目录存在
os.makedirs(os.path.dirname(save_path), exist_ok=True)
# 将内容写入文件
with open(save_path, 'wb') as file:
for chunk in response.iter_content(chunk_size=8192): # 分块写入，避免占用过多内存
if chunk: # 过滤掉空块
file.write(chunk)
print(f"文件已成功保存到 {save_path}")
except requests.exceptions.RequestException as e:
print(f"下载失败: {e}")
except Exception as e:
print(f"发生错误: {e}")
def load_all_data(self):
"""加载所有必要的数据表"""
# 省市区人员关系表
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "676512ac3e54dc3159460c0a"}
json_dict = api_instance.entry_data_list(payload)
self.json_list = json_dict.get("data")
# 获取简道云员工id
payload = {"api_key": "6694d3c4fcb69ca9a111a6c4",
"entry_id": "6769204a1902c9341340a1bc",
}
staff_id = api_instance.entry_data_list(payload)
self.staff_id_list = staff_id.get("data") # api请求格式，将数据封装在data字典里
# 获取NGV数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "675bb02bd2d53c2034c665e4"}
self.NGV_data_list = api_instance.entry_data_list(payload).get("data", [])
# print("NGV获取后的类型：", type(self.NGV_data_list))
@staticmethod
def build_index(json_list):
index = {}
for json_item in json_list:
try:
key = (json_item['_widget_1734677164861'], json_item['_widget_1734677164862'],
json_item['_widget_1734677164863']) # 省市区
if '_widget_1734677164870' not in json_item: # 异常回访客服
raise KeyError("缺少 '异常回访客服' 键")
index[key] = json_item
except KeyError as e:
print(f"警告：{e}，跳过该条记录: {json_item}")
continue
print('index', index)
return index
@staticmethod
def find_customer_service(province_name, city_name, area_name, index):
key = (province_name, city_name, area_name)
# print(index)
if key not in index:
return "数据缺失: 未找到对应的异常回访客服"
return index[key]
@staticmethod
def get_staff_id(row_item, name):
"""辅助函数，用于获取员工ID"""
if str(row_item["_widget_1734942794144"]) == str(name): # 检查姓名是否匹配
return row_item["_widget_1734942794145"] # 返回员工ID
return None
def assign_customer_service(self, province_name, city_name, area_name, index):
"""根据省市区派发给异常回访客服"""
# try:
customer_service_info = self.find_customer_service(province_name, city_name, area_name, index)
customer_service = customer_service_info.get('_widget_1734677164870', {}).get('username') # 异常回访客服
return customer_service
# except Exception as e:
# print(f"Error finding customer service: {e}")
# return "分配失败，请检查", "分配失败，请检查", "分配失败，请检查"
def main(self):
task_start_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
global png_url, key, upload_key
self.load_all_data()
self.data_yichang_S = common_module.get_yichang_details(days_back=1).astype(str) # 获取data_NGV 并转为str
self.index = self.build_index(self.json_list)
print("开始运行main")
print(self.date_one)
data_yichang = self.data_yichang_S.copy()
def replace_values(series):
# 使用条件判断来进行替换
return series.apply(lambda x: '' if pd.isna(x) or x in ['NA', 'None', ''] else x)
# 对整个DataFrame的所有列应用替换函数
data_yichang = data_yichang.apply(replace_values)
print(data_yichang.iterrows())
for index_num, row in data_yichang.iterrows(): # 对过滤后的每一条进行派发
try:
print("1111")
payload_dict = {}
distribution_date = datetime.datetime.now(datetime.timezone.utc)
distribution_date = distribution_date.strftime('%Y-%m-%dT%H:%M:%S.%f')[:-3] + 'Z'
date_obj1 = datetime.datetime.strptime(row["init_day"], "%Y%m%d").strftime("%Y-%m-%d")
date_obj2 = datetime.datetime.strptime(row["push_day"], "%Y%m%d").strftime("%Y-%m-%d")
NGV_roles = {
'service_impl_principal': row['service_impl_principal'], # 运营负责人
'area_manager': row['area_manager'], # 区域经理
'technician': row['technician'], # 运营专家
}
print('NGV_roles', NGV_roles)
for role, name in NGV_roles.items(): # 寻找对应的员工ID
for row_item in self.staff_id_list:
staff_id = self.get_staff_id(row_item, name)
if staff_id:
NGV_roles[role] = staff_id
break # 找到后退出循环
else:
NGV_roles[role] = None # 如果没有找到对应的员工ID
print('NGV_roles[role]', NGV_roles)
relationship_manager, area_manager, technician = [NGV_roles[role] for role in
['service_impl_principal',
'area_manager',
'technician']]
UUid = time.strftime("%Y%m%d%H%M%S", time.localtime())
NGV_data_id = None
# 获取关联数据
for NGV_Data in self.NGV_data_list:
# NGV_Data = NGV_Data.get("data")
if row["org_code"] == NGV_Data.get("_widget_1734062123071"): # 门店编码
NGV_data_id = NGV_Data.get("_id")
province_name = NGV_Data.get("_widget_1734062123090")
city_name = NGV_Data.get("_widget_1734062123092")
area_name = NGV_Data.get("_widget_1734062123094")
print('111111', NGV_data_id, province_name, city_name, area_name)
if not NGV_data_id:
print("未找到数据ID")
# 根据省市区派发给异常回访客服
print('333', province_name, city_name, area_name)
customer_service = self.assign_customer_service(province_name, city_name, area_name, self.index)
payload_dict.update({
"_widget_1748241895829": {"value": row["health_warning_info"]}, # 活跃健康状态变化
"_widget_1748241895830": {"value": row["org_name"]}, # 门店名称
"_widget_1748241895831": {"value": row["contacts"]}, # 联系人
"_widget_1748241895832": {"value": row['contact_mobile']}, # 联系方式
"_widget_1748241895833": {"value": int(time.mktime(time.strptime(date_obj1, "%Y-%m-%d")) * 1000) if row[
"init_day"] != '' else ''},
# 初始日
"_widget_1748241895834": {"value": int(time.mktime(time.strptime(date_obj2, "%Y-%m-%d")) * 1000) if row[
"push_day"] != '' else ''},
# 推进日
"_widget_1748246808678": {"value": customer_service}, # 当前跟进人
"_widget_1748246808679": {"value": relationship_manager}, # 运营负责人
"_widget_1748246808680": {"value": customer_service}, # 区域客服
"_widget_1748241895839": {
"value": int(time.mktime(time.strptime(row["saas_create_time"], "%Y-%m-%d")) * 1000) if row[
"saas_create_time"] != '' else ''},
# 开户时间
"_widget_1748246808681": {"value": technician}, # 技术专家
"_widget_1748246808682": {"value": area_manager}, # 区域经理
"_widget_1748241895842": {"value": row['org_code']}, # 门店编码
"_widget_1748241895844": {"value": row['group_name']}, # 公司名称
"_widget_1748241895846": {"value": row['group_grade']}, # 公司等级
"_widget_1748241895847": {"value": row['region_name']}, # 大区
"_widget_1748241895848": {"value": row['province_name']}, # 省
"_widget_1748241895849": {"value": row['org_type']}, # 门店类型
"_widget_1748241895850": {"value": row['saas_edition_fmt']}, # 系统版本
"_widget_1748241895851": {"value": row['saas_customer_type']}, # saas客户类型
"_widget_1748241895852": {"value": row['org_stage']}, # 门店阶段
"_widget_1748241895853": {"value": row['contact_mobile']}, # 操作模式E.L/E.S
"_widget_1748241895855": {"value": row['city_name']}, # 城市
"_widget_1748247754304": {"value": NGV_data_id}, # 数据id
"_widget_1748512176655": {"value": "未处理"}, # 跟进状态
})
routine_follow_up_payload = {
"api_key": "675b900991ad2491c69389ca",
"entry_id": "68340de79f116c0b66b6b0cc", # 异常服务跟进待办
"is_start_workflow": "true",
"data": payload_dict,
"transaction_id": UUid
}
# print(routine_follow_up_payload)
res = api_instance.data_batch_create(routine_follow_up_payload)
logger.info(f"创建结果：{res}")
except:
pass
common_module.send_task_status(task_start_time, "异常服务待办派发")
if __name__ == '__main__':
start = NewExceptionTask()
start.main()
back_ground_module/JCB_abnormal_revisit.py
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from datetime import date, timedelta, datetime
import holidays
from config import Config
import pandas as pd
import pymysql # 使用 pymysql 替代 mysql.connector
from log_config import configure_task_logger, configure_error_task_logger
from api import API
from back_ground_module import CommonModule
common_module = CommonModule()
api_instance = API()
global last_day_end_customer_service, is_customer_service_data_id, customer_service_data_id
class JCBAbnormalRevisit:
"""接车宝异常回访"""
def __init__(self):
# 使用 pymysql 连接数据库
self.daily_revisit_list = None
self.abnormal_list = None
self.field_mapping = {}
self.staff_id_list = None
self.customer_service_list = None
def load_all_data(self):
# 获取接车宝异常待办
payload = {"api_key": "6717470a0b3975ef583c6df1",
"entry_id": "67c156ba635191b64af8a110",
}
abnormal_service = api_instance.entry_data_list(payload)
self.abnormal_list = abnormal_service.get("data") # api请求格式，将数据封装在data字典里
# 获取接车宝日常回访单
payload = {"api_key": "6717470a0b3975ef583c6df1",
"entry_id": "67174710da507490d8ac12c1",
}
daily_revisit = api_instance.entry_data_list(payload)
self.daily_revisit_list = daily_revisit.get("data") # api请求格式，将数据封装在data字典里
def load_cus_data(self):
# 获取接车宝客服表单
payload = {"api_key": "6717470a0b3975ef583c6df1",
"entry_id": "67b6f2462f9ac03b783d409a",
}
customer_service = api_instance.entry_data_list(payload)
customer_service_list = customer_service.get("data") # api请求格式，将数据封装在data字典里
return customer_service_list
def today_customer_service_list(self):
# 获取今日接车宝派发客服顺序
today_customer_service_list = []
all_customer_service_list = []
today_customer_service_start_list = []
for row_items in self.load_cus_data():
# print(row_items)
customer_service_name_id = row_items.get("_widget_1740042824214", {}).get("username", {})
customer_service_name = row_items.get("_widget_1740042824214", {}).get("name", {})
customer_service_state = row_items.get("_widget_1740117343937", {})
is_last_day_end = row_items.get("_widget_1740042824216", {})
customer_service_data_id = row_items.get("_id", {})
print(customer_service_name, customer_service_name_id, customer_service_state, is_last_day_end)
all_customer_service_list.append(
[customer_service_name, customer_service_name_id, customer_service_state, is_last_day_end,
customer_service_data_id])
if is_last_day_end == "是": # 判断是否是下次开始位置
last_day_end_customer_service = customer_service_name_id
is_customer_service_data_id = row_items.get("_id", {})
split_index = None
for index, row in enumerate(all_customer_service_list):
print(row[3])
if row[3] == "是":
split_index = index
print(f"找到索引 {index}")
break
if split_index is not None:
# 根据索引切割列表
first_part = all_customer_service_list[split_index:] # 索引位置及之后的行
second_part = all_customer_service_list[:split_index] # 索引位置之前的行
# 调换两个子列表的位置并重新组合
today_customer_service_start_list = first_part + second_part
else:
# 如果没有找到“是”，保持原列表不变
today_customer_service_start_list = all_customer_service_list
pass
for index, row in enumerate(today_customer_service_start_list):
if row[2] == "开":
today_customer_service_list.append(row[1])
return today_customer_service_list, is_customer_service_data_id, all_customer_service_list
def send_request(self, df):
today_customer_service_list, is_customer_service_data_id, all_customer_service_list = self.today_customer_service_list()
# 初始化派发索引
next_dispatcher_index = 0
# 显式循环分配跟进人
follow_up_persons = []
for _ in range(len(df)):
follow_up_person = today_customer_service_list[next_dispatcher_index]
follow_up_persons.append(follow_up_person)
next_dispatcher_index = (next_dispatcher_index + 1) % len(today_customer_service_list)
# 添加跟进人到 DataFrame
df["跟进人"] = follow_up_persons
# 获取下一个派发人
next_dispatcher = today_customer_service_list[next_dispatcher_index]
new_sign_abnormal_data = [self.row_to_dict(row, self.field_mapping) for index, row in
df.iterrows()]
data = {'api_key': Config.EFFICIENT_CAR_PICKUP_APP_ID, 'entry_id': "67174710da507490d8ac12c1",
"data_list": new_sign_abnormal_data} # 派发数据
api_instance.entry_data_batch_create(data)
data1 = {"api_key": Config.EFFICIENT_CAR_PICKUP_APP_ID,
"entry_id": Config.EFFICIENT_CAR_PICKUP_CUSTOMER_SERVICE_ID,
"data_id": is_customer_service_data_id,
"data":
{"_widget_1740042824216": {"value": ""}, }
} # 原来的是"_widget_1740042824216": {"value": "是"},修改昨日截至人员
next_customer_service_data_id = None
for index, row in enumerate(all_customer_service_list):
print(row[3])
if row[1] == next_dispatcher:
next_customer_service_data_id = row[4]
break
data2 = {"api_key": Config.EFFICIENT_CAR_PICKUP_APP_ID,
"entry_id": Config.EFFICIENT_CAR_PICKUP_CUSTOMER_SERVICE_ID,
"data_id": next_customer_service_data_id,
"data":
{"_widget_1740042824216": {"value": "是"}, }}# 明日派发起点人员
api_instance.entry_data_update(data1)
api_instance.entry_data_update(data2)
def main(self):
self.load_all_data()
task_start_time =datetime.now().strftime("%Y-%m-%d %H:%M:%S")
data_JCB = common_module.get_jcb_details()
# 保存为CSV文件
output_dir = "output" # 设置输出目录
# 创建输出目录（如果不存在）
import os
os.makedirs(output_dir, exist_ok=True)
# data_JCB.to_csv(os.path.join(output_dir, 'JCB_all_data.csv'), index=False)
self.fields()
# 异常待办回访 近1个月开单为0客户
# 当前日期
current_date = datetime.now()
current_date = current_date + timedelta(days=1)
current_date_str = current_date.strftime("%Y-%m-%d")
# current_date = datetime.now()
thirty_days_ago = current_date - timedelta(days=30)
thirty_days_ago = thirty_days_ago.date()
abnormal_data = []
JDY_abnormal_data = []
JDY_revisit_data = []
# df = pd.read_csv(os.path.join(output_dir, "JCB_异常待办.csv")) # 读取异常待办表
# print(df)
for index, row in data_JCB.iterrows():
new_row = row.copy()
new_row['开户日'] = datetime.strptime(new_row['开户日'], "%Y-%m-%d").date()
if new_row['开户日'] < thirty_days_ago and row['近30天开单天数'] == 0 and row['客户状态'] == "留存":
# print(row['账号'], row['开户日'], row['近30天开单天数'], row["客户状态"])
row["日期"] = datetime.strptime(row['开户日'], "%Y-%m-%d").date()
row['日期'] = row["日期"].strftime("%Y-%m-%d")
abnormal_data.append(row)
# 推送给客服
abnormal_data = pd.DataFrame(abnormal_data)
abnormal_data["表单类型"] = "异常待办"
abnormal_data["派发日期"] = current_date_str
# abnormal_data.to_excel(os.path.join(output_dir, 'JCB_异常待办.xlsx'), index=False) # 派发B(所有异常待办)
for abnormal_items in self.abnormal_list:
last_send_date = abnormal_items.get("_widget_1740723898405", {}) # 派发日期
last_30_days_orders = abnormal_items.get("_widget_1740723898401", {}) # 近30天开单数
phone = abnormal_items.get("_widget_1740723898391", {}) # 手机号
account = abnormal_items.get("_widget_1740723898390", {}) # 账号
data_id = abnormal_items.get("_id", {}) # 数据id
JDY_abnormal_data.append([data_id, account, phone, last_send_date, last_30_days_orders])
JDY_abnormal_data = pd.DataFrame(JDY_abnormal_data,
columns=["数据id", "账号", "联系手机号", "派发日期",
"近30天开单天数"]) # 派发A（简道云上异常待办）
# JDY_abnormal_data.columns = ["数据id", "账号", "联系手机号", "派发日期", "近30天开单天数"]
# JDY_abnormal_data.to_excel(os.path.join(output_dir, 'JCB_云端异常待办.xlsx'), index=False) # 派发A
# 将 '联系手机号' 列转换为字符串类型
JDY_abnormal_data['联系手机号'] = JDY_abnormal_data['联系手机号'].astype(str).str.replace('.0', '')
abnormal_data['联系手机号'] = abnormal_data['联系手机号'].astype(str)
# JDY_abnormal_data.to_excel(os.path.join(output_dir, 'JCB_云端异常待办.xlsx'), index=False) # 派发A
# abnormal_data.to_excel(os.path.join(output_dir, 'JCB_今日异常待办.xlsx'), index=False) # 派发B
today = datetime.now().weekday()
# 随机抽40条派发
df_40 = pd.DataFrame()
if 0 <= today <= 4:
# if 1>2:
# 假设 JDY_abnormal_data 和 abnormal_data 都有重复列 '重复列'
df3 = pd.merge(JDY_abnormal_data, abnormal_data, on=["联系手机号", "账号"], how='inner',
suffixes=('', '_y'))
# 删除以 _y 结尾的列（即来自右侧 DataFrame 的重复列）
df3 = df3.loc[:, ~df3.columns.str.endswith('_y')]
df3['派发日期'] = pd.to_datetime(df3['派发日期']).dt.strftime("%Y-%m-%d")
# df3.to_excel(os.path.join(output_dir, 'JCB_异常待办情况1.xlsx'),
# index=False, ) # B存在，A存在 ，今日派发与历史派发都存在，派发并删历史
df_40 = df3[df3.index < 40]
# df_40.to_excel(os.path.join(output_dir, 'JCB_异常待办情况2.xlsx'), index=False, )
for index, row in df_40.iterrows(): # 删除已推送的数据
delete_data = {"api_key": Config.EFFICIENT_CAR_PICKUP_APP_ID,
"entry_id": Config.EFFICIENT_CAR_PICKUP_CUSTOMER_HISTORY_ID,
"data_id": row["数据id"]}
# print(delete_data)
api_instance.entry_data_delete(delete_data)
# B不存在A存在 今日派发不存在，历史存在，删历史
# 使用 outer 合并，并添加指示器列 _merge
df_merged = pd.merge(JDY_abnormal_data, abnormal_data, on=["联系手机号", "账号"], how='outer', indicator=True,
suffixes=('', '_y')) # outer保留所有数据，indicator标注来源
# 筛选出只存在于 JDY_abnormal_data 中的行
df_a_not_in_b = df_merged[df_merged['_merge'] == 'left_only']
# 删除以 _y 结尾的列（即来自右侧 DataFrame 的重复列）
df_a_not_in_b = df_a_not_in_b.loc[:, ~df_a_not_in_b.columns.str.endswith('_y')]
df_a_not_in_b['派发日期'] = pd.to_datetime(df_a_not_in_b['派发日期']).dt.strftime("%Y-%m-%d")
# 保存到 Excel 文件
# df_a_not_in_b.to_excel(os.path.join(output_dir, 'JCB_异常待办情况_A存在B不存在.xlsx'), index=False)
for index, row in df_a_not_in_b.iterrows(): # 删除已推送的数据
delete_data = {"api_key": Config.EFFICIENT_CAR_PICKUP_APP_ID,
"entry_id": Config.EFFICIENT_CAR_PICKUP_CUSTOMER_HISTORY_ID,
"data_id": row["数据id"]}
# print(delete_data)
api_instance.entry_data_delete(delete_data)
# B存在A不存在 今日派发存在，历史不存在，为新增异常，直接派发
df_merged = pd.merge(JDY_abnormal_data, abnormal_data, on=["联系手机号", "账号"], how='outer', indicator=True,
suffixes=('_x', '')) # outer保留所有数据，indicator标注来源
# df_merged.to_excel(os.path.join(output_dir, 'JCB_异常待办情况_B存在A不存在_134434.xlsx'), index=False)
# 筛选出只存在于 JDY_abnormal_data 中的行
df_b_not_in_a = df_merged[df_merged['_merge'] == 'right_only']
# df_b_not_in_a.to_excel(os.path.join(output_dir, 'JCB_异常待办情况_B存在A不存在_111.xlsx'), index=False)
# 删除以 _y 结尾的列（即来自右侧 DataFrame 的重复列）
df_b_not_in_a = df_b_not_in_a.loc[:, ~df_b_not_in_a.columns.str.endswith('_x')]
# df_b_not_in_a.to_excel(os.path.join(output_dir, 'JCB_异常待办情况_B存在A不存在_122.xlsx'), index=False)
df_b_not_in_a['派发日期'] = pd.to_datetime(df_b_not_in_a['派发日期']).dt.strftime("%Y-%m-%d")
# 保存到 Excel 文件
# df_b_not_in_a.to_excel(os.path.join(output_dir, 'JCB_异常待办情况_B存在A不存在.xlsx'), index=False)
# 合并两个当日派发的df
df_abnormal_data = pd.concat([df_40, df_b_not_in_a], ignore_index=True)
# df_abnormal_data.to_excel(os.path.join(output_dir, 'JCB_异常待办情况_合并当日派发.xlsx'), index=False)
for abnormal_items in self.daily_revisit_list: # 遍历云端已经派发的数据
account = abnormal_items.get("_widget_1739258942667", {}) # 账号
sub_date = abnormal_items.get("createTime", {}) # 提交时间
update_date = abnormal_items.get("updateTime", {}) # 更新时间
entry_style = abnormal_items.get("_widget_1739951204545", {}) # 表单类型
entry_type = abnormal_items.get("flowState", {}) # 表单状态 0流转中 1流转完成 2 手动结束
data_id = abnormal_items.get("_id", {}) # 数据id
JDY_revisit_data.append([data_id, account, sub_date, update_date, entry_style, entry_type])
JDY_revisit_data = pd.DataFrame(JDY_revisit_data)
JDY_revisit_data.columns = ["数据id", "账号", "提交时间", "更新时间", "表单类型", "表单状态"]
# JDY_revisit_data.to_excel(os.path.join(output_dir, 'JCB_日常回访_原始数据.xlsx'), index=False)
filtered_data = JDY_revisit_data[JDY_revisit_data['表单类型'] == '异常待办'] # 过滤表单类型
# filtered_data = filtered_data[filtered_data['表单状态'] == 1] # 过滤表单状态
# filtered_data.to_excel(os.path.join(output_dir, 'JCB_日常回访_过滤数据.xlsx'), index=False)
filtered_data['提交时间'] = pd.to_datetime(filtered_data['提交时间']).dt.strftime("%Y-%m-%d")
latest_update_time = filtered_data.groupby('账号')['提交时间'].max().reset_index()
latest_update_time.rename(columns={'提交时间': '最新提交时间'}, inplace=True)
filtered_data_with_latest = pd.merge(
filtered_data,
latest_update_time,
left_on=['账号', '提交时间'],
right_on=['账号', '最新提交时间']
)
# 过滤出每个账号中提交时间为最新的记录
latest_JDY_abnormal_data = filtered_data_with_latest[
filtered_data_with_latest['提交时间'] == filtered_data_with_latest['最新提交时间']
]
# latest_JDY_abnormal_data.to_excel(os.path.join(output_dir, 'JCB_日常回访_最新数据_1.xlsx'), index=False)
latest_JDY_abnormal_data['提交时间'] = pd.to_datetime(latest_JDY_abnormal_data['提交时间']).dt.strftime("%Y-%m-%d")
thirty_days_ago = (current_date - timedelta(days=30)).strftime("%Y-%m-%d")
final_JDY_abnormal_data = latest_JDY_abnormal_data[latest_JDY_abnormal_data['提交时间'] > thirty_days_ago] # 筛选出提交时间为近30天的数据
# final_JDY_abnormal_data.to_excel(os.path.join(output_dir, 'JCB_日常回访_最新数据.xlsx'), index=False)
df_abnormal_data = df_abnormal_data[~df_abnormal_data['账号'].isin(final_JDY_abnormal_data['账号'])]
# empty_num = df_abnormal_data['手机号'].isnull().sum()
df_abnormal_data = df_abnormal_data[df_abnormal_data["联系手机号"] != "None"]
# df_abnormal_data.to_excel(os.path.join(output_dir, 'JCB_异常待办情况_派发数据.xlsx'), index=False)
self.send_request(df_abnormal_data)
common_module.send_task_status(task_start_time, "接车宝异常派发")
# df_abnormal_data = [self.row_to_dict(row, self.field_mapping) for index, row in
# df_abnormal_data.iterrows()]
#
# data = {'api_key': Config.EFFICIENT_CAR_PICKUP_APP_ID, 'entry_id':"67174710da507490d8ac12c1",
# "data_list": df_abnormal_data}
#
#
# result = api_instance.entry_data_batch_create(data)
@staticmethod
def row_to_dict(row, field_mapping):
"""将一行数据转换为指定格式的字典"""
result = {}
# print(field_mapping)
for col_name, widget_id in field_mapping.items():
# print(col_name, widget_id)
if col_name in row:
value = row[col_name]
clean_value = None if pd.isna(value) else value
result[widget_id] = {"value": clean_value}
return result
def fields(self):
self.field_mapping = {"日期": "_widget_1739252804406", "产品名称": "_widget_1739252804397",
"账号": "_widget_1739258942667", "联系手机号": "_widget_1739252804407",
"使用时长": "_widget_1739252804409", "开户日": "_widget_1739252804396",
"到期日": "_widget_1739252804408", "续约日": "_widget_1739252804410",
"客户状态": "_widget_1739252804400", "近一周开单量": "_widget_1739252804413",
"近一周是否活跃": "_widget_1739252804414",
"G状态：近30天开单大于等于10天": "_widget_1739252804415",
"当月开单天数": "_widget_1739252804416", "近30天开单天数": "_widget_1739252804417",
"当月G天数": "_widget_1739252804418", "日分区": "_widget_1739252804419",
"表单类型": "_widget_1739951204545", "派发日期": "_widget_1740036367181",
"跟进人": "_widget_1740043340255",
}
if __name__ == "__main__":
start = JCBAbnormalRevisit()
start.main()
# if result is not None:
# print(result.head()) # 打印前几行数据
back_ground_module/JCB_efficient_car_pickup.py
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from datetime import date, timedelta, datetime
import holidays
from config import Config
import pandas as pd
import pymysql # 使用 pymysql 替代 mysql.connector
from back_ground_module import CommonModule
from log_config import configure_task_logger, configure_error_task_logger
from api import API
common_module = CommonModule()
api_instance = API()
class JCBEfficientCarPickup:
"""接车宝日常回访"""
def __init__(self):
# 使用 pymysql 连接数据库
self.field_mapping = {}
self.staff_id_list = None
self.customer_service_list = None
def load_cus_data(self):
# 获取接车宝客服表单
payload = {"api_key": "6717470a0b3975ef583c6df1",
"entry_id": "67b6f2462f9ac03b783d409a",
}
customer_service = api_instance.entry_data_list(payload)
customer_service_list = customer_service.get("data") # api请求格式，将数据封装在data字典里
return customer_service_list
def today_customer_service_list(self):
# 获取今日接车宝派发客服顺序
today_customer_service_list = []
all_customer_service_list = []
today_customer_service_start_list = []
for row_items in self.load_cus_data():
# print(row_items)
customer_service_name_id = row_items.get("_widget_1740042824214", {}).get("username", {})
customer_service_name = row_items.get("_widget_1740042824214", {}).get("name", {})
customer_service_state = row_items.get("_widget_1740117343937", {})
is_last_day_end = row_items.get("_widget_1740042824216", {})
customer_service_data_id = row_items.get("_id", {})
print(customer_service_name, customer_service_name_id, customer_service_state, is_last_day_end)
all_customer_service_list.append(
[customer_service_name, customer_service_name_id, customer_service_state, is_last_day_end,
customer_service_data_id])
if is_last_day_end == "是": # 判断是否是下次开始位置
last_day_end_customer_service = customer_service_name_id
is_customer_service_data_id = row_items.get("_id", {})
split_index = None
for index, row in enumerate(all_customer_service_list):
print(row[3])
if row[3] == "是":
split_index = index
print(f"找到索引 {index}")
break
if split_index is not None:
# 根据索引切割列表
first_part = all_customer_service_list[split_index:] # 索引位置及之后的行
second_part = all_customer_service_list[:split_index] # 索引位置之前的行
# 调换两个子列表的位置并重新组合
today_customer_service_start_list = first_part + second_part
else:
# 如果没有找到“是”，保持原列表不变
today_customer_service_start_list = all_customer_service_list
pass
for index, row in enumerate(today_customer_service_start_list):
if row[2] == "开":
today_customer_service_list.append(row[1])
return today_customer_service_list, is_customer_service_data_id, all_customer_service_list
def send_request(self, df):
today_customer_service_list, is_customer_service_data_id, all_customer_service_list = self.today_customer_service_list()
# 初始化派发索引
next_dispatcher_index = 0
# 显式循环分配跟进人
follow_up_persons = []
for _ in range(len(df)):
follow_up_person = today_customer_service_list[next_dispatcher_index]
follow_up_persons.append(follow_up_person)
next_dispatcher_index = (next_dispatcher_index + 1) % len(today_customer_service_list)
# 添加跟进人到 DataFrame
df["跟进人"] = follow_up_persons
# 获取下一个派发人
next_dispatcher = today_customer_service_list[next_dispatcher_index]
new_sign_abnormal_data = [self.row_to_dict(row, self.field_mapping) for index, row in
df.iterrows()]
data = {'api_key': Config.EFFICIENT_CAR_PICKUP_APP_ID, 'entry_id': Config.EFFICIENT_CAR_PICKUP_ENTRY_ID,
"data_list": new_sign_abnormal_data}
result = api_instance.entry_data_batch_create(data)
data1 = {"api_key": Config.EFFICIENT_CAR_PICKUP_APP_ID,
"entry_id": Config.EFFICIENT_CAR_PICKUP_CUSTOMER_SERVICE_ID,
"data_id": is_customer_service_data_id,
"data":
{"_widget_1740042824216": {"value": ""}, }
} # 原来的是"_widget_1740042824216": {"value": "是"},修改昨日截至人员
next_customer_service_data_id = None
for index, row in enumerate(all_customer_service_list):
print(row[3])
if row[1] == next_dispatcher:
next_customer_service_data_id = row[4]
break
data2 = {"api_key": Config.EFFICIENT_CAR_PICKUP_APP_ID,
"entry_id": Config.EFFICIENT_CAR_PICKUP_CUSTOMER_SERVICE_ID,
"data_id": next_customer_service_data_id,
"data":
{"_widget_1740042824216": {"value": "是"}, }}
api_instance.entry_data_update(data1)
api_instance.entry_data_update(data2)
def main(self):
task_start_time =datetime.now().strftime("%Y-%m-%d %H:%M:%S")
data_JCB = common_module.get_jcb_details()
print(data_JCB)
# 保存为CSV文件
output_dir = "output" # 设置输出目录
# 创建输出目录（如果不存在）
import os
os.makedirs(output_dir, exist_ok=True)
# data_JCB.to_csv(os.path.join(output_dir, 'JCB_all_data.csv'), index=False)
self.fields()
# 新签异常待办回访。
# 当前日期
current_date = datetime.now()
current_date = current_date + timedelta(days=0)
current_date_str = current_date.strftime("%Y-%m-%d")
seven_days_ago = current_date - timedelta(days=7)
seven_days_ago = seven_days_ago.date()
# print(three_days_ago)
new_sign_abnormal = []
for index, row in data_JCB.iterrows():
new_row = row.copy()
# 先转成字符串，再解析回 date 对象
new_row['开户日'] = datetime.strptime(str(row['开户日']), "%Y-%m-%d").date()
if new_row['开户日'] == seven_days_ago and row['当月开单天数'] == 0:
# print(row['账号'], row['开户日'], row['当月开单天数'])
row["日期"] = datetime.strptime(str(row['开户日']), "%Y-%m-%d").date()
row['日期'] = row["日期"].strftime("%Y-%m-%d")
new_sign_abnormal.append(row)
new_sign_abnormal = pd.DataFrame(new_sign_abnormal)
new_sign_abnormal["表单类型"] = "新签异常待办"
new_sign_abnormal["派发日期"] = current_date_str
self.send_request(new_sign_abnormal) # 发送请求
# 优质客户转商机
# current_date = datetime.now()
thirty_days_ago = current_date - timedelta(days=30)
sixty_days_ago = current_date - timedelta(days=60)
thirty_days_ago = thirty_days_ago.date()
sixty_days_ago = sixty_days_ago.date()
customer_to_opportunity = []
for index, row in data_JCB.iterrows():
new_row = row.copy()
# 先转成字符串，再解析回 date 对象
new_row['到期日'] = datetime.strptime(str(row['到期日']), "%Y-%m-%d").date()
if new_row['到期日'] == thirty_days_ago and row['近一周开单量'] >= 3 and row[
'G状态：近30天开单大于等于10天'] == 1:
print(row['账号'], row['到期日'], row['当月开单天数'], row['当月G天数'])
row["日期"] = datetime.strptime(str(row['开户日']), "%Y-%m-%d").date()
row['日期'] = row["日期"].strftime("%Y-%m-%d")
customer_to_opportunity.append(row)
# 推送给客服
pass
if new_row['到期日'] == sixty_days_ago and row['近一周开单量'] >= 3 and row[
'G状态：近30天开单大于等于10天'] == 1:
print(row['账号'], row['到期日'], row['当月开单天数'], row['当月G天数'])
row["日期"] = datetime.strptime(str(row['开户日']), "%Y-%m-%d").date()
row['日期'] = row["日期"].strftime("%Y-%m-%d")
customer_to_opportunity.append(row)
# 推送给客服
pass
customer_to_opportunity = pd.DataFrame(customer_to_opportunity)
customer_to_opportunity["表单类型"] = "续约优质客户转商机"
customer_to_opportunity["派发日期"] = current_date_str
self.send_request(customer_to_opportunity)
# 过期7天客服回访
# current_date = datetime.now()
seven_days_ago = current_date - timedelta(days=7)
seven_days_ago = seven_days_ago.date()
outdated_30 = []
for index, row in data_JCB.iterrows():
new_row = row.copy()
new_row['到期日'] = datetime.strptime(str(row['到期日']), "%Y-%m-%d").date()
# seven_days_ago = seven_days_ago.date()
# print(row['到期日'], seven_days_ago)
if new_row['到期日'] == seven_days_ago and row['客户状态'] == "过期":
print(row['账号'], row['到期日'], row['当月开单天数'], row['当月G天数'])
row["日期"] = datetime.strptime(str(row['开户日']), "%Y-%m-%d").date()
row['日期'] = row["日期"].strftime("%Y-%m-%d")
outdated_30.append(row)
# 推送给客服
pass
outdated_30 = pd.DataFrame(outdated_30)
outdated_30["表单类型"] = "过期7天回访"
outdated_30["派发日期"] = current_date_str
self.send_request(outdated_30)
common_module.send_task_status(task_start_time, "接车宝日常派发")
@staticmethod
def row_to_dict(row, field_mapping):
"""将一行数据转换为指定格式的字典"""
result = {}
# print(field_mapping)
for col_name, widget_id in field_mapping.items():
# print(col_name, widget_id)
if col_name in row:
value = row[col_name]
clean_value = None if pd.isna(value) else value
result[widget_id] = {"value": clean_value}
return result
def fields(self):
self.field_mapping = {"日期": "_widget_1739252804406", "产品名称": "_widget_1739252804397",
"账号": "_widget_1739258942667", "联系手机号": "_widget_1739252804407",
"使用时长": "_widget_1739252804409", "开户日": "_widget_1739252804396",
"到期日": "_widget_1739252804408", "续约日": "_widget_1739252804410",
"客户状态": "_widget_1739252804400", "近一周开单量": "_widget_1739252804413",
"近一周是否活跃": "_widget_1739252804414",
"G状态：近30天开单大于等于10天": "_widget_1739252804415",
"当月开单天数": "_widget_1739252804416", "近30天开单天数": "_widget_1739252804417",
"当月G天数": "_widget_1739252804418", "日分区": "_widget_1739252804419",
"表单类型": "_widget_1739951204545", "派发日期": "_widget_1740036367181",
"跟进人": "_widget_1740043340255",
}
if __name__ == "__main__":
start = JCBEfficientCarPickup()
start.main()
back_ground_module/__init__.py
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from back_ground_module.common_module import CommonModule
from back_ground_module.revisit_new_services_180 import NewServicesRevisit
from back_ground_module.update_NGV_data import UpdateNGVData
from back_ground_module.revisit_key_customer import KeyCustomerRevisit
from back_ground_module.revisit_renew_services_90_120_180 import RenewServicesRevisit
from back_ground_module.update_all_NGV_data_daily import UpdateAllNGVDataDaily
from back_ground_module.JCB_efficient_car_pickup import JCBEfficientCarPickup
from back_ground_module.JCB_abnormal_revisit import JCBAbnormalRevisit
from back_ground_module.data_Support_Private_Mini_Program import importSYXCXData
from back_ground_module.data_Support_Commission import importCommissionData
from back_ground_module.data_Support_DifferentIndustries import importDifferentIndustriesData
from back_ground_module.data_Support_GroupNotification import importGroupNotificationData
from back_ground_module.update_email_to_store_daily_use import EmailProcessor
from back_ground_module.Exception_Task import NewExceptionTask
from back_ground_module.revisit_all_information import RevisitAllInformation
from back_ground_module.yida_Fpo_Jandaoyun import YDFpoJiandaoyun
from back_ground_module.get_process_time import TimeConsumingProcess
from back_ground_module.update_BI_CRM_info import CRMDataProcessor
from back_ground_module.update_ID_form import update_ID_form
from back_ground_module.indtall_event_dispatcher import InstallEventDispatcher
from back_ground_module.新签180天重构 import NewServicesRevisitTest
from back_ground_module.update_denominator_reporting_adjustment_to_bi import DenominatorReportingAdjustment
from back_ground_module.update_molecule_reporting_adjustment_to_bi import MoleculeReportingAdjustment
from back_ground_module.import_performance_data import ImportPerformanceData
from back_ground_module.data_monitor import DataMonitor
from back_ground_module.new_dealer_service_order_to_bi import NewDealerServiceOrderToBI
back_ground_module/common_module.py
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from datetime import datetime, timezone, timedelta, date, UTC
import holidays
from config import Config
import psycopg2
import pandas as pd
import pymysql
from api import API
from log_config import configure_task_logger, configure_error_task_logger
api_instance = API()
# 获取已经配置好的常规日志记录器
logger = configure_task_logger()
# 获取已经配置好的错误任务日志记录器
error_task_logger = configure_error_task_logger()
class CommonModule:
"""工具类"""
def __init__(self):
# 初始化中国节假日对象
self.cn_holidays = holidays.country_holidays('CN', years=2025)
# 创建一个存储日期的集合，用于去重
self.date_set = set()
self.conn = Config.CONN_INFO
def time_to_UTC(self, time_input):
"""
时间转为UTC格式（兼容字符串和Timestamp输入）
:param time_input: 支持以下格式：
- 字符串格式："2025-06-05 14:30:00" 或 "2025-06-05"
- Pandas Timestamp对象
:return: ISO8601格式的UTC时间字符串（如"2025-06-05T06:30:00Z"）
"""
# 处理Timestamp输入
if isinstance(time_input, pd.Timestamp):
dt = time_input.to_pydatetime()
# 处理字符串输入
else:
try:
dt = datetime.strptime(time_input, "%Y-%m-%d %H:%M:%S")
except ValueError:
try:
dt = datetime.strptime(time_input, "%Y-%m-%d")
except ValueError as e:
raise ValueError(f"不支持的日期格式: {time_input}") from e
# 转换为UTC时间（假设原始时间为东八区）
dt_utc = dt - timedelta(hours=8)
return dt_utc.replace(tzinfo=timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ")
def get_holiday_list(self, year=None):
"""
获取指定年份的节假日和周日列表。
如果没有提供年份，则使用当前年份。
"""
if year is None:
year = date.today().year
# 清空集合，防止重复添加数据
self.date_set.clear()
# 添加节假日到集合
for holiday in self.cn_holidays:
if holiday.year == year:
self.date_set.add(str(holiday))
# 添加该年的所有周日到集合
start_date = date(year, 1, 1)
end_date = date(year, 12, 31)
current_date = start_date
while current_date <= end_date:
if current_date.weekday() == 6: # 周日的weekday值为6
self.date_set.add(str(current_date))
current_date += timedelta(days=1)
# 将集合转换为排序后的列表
return sorted(list(self.date_set), reverse=False)
def get_ngv_details(self, days_back=1):
"""
从固定的数据库中获取前几天的NGV明细。
参数 `days_back` 表示相对于今天的天数偏移量，默认为1（即前一天）。
返回包含NGV明细的pandas DataFrame。
"""
try:
# 获得连接
conn = psycopg2.connect(**self.conn)
cursor = conn.cursor()
# 获取指定天数前的日期
now_time = datetime.now()
target_time = now_time + timedelta(days=-days_back)
target_date_id = int(target_time.strftime('%Y%m%d')) # 获取目标日期
# sql语句查询
sql = f"""
SELECT * FROM "public"."holo_ads_report_saas_profile_ngv_detail_d" WHERE "date_id" = '{target_date_id}' ;
"""
# 执行语句并获取结果集
cursor.execute(sql)
rows = cursor.fetchall()
all_fields = cursor.description
# 执行结果转化为dataframe
col = [i[0] for i in all_fields]
data_NGV = pd.DataFrame(rows, columns=col)
# 尝试自动解析日期时间字符串
time_format = "%Y-%m-%d %H:%M:%S"
if 'saas_create_time' in data_NGV.columns:
data_NGV['saas_create_time'] = pd.to_datetime(data_NGV['saas_create_time'], format=time_format,
errors='coerce')
data_NGV['saas_create_time'] = data_NGV['saas_create_time'].dt.strftime('%Y-%m-%d')
# 关闭游标和连接
cursor.close()
conn.close()
return data_NGV
except Exception as e:
print(f"Error occurred: {e}")
return None
def get_yichang_details(self, days_back=1):
"""
从固定的数据库中获取前几天的异常明细。
参数 `days_back` 表示相对于今天的天数偏移量，默认为1（即前一天）。
返回包含异常明细的pandas DataFrame。
"""
try:
# 获得连接
conn = psycopg2.connect(**self.conn)
cursor = conn.cursor()
# 获取指定天数前的日期
now_time = datetime.now()
target_time = now_time + timedelta(days=-days_back)
target_date_id = int(target_time.strftime('%Y%m%d')) # 获取目标日期
# sql语句查询
sql = f"""SELECT * FROM "public"."holo_ads_dataservice_saas_org_health_warning" WHERE "pt" = '{target_date_id}' and "org_type" = '一般';"""
# 执行语句并获取结果集
cursor.execute(sql)
rows = cursor.fetchall()
all_fields = cursor.description
# 执行结果转化为dataframe
col = [i[0] for i in all_fields]
data_yichang = pd.DataFrame(rows, columns=col)
# 尝试自动解析日期时间字符串
time_format = "%Y-%m-%d %H:%M:%S"
if 'saas_create_time' in data_yichang.columns:
data_yichang['saas_create_time'] = pd.to_datetime(data_yichang['saas_create_time'], format=time_format,
errors='coerce')
data_yichang['saas_create_time'] = data_yichang['saas_create_time'].dt.strftime('%Y-%m-%d')
# 关闭游标和连接
cursor.close()
conn.close()
return data_yichang
except Exception as e:
print(f"Error occurred: {e}")
return None
def get_saas_data(self):
pass
def get_jcb_details(self, ):
"""
从固定的数据库中获取前几天的NGV明细。
参数 `days_back` 表示相对于今天的天数偏移量，默认为1（即前一天）。
返回包含NGV明细的pandas DataFrame。
"""
# 保存为CSV文件
output_dir = "output" # 设置输出目录
# 创建输出目录（如果不存在）
import os
os.makedirs(output_dir, exist_ok=True)
try:
# 获得连接并创建游标
conn = pymysql.connect(
host=Config.BI_CONN_host,
database=Config.BI_CONN_INFO_database,
user=Config.BI_CONN_INFO_user,
password=Config.BI_CONN_INFO_password,
# charset='utf8mb4', # 设置字符集以避免编码问题
# cursorclass=pymysql.cursors.DictCursor # 返回字典形式的结果
)
cursor = conn.cursor()
# 获取指定天数前的日期
# now_time = datetime.now()
# target_time = now_time + timedelta(days=-days_back)
target_date_id = "接车宝" # 获取目标日期
# SQL 查询语句
sql = f"""
SELECT * FROM jdy_hs_holo_dws_sales_magic_box_ngv_d WHERE 产品名称 = '{target_date_id}';
"""
# 执行查询并获取结果
cursor.execute(sql)
rows = cursor.fetchall() # pymysql 的 DictCursor 会返回字典列表
# 将结果转换为 DataFrame
if rows: # 如果有数据
data_NGV = pd.DataFrame(rows)
if data_NGV.shape[1] > 16:
data_NGV = data_NGV.iloc[:, :16]
else: # 如果没有数据，返回空 DataFrame
data_NGV = pd.DataFrame()
# 尝试自动解析日期时间字符串
time_format = "%Y-%m-%d %H:%M:%S"
if 'saas_create_time' in data_NGV.columns:
data_NGV['saas_create_time'] = pd.to_datetime(data_NGV['saas_create_time'], format=time_format,
errors='coerce')
data_NGV['saas_create_time'] = data_NGV['saas_create_time'].dt.strftime('%Y-%m-%d')
# 关闭游标
cursor.close()
headers = [
"日期",
"产品名称",
"账号", # 唯一值
"联系手机号",
"开户日",
"使用时长",
"续约日",
"到期日",
"客户状态",
"近一周开单量",
"近一周是否活跃",
"G状态：近30天开单大于等于10天",
"当月开单天数",
"近30天开单天数",
"当月G天数",
"日分区",
]
data_NGV.columns = headers
cols_to_str =["日期","开户日","续约日","到期日"]
data_NGV[cols_to_str] = data_NGV[cols_to_str].apply(lambda x: x.astype(str))
data_NGV.to_csv(os.path.join(output_dir, f"{target_date_id}.csv"), index=False)
return data_NGV
except Exception as e:
print(f"Error occurred: {e}")
return None
def get_syxcx_details(self, ):
"""
从f6operation_data_relay数据库中获取私域小程序数据。
返回pandas DataFrame。
"""
try:
# 获得连接并创建游标
conn = pymysql.connect(
host=Config.BI_CONN_host,
database=Config.BI_CONN_INFO_database,
user=Config.BI_CONN_INFO_user,
password=Config.BI_CONN_INFO_password,
# charset='utf8mb4', # 设置字符集以避免编码问题
# cursorclass=pymysql.cursors.DictCursor # 返回字典形式的结果
)
cursor = conn.cursor()
# 获取指定天数前的日期
# now_time = datetime.now()
# target_time = now_time + timedelta(days=-days_back)
# SQL 查询语句
sql = f"""
SELECT * FROM jiandaoyun_dailyvisit_privateminiprogram;
"""
# 执行查询并获取结果
cursor.execute(sql)
rows = cursor.fetchall() # pymysql 的 DictCursor 会返回字典列表
# 将结果转换为 DataFrame
if rows: # 如果有数据
data_SY = pd.DataFrame(rows)
else: # 如果没有数据，返回空 DataFrame
data_SY = pd.DataFrame()
# 关闭游标
cursor.close()
headers = [
"公司ID", "公众号名称", "小程序模板类型", "是否开通微信商城", "上架商品数",
"上架套餐卡数", "上架实体商品数", "上架项目数", "上架套餐数", "微信公众号粉丝数",
"微信公众号绑定手机粉丝数", "是否开通微信小程序", "微信小程序绑定用户数", "微信小程序绑定手机用户量",
"微信订单数", "微信支付订单量", "线下订单数"
]
data_SY.columns = headers
return data_SY
except Exception as e:
print(f"Error occurred: {e}")
return None
def get_commission_details(self, ):
"""
从f6operation_data_relay数据库中获取小六提成数据。
返回pandas DataFrame。
"""
try:
# 获得连接并创建游标
conn = pymysql.connect(
host=Config.BI_CONN_host,
database=Config.BI_CONN_INFO_database,
user=Config.BI_CONN_INFO_user,
password=Config.BI_CONN_INFO_password,
# charset='utf8mb4', # 设置字符集以避免编码问题
# cursorclass=pymysql.cursors.DictCursor # 返回字典形式的结果
)
cursor = conn.cursor()
# 获取指定天数前的日期
# now_time = datetime.now()
# target_time = now_time + timedelta(days=-days_back)
# SQL 查询语句
sql = f"""
SELECT * FROM JianDaoYun_DailyVisit_Commission;
"""
# 执行查询并获取结果
cursor.execute(sql)
rows = cursor.fetchall() # pymysql 的 DictCursor 会返回字典列表
# 将结果转换为 DataFrame
if rows: # 如果有数据
data_commission = pd.DataFrame(rows)
else: # 如果没有数据，返回空 DataFrame
data_commission = pd.DataFrame()
# 关闭游标
cursor.close()
headers = [
"门店id", "提成类型_二级分类", "提成基数（本月）", "提成基数（上月）", "公司id", "门店编码", "门店名称"
]
data_commission.columns = headers
return data_commission
except Exception as e:
print(f"Error occurred: {e}")
return None
def get_differentindustries_details(self, ):
"""
从f6operation_data_relay数据库中获取小六提成数据。
返回pandas DataFrame。
"""
try:
# 获得连接并创建游标
conn = pymysql.connect(
host=Config.BI_CONN_host,
database=Config.BI_CONN_INFO_database,
user=Config.BI_CONN_INFO_user,
password=Config.BI_CONN_INFO_password,
# charset='utf8mb4', # 设置字符集以避免编码问题
# cursorclass=pymysql.cursors.DictCursor # 返回字典形式的结果
)
cursor = conn.cursor()
# 获取指定天数前的日期
# now_time = datetime.now()
# target_time = now_time + timedelta(days=-days_back)
# SQL 查询语句
sql = f"""
SELECT * FROM JianDaoYun_DailyVisit_DifferentIndustries;
"""
# 执行查询并获取结果
cursor.execute(sql)
rows = cursor.fetchall() # pymysql 的 DictCursor 会返回字典列表
# 将结果转换为 DataFrame
if rows: # 如果有数据
data_commission = pd.DataFrame(rows)
else: # 如果没有数据，返回空 DataFrame
data_commission = pd.DataFrame()
# 关闭游标
cursor.close()
headers = [
"门店id", "商品名称", "服务期结束时间", "门店名称", "公司id", "门店编码"
]
data_commission.columns = headers
return data_commission
except Exception as e:
print(f"Error occurred: {e}")
return None
def get_perforamnce_details(self, ):
"""
从f6operation_data_relay数据库中获取履约表数据
返回pandas DataFrame。
"""
try:
# 获得连接并创建游标
conn = pymysql.connect(
host=Config.BI_CONN_host,
database=Config.BI_CONN_INFO_database,
user=Config.BI_CONN_INFO_user,
password=Config.BI_CONN_INFO_password,
# charset='utf8mb4', # 设置字符集以避免编码问题
# cursorclass=pymysql.cursors.DictCursor # 返回字典形式的结果
)
cursor = conn.cursor()
# SQL 查询语句
sql = f"""
SELECT * FROM SAAS_Fulfillment_Details;
"""
# 执行查询并获取结果
cursor.execute(sql)
rows = cursor.fetchall() # pymysql 的 DictCursor 会返回字典列表
# 将结果转换为 DataFrame
if rows: # 如果有数据
data_commission = pd.DataFrame(rows)
else: # 如果没有数据，返回空 DataFrame
data_commission = pd.DataFrame()
# 关闭游标
cursor.close()
headers = ["订单id", "f6订单编号", "宜搭的实例id", "商品id", "商品名称", "发布商品类型", "发布商品类型描述",
"门店id", "门店名称", "门店编码", "运营负责人", "区域经理", "商户中心id", "saas开户时间",
"公司id", "公司名称", "产生来源", "产生来源描述", "类型", "类型描述", "服务年份",
"订单服务期第几年", "服务期起始时间", "服务期结束时间", "提成业务类型", "提成类别",
"下单支付成功时间", "实付金额", "系统成本价", "版本费", "服务费", "介绍人员工ID",
"介绍业绩归属人员工ID", "处理人ID employee_id", "业绩归属人员工ID", "操作时间",
"处理人是否跟进,0: 未跟进，1: 已跟进", "满意度评分", "评价完成时间", "介绍人用户类型",
"下单支付成功日期", "培训完成时间", "订单所处阶段", "日分区"]
data_commission.columns = headers
float_columns = ["实付金额", "系统成本价", "版本费", "服务费"]
for col in float_columns:
data_commission[col] = data_commission[col].astype(float)
return data_commission
except Exception as e:
print(f"Error occurred: {e}")
return None
def get_commission_details(self, ):
"""
从f6operation_data_relay数据库中获取小六提成数据。
返回pandas DataFrame。
"""
try:
# 获得连接并创建游标
conn = pymysql.connect(
host=Config.BI_CONN_host,
database=Config.BI_CONN_INFO_database,
user=Config.BI_CONN_INFO_user,
password=Config.BI_CONN_INFO_password,
# charset='utf8mb4', # 设置字符集以避免编码问题
# cursorclass=pymysql.cursors.DictCursor # 返回字典形式的结果
)
cursor = conn.cursor()
# 获取指定天数前的日期
# now_time = datetime.now()
# target_time = now_time + timedelta(days=-days_back)
# SQL 查询语句
sql = f"""
SELECT * FROM JianDaoYun_DailyVisit_Commission;
"""
# 执行查询并获取结果
cursor.execute(sql)
rows = cursor.fetchall() # pymysql 的 DictCursor 会返回字典列表
# 将结果转换为 DataFrame
if rows: # 如果有数据
data_commission = pd.DataFrame(rows)
else: # 如果没有数据，返回空 DataFrame
data_commission = pd.DataFrame()
# 关闭游标
cursor.close()
headers = [
"门店id", "提成类型_二级分类", "提成基数（本月）", "提成基数（上月）", "公司id", "门店编码", "门店名称"
]
data_commission.columns = headers
return data_commission
except Exception as e:
print(f"Error occurred: {e}")
return None
def get_GroupNotification_details(self, ):
"""
从f6operation_data_relay数据库中获取小六提成数据。
返回pandas DataFrame。
"""
try:
# 获得连接并创建游标
conn = pymysql.connect(
host=Config.BI_CONN_host,
database=Config.BI_CONN_INFO_database,
user=Config.BI_CONN_INFO_user,
password=Config.BI_CONN_INFO_password,
# charset='utf8mb4', # 设置字符集以避免编码问题
# cursorclass=pymysql.cursors.DictCursor # 返回字典形式的结果
)
cursor = conn.cursor()
# 获取指定天数前的日期
# now_time = datetime.now()
# target_time = now_time + timedelta(days=-days_back)
# SQL 查询语句
sql = f"""
SELECT * FROM jiandaoyun_dailyvisit_groupnotification;
"""
# 执行查询并获取结果
cursor.execute(sql)
rows = cursor.fetchall() # pymysql 的 DictCursor 会返回字典列表
# 将结果转换为 DataFrame
if rows: # 如果有数据
data_commission = pd.DataFrame(rows)
else: # 如果没有数据，返回空 DataFrame
data_commission = pd.DataFrame()
# 关闭游标
cursor.close()
headers = [
"公司id", "是否启动短信功能", "是否购买短信包", "累计购买总数", "累计发送成功总人数", "剩余短信条数",
"实付总金额", "短信剩余量是否小于20%", "第一次短信购买时间", "最近一次短信购买时间"
]
data_commission.columns = headers
return data_commission
except Exception as e:
print(f"Error occurred: {e}")
return None
from datetime import datetime, timedelta, UTC, timezone
def send_task_status(self, task_start_time: str, task_name: str) -> None:
"""
将任务状态发送到简道云（开始时间为北京时间，需转换到 UTC）
:param task_start_time: 任务开始时间（字符串格式："%Y-%m-%d %H:%M:%S"，表示北京时间 UTC+8）
:param task_name: 任务名称
"""
print(1)
try:
# 1. 获取当前 UTC 时间（时区感知对象）
end_time_utc = datetime.now(UTC) # ✅ 替代 utcnow()
# 2. 解析传入的北京时间（UTC+8）
task_start_naive = datetime.strptime(task_start_time, "%Y-%m-%d %H:%M:%S")
# 3. 转换为 UTC 时间（减去 8 小时，并附加 UTC 时区）
task_start_utc = task_start_naive - timedelta(hours=8)
task_start_utc = task_start_utc.replace(tzinfo=timezone.utc) # 显式标记为 UTC
# 4. 计算运行时间（时区感知对象可直接相减）
run_time = end_time_utc - task_start_utc
run_time_sec = int(run_time.total_seconds())
# 5. 格式化时间为 UTC 的 ISO 8601 格式（带 "Z"）
today_utc = end_time_utc.strftime("%Y-%m-%d")
task_end_iso = end_time_utc.strftime("%Y-%m-%dT%H:%M:%SZ")
task_start_iso = task_start_utc.strftime("%Y-%m-%dT%H:%M:%SZ")
print(task_end_iso)
print(task_start_iso)
# 6. 构造请求数据（所有时间以 UTC 格式发送）
payload = {
"api_key": Config.SCHEDULED_TASKS_APP_ID,
"entry_id": Config.JDY_TASKS_ENTRY_ID,
"data": {
"_widget_1744873387500": {"value": today_utc}, # UTC 日期
"_widget_1743644977694": {"value": task_name},
"_widget_1744873387501": {"value": task_start_iso}, # UTC 开始时间
"_widget_1744873387502": {"value": task_end_iso}, # UTC 结束时间
"_widget_1744873387504": {"value": run_time_sec},
}
}
# 7. 发送请求
response = api_instance.data_batch_create(payload)
logger.info(f"任务状态发送成功: {response}")
except Exception as e:
logger.error(f"任务状态发送失败: {e}")
back_ground_module/data_Support_Commission.py
+83
View File
@@ -0,0 +1,83 @@
# -*- coding: utf-8 -*-
import pandas as pd
import datetime
from config import Config
from api import API
import pymysql # 使用 pymysql 替代 mysql.connector
from back_ground_module import CommonModule
start_time = datetime.datetime.now()
api_instance = API()
common_module = CommonModule()
class importCommissionData:
"""
小六提成数据支撑
"""
def __init__(self):
self.field_mapping = {}
self.fields()
def main(self):
task_start_time =datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
payload = {"api_key": Config.SaaS_Tasks_APP_ID,
"entry_id": Config.Commission_form_ID,
}
abnormal_service = api_instance.entry_data_list(payload)
abnormal_list = abnormal_service.get("data") # api请求格式，将数据封装在data字典里
for i in range(0,len(abnormal_list)): # 删除历史数据
try:
delete_data = {"api_key": Config.SaaS_Tasks_APP_ID,
"entry_id": Config.Commission_form_ID,
"data_id": abnormal_list[i]['_id']}
api_instance.entry_data_delete(delete_data)
except:
pass
data_commission = common_module.get_commission_details()
# 生成包含所有行转换后的字典列表
data_commission = [self.row_to_dict(row, self.field_mapping) for index, row in data_commission.iterrows()]
data_commission = {'api_key': Config.SaaS_Tasks_APP_ID, 'entry_id': Config.Commission_form_ID, "data_list": data_commission}
result = api_instance.entry_data_batch_create(data_commission)
result_str = str(result)
# print(result_str[:500])
# 保存到Excel文件
# output_path = r'D:\Idea Project\F6+宜搭+其它(1)\new\文件输出\ngv明细1.xlsx'
# data_NGV_j.to_excel(output_path, index=False)
end_time = datetime.datetime.now()
time_diff = end_time - start_time
# 打印天数、秒数和微秒数
print(f"执行时间: {time_diff.days} 天, {time_diff.seconds} 秒, {time_diff.microseconds} 微秒")
common_module.send_task_status(task_start_time, "小六提成数据支撑")
@staticmethod
def row_to_dict(row, field_mapping):
"""将一行数据转换为指定格式的字典"""
result = {}
for col_name, widget_id in field_mapping.items():
if col_name in row:
value = row[col_name]
clean_value = None if pd.isna(value) else value
result[widget_id] = {"value": clean_value}
return result
def fields(self):
self.field_mapping = {
"门店id": "_widget_1742884710674",
"提成类型_二级分类": "_widget_1742884710675",
"提成基数（本月）": "_widget_1742884710676",
"提成基数（上月）": "_widget_1742884710677",
"公司id": "_widget_1748930441629",
"门店编码": "_widget_1748931089356",
"门店名称": "_widget_1748931089357"
}
if __name__ == '__main__':
start = importCommissionData()
start.main()
back_ground_module/data_Support_DifferentIndustries.py
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# -*- coding: utf-8 -*-
import pandas as pd
import datetime
from config import Config
from api import API
import pymysql # 使用 pymysql 替代 mysql.connector
from back_ground_module import CommonModule
start_time = datetime.datetime.now()
api_instance = API()
common_module = CommonModule()
class importDifferentIndustriesData:
"""异业合作数据支撑"""
def __init__(self):
self.field_mapping = {}
self.fields()
def main(self):
task_start_time =datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
payload = {"api_key": Config.SaaS_Tasks_APP_ID,
"entry_id": Config.DifferentIndustries_form_ID,
}
abnormal_service = api_instance.entry_data_list(payload)
abnormal_list = abnormal_service.get("data") # api请求格式，将数据封装在data字典里
for i in range(0,len(abnormal_list)): # 删除历史数据
try:
delete_data = {"api_key": Config.SaaS_Tasks_APP_ID,
"entry_id": Config.DifferentIndustries_form_ID,
"data_id": abnormal_list[i]['_id']}
api_instance.entry_data_delete(delete_data)
except:
pass
data_commission = common_module.get_differentindustries_details()
# 生成包含所有行转换后的字典列表
data_commission = [self.row_to_dict(row, self.field_mapping) for index, row in data_commission.iterrows()]
data_commission = {'api_key': Config.SaaS_Tasks_APP_ID, 'entry_id': Config.DifferentIndustries_form_ID, "data_list": data_commission}
result = api_instance.entry_data_batch_create(data_commission)
result_str = str(result)
# print(result_str[:500])
# 保存到Excel文件
# output_path = r'D:\Idea Project\F6+宜搭+其它(1)\new\文件输出\ngv明细1.xlsx'
# data_NGV_j.to_excel(output_path, index=False)
end_time = datetime.datetime.now()
time_diff = end_time - start_time
# 打印天数、秒数和微秒数
print(f"执行时间: {time_diff.days} 天, {time_diff.seconds} 秒, {time_diff.microseconds} 微秒")
common_module.send_task_status(task_start_time, "异业合作数据支撑")
@staticmethod
def row_to_dict(row, field_mapping):
"""将一行数据转换为指定格式的字典"""
result = {}
for col_name, widget_id in field_mapping.items():
if col_name in row:
value = row[col_name]
clean_value = None if pd.isna(value) else value
result[widget_id] = {"value": clean_value}
return result
def fields(self):
self.field_mapping = {
"门店id": "_widget_1742884829007",
"商品名称": "_widget_1742884829008",
"服务期结束时间": "_widget_1742884829009",
"门店名称": "_widget_1748931208851",
"公司id": "_widget_1748930826642",
"门店编码": "_widget_1748931208852"
}
if __name__ == '__main__':
start = importDifferentIndustriesData()
start.main()
back_ground_module/data_Support_GroupNotification.py
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# -*- coding: utf-8 -*-
import pandas as pd
import datetime
from config import Config
from api import API
import pymysql # 使用 pymysql 替代 mysql.connector
from back_ground_module import CommonModule
start_time = datetime.datetime.now()
api_instance = API()
common_module = CommonModule()
class importGroupNotificationData:
"""短信数据支撑"""
def __init__(self):
self.field_mapping = {}
self.fields()
def main(self):
task_start_time =datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
payload = {"api_key": Config.SaaS_Tasks_APP_ID,
"entry_id": Config.GroupNotification_form_ID,
}
abnormal_service = api_instance.entry_data_list(payload)
abnormal_list = abnormal_service.get("data") # api请求格式，将数据封装在data字典里
# print(abnormal_list)
delete_id_list = []
for i in range(0,len(abnormal_list)): # 删除历史数据
try:
# delete_data = {"api_key": Config.SaaS_Tasks_APP_ID,
# "entry_id": Config.GroupNotification_form_ID,
# "data_id": abnormal_list[i]['_id']}
# api_instance.entry_data_delete(delete_data)
delete_id_list.append(abnormal_list[i]['_id'])
except Exception as e:
print(e)
# print(delete_id_list)
delete_payload = {"api_key": Config.SaaS_Tasks_APP_ID,
"entry_id": Config.GroupNotification_form_ID,
"data_ids": delete_id_list}
api_instance.entry_data_batch_delete(delete_payload)
data_commission = common_module.get_GroupNotification_details()
# 生成包含所有行转换后的字典列表
data_commission = [self.row_to_dict(row, self.field_mapping) for index, row in data_commission.iterrows()]
data_commission = {'api_key': Config.SaaS_Tasks_APP_ID, 'entry_id': Config.GroupNotification_form_ID, "data_list": data_commission}
result = api_instance.entry_data_batch_create(data_commission)
# result_str = str(result)
# print(result_str[:500])
# 保存到Excel文件
# output_path = r'D:\Idea Project\F6+宜搭+其它(1)\new\文件输出\ngv明细1.xlsx'
# data_NGV_j.to_excel(output_path, index=False)
end_time = datetime.datetime.now()
time_diff = end_time - start_time
# 打印天数、秒数和微秒数
print(f"执行时间: {time_diff.days} 天, {time_diff.seconds} 秒, {time_diff.microseconds} 微秒")
common_module.send_task_status(task_start_time, "短信数据支撑")
@staticmethod
def row_to_dict(row, field_mapping):
"""将一行数据转换为指定格式的字典"""
result = {}
for col_name, widget_id in field_mapping.items():
if col_name in row:
value = row[col_name]
clean_value = None if pd.isna(value) else value
result[widget_id] = {"value": clean_value}
return result
def fields(self):
self.field_mapping = {
"公司id": "_widget_1743065201885",
"是否启动短信功能": "_widget_1743065201886",
"是否购买短信包": "_widget_1743065201887",
"累计购买总数": "_widget_1743065201888",
"累计发送成功总人数": "_widget_1743065201889",
"剩余短信条数": "_widget_1743065201890",
"第一次短信购买时间": "_widget_1743065201891",
"最近一次短信购买时间": "_widget_1743065201892",
"实付总金额": "_widget_1743065201893",
"短信剩余量是否小于20%": "_widget_1743065201894"
}
if __name__ == '__main__':
start = importGroupNotificationData()
start.main()
back_ground_module/data_Support_Private_Mini_Program.py
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# -*- coding: utf-8 -*-
import pandas as pd
import datetime
from config import Config
from api import API
import pymysql # 使用 pymysql 替代 mysql.connector
from back_ground_module import CommonModule
start_time = datetime.datetime.now()
api_instance = API()
common_module = CommonModule()
class importSYXCXData:
"""私域小程序数据支撑"""
def __init__(self):
self.field_mapping = {}
self.fields()
def main(self):
task_start_time =datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
payload = {"api_key": Config.SaaS_Tasks_APP_ID,
"entry_id": Config.SYXCX_form_ID,
}
abnormal_service = api_instance.entry_data_list(payload)
abnormal_list = abnormal_service.get("data") # api请求格式，将数据封装在data字典里
for i in range(0,len(abnormal_list)): # 删除历史数据
try:
delete_data = {"api_key": Config.SaaS_Tasks_APP_ID,
"entry_id": Config.SYXCX_form_ID,
"data_id": abnormal_list[i]['_id']}
api_instance.entry_data_delete(delete_data)
except:
pass
data_SY = common_module.get_syxcx_details()
# 生成包含所有行转换后的字典列表
data_SY = [self.row_to_dict(row, self.field_mapping) for index, row in data_SY.iterrows()]
data_SY = {'api_key': Config.SaaS_Tasks_APP_ID, 'entry_id': Config.SYXCX_form_ID, "data_list": data_SY}
result = api_instance.entry_data_batch_create(data_SY)
result_str = str(result)
# print(result_str[:500])
# 保存到Excel文件
# output_path = r'D:\Idea Project\F6+宜搭+其它(1)\new\文件输出\ngv明细1.xlsx'
# data_NGV_j.to_excel(output_path, index=False)
end_time = datetime.datetime.now()
time_diff = end_time - start_time
# 打印天数、秒数和微秒数
print(f"执行时间: {time_diff.days} 天, {time_diff.seconds} 秒, {time_diff.microseconds} 微秒")
common_module.send_task_status(task_start_time, "私域小程序数据支撑")
@staticmethod
def row_to_dict(row, field_mapping):
"""将一行数据转换为指定格式的字典"""
result = {}
for col_name, widget_id in field_mapping.items():
if col_name in row:
value = row[col_name]
clean_value = None if pd.isna(value) else value
result[widget_id] = {"value": clean_value}
return result
def fields(self):
self.field_mapping = {
"公司ID": "_widget_1742795002375",
"公众号名称": "_widget_1742795002376",
"小程序模板类型": "_widget_1742795002377",
"是否开通微信商城": "_widget_1742795002378",
"上架商品数": "_widget_1742795002379",
"上架套餐卡数": "_widget_1742795002380",
"上架实体商品数": "_widget_1742795002381",
"上架项目数": "_widget_1742795002382",
"上架套餐数": "_widget_1742795002383",
"微信公众号粉丝数": "_widget_1742795002384",
"微信公众号绑定手机粉丝数": "_widget_1742795002385",
"是否开通微信小程序": "_widget_1742795002386",
"微信小程序绑定用户数": "_widget_1742795002387",
"微信小程序绑定手机用户量": "_widget_1742795002388",
"微信订单数": "_widget_1742795002389",
"微信支付订单量": "_widget_1742795002390",
"线下订单数": "_widget_1742795002391"
}
if __name__ == '__main__':
start = importSYXCXData()
start.main()
back_ground_module/data_monitor.py
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"""字段监控"""
import sys
from datetime import datetime, timedelta, timezone
import pandas as pd
import zipfile
import logging
from pathlib import Path
import json
import requests
from api import API
import time
import os
from log_config import configure_task_logger, configure_error_task_logger
from back_ground_module import CommonModule
# 获取已经配置好的常规日志记录器
logger = configure_task_logger()
# 获取已经配置好的错误任务日志记录器
error_task_logger = configure_error_task_logger()
common_tools = CommonModule()
# ---------------------------- 配置项 ----------------------------
class Config:
OUTPUT_DIR = "output"
DATA_DIR = "数据快照存储"
ARCHIVE_DIR = "压缩包存储"
RETAIN_DAYS = 7
COMPRESS_FORMAT = "zip"
LOG_FILE = os.path.join(OUTPUT_DIR+"data_monitor.log")
CHANGES_FILE = os.path.join(OUTPUT_DIR+"changes_summary.csv")
MAX_RETRIES = 3
RETRY_DELAY = 0.5
# ---------------------- 日志配置 -----------------------
# class Logger:
# @staticmethod
# def setup():
# logging.basicConfig(
# level=logging.INFO,
# format='%(asctime)s - %(levelname)s - %(message)s',
# handlers=[
# logging.StreamHandler(),
# logging.FileHandler(Config.LOG_FILE)
# ]
# )
# return logging.getLogger(__name__)
#
#
# logger = Logger.setup()
# ---------------------- 工具函数 -----------------------
class Utils:
@staticmethod
def get_path(*path_parts):
return str(Path(*path_parts))
@staticmethod
def ensure_dir(path):
Path(path).mkdir(parents=True, exist_ok=True)
logger.debug(f"确保目录存在: {path}")
@staticmethod
def get_iso_time():
return datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%S.%f")[:-3] + "Z"
@staticmethod
def is_first_run_today():
today = datetime.now(timezone.utc).strftime("%Y-%m-%d")
snapshot_file = Utils.get_path(Config.OUTPUT_DIR, Config.DATA_DIR, f"snapshot_{today}.csv")
widget_file = Utils.get_path(Config.OUTPUT_DIR, Config.DATA_DIR, f"all_widgets_{today}.csv")
return not (os.path.exists(snapshot_file) and os.path.exists(widget_file))
# ---------------------- API 客户端 -----------------------
class APIClient:
def __init__(self):
self.headers = {
'Authorization': 'Bearer qygHulymo1fekJk4CIZyNKjyQAzG8CFN',
'Content-Type': 'application/json'
}
self.api = API()
def request(self, url, payload, method='POST'):
for retry in range(Config.MAX_RETRIES + 1):
try:
response = requests.request(
method, url, headers=self.headers,
data=payload, timeout=30
)
response.raise_for_status()
return response
except requests.exceptions.RequestException as e:
if retry == Config.MAX_RETRIES:
raise
time.sleep(Config.RETRY_DELAY)
logger.warning(f"请求失败 (尝试 {retry + 1}/{Config.MAX_RETRIES}): {str(e)}")
# ---------------------- 数据处理类 -----------------------
class DataHandler:
def __init__(self):
self.execution_time = Utils.get_iso_time()
self.today = datetime.now(timezone.utc).strftime("%Y-%m-%d")
self.setup_dirs()
self.api = APIClient()
def setup_dirs(self):
self.data_dir = Utils.get_path(Config.OUTPUT_DIR, Config.DATA_DIR)
self.archive_dir = Utils.get_path(Config.OUTPUT_DIR, Config.ARCHIVE_DIR)
Utils.ensure_dir(self.data_dir)
Utils.ensure_dir(self.archive_dir)
self.last_data_file = Utils.get_path(self.data_dir, "last_data.csv")
self.last_widget_file = Utils.get_path(self.data_dir, "last_widget_data.csv")
def load_last_data(self):
try:
last_data = pd.read_csv(self.last_data_file) if os.path.exists(self.last_data_file) else None
last_widget = pd.read_csv(self.last_widget_file) if os.path.exists(self.last_widget_file) else None
return last_data, last_widget
except Exception as e:
error_task_logger.error(f"加载上次数据失败: {str(e)}")
return None, None
def save_last_data(self, data, widget_data):
try:
data.to_csv(self.last_data_file, index=False)
widget_data.to_csv(self.last_widget_file, index=False)
return True
except Exception as e:
error_task_logger.error(f"保存当前数据失败: {str(e)}")
return False
def save_to_csv(self, data, filename):
try:
temp_file = filename + '.tmp'
data.to_csv(temp_file, index=False)
if os.path.exists(filename):
os.remove(filename)
os.rename(temp_file, filename)
return True
except Exception as e:
error_task_logger.error(f"保存文件失败: {filename}, 错误: {str(e)}")
return False
# ---------------------- 数据监控主类 -----------------------
class DataMonitor(DataHandler):
def __init__(self):
super().__init__()
self.last_data, self.last_widget = self.load_last_data()
def fetch_apps(self):
url = "https://api.jiandaoyun.com/api/v5/app/list"
payload = json.dumps({"skip": 0, "limit": 100})
response = self.api.request(url, payload)
return pd.DataFrame(response.json().get("apps", []))
def fetch_entries(self, app_df):
url = "https://api.jiandaoyun.com/api/v5/app/entry/list"
all_entries = []
for _, app in app_df.iterrows():
payload = json.dumps({"app_id": app['app_id']})
response = self.api.request(url, payload)
entries = response.json().get("forms", [])
if entries:
entry_df = pd.DataFrame(entries)
entry_df['app_id'] = app['app_id']
all_entries.append(entry_df)
return pd.concat(all_entries, ignore_index=True) if all_entries else None
def fetch_widgets(self, entry_df):
url = "https://api.jiandaoyun.com/api/v5/app/entry/widget/list"
all_widgets = []
for _, entry in entry_df.iterrows():
payload = json.dumps({
"app_id": entry['app_id'],
"entry_id": entry['entry_id']
})
response = self.api.request(url, payload)
widgets = response.json().get('widgets', [])
if widgets:
widget_df = pd.DataFrame(widgets)
widget_df['app_id'] = entry['app_id']
widget_df['entry_id'] = entry['entry_id']
all_widgets.append(widget_df)
return pd.concat(all_widgets, ignore_index=True) if all_widgets else None
def fetch_monitor_data(self):
payload = {"api_key": "6694d3c4fcb69ca9a111a6c4", "entry_id": "6850c044f17c934b3ec01fea"}
data = self.api.api.entry_data_list(payload).get("data")
data_list = pd.DataFrame(data)
for col in data_list.columns:
if data_list[col].apply(lambda x: isinstance(x, (dict, list))).any():
data_list[col] = data_list[col].astype(str)
return data_list.drop_duplicates()
def match_widgets(self, data_list, widget_list):
if '_widget_1750122565203' not in data_list.columns:
raise ValueError("数据列表中缺少 '_widget_1750122565203' 列")
return widget_list[widget_list['entry_id'].isin(data_list['_widget_1750122565203'])]
def archive_old_data(self):
keep_dates = [
(datetime.now(timezone.utc) - timedelta(days=i)).strftime("%Y-%m-%d")
for i in range(Config.RETAIN_DAYS)
]
files_to_archive = [
f for f in os.listdir(self.data_dir)
if (f.startswith("snapshot_") or f.startswith("all_widgets_")) and f.endswith(".csv")
]
for filename in files_to_archive:
date_str = filename[9:-4] if filename.startswith("snapshot_") else filename[12:-4]
if date_str not in keep_dates:
year_month = date_str[:7]
archive_name = Utils.get_path(self.archive_dir, f"snapshots_{year_month}.{Config.COMPRESS_FORMAT}")
file_path = Utils.get_path(self.data_dir, filename)
with zipfile.ZipFile(archive_name, 'a', zipfile.ZIP_DEFLATED) as zipf:
zipf.write(file_path, arcname=filename)
os.remove(file_path)
logger.debug(f"已归档 {filename} 到 {archive_name}")
def compare_data(self, current_data):
if not os.path.exists(self.last_data_file):
return None
last_data = pd.read_csv(self.last_data_file)
last_data['unique_id'] = last_data['name'].astype(str) + last_data['app_id'].astype(str)
current_data['unique_id'] = current_data['name'].astype(str) + current_data['app_id'].astype(str)
merged = pd.merge(
last_data, current_data,
on=['unique_id'],
how='outer',
suffixes=('_last', '_current'),
indicator=True
)
changes = {
'added': merged[merged['_merge'] == 'right_only'],
'deleted': merged[merged['_merge'] == 'left_only'],
'modified': pd.DataFrame()
}
for col in ['label', 'type']:
last_col = f"{col}_last"
current_col = f"{col}_current"
if last_col in merged.columns and current_col in merged.columns:
mask = (merged['_merge'] == 'both') & (merged[last_col] != merged[current_col])
mask = mask & ~merged[last_col].isna() & ~merged[current_col].isna()
if mask.any():
modified = merged.loc[mask].copy()
modified['changed_field'] = col
modified['old_value'] = modified[last_col]
modified['new_value'] = modified[current_col]
modified['change_status'] = 'update'
changes['modified'] = pd.concat([changes['modified'], modified])
return changes
def save_changes(self, changes, apps, entries):
result_rows = []
for change_type in ['added', 'deleted', 'modified']:
suffix = 'current' if change_type in ['added', 'modified'] else 'last'
for _, row in changes[change_type].iterrows():
app_id = row[f'app_id_{suffix}']
entry_id = row[f'entry_id_{suffix}']
app_name = apps.loc[apps['app_id'] == app_id, 'name'].values[0] if not apps[
apps['app_id'] == app_id].empty else '未知应用'
entry_name = \
entries.loc[(entries['app_id'] == app_id) & (entries['entry_id'] == entry_id), 'name'].values[0] if not \
entries[(entries['app_id'] == app_id) & (entries['entry_id'] == entry_id)].empty else '未知表单'
if change_type == 'added':
content = f"新增字段: {row['label_current']}"
elif change_type == 'deleted':
content = f"删除字段: {row['label_last']}"
else:
content = f"由\"{row['old_value']}\"修改为\"{row['new_value']}\""
result_rows.append({
'程序执行时间': self.execution_time,
'unique_id': row['unique_id'],
'app_id': app_id,
'app_name': app_name,
'entry_id': entry_id,
'entry_name': entry_name,
'change_type': {'added': '新增', 'deleted': '删除', 'modified': '修改'}[change_type],
'具体内容': content
})
if result_rows:
result_df = pd.DataFrame(result_rows)
changes_file = Utils.get_path(self.data_dir, Config.CHANGES_FILE)
result_df.to_csv(changes_file, mode='a', header=not os.path.exists(changes_file), index=False)
self.add_to_jiandaoyun(result_df)
return True
return False
def add_to_jiandaoyun(self, result_df):
all_data = [{
"_widget_1751446961315": {"value": row["app_name"]},
"_widget_1751446961316": {"value": row["entry_name"]},
"_widget_1751446961317": {"value": row["change_type"]},
"_widget_1751446961318": {"value": row["具体内容"]},
"_widget_1751446961319": {"value": row["程序执行时间"]},
} for _, row in result_df.iterrows()]
payload = {
"api_key": "6694d3c4fcb69ca9a111a6c4",
"entry_id": "6863a402a77925690a470cc5",
"data_list": all_data
}
response = self.api.api.entry_data_batch_create(payload)
if isinstance(response, list):
logger.info(f"成功写入 {len(response)} 条变更数据到简道云")
return True
else:
error_task_logger.error(f"写入简道云失败: {response.get('message', '未知错误')}")
return False
def run_daily_snapshot(self):
logger.info("=== 开始每日数据快照任务 ===")
apps = self.fetch_apps()
entries = self.fetch_entries(apps)
widgets = self.fetch_widgets(entries)
monitor_data = self.fetch_monitor_data()
matched_data = self.match_widgets(monitor_data, widgets)
self.save_to_csv(widgets, Utils.get_path(self.data_dir, f"all_widgets_{self.today}.csv"))
self.save_to_csv(matched_data, Utils.get_path(self.data_dir, f"snapshot_{self.today}.csv"))
self.archive_old_data()
self.save_last_data(matched_data, widgets)
logger.info("=== 每日数据快照任务成功完成 ===")
return True
def run_hourly_check(self):
logger.info("=== 开始每小时数据检查任务 ===")
apps = self.fetch_apps()
entries = self.fetch_entries(apps)
widgets = self.fetch_widgets(entries)
monitor_data = self.fetch_monitor_data()
current_data = self.match_widgets(monitor_data, widgets)
changes = self.compare_data(current_data)
if changes and any(len(v) > 0 for v in changes.values()):
self.save_changes(changes, apps, entries)
self.save_last_data(current_data, widgets)
logger.info("=== 每小时数据检查任务成功完成 ===")
return True
def main(self):
import datetime
task_start_time =datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
logger.info(f"=== 开始数据监控任务 ({self.execution_time}) ===")
if Utils.is_first_run_today():
success = self.run_daily_snapshot()
else:
success = self.run_hourly_check()
common_tools.send_task_status(task_start_time, "字段监控")
logger.info("=== 数据监控任务完成 ===")
return success
if __name__ == "__main__":
Utils.ensure_dir(Config.OUTPUT_DIR)
monitor = DataMonitor()
if not monitor.main():
sys.exit(1)
back_ground_module/datasource/JCB_efficient_car_pickup.py
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from datetime import date, timedelta, datetime
import holidays
from config import Config
import psycopg2
import pandas as pd
import pymysql # 使用 pymysql 替代 mysql.connector
class JCB_efficient_car_pickup:
def __init__(self):
# 使用 pymysql 连接数据库
self.conn = pymysql.connect(
host=Config.JCB_CONN_host,
database=Config.JCB_CONN_INFO_database,
user=Config.JCB_CONN_INFO_user,
password=Config.JCB_CONN_INFO_password,
# charset='utf8mb4', # 设置字符集以避免编码问题
# cursorclass=pymysql.cursors.DictCursor # 返回字典形式的结果
)
def get_jcb_details(self, days_back=1):
"""
从固定的数据库中获取前几天的NGV明细。
参数 `days_back` 表示相对于今天的天数偏移量，默认为1（即前一天）。
返回包含NGV明细的pandas DataFrame。
"""
try:
# 获得连接并创建游标
cursor = self.conn.cursor()
# 获取指定天数前的日期
# now_time = datetime.now()
# target_time = now_time + timedelta(days=-days_back)
target_date_id = "接车宝" # 获取目标日期
# SQL 查询语句
sql = f"""
SELECT * FROM jdy_hs_holo_dws_sales_magic_box_ngv_d WHERE 产品名称 = '{target_date_id}';
"""
# 执行查询并获取结果
cursor.execute(sql)
rows = cursor.fetchall() # pymysql 的 DictCursor 会返回字典列表
# 将结果转换为 DataFrame
if rows: # 如果有数据
data_NGV = pd.DataFrame(rows)
else: # 如果没有数据，返回空 DataFrame
data_NGV = pd.DataFrame()
# 尝试自动解析日期时间字符串
time_format = "%Y-%m-%d %H:%M:%S"
if 'saas_create_time' in data_NGV.columns:
data_NGV['saas_create_time'] = pd.to_datetime(data_NGV['saas_create_time'], format=time_format,
errors='coerce')
data_NGV['saas_create_time'] = data_NGV['saas_create_time'].dt.strftime('%Y-%m-%d')
# 关闭游标
cursor.close()
return data_NGV
except Exception as e:
print(f"Error occurred: {e}")
return None
if __name__ == "__main__":
start = JCB_efficient_car_pickup()
result = start.get_jcb_details(days_back=1)
if result is not None:
print(result.head()) # 打印前几行数据
back_ground_module/datasource/saas_private_mini_program.py
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from datetime import date, timedelta, datetime
import holidays
from config import Config
import psycopg2
import pandas as pd
class GetProvateMiniProgram(Config):
def get_private_mini_program_details(self, days_back=1):
"""
从固定的数据库中获取前几天的NGV明细。
参数 `days_back` 表示相对于今天的天数偏移量，默认为1（即前一天）。
返回包含NGV明细的pandas DataFrame。
"""
try:
# 获得连接
conn = psycopg2.connect(**self.conn)
cursor = conn.cursor()
# 获取指定天数前的日期
now_time = datetime.now()
target_time = now_time + timedelta(days=-days_back)
target_date_id = int(target_time.strftime('%Y%m%d')) # 获取目标日期
# sql语句查询
sql = f"""
SELECT * FROM "public"."holo_ads_report_saas_profile_ngv_detail_d" WHERE "date_id" = '{target_date_id}' ;
"""
# 执行语句并获取结果集
cursor.execute(sql)
rows = cursor.fetchall()
all_fields = cursor.description
# 执行结果转化为dataframe
col = [i[0] for i in all_fields]
data_NGV = pd.DataFrame(rows, columns=col)
# 尝试自动解析日期时间字符串
time_format = "%Y-%m-%d %H:%M:%S"
if 'saas_create_time' in data_NGV.columns:
data_NGV['saas_create_time'] = pd.to_datetime(data_NGV['saas_create_time'], format=time_format,
errors='coerce')
data_NGV['saas_create_time'] = data_NGV['saas_create_time'].dt.strftime('%Y-%m-%d')
# 关闭游标和连接
cursor.close()
conn.close()
return data_NGV
except Exception as e:
print(f"Error occurred: {e}")
return None
back_ground_module/get_process_time.py
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from yd_api import YDAPI
import pandas as pd
from tqdm import tqdm
import hashlib
from datetime import datetime, timedelta
import pandas as pd
import mysql.connector
from mysql.connector import Error
import json
from back_ground_module import CommonModule
import numpy as np
from config import Config
common_module = CommonModule()
# 初始化 API 实例和 Token
api_instance = YDAPI()
TOKEN = api_instance.generateToken()
FORMID = "FORM-XHA66881FHMAR0F07GT4Y59GGA972DD6B5OHLB"
appType = "APP_RTPWHV37ENXPQUZHTL25"
systemToken = "IA766O61SHFZT6UB0WNOB58GI5RW2K58KCU1LL6"
class TimeConsumingProcess():
"""
获取流程表单数据耗时
"""
def fetch_process_data(self):
"""获取所有流程实例"""
today_midnight = datetime.now().replace(hour=0, minute=0, second=0, microsecond=0)
yesterday_midnight = today_midnight - timedelta(days=1)
start_time = yesterday_midnight.strftime("%Y-%m-%d") # 昨天0点
end_time = today_midnight.strftime("%Y-%m-%d") # 今天0点
form_data_two = api_instance.read_processes_instances(
token=TOKEN, formUuid=FORMID, page=1, n=100,
appType=appType, systemToken=systemToken, instanceStatus="",
createFromTimeGMT=start_time, createToTimeGMT=end_time
) # 之后添加增量更新
all_process_list = []
PAGES_two = form_data_two.get('totalCount') // 100 + 1
# # 手动控制小于3w
# PAGES_two = 290
for a in tqdm(range(1, PAGES_two + 1)):
try:
form_data_two = api_instance.read_processes_instances(
token=TOKEN, formUuid=FORMID, page=a, n=100,
appType=appType, systemToken=systemToken, instanceStatus="",
createFromTimeGMT=start_time, createToTimeGMT=end_time
)
all_process_list = all_process_list + form_data_two.get("data")
except Exception as e:
print(f"Error fetching page {a}: {e}")
continue
return all_process_list
def extract_approval_records(self, process_instances):
"""提取每条流程的审批记录"""
all_data_list = []
for data in tqdm(process_instances, desc="处理流程实例"):
processInstanceId = data.get("processInstanceId")
version = data.get("version")
res_new = api_instance.get_approval_records(
token=TOKEN, processInstanceId=processInstanceId,
appType=appType, systemToken=systemToken
)
records_new = res_new.get('result', [])
for record in records_new:
operateTimeGMT = record.get('operateTimeGMT')
# if operateTimeGMT is not None:
# operateTime = datetime.fromtimestamp(operateTimeGMT / 1000).strftime('%Y-%m-%d %H:%M:%S')
# else:
# operateTime = operateTimeGMT
showName = record.get('showName')
operatorName = record.get('operatorName')
action = record.get('action')
# data_id = record.get('dataId')
activity_id = record.get('activityId')
all_data_list.append(
[operateTimeGMT, showName, operatorName, action, processInstanceId, version, activity_id])
df = pd.DataFrame(all_data_list)
# df.to_csv("审批记录.csv", index=False)
return all_data_list
def group_by_process(self, all_data_list):
"""按 '提交申请' 分组，一个流程为一组"""
result_groups = []
current_group = []
j = 1
for record in all_data_list:
showName = record[1]
if showName == "提交申请":
record.append(0)
j = 1
if current_group:
result_groups.append(current_group)
current_group = []
current_group.append(record)
else:
record.append(j)
j += 1
current_group.append(record)
if current_group:
result_groups.append(current_group)
return result_groups
def transform_to_wide_table(self, result_groups):
"""将审批记录从长表转为宽表"""
flattened_rows = []
for group in result_groups:
row_data = {}
# 遍历其余审批节点
for i, item in enumerate(group, start=1):
operateTimeGMT, showName, operatorName, action, dataId, version, activity_id, index, = item
if action == "已撤销":
showName = "该节点已撤销"
row_data.update({
f'审批{i}时间': operateTimeGMT,
f'审批{i}节点名': showName,
f'审批{i}人': operatorName,
f'审批{i}动作': action,
f'序号{i}': index,
f'审批{i}数据id': dataId,
f'审批{i}流程版本': version,
f'审批{i}流程节点id': activity_id
})
flattened_rows.append(row_data)
# 转换为DataFrame
df_final = pd.DataFrame(flattened_rows)
# 计算最大审批步骤
max_steps = max(len(group) - 1 for group in result_groups) # 减去提交节点
# 构建所有列名
all_columns = [
'审批时间', '审批节点名', '审批人', '审批动作', '序号', '数据id', '流程版本', '流程节点id'
]
for i in range(1, max_steps + 1):
all_columns.extend([
f'审批{i}时间',
f'审批{i}节点名',
f'审批{i}人',
f'审批{i}动作',
f'序号{i}',
f'审批{i}数据id',
f'审批{i}流程版本',
f'审批{i}流程节点id'
])
# 统一列结构并填充缺失值
df_final = df_final.reindex(columns=all_columns)
# number填充为0string填充为-
numeric_cols = df_final.select_dtypes(include=['number']).columns
str_cols = df_final.select_dtypes(include=['object']).columns
df_final[numeric_cols] = df_final[numeric_cols].fillna(0)
df_final[str_cols] = df_final[str_cols].fillna("-")
df_final = df_final[df_final['审批时间'].notna()]
# 导出CSV
# df_final.to_csv("审批流程行转列结果_with_node_name.csv", index=False)
return df_final, max_steps
def classify_flows(self, df_final, max_steps):
"""根据审批节点名 + 动作组合进行流程分组"""
def extract_signature(row):
signature = []
i = 1
while f'审批{i}节点名' in row:
node_name = row[f'审批{i}节点名']
action = row[f'审批{i}动作']
if node_name == "-":
break
signature.append((node_name, action))
i += 1
return signature
def has_special_action(signature):
special_actions = {"已撤销", "已转交", "已退回", "已拒绝"}
for _, action in signature:
if action in special_actions:
return True
return False
def get_hash(signature):
sig_str = str(signature)
return hashlib.md5(sig_str.encode('utf-8')).hexdigest()
df_final['signature'] = df_final.apply(extract_signature, axis=1)
group_map = {}
current_group_id = 1
df_final['group_id'] = 0
for idx, row in df_final.iterrows():
sig = row['signature']
if has_special_action(sig):
df_final.at[idx, 'group_id'] = 5000
# current_group_id += 1
else:
sig_hash = get_hash(sig)
if sig_hash not in group_map:
group_map[sig_hash] = current_group_id
current_group_id += 1
df_final.at[idx, 'group_id'] = group_map[sig_hash]
# df_final.to_csv("审批流程分类结果.csv", index=False)
# print("✅ 分组完成，已保存至 '审批流程分类结果.csv'")
result_rows = []
for index, row in df_final.iterrows():
base_info = {'group_id': row["group_id"]}
process_id_list = []
process_list = []
for i in range(1, max_steps):
prefix = f'审批{i}'
if row[f'{prefix}流程节点id'] != "-":
process_id = row[f'{prefix}流程节点id']
process_id_list.append(process_id)
if row[f'{prefix}节点名'] != "-":
process = row[f'{prefix}节点名']
process_list.append(process)
for i in range(1, max_steps): # 审批1到审批n
prefix = f'审批{i}'
approval_data = {}
if f'{prefix}时间' in df_final.columns and pd.notna(row[f'{prefix}时间']) and row[
f'{prefix}时间'] != '-':
approval_data = {
'审批时间': row[f'{prefix}时间'],
'审批节点名': row[f'{prefix}节点名'],
'审批人': row[f'{prefix}人'],
'审批动作': row[f'{prefix}动作'],
'序号': row[f'序号{i}'] if f'序号{i}' in df_final.columns else '-',
f'审批数据id': row[f'审批{i}数据id'] if f'审批{i}数据id' in df_final.columns else '-',
f'审批流程版本': row[f'审批{i}流程版本'] if f'审批{i}流程版本' in df_final.columns else '-',
f'审批流程节点id': row[
f'审批{i}流程节点id'] if f'审批{i}流程节点id' in df_final.columns else '-',
f'审批节点id合并': process_id_list,
f'审批节点名合并': process_list
}
# 合并基础数据和审批数据
result_row = {**base_info, **approval_data}
result_rows.append(result_row)
dfn = pd.DataFrame(result_rows)
# dfn.to_csv("审批流程分类结果_with_node_name.csv", index=False)
return dfn
def time_calculate(self, df_final):
"""计算每个审批步骤之间的耗时（秒），并设置"提交申请"的耗时为0"""
# 创建副本避免SettingWithCopyWarning
df_final = df_final.copy()
# 确保审批时间为 datetime 类型
df_final["审批时间"] = pd.to_datetime(df_final["审批时间"])
# 处理空值（修复FutureWarning）
numeric_cols = df_final.select_dtypes(include=['number']).columns
df_final[numeric_cols] = df_final[numeric_cols].fillna(0)
str_cols = df_final.select_dtypes(include=['object']).columns
df_final[str_cols] = df_final[str_cols].fillna("-")
# 处理JSON列（修复其他SettingWithCopyWarning）
df_final.loc[:, '审批节点id合并'] = df_final['审批节点id合并'].apply(
lambda x: json.dumps(x, ensure_ascii=False) if isinstance(x, (list, dict)) else x
)
df_final.loc[:, '审批节点名合并'] = df_final['审批节点名合并'].apply(
lambda x: json.dumps(x, ensure_ascii=False) if isinstance(x, (list, dict)) else x
)
# 计算耗时
df_final.loc[:, '耗时'] = df_final['审批时间'].diff().dt.total_seconds().div(60)
df_final.loc[df_final['审批动作'] == '提交申请', '耗时'] = 0
df_final['耗时'] = df_final['耗时'].fillna(0)
# 处理时间转换（修复第一个SettingWithCopyWarning）
df_final.loc[:, "审批时间"] = pd.to_datetime(df_final["审批时间"]).dt.strftime('%Y-%m-%d %H:%M:%S')
# 拼接url
df_final[
"url"] = "https://f6car.aliwork.com/APP_RTPWHV37ENXPQUZHTL25/formDetail/FORM-XHA66881FHMAR0F07GT4Y59GGA972DD6B5OHLB?formInstId=" + \
df_final["审批数据id"].astype(str)
return df_final
def write_to_bi(self, df_final):
# 连接信息
table_name = "yida_process_time_statistics"
# 连接数据库
connection = mysql.connector.connect(
host=Config.BI_CONN_host,
user=Config.BI_CONN_INFO_user,
password=Config.BI_CONN_INFO_password,
database=Config.BI_CONN_INFO_database
)
print(f"成功连接 {Config.BI_CONN_INFO_database}")
cursor = connection.cursor()
# 数据预处理
df = df_final.copy()
# 1. 转换时间戳为字符串
for col in df.select_dtypes(include=['datetime64[ns]', 'datetimetz']).columns:
df[col] = pd.to_datetime(df[col]).dt.strftime('%Y-%m-%d %H:%M:%S')
# 2. 增强空值处理（包含更多可能的空值表示）
empty_values = [np.nan, None, '', 'null', 'NULL', 'NA', 'NaN', 'None', '-']
df = df.replace(empty_values, None)
# 3. 严格过滤条件（确保所有关键字段都有有效值）
required_columns = ['审批节点名', '审批时间', 'group_id', '审批人', '审批动作']
df = df.dropna(subset=required_columns, how='any')
# 4. 额外检查：确保时间格式正确
df = df[df['审批时间'].str.match(r'^\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2}$') | df['审批时间'].isnull()]
# 生成插入语句
try:
columns = ', '.join(df.columns)
placeholders = ', '.join(['%s'] * len(df.columns))
insert_query = f"INSERT INTO {table_name} ({columns}) VALUES ({placeholders})"
# 批量插入数据
records = [tuple(row) for row in df.values]
cursor.executemany(insert_query, records)
connection.commit()
print(f"成功导入 {cursor.rowcount} 条记录到 {table_name} 表")
except Exception as e:
connection.rollback()
print(f"写入失败: {str(e)}")
# 打印前5条问题数据
print("问题数据示例:")
print(df.head().to_string())
finally:
cursor.close()
connection.close()
def main(self):
task_start_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
# Step 1: 获取流程实例
process_instances = self.fetch_process_data()
# Step 2: 提取审批记录
all_data_list = self.extract_approval_records(process_instances)
# Step 3: 按 '提交申请' 分组
result_groups = self.group_by_process(all_data_list)
# Step 4: 转换为宽表
df_final, max_steps = self.transform_to_wide_table(result_groups)
# Step 5: 对流程进行分类并保存结果
df_final1 = self.classify_flows(df_final, max_steps)
# Step 6: 耗时计算
df_final2 = self.time_calculate(df_final1)
# Step 7: 向BI写入数据
self.write_to_bi(df_final2)
common_module.send_task_status(task_start_time, "宜搭流程耗时写入BI")
if __name__ == '__main__':
start = TimeConsumingProcess()
start.main()
back_ground_module/import_performance_data.py
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# -*- coding: utf-8 -*-
import pandas as pd
import datetime
from config import Config
from api import API
import pymysql # 使用 pymysql 替代 mysql.connector
from back_ground_module import CommonModule
from tqdm import tqdm
start_time = datetime.datetime.now()
api_instance = API()
common_module = CommonModule()
class ImportPerformanceData:
"""
履约表数据支撑
"""
def __init__(self):
self.staff_name_to_id = None
self.staff_id_list = None
self.performance_data_list = None
self.field_mapping = {}
self.fields()
def load_all_data(self):
"""加载所有数据"""
payload = {"api_key": "675b900991ad2491c69389ca",
"entry_id": "68637c9818bc333fc14c30ad", # 需要修改
}
performance_data = api_instance.entry_data_list(payload)
self.performance_data_list = performance_data.get("data") # 履约表
# 获取简道云员工id
payload = {"api_key": "6694d3c4fcb69ca9a111a6c4",
"entry_id": "6769204a1902c9341340a1bc",
}
staff_id = api_instance.entry_data_list(payload)
self.staff_id_list = staff_id.get("data") # api请求格式，将数据封装在data字典里
# 预处理员工姓名到ID的映射
self.staff_name_to_id = {
str(item["_widget_1734942794144"]): item["_widget_1734942794145"]
for item in self.staff_id_list
}
def process_data(self, df):
"""处理数据的主函数"""
new_df = self.convert_to_utc(df)
all_data = []
# 预定义角色映射
role_mapping = {
'运营负责人': '运营负责人',
'区域经理': '区域经理'
}
# 使用iterrows的替代方案itertuples更快，但需要确保列名是有效的Python标识符
for row in tqdm(new_df.itertuples(index=False), total=len(new_df)):
row_dict = row._asdict()
# 成员字段替换
for role, field in role_mapping.items():
name = getattr(row, field, None)
if name and str(name) in self.staff_name_to_id:
row_dict[role] = self.staff_name_to_id[str(name)]
else:
row_dict[role] = None
# 简道云字段替换
data_dict = self.row_to_dict(row_dict, self.field_mapping)
all_data.append(data_dict)
return all_data
def convert_to_utc(self, df):
# 创建副本避免修改原DataFrame
new_df = df.copy()
time_columns = ['saas开户时间', '服务期起始时间', '下单支付成功时间', '操作时间',
"下单支付成功日期", "服务期结束时间"]
for col in tqdm(time_columns):
if col in tqdm(new_df.columns): # 安全检查列是否存在
try:
# 1. 转换为datetime（自动推断格式，处理无效值为NaT）
new_df[col] = pd.to_datetime(new_df[col], errors='coerce', utc=False)
# 2. 时区转换（仅对有效日期操作）
mask = new_df[col].notna() # 只处理非空值
if mask.any(): # 如果有有效日期才转换
# 本地化为北京时间，然后转换为UTC
new_df.loc[mask, col + '_utc'] = (
new_df.loc[mask, col]
.dt.tz_localize('Asia/Shanghai', ambiguous='infer', nonexistent='shift_forward')
.dt.tz_convert('UTC')
.dt.strftime('%Y-%m-%dT%H:%M:%SZ')
)
else:
new_df[col + '_utc'] = pd.NA # 全部为空时保持一致性
except Exception as e:
print(f"处理列 {col} 时出错: {str(e)}")
new_df[col + '_utc'] = pd.NA # 出错时设为NA
return new_df
def main(self):
task_start_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
self.load_all_data()
# Step1:获取履约表数据
df = common_module.get_perforamnce_details()
print(df)
print("数据获取完成")
# Step2:清空现有数据
id_list = [item["_id"] for item in self.performance_data_list]
delete_payload = {
"api_key": "675b900991ad2491c69389ca",
"entry_id": "68637c9818bc333fc14c30ad",
"data_ids": id_list
}
api_instance.entry_data_batch_delete(delete_payload)
print("数据删除完成")
# Step3:将数据写入简道云中
all_data = self.process_data(df)
# 分批处理，每批1000条
batch_size = 1000
for i in tqdm(range(0, len(all_data), batch_size)):
batch = all_data[i:i + batch_size]
payload = {
"api_key": "675b900991ad2491c69389ca",
"entry_id": "68637c9818bc333fc14c30ad",
"data_list": batch
}
api_instance.entry_data_batch_create(payload)
print("数据写入完成")
common_module.send_task_status(task_start_time, "履约表数据支撑")
@staticmethod
def row_to_dict(row, field_mapping):
"""将一行数据转换为指定格式的字典"""
result = {}
for col_name, widget_id in field_mapping.items():
if col_name in row:
value = row[col_name]
# 处理Timestamp类型
if pd.isna(value):
clean_value = None
elif isinstance(value, pd.Timestamp):
clean_value = value.strftime('%Y-%m-%dT%H:%M:%SZ')
else:
clean_value = value
result[widget_id] = {"value": clean_value}
return result
def fields(self):
self.field_mapping = {
'公司名称': '_widget_1751350424090', '门店名称': '_widget_1751350424083',
'门店编码': '_widget_1751350424084',
'运营负责人': '_widget_1751350424085', '区域经理': '_widget_1751350424086',
'saas开户时间': '_widget_1751350424088', '服务期起始时间': '_widget_1751350424097',
'下单支付成功时间': '_widget_1751350424101', '操作时间': '_widget_1751350424110',
'下单支付成功日期': '_widget_1751350424115', '服务期结束时间': '_widget_1751350424098',
'订单id': '_widget_1751350424075', 'f6订单编号': '_widget_1751350424076',
'宜搭的实例id': '_widget_1751350424077', '商品id': '_widget_1751350424078',
'商品名称': '_widget_1751350424079', '发布商品类型': '_widget_1751350424080',
'发布商品类型描述': '_widget_1751350424081', '门店id': '_widget_1751350424082',
'商户中心id': '_widget_1751350424087', '公司id': '_widget_1751350424089',
'产生来源': '_widget_1751350424091', '产生来源描述': '_widget_1751350424092',
'类型': '_widget_1751350424093', '类型描述': '_widget_1751350424094', '服务年份': '_widget_1751350424095',
'订单服务期第几年': '_widget_1751350424096', '提成业务类型': '_widget_1751350424099',
'提成类别': '_widget_1751350424100', '实付金额': '_widget_1751881109632',
'系统成本价': '_widget_1751881109633', '版本费': '_widget_1751881109634',
'服务费': '_widget_1751881109635', '介绍人员工ID': '_widget_1751350424106',
'介绍业绩归属人员工ID': '_widget_1751350424107', '处理人ID employee_id': '_widget_1751350424108',
'业绩归属人员工ID': '_widget_1751350424109', '处理人是否跟进,0: 未跟进，1: 已跟进': '_widget_1751350424111',
'满意度评分': '_widget_1751350424112', '评价完成时间': '_widget_1751350424113',
'介绍人用户类型': '_widget_1751350424114', '培训完成时间': '_widget_1751350424116',
'订单所处阶段': '_widget_1751350424117', '日分区': '_widget_1751350424118',
}
if __name__ == '__main__':
start = ImportPerformanceData()
start.main()
back_ground_module/indtall_event_dispatcher.py
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from api import API
from back_ground_module import CommonModule
import datetime
import pandas as pd
from log_config import configure_task_logger, configure_error_task_logger
api_instance = API()
common_module = CommonModule()
start_time = datetime.datetime.now()
# 获取已经配置好的常规日志记录器
logger = configure_task_logger()
# 获取已经配置好的错误任务日志记录器
error_task_logger = configure_error_task_logger()
class InstallEventDispatcher:
"""安装服务历史派发"""
def __init__(self):
# 直接在初始化时设置映射关系
self.services_list = None
self.reversed_field_mapping = {
"省": "_widget_1750301534569",
"市": "_widget_1750301534570",
"区": "_widget_1750301534571",
"门店名称": "_widget_1750301534572",
"门店id": "_widget_1750301534573",
"负责人": "_widget_1750301534574",
"联系电话": "_widget_1750301534575",
"线索状态": "_widget_1750301534577",
"线索来源": "_widget_1750301534576",
}
self.field_mapping = {
"省": "_widget_1744177321450",
"市": "_widget_1744182647145",
"区": "_widget_1744182647146",
"门店名称": "_widget_1744177321449",
"门店id": "_widget_1744177321451",
"负责人": "_widget_1744177321452",
"联系电话": "_widget_1744177321453",
"线索来源": "_widget_1744187212674",
}
self.install_service_lead = None
def load_all_data(self):
"""加载所有必要的数据表"""
# 安装服务线索池
payload = {"api_key": "66f3a68c6e56814df2c6b1af", "entry_id": "68537b5e60a6295c6c09b464"}
json_dict = api_instance.entry_data_list(payload)
self.install_service_lead = json_dict.get("data")
# 安装服务客服表
payload = {"api_key": "66f3a68c6e56814df2c6b1af", "entry_id": "6809d4ef063ece5c83fc61ad"}
json_dict = api_instance.entry_data_list(payload)
self.services_list = json_dict.get("data")
def row_to_dict(self, row, field_mapping):
"""将一行数据转换为指定格式的字典"""
result = {}
for col_name, widget_id in field_mapping.items():
if col_name in row:
value = row[col_name]
clean_value = None if pd.isna(value) else value
result[widget_id] = {"value": clean_value}
return result
def reversed_dict(self, old_dict, field_mapping):
"""将字段ID映射回中文名称"""
id_to_name = {v: k for k, v in field_mapping.items()}
new_dict = {}
for old_key, value in old_dict.items():
# 使用get方法实现高效查找，未找到时保留原键
new_key = id_to_name.get(old_key, old_key)
new_dict[new_key] = value
return new_dict
def main(self):
"""主函数"""
start_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
# 1.加载所有数据
self.load_all_data()
install_service_lead_list = self.install_service_lead
# 将list的字段映射为中文
new_sign_abnormal_data = [
self.reversed_dict(old_dict, self.reversed_field_mapping)
for old_dict in install_service_lead_list
]
# 2.获取今日值班客服
today_duty_staff = []
for item in self.services_list:
if item.get("_widget_1740117343937") == "开":
today_duty_staff.append(item.get("_widget_1740042824214").get("username"))
count = len(today_duty_staff)
if count == 0:
print("今日值班客服为空，请检查数据")
return
# 3.数据准备
new_sign_abnormal_data = [item for item in new_sign_abnormal_data if item["线索状态"] != "已派发"]
# 截取今日需要派发的数据
new_sign_abnormal_data = new_sign_abnormal_data[:count]
# 获取今日要派发数据的id
id_list = [item["_id"] for item in new_sign_abnormal_data]
new_sign_abnormal_data = [
self.row_to_dict(row, self.field_mapping)
for row in new_sign_abnormal_data]
# 4.派发今日数据
i = 0
for item in new_sign_abnormal_data:
item.update({"_widget_1744182647149": {"value":today_duty_staff[i]}})
data = {
'api_key': "66f3a68c6e56814df2c6b1af",
'entry_id': "67f5dc467a9f5b2710da965a", # 安装服务意向表
# 'entry_id': "6853c7cc512ffef038917440", # 测试表
"data": item
}
api_instance.data_batch_create(data)
i += 1
# 5.修改原数据状态为已派发
for id in id_list:
data = {
'api_key': "66f3a68c6e56814df2c6b1af",
'entry_id': "68537b5e60a6295c6c09b464",
"data_id": id,
"data": {"_widget_1750301534577": {"value": "已派发"}}
}
api_instance.entry_data_update(data)
common_module.send_task_status(start_time, "安装服务历史派发")
if __name__ == "__main__":
install_event_dispatcher = InstallEventDispatcher()
install_event_dispatcher.main()
back_ground_module/logs/detail_task.log
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back_ground_module/logs/error_task.log
+1
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2025-08-08 11:36:30,090 - error_task_logger - ERROR - 数据处理完成
back_ground_module/logs/task.log
+2
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2025-08-08 11:36:30,090 - task_logger - INFO - 数据处理完成
2025-08-08 11:36:30,210 - task_logger - INFO - 任务状态发送成功: {'data': {'creator': {'name': 'F6汽车科技', 'username': '#admin', 'status': 1, 'type': 0}, 'updater': {'name': 'F6汽车科技', 'username': '#admin', 'status': 1, 'type': 0}, 'deleter': None, 'createTime': '2025-08-08T03:36:29.601Z', 'updateTime': '2025-08-08T03:36:29.601Z', 'deleteTime': None, '_widget_1744873387500': '2025-08-08T00:00:00.000Z', '_widget_1743644977694': '经销商新签服务单转BI', '_widget_1744873387501': '2025-08-08T03:36:29.000Z', '_widget_1744873387502': '2025-08-08T03:36:30.000Z', '_widget_1744873387504': '1', '_id': '689570bd4d37fe546faea135', 'appId': '6694d3c4fcb69ca9a111a6c4', 'entryId': '67ede908eb9c22261016466e'}}
back_ground_module/new_dealer_service_order_to_bi.py
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# -*- coding: utf-8 -*-
import pandas as pd
import datetime
from config import Config
from api import API
import pymysql # 使用 pymysql 替代 mysql.connector
from back_ground_module import CommonModule
import os
import mysql.connector
import pandas as pd
import json
import numpy as np
import mysql.connector
from mysql.connector import Error
from log_config import configure_task_logger, configure_error_task_logger
start_time = datetime.datetime.now()
api_instance = API()
common_module = CommonModule()
# 获取已经配置好的常规日志记录器
logger = configure_task_logger()
# 获取已经配置好的错误任务日志记录器
error_task_logger = configure_error_task_logger()
# 保存为CSV文件
output_dir = "output" # 设置输出目录
# 创建输出目录（如果不存在）
os.makedirs(output_dir, exist_ok=True)
class NewDealerServiceOrderToBI:
# 经销商新签服务单转BI
def __init__(self):
self.dealer_service_data = None
self.field_mapping = {'购买的产品名称': '_widget_1742197585104', '经销商名称': '_widget_1741164213155',
'经销商简称': '_widget_1741164213151', '负责人姓名': '_widget_1741165503706',
'负责人手机号': '_widget_1741165503711', '经销商可使用的群数量': '_widget_1741165503710',
'订单编码': '_widget_1741164213149', '订单支付时间': '_widget_1741164213159',
'商户门店ID': '_widget_1741164213152', '开通时间': '_widget_1741164213171',
'详细地址': '_widget_1741164213172', '联系电话': '_widget_1741165503708',
'系统到期时间': '_widget_1741165503709', '开通状态': '_widget_1741165503714',
'销售负责人': '_widget_1741165503716', '运营顾问': '_widget_1741165503718',
'运营专家': '_widget_1741165503719', '区域经理': '_widget_1741165503717',
'业务人员': '_widget_1741165503721', '是否设置经营范围': '_widget_1742200372555',
'不设置经营范围原因': '_widget_1742268351775', '是否建群': '_widget_1742200372553',
'不建群原因': '_widget_1742268351776', '是否设置备货清单': '_widget_1742200372634',
'不设置备货清单原因': '_widget_1742268351778', '是否设置报价': '_widget_1742260928184',
'不设置报价原因': '_widget_1742268351777', '是否上货': '_widget_1742200372559',
'不上货原因': '_widget_1742268351779', '是否培训系统使用': '_widget_1749717287367',
'不培训系统使用原因': '_widget_1749717287369', '是否补货': '_widget_1749717287373',
'不补货原因': '_widget_1749717287375',
'是否进行滞销回抽+盘点介绍': '_widget_1742200372561',
'不进行滞销回抽+盘点介绍原因': '_widget_1742268351780',
'服务是否满意': '_widget_1743148999298', '服务不满意原因': '_widget_1743148999308',
'产品是否满意': '_widget_1743148999300', '产品不满意原因': '_widget_1743148999309',
# '上传评价图片': '_widget_1743148999310',
'培训完成时间':'_widget_1754472835261',
'审核备注': '_widget_1743500862664',
'完成日期时间': '_widget_1753162835213', '流水号': '_widget_1753163217437',
'提交人': 'creator', '提交时间': 'createTime', '更新时间': 'updateTime'}
def load_all_data(self):
# 获取经销商新签服务单数据
payload = {"api_key": "673d8427549d00c3d753c530",
"entry_id": "67c80eb3d2af9b9821928f45",
}
dealer_service = api_instance.entry_data_list(payload)
self.dealer_service_data = dealer_service.get("data") # api请求格式，将数据封装在data字典里
def data_process(self):
df = pd.DataFrame(self.dealer_service_data)
# 反转映射字典
reverse_mapping = {v: k for k, v in self.field_mapping.items()}
# 1.列明替换
df.columns = [reverse_mapping.get(col, col) for col in df.columns]
# 2.成员字段取值
user_columns = ["提交人", "销售负责人", "区域经理", "业务人员", "运营顾问", "运营专家"]
for col in user_columns:
df[col] = df[col].map(lambda x: x.get("name", "") if isinstance(x, dict) else "")
# 3.日期字段转为北京时间
time_columns = ["订单支付时间", "开通时间", "系统到期时间", "完成日期时间", "提交时间", "更新时间","培训完成时间"]
df[time_columns] = df[time_columns].apply(
lambda col: pd.to_datetime(col, errors='coerce')
.dt.tz_localize(None)
.dt.strftime('%Y-%m-%d %H:%M:%S')
)
return df
def write_to_bi(self, df):
# 数据库连接信息
HS_DB_Config = {
'host': "f6-public.rwlb.rds.aliyuncs.com",
'user': "rw_operation_data_relay",
'password': "m+q5Z4%IVuF9bf",
'database': "f6operation_data_relay"
}
table_name = "new_dealer_service_order_to_bi" # 替换为你的实际表名
# 建立数据库连接
connection = mysql.connector.connect(
host=HS_DB_Config["host"],
user=HS_DB_Config["user"],
password=HS_DB_Config["password"],
database=HS_DB_Config["database"]
)
cursor = connection.cursor()
try:
# 查询表列名
cursor.execute(f"SHOW COLUMNS FROM {table_name}")
columns_info = cursor.fetchall()
db_columns = [col[0] for col in columns_info] # 提取列名
df = df.replace([None, np.nan, pd.NA, 'nan', 'NaN', 'NAN', ''], None)
# 保留 DataFrame 中与数据库列名匹配的列
filtered_df = df[df.columns.intersection(db_columns)]
# 如果没有匹配的列，直接返回
if filtered_df.empty:
print("DataFrame 中没有与数据库表结构匹配的列。")
return
# 筛选列之后，插入前处理 dict 类型
filtered_df = filtered_df.copy()
for col in filtered_df.columns:
if filtered_df[col].apply(lambda x: isinstance(x, (dict, list)) if x is not None else False).any():
filtered_df.loc[:, col] = filtered_df[col].apply(
lambda x: json.dumps(x, ensure_ascii=False) if x is not None else x
)
# 构建插入语句
placeholders = ', '.join(['%s'] * len(filtered_df.columns))
# 使用反引号避免特殊列明
columns = ', '.join([f"`{col}`" for col in filtered_df.columns])
insert_sql = f"INSERT INTO {table_name} ({columns}) VALUES ({placeholders})"
# 将 DataFrame 写入数据库
for _, row in filtered_df.iterrows():
cursor.execute(insert_sql, tuple(row))
connection.commit()
print(f"成功写入 {len(filtered_df)} 条记录到 {table_name} 表中。")
except Exception as e:
print("写入数据库时发生错误：", e)
connection.rollback()
finally:
cursor.close()
connection.close()
def clear_table_data(self):
"""
清空指定 MySQL 表的数据。
参数已写死在函数内部，直接调用即可。
"""
# 数据库连接信息
HS_DB_Config = {
'host': "f6-public.rwlb.rds.aliyuncs.com",
'user': "rw_operation_data_relay",
'password': "m+q5Z4%IVuF9bf",
'database': "f6operation_data_relay"
}
table_name = "new_dealer_service_order_to_bi" # 要清空的表名
connection = None
try:
# 建立数据库连接
connection = mysql.connector.connect(
host=HS_DB_Config["host"],
user=HS_DB_Config["user"],
password=HS_DB_Config["password"],
database=HS_DB_Config["database"]
)
if connection.is_connected():
cursor = connection.cursor()
# 使用TRUNCATE清空表数据
cursor.execute(f"TRUNCATE TABLE {table_name}")
connection.commit()
print(f"成功清空表 {table_name} 中的所有数据")
except Error as e:
print(f"清空表时发生错误: {e}")
if connection and connection.is_connected():
connection.rollback()
finally:
if connection and connection.is_connected():
cursor.close()
connection.close()
print("数据库连接已关闭")
def main(self):
task_start_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
# step1: 获取数据
self.load_all_data()
# step2:数据处理
df = self.data_process()
# # step3:数据库删除
self.clear_table_data()
#
# # step4:数据写入BI
self.write_to_bi(df)
common_module.send_task_status(task_start_time, "经销商新签服务单转BI")
if __name__ == '__main__':
start = NewDealerServiceOrderToBI()
start.main()
back_ground_module/output/数据快照存储/all_widgets_2025-07-03.csv
+12666
View File
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back_ground_module/output/数据快照存储/all_widgets_2025-07-08.csv
+12691
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File diff suppressed because it is too large Load Diff
back_ground_module/output/数据快照存储/last_data.csv
+529
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@@ -0,0 +1,529 @@
name,widgetName,label,type,items,app_id,entry_id
_widget_1690785229260,_widget_1690785229260,怎么称呼您,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1690785229261,_widget_1690785229261,您门店或公司名称,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693382214358,_widget_1693382214358,您的联系方式,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1690785326597,_widget_1690785326597,地址,address,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1690785229266,_widget_1690785229266,备注,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1690785229284,_widget_1690785229284,客户概况,textarea,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1690787826014,_widget_1690787826014,门头照片（可上传多张）,image,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1690785229278,_widget_1690785229278,意向书来源,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1741837239117,_widget_1741837239117,业务类型,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693381022904,_widget_1693381022904,客户渠道,combo,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1715146829031,_widget_1715146829031,轻连锁类型,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1690785229280,_widget_1690785229280,小六,user,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1694154771486,_widget_1694154771486,技术专家,user,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1690785229281,_widget_1690785229281,战区经理,user,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1718855270618,_widget_1718855270618,该养车门店是否已退出？,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1718855270620,_widget_1718855270620,退出情况说明,textarea,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1718855270621,_widget_1718855270621,该养车门店是否有F6系统需求？,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1690785229282,_widget_1690785229282,意向阶段,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693551051341,_widget_1693551051341,客户门店数,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1690785229283,_widget_1690785229283,意向版本,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693381022909,_widget_1693381022909,客户沟通记录,subform,"[{'name': '_widget_1693381022911', 'widgetName': '_widget_1693381022911', 'label': '跟进日期', 'type': 'datetime'}, {'name': '_widget_1693381022912', 'widgetName': '_widget_1693381022912', 'label': '沟通方式', 'type': 'combo'}, {'name': '_widget_1693381022914', 'widgetName': '_widget_1693381022914', 'label': '沟通概要', 'type': 'textarea'}]",66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693381022908,_widget_1693381022908,下次跟进日期,datetime,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1696902504775,_widget_1696902504775,理论下次跟进日期,datetime,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1694398435902,_widget_1694398435902,最近一次沟通日期,datetime,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693381022915,_widget_1693381022915,客户在用系统名称,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693381022916,_widget_1693381022916,预计成交金额（单位：元）,number,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693381022917,_widget_1693381022917,预计成交日期,datetime,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1699321775702,_widget_1699321775702,实际成交日期,datetime,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693381022918,_widget_1693381022918,下单手机号,phone,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693381022919,_widget_1693381022919,放弃原因分类,combo,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693381022921,_widget_1693381022921,价格原因,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693381022923,_widget_1693381022923,产品原因,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693381022925,_widget_1693381022925,门店原因,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693381022930,_widget_1693381022930,加盟外部连锁,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693381022927,_widget_1693381022927,内部业务影响（包含接车宝会员宝安装服务）,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1724313867483,_widget_1724313867483,输单原因分类,combo,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1723603567435,_widget_1723603567435,竞品名称,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693381022929,_widget_1693381022929,输单/放弃说明,textarea,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1708935626093,_widget_1708935626093,线索沟通情况,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1709019633297,_widget_1709019633297,客户业务需求,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1708935626085,_widget_1708935626085,客户手机号是否是微信号？,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1708935626087,_widget_1708935626087,企微是否已加好友？,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1708935626089,_widget_1708935626089,BOSS系统里是否有该客户信息,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1709027488072,_widget_1709027488072,客户BOSS业务信息,checkboxgroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1708935626095,_widget_1708935626095,联系人身份,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1709100220536,_widget_1709100220536,门店业务类型,combo,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1708935626104,_widget_1708935626104,客户门店工位数,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1708935626100,_widget_1708935626100,客户是否有需求,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1708935626102,_widget_1708935626102,客户主要需求功能模块（可多选）,checkboxgroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1708935626107,_widget_1708935626107,客户原系统,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1708935626091,_widget_1708935626091,客户预算,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1708935626098,_widget_1708935626098,预计使用时间,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1709186927667,_widget_1709186927667,门头照片等,image,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1709100220453,_widget_1709100220453,SDR联系记录,subform,"[{'name': '_widget_1709100220457', 'widgetName': '_widget_1709100220457', 'label': '日期时间', 'type': 'datetime'}, {'name': '_widget_1709100220455', 'widgetName': '_widget_1709100220455', 'label': '联系情况', 'type': 'text'}]",66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1708935626292,_widget_1708935626292,SDR判断客户是否需要进一步跟进,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1710292803370,_widget_1710292803370,SDR建议线索跟进时间,combo,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1710037836605,_widget_1710037836605,线索放弃说明,textarea,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1709543713740,_widget_1709543713740,SDR放弃意见,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1725501916821,_widget_1725501916821,提交时间,datetime,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1725507662927,_widget_1725507662927,提交人,user,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1690785229279,_widget_1690785229279,城市,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1692070536228,_widget_1692070536228,区,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1697423018006,_widget_1697423018006,战区,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1694076921201,_widget_1694076921201,线上线下,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1709868059118,_widget_1709868059118,线索跟进角色,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1709781645383,_widget_1709781645383,客户跟进角色,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1725875301461,_widget_1725875301461,技术支持提交人,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1725933630175,_widget_1725933630175,是否有效线索,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1690785229262,_widget_1690785229262,您的联系方式,phone,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1723431564839,_widget_1723431564839,线索状态,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_0201002000002,_widget_0201002000002,经销商名称,company,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1732095401220,_widget_1732095401220,经销商简称,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_0201002000005,_widget_0201002000005,所属公海,account_pool,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1732095401222,_widget_1732095401222,营业执照号,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1732095401223,_widget_1732095401223,营业执照名称,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1732153235945,_widget_1732153235945,详细地址,address,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1732095401224,_widget_1732095401224,负责人姓名,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1732095401225,_widget_1732095401225,负责人手机号,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1732095401226,_widget_1732095401226,联系电话,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1742200662775,_widget_1742200662775,购买年限,combo,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1742278002584,_widget_1742278002584,购买版本,combo,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1732095401227,_widget_1732095401227,经销商可购买的群数量,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_0201002000003,_widget_0201002000003,销售负责人,user,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1732153235954,_widget_1732153235954,运营顾问,user,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1732153235955,_widget_1732153235955,运营专家,user,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1732153235956,_widget_1732153235956,区域经理,user,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1741165766484,_widget_1741165766484,业务,user,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1732180937809,_widget_1732180937809,经销商ID,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1732180937812,_widget_1732180937812,开通状态,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1732180937811,_widget_1732180937811,开通时间,datetime,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1741160451740,_widget_1741160451740,系统到期时间,datetime,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1630862543415,_widget_1630862543415,客户状态,combo,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1630862543434,_widget_1630862543434,客户级别,combo,,673d8427549d00c3d753c530,020100200000000000000001
_widget_0201002000001,_widget_0201002000001,客户编码,sn,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1646826421878,_widget_1646826421878,客户邮箱,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1630862543637,_widget_1630862543637,所属行业,combo,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1732178180219,_widget_1732178180219,客户来源表单字段,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_0201002000006,_widget_0201002000006,销售归属部门,dept,,673d8427549d00c3d753c530,020100200000000000000001
_widget_0201002000004,_widget_0201002000004,协作人,usergroup,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1631071964934,_widget_1631071964934,客户详情,textarea,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1631071964761,_widget_1631071964761,客户来源,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1663742427957,_widget_1663742427957,客户查重,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1663742427909,_widget_1663742427909,客户查重：客户表内该客户数量,number,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1709110880998,_widget_1709110880998,结算期限,combo,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1709110881001,_widget_1709110881001,信用额度/元,number,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1709110881002,_widget_1709110881002,发票抬头,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1709110881003,_widget_1709110881003,发票税号,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1709110881004,_widget_1709110881004,税种,combo,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1709110881007,_widget_1709110881007,增值税税率 %,number,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1709110881008,_widget_1709110881008,开户电话,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1709110881009,_widget_1709110881009,开户银行,combo,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1709110881016,_widget_1709110881016,银行账户,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1734062123070,_widget_1734062123070,门店名称,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123068,_widget_1734062123068,公司名称,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123071,_widget_1734062123071,门店编码,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123072,_widget_1734062123072,公司等级,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123073,_widget_1734062123073,门店类型,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123085,_widget_1734062123085,是否主店,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123067,_widget_1734062123067,公司id,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123069,_widget_1734062123069,门店id,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123169,_widget_1734062123169,经营模式,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123170,_widget_1734062123170,联系人,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123172,_widget_1734062123172,手机号码,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123179,_widget_1734062123179,是否主店,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123180,_widget_1734062123180,门店数,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123066,_widget_1734062123066,日期,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123065,_widget_1734062123065,日期批次,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1749000071375,_widget_1749000071375,日期（时间字段）,datetime,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123192,_widget_1734062123192,是否加店,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123194,_widget_1734062123194,门店规模,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123196,_widget_1734062123196,经营范围,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123197,_widget_1734062123197,维修厂类型,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123199,_widget_1734062123199,工位数,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123201,_widget_1734062123201,门店阶段,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123203,_widget_1734062123203,门店分层,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1742890765211,_widget_1742890765211,门头照片,image,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123090,_widget_1734062123090,省,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123092,_widget_1734062123092,市,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123094,_widget_1734062123094,区,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123095,_widget_1734062123095,大区,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123097,_widget_1734062123097,小区,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123099,_widget_1734062123099,前置仓名称,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123102,_widget_1734062123102,区域经理,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123103,_widget_1734062123103,续约顾问,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123105,_widget_1734062123105,运营负责人,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123204,_widget_1734062123204,运营专家,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1748496855779,_widget_1748496855779,区域经理（成员字段）,user,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1748496855780,_widget_1748496855780,运营负责人（成员字段）,user,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1748496855778,_widget_1748496855778,续约顾问（成员字段）,user,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1751877712235,_widget_1751877712235,运营专家（成员字段）,user,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123075,_widget_1734062123075,ERP操作模式,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123076,_widget_1734062123076,公众号,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123077,_widget_1734062123077,小程序,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123078,_widget_1734062123078,微信商城,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123079,_widget_1734062123079,洗车摄像头,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123106,_widget_1734062123106,有效账户数,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123175,_widget_1734062123175,安装服务,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123184,_widget_1734062123184,SaaS版本,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123074,_widget_1734062123074,客户状态,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123081,_widget_1734062123081,开户日,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123082,_widget_1734062123082,应续约日,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123083,_widget_1734062123083,使用天数,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123084,_widget_1734062123084,使用年数,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123176,_widget_1734062123176,上线日期,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123177,_widget_1734062123177,过期日,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123178,_widget_1734062123178,实际续约日,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1749000071377,_widget_1749000071377,开户日（日期字段）,datetime,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1749000071382,_widget_1749000071382,应续约日（日期字段）,datetime,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1749000071384,_widget_1749000071384,上线日期（日期字段）,datetime,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1749000071389,_widget_1749000071389,过期日（日期字段）,datetime,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1749000071391,_widget_1749000071391,实际续约日（日期字段）,datetime,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123111,_widget_1734062123111,G状态,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123115,_widget_1734062123115,活跃状态,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123117,_widget_1734062123117,近30天业务天数,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123119,_widget_1734062123119,近7天业务单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123120,_widget_1734062123120,近7天业务天数,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123122,_widget_1734062123122,UV数,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123167,_widget_1734062123167,G变化(月),text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123173,_widget_1734062123173,G月份,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123174,_widget_1734062123174,G转化率,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123182,_widget_1734062123182,G变化类型,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123183,_widget_1734062123183,G流失天数,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123185,_widget_1734062123185,M-1(G),number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123186,_widget_1734062123186,M-2(G),number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123187,_widget_1734062123187,M-3(G),number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123188,_widget_1734062123188,M-4(G),number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123189,_widget_1734062123189,M-5(G),number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123190,_widget_1734062123190,M-6(G),number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123191,_widget_1734062123191,G天数,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123202,_widget_1734062123202,本月G天数,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123116,_widget_1734062123116,近30天业务单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123155,_widget_1734062123155,近30天维修单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123156,_widget_1734062123156,近30天洗车单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123157,_widget_1734062123157,近30天维修开单天数,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123158,_widget_1734062123158,近30天洗车开单天数,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123159,_widget_1734062123159,近30天销售单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123160,_widget_1734062123160,近30天销售单开单天数,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123161,_widget_1734062123161,近30天采购单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123162,_widget_1734062123162,近30天采购开单天数,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123163,_widget_1734062123163,近30天卡业务单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123164,_widget_1734062123164,近30天卡业务天数,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123118,_widget_1734062123118,自然月业务天数,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123123,_widget_1734062123123,T_1开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123124,_widget_1734062123124,T_2开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123125,_widget_1734062123125,T_3开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123126,_widget_1734062123126,T_4开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123127,_widget_1734062123127,T_5开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123128,_widget_1734062123128,T_6开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123129,_widget_1734062123129,T_7开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123130,_widget_1734062123130,T_8开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123131,_widget_1734062123131,T_9开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123132,_widget_1734062123132,T_10开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123133,_widget_1734062123133,T_11开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123134,_widget_1734062123134,T_12开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123135,_widget_1734062123135,T_13开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123136,_widget_1734062123136,T_14开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123137,_widget_1734062123137,T_15开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123138,_widget_1734062123138,T_16开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123139,_widget_1734062123139,T_17开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123140,_widget_1734062123140,T_18开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123141,_widget_1734062123141,T_19开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123142,_widget_1734062123142,T_20开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123143,_widget_1734062123143,T_21开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123144,_widget_1734062123144,T_22开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123145,_widget_1734062123145,T_23开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123146,_widget_1734062123146,T_24开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123147,_widget_1734062123147,T_25开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123148,_widget_1734062123148,T_26开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123149,_widget_1734062123149,T_27开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123150,_widget_1734062123150,T_28开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123151,_widget_1734062123151,T_29开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123152,_widget_1734062123152,T_30开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123153,_widget_1734062123153,T_31开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123080,_widget_1734062123080,is_maintenance_service,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123086,_widget_1734062123086,license_code,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123087,_widget_1734062123087,license_name,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123088,_widget_1734062123088,org_crm_id,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123089,_widget_1734062123089,province_id,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123091,_widget_1734062123091,city_id,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123093,_widget_1734062123093,area_id,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123096,_widget_1734062123096,region_short_name,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123098,_widget_1734062123098,carzone_store_id,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123100,_widget_1734062123100,customer_carzone_id,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123101,_widget_1734062123101,salesmen,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123104,_widget_1734062123104,impl_principal,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123107,_widget_1734062123107,active_user_type,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123108,_widget_1734062123108,limit_user_count,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123109,_widget_1734062123109,limit_user_type,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123110,_widget_1734062123110,is_n,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123112,_widget_1734062123112,is_v,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123113,_widget_1734062123113,is_visited,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123114,_widget_1734062123114,is_active,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123121,_widget_1734062123121,pv_count,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123154,_widget_1734062123154,etl_time,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123165,_widget_1734062123165,gd_sales_bill_count_last_30_day,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123166,_widget_1734062123166,gd_sales_bill_day_count_last_30_day,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123168,_widget_1734062123168,saas_package,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123171,_widget_1734062123171,contact_number,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123181,_widget_1734062123181,recent_bill_warning_days,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123193,_widget_1734062123193,pt,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123195,_widget_1734062123195,qualification_type_fmt,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123198,_widget_1734062123198,area,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123200,_widget_1734062123200,header_type_fmt,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123205,_widget_1734062123205,tmall_maintain_service_status_desc,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1745908548852,_widget_1745908548852,江苏易捷门店归属公司,radiogroup,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1742795002375,_widget_1742795002375,公司ID,text,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002376,_widget_1742795002376,公众号名称,text,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002377,_widget_1742795002377,小程序模板类型,text,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002378,_widget_1742795002378,是否开通微信商城,number,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002379,_widget_1742795002379,上架商品数,number,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002380,_widget_1742795002380,上架套餐卡数,number,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002381,_widget_1742795002381,上架实体商品数,number,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002382,_widget_1742795002382,上架项目数,number,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002383,_widget_1742795002383,上架套餐数,number,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002384,_widget_1742795002384,微信公众号粉丝数,number,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002385,_widget_1742795002385,微信公众号绑定手机粉丝数,number,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002386,_widget_1742795002386,是否开通微信小程序,number,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002387,_widget_1742795002387,微信小程序绑定用户数,number,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002388,_widget_1742795002388,微信小程序绑定手机用户量,number,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002389,_widget_1742795002389,微信订单数,number,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002390,_widget_1742795002390,微信支付订单量,number,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002391,_widget_1742795002391,线下订单数,number,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742884710674,_widget_1742884710674,门店id,text,,675b900991ad2491c69389ca,67e24f665adf5a8611f3e589
_widget_1742884710675,_widget_1742884710675,提成类型_二级分类,text,,675b900991ad2491c69389ca,67e24f665adf5a8611f3e589
_widget_1742884710676,_widget_1742884710676,提成基数（本月）,number,,675b900991ad2491c69389ca,67e24f665adf5a8611f3e589
_widget_1742884710677,_widget_1742884710677,提成基数（上月）,number,,675b900991ad2491c69389ca,67e24f665adf5a8611f3e589
_widget_1748930441629,_widget_1748930441629,公司id,text,,675b900991ad2491c69389ca,67e24f665adf5a8611f3e589
_widget_1748931089356,_widget_1748931089356,门店编码,text,,675b900991ad2491c69389ca,67e24f665adf5a8611f3e589
_widget_1748931089357,_widget_1748931089357,门店名称,text,,675b900991ad2491c69389ca,67e24f665adf5a8611f3e589
_widget_1742884829007,_widget_1742884829007,门店id,text,,675b900991ad2491c69389ca,67e24fdd8dfcfa918e17c30b
_widget_1742884829008,_widget_1742884829008,商品名称,text,,675b900991ad2491c69389ca,67e24fdd8dfcfa918e17c30b
_widget_1742884829009,_widget_1742884829009,服务期结束时间,text,,675b900991ad2491c69389ca,67e24fdd8dfcfa918e17c30b
_widget_1748930826642,_widget_1748930826642,公司id,text,,675b900991ad2491c69389ca,67e24fdd8dfcfa918e17c30b
_widget_1748931208852,_widget_1748931208852,门店编码,text,,675b900991ad2491c69389ca,67e24fdd8dfcfa918e17c30b
_widget_1748931208851,_widget_1748931208851,门店名称,text,,675b900991ad2491c69389ca,67e24fdd8dfcfa918e17c30b
_widget_1743065201885,_widget_1743065201885,公司id,text,,675b900991ad2491c69389ca,67e5107198ba1b20d5df3974
_widget_1743065201886,_widget_1743065201886,是否启动短信功能,text,,675b900991ad2491c69389ca,67e5107198ba1b20d5df3974
_widget_1743065201887,_widget_1743065201887,是否购买短信包,text,,675b900991ad2491c69389ca,67e5107198ba1b20d5df3974
_widget_1743065201888,_widget_1743065201888,累计购买总数,text,,675b900991ad2491c69389ca,67e5107198ba1b20d5df3974
_widget_1743065201889,_widget_1743065201889,累计发送成功总人数,text,,675b900991ad2491c69389ca,67e5107198ba1b20d5df3974
_widget_1743065201890,_widget_1743065201890,剩余短信条数,text,,675b900991ad2491c69389ca,67e5107198ba1b20d5df3974
_widget_1743065201891,_widget_1743065201891,第一次短信购买时间,text,,675b900991ad2491c69389ca,67e5107198ba1b20d5df3974
_widget_1743065201892,_widget_1743065201892,最近一次短信购买时间,text,,675b900991ad2491c69389ca,67e5107198ba1b20d5df3974
_widget_1743065201893,_widget_1743065201893,实付总金额,text,,675b900991ad2491c69389ca,67e5107198ba1b20d5df3974
_widget_1743065201894,_widget_1743065201894,短信剩余量是否小于20%,text,,675b900991ad2491c69389ca,67e5107198ba1b20d5df3974
_widget_1748241895830,_widget_1748241895830,门店名称,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895831,_widget_1748241895831,联系人,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895839,_widget_1748241895839,开户时间,datetime,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895842,_widget_1748241895842,门店编码,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895832,_widget_1748241895832,联系方式,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895850,_widget_1748241895850,系统版本,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895844,_widget_1748241895844,公司名称,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748246808679,_widget_1748246808679,运营顾问,user,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748246808682,_widget_1748246808682,区域经理,user,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895846,_widget_1748241895846,公司等级,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748246808681,_widget_1748246808681,运营专家,user,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895853,_widget_1748241895853,操作模式E.L/E.S,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895829,_widget_1748241895829,活跃健康状态变化,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895833,_widget_1748241895833,初始日,datetime,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895834,_widget_1748241895834,推进日,datetime,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748512176640,_widget_1748512176640,异常跟进情况描述,textarea,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748512176641,_widget_1748512176641,异常变化原因,radiogroup,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748512176643,_widget_1748512176643,正常使用,radiogroup,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748512176645,_widget_1748512176645,门店原因,radiogroup,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748512176647,_widget_1748512176647,服务原因,radiogroup,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748512176649,_widget_1748512176649,产品原因,radiogroup,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748512176651,_widget_1748512176651,未正式切换,radiogroup,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748512176655,_widget_1748512176655,跟进状态,radiogroup,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748246808678,_widget_1748246808678,当前跟进人,user,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748512176654,_widget_1748512176654,跟进时间,datetime,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1751273412737,_widget_1751273412737,是否跟进完成,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748246808680,_widget_1748246808680,区域客服,user,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895847,_widget_1748241895847,大区,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895848,_widget_1748241895848,省,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895855,_widget_1748241895855,城市,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895849,_widget_1748241895849,门店类型,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895851,_widget_1748241895851,saas客户类型,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895852,_widget_1748241895852,门店阶段,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748247754304,_widget_1748247754304,关联数据,lookup,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1751250294777,_widget_1751250294777,姓名1,text,,6694d3c4fcb69ca9a111a6c4,6861f5772b0d3575e14eba4a
_widget_1751505196330,_widget_1751505196330,图片,image,,6694d3c4fcb69ca9a111a6c4,6861f5772b0d3575e14eba4a
_widget_1751507507755,_widget_1751507507755,定位,location,,6694d3c4fcb69ca9a111a6c4,6861f5772b0d3575e14eba4a
_widget_1739951204545,_widget_1739951204545,表单类型,combo,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739252804406,_widget_1739252804406,日期,datetime,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739258942667,_widget_1739258942667,账号,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739252804419,_widget_1739252804419,日分区,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739252804397,_widget_1739252804397,产品名称,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739252804407,_widget_1739252804407,联系手机号,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739252804409,_widget_1739252804409,使用时长,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739252804396,_widget_1739252804396,开户日,datetime,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739252804408,_widget_1739252804408,到期日,datetime,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739252804410,_widget_1739252804410,续约日,datetime,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739252804400,_widget_1739252804400,客户状态,combo,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739252804413,_widget_1739252804413,近一周开单量,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739252804414,_widget_1739252804414,近一周是否活跃,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739252804415,_widget_1739252804415,G状态：近30天开单大于等于10天,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739252804416,_widget_1739252804416,当月开单天数,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739252804417,_widget_1739252804417,近30天开单天数,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739252804418,_widget_1739252804418,当月G天数,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740036367181,_widget_1740036367181,派发日期,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740043340255,_widget_1740043340255,跟进人,user,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1741252143304,_widget_1741252143304,是否联系上·新签,combo,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1741252143306,_widget_1741252143306,是否联系上·异常,combo,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1741252143308,_widget_1741252143308,是否联系上·续约商机,combo,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1741252143310,_widget_1741252143310,是否联系上·过期召回,combo,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1741256466947,_widget_1741256466947,未接通原因备注,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740721384110,_widget_1740721384110,省市区,address,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1741312871468,_widget_1741312871468,省市区·续约,address,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740721384111,_widget_1740721384111,门店名称,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1741312871469,_widget_1741312871469,门店名称·续约,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740721384112,_widget_1740721384112,负责人姓名,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1741312871470,_widget_1741312871470,负责人姓名·续约,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740721384122,_widget_1740721384122,回访人·新签,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740721384117,_widget_1740721384117,未开单原因·新签,textarea,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740721384125,_widget_1740721384125,是否愿意继续使用·新签,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740721384127,_widget_1740721384127,回访人·异常,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740721384128,_widget_1740721384128,未开单原因·异常,textarea,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740721384129,_widget_1740721384129,是否愿意继续使用·异常,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740721384131,_widget_1740721384131,回访人·续约商机,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740721384132,_widget_1740721384132,是否有转化SaaS意愿·续约商机,combo,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740721384133,_widget_1740721384133,系统使用情况·续约商机,textarea,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1749088869175,_widget_1749088869175,SaaS转化结果·续约商机,radiogroup,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1749088869177,_widget_1749088869177,转化SaaS订单号·续约商机,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1749088869190,_widget_1749088869190,其他转化结果·续约商机,textarea,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740721384135,_widget_1740721384135,回访人·过期召回,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740721384136,_widget_1740721384136,未续约单原因·过期召回,textarea,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740721384137,_widget_1740721384137,是否有续约意愿·过期召回,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1749090854370,_widget_1749090854370,沟通跟进结果·过期召回,radiogroup,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1749090854372,_widget_1749090854372,转化SaaS订单号·过期召回,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1749090854373,_widget_1749090854373,接车宝续约订单号·过期召回,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1749090854374,_widget_1749090854374,其他召回情况说明·过期召回,textarea,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1751356539629,_widget_1751356539629,完成日期时间,datetime,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1751271771674,_widget_1751271771674,是否完成,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1751356033346,_widget_1751356033346,流水号,sn,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740042824214,_widget_1740042824214,客服人员,user,,6717470a0b3975ef583c6df1,67b6f2462f9ac03b783d409a
_widget_1740117343937,_widget_1740117343937,开关,combo,,6717470a0b3975ef583c6df1,67b6f2462f9ac03b783d409a
_widget_1740042824216,_widget_1740042824216,下次开始位置,text,,6717470a0b3975ef583c6df1,67b6f2462f9ac03b783d409a
_widget_1740723898388,_widget_1740723898388,日期,datetime,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898389,_widget_1740723898389,产品名称,text,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898390,_widget_1740723898390,账号,text,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898391,_widget_1740723898391,联系手机号,number,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898392,_widget_1740723898392,开户日,datetime,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898393,_widget_1740723898393,使用时长,number,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898394,_widget_1740723898394,续约日,text,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898395,_widget_1740723898395,到期日,datetime,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898396,_widget_1740723898396,客户状态,text,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898397,_widget_1740723898397,近一周开单量,number,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898398,_widget_1740723898398,近一周是否活跃,number,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898399,_widget_1740723898399,G状态：近30天开单大于等于10天,number,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898400,_widget_1740723898400,当月开单天数,number,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898401,_widget_1740723898401,近30天开单天数,number,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898402,_widget_1740723898402,当月G天数,number,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898403,_widget_1740723898403,日分区,number,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898404,_widget_1740723898404,表单类型,text,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898405,_widget_1740723898405,派发日期,datetime,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_0201002000001,_widget_0201002000001,客户编码,sn,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_0201002000002,_widget_0201002000002,门店名称,company,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1630862543434,_widget_1630862543434,客户级别,combo,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1631071964761,_widget_1631071964761,客户来源,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_0201002000005,_widget_0201002000005,所属公海,account_pool,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1663742427957,_widget_1663742427957,客户查重,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1750126318263,_widget_1750126318263,门店名称（后台传值）,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1746675108119,_widget_1746675108119,原系统名称,combo,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1749204198412,_widget_1749204198412,原系统情况描述,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1630862543637,_widget_1630862543637,门店类型,combo,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1746675108151,_widget_1746675108151,门店设备,combocheck,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1746675108121,_widget_1746675108121,门店业务,combocheck,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1746675108115,_widget_1746675108115,工位数,number,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1747321321284,_widget_1747321321284,员工数,number,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1746675108123,_widget_1746675108123,系统操作人员,combocheck,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737097782383,_widget_1737097782383,门店环境,image,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1630862543415,_widget_1630862543415,BD状态,combo,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1747123933309,_widget_1747123933309,客户BD日期,datetime,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1751366502797,_widget_1751366502797,意向程度,combo,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1747661411161,_widget_1747661411161,Test开始日期,datetime,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1747661411178,_widget_1747661411178,Test天数,number,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1747664949166,_widget_1747664949166,Test账号状态,combo,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_0201002000003,_widget_0201002000003,BD负责人,user,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_0201002000004,_widget_0201002000004,BD协作人,usergroup,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_0201002000006,_widget_0201002000006,销售归属部门,dept,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1747133970117,_widget_1747133970117,BD阻塞原因,combo,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1747669642443,_widget_1747669642443,BD阻塞原因分类,combo,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1747133970121,_widget_1747133970121,BD阻塞原因详细描述,textarea,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1749290572780,_widget_1749290572780,签约&上线负责人,user,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1747123933310,_widget_1747123933310,客户签约日期,datetime,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1747123933311,_widget_1747123933311,客户付款日期,datetime,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1749632087678,_widget_1749632087678,付款金额(泰铢),number,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1749632087641,_widget_1749632087641,付款截图,image,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1749632087639,_widget_1749632087639,上传发票附件,upload,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1740460160201,_widget_1740460160201,上线状态,combo,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1747123933312,_widget_1747123933312,上线日期,datetime,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1747133970122,_widget_1747133970122,上线失败原因,combo,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1631071964934,_widget_1631071964934,上线失败原因描述,textarea,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1749108058561,_widget_1749108058561,门店系统使用情况说明,textarea,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1747123507416,_widget_1747123507416,开户门店ID,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013289,_widget_1737092013289,公司名称,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013291,_widget_1737092013291,主店简称,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013292,_widget_1737092013292,营业执照号,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013293,_widget_1737092013293,营业执照名称,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013300,_widget_1737092013300,门店logo,image,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013301,_widget_1737092013301,pc首页左上角logo,image,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013302,_widget_1737092013302,pc首页左上角logo缩略图,image,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013321,_widget_1737092013321,门头照片,image,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737097231480,_widget_1737097231480,府,combo,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737097231482,_widget_1737097231482,县,combo,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013299,_widget_1737092013299,地址（省市区）,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737097782393,_widget_1737097782393,详情地址,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013314,_widget_1737092013314,营业开始时间,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013313,_widget_1737092013313,营业结束时间,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013312,_widget_1737092013312,经度,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013311,_widget_1737092013311,纬度,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013310,_widget_1737092013310,负责人名字,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013308,_widget_1737092013308,负责人手机号,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013309,_widget_1737092013309,服务接待固话,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013315,_widget_1737092013315,服务接待名称,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013316,_widget_1737092013316,服务接待手机号,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013320,_widget_1737092013320,账号数上限,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013318,_widget_1737092013318,税号,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013317,_widget_1737092013317,分支编号,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013319,_widget_1737092013319,嘉实多内部门店编码,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013339,_widget_1737092013339,运营顾问(上线负责人),user,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013340,_widget_1737092013340,运营专家,user,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013341,_widget_1737092013341,区域经理,user,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1750125550901,_widget_1750125550901,状态,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1663742427909,_widget_1663742427909,客户查重：客户表内该客户数量,number,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1709110880998,_widget_1709110880998,结算期限,combo,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1709110881001,_widget_1709110881001,信用额度/元,number,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1709110881002,_widget_1709110881002,发票抬头,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1709110881003,_widget_1709110881003,发票税号,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1709110881004,_widget_1709110881004,税种,combo,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1709110881007,_widget_1709110881007,增值税税率 %,number,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1709110881008,_widget_1709110881008,开户电话,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1709110881009,_widget_1709110881009,开户银行,combo,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1709110881016,_widget_1709110881016,银行账户,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1742174728275,_widget_1742174728275,指标归属日期,datetime,,673457d6837e60a418e0e56b,67d636bb6212b7619a7a4231
_widget_1742091963874,_widget_1742091963874,公司ID,text,,673457d6837e60a418e0e56b,67d636bb6212b7619a7a4231
_widget_1742091963875,_widget_1742091963875,公司名称,text,,673457d6837e60a418e0e56b,67d636bb6212b7619a7a4231
_widget_1742091963876,_widget_1742091963876,门店ID,text,,673457d6837e60a418e0e56b,67d636bb6212b7619a7a4231
_widget_1742091963877,_widget_1742091963877,门店名称,text,,673457d6837e60a418e0e56b,67d636bb6212b7619a7a4231
_widget_1742091963878,_widget_1742091963878,门店简称,text,,673457d6837e60a418e0e56b,67d636bb6212b7619a7a4231
_widget_1742091963879,_widget_1742091963879,门店创建时间,datetime,,673457d6837e60a418e0e56b,67d636bb6212b7619a7a4231
_widget_1742091963880,_widget_1742091963880,指标类型,combo,,673457d6837e60a418e0e56b,67d636bb6212b7619a7a4231
_widget_1742091963881,_widget_1742091963881,指标子类型,combo,,673457d6837e60a418e0e56b,67d636bb6212b7619a7a4231
_widget_1742091963882,_widget_1742091963882,指标值,number,,673457d6837e60a418e0e56b,67d636bb6212b7619a7a4231
_widget_0201002000002,_widget_0201002000002,客户名称,company,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_0201002000001,_widget_0201002000001,客户编码,sn,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1630862543415,_widget_1630862543415,客户状态,combo,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1631071964761,_widget_1631071964761,客户来源,text,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1630862543434,_widget_1630862543434,客户级别,combo,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_0201002000005,_widget_0201002000005,所属公海,account_pool,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1663742427957,_widget_1663742427957,客户查重,text,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1630862543637,_widget_1630862543637,所属行业,combo,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1646826421878,_widget_1646826421878,客户邮箱,text,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1631071964919,_widget_1631071964919,客户地址,address,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1631071964934,_widget_1631071964934,客户详情,textarea,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_0201002000003,_widget_0201002000003,销售负责人,user,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_0201002000006,_widget_0201002000006,销售归属部门,dept,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_0201002000004,_widget_0201002000004,协作人,usergroup,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1663742427909,_widget_1663742427909,客户查重：客户表内该客户数量,number,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1709110880998,_widget_1709110880998,结算期限,combo,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1709110881001,_widget_1709110881001,信用额度/元,number,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1709110881002,_widget_1709110881002,发票抬头,text,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1709110881003,_widget_1709110881003,发票税号,text,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1709110881004,_widget_1709110881004,税种,combo,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1709110881007,_widget_1709110881007,增值税税率 %,number,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1709110881008,_widget_1709110881008,开户电话,text,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1709110881009,_widget_1709110881009,开户银行,combo,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1709110881016,_widget_1709110881016,银行账户,text,,675a7f2a54c95e84fb66393e,020100200000000000000001
1 name widgetName label type items app_id entry_id
2 _widget_1690785229260 _widget_1690785229260 怎么称呼您 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
3 _widget_1690785229261 _widget_1690785229261 您门店或公司名称 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
4 _widget_1693382214358 _widget_1693382214358 您的联系方式 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
5 _widget_1690785326597 _widget_1690785326597 地址 address 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
6 _widget_1690785229266 _widget_1690785229266 备注 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
7 _widget_1690785229284 _widget_1690785229284 客户概况 textarea 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
8 _widget_1690787826014 _widget_1690787826014 门头照片（可上传多张） image 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
9 _widget_1690785229278 _widget_1690785229278 意向书来源 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
10 _widget_1741837239117 _widget_1741837239117 业务类型 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
11 _widget_1693381022904 _widget_1693381022904 客户渠道 combo 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
12 _widget_1715146829031 _widget_1715146829031 轻连锁类型 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
13 _widget_1690785229280 _widget_1690785229280 小六 user 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
14 _widget_1694154771486 _widget_1694154771486 技术专家 user 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
15 _widget_1690785229281 _widget_1690785229281 战区经理 user 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
16 _widget_1718855270618 _widget_1718855270618 该养车门店是否已退出？ radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
17 _widget_1718855270620 _widget_1718855270620 退出情况说明 textarea 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
18 _widget_1718855270621 _widget_1718855270621 该养车门店是否有F6系统需求？ radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
19 _widget_1690785229282 _widget_1690785229282 意向阶段 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
20 _widget_1693551051341 _widget_1693551051341 客户门店数 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
21 _widget_1690785229283 _widget_1690785229283 意向版本 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
22 _widget_1693381022909 _widget_1693381022909 客户沟通记录 subform [{'name': '_widget_1693381022911', 'widgetName': '_widget_1693381022911', 'label': '跟进日期', 'type': 'datetime'}, {'name': '_widget_1693381022912', 'widgetName': '_widget_1693381022912', 'label': '沟通方式', 'type': 'combo'}, {'name': '_widget_1693381022914', 'widgetName': '_widget_1693381022914', 'label': '沟通概要', 'type': 'textarea'}] 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
23 _widget_1693381022908 _widget_1693381022908 下次跟进日期 datetime 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
24 _widget_1696902504775 _widget_1696902504775 理论下次跟进日期 datetime 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
25 _widget_1694398435902 _widget_1694398435902 最近一次沟通日期 datetime 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
26 _widget_1693381022915 _widget_1693381022915 客户在用系统名称 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
27 _widget_1693381022916 _widget_1693381022916 预计成交金额（单位：元） number 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
28 _widget_1693381022917 _widget_1693381022917 预计成交日期 datetime 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
29 _widget_1699321775702 _widget_1699321775702 实际成交日期 datetime 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
30 _widget_1693381022918 _widget_1693381022918 下单手机号 phone 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
31 _widget_1693381022919 _widget_1693381022919 放弃原因分类 combo 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
32 _widget_1693381022921 _widget_1693381022921 价格原因 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
33 _widget_1693381022923 _widget_1693381022923 产品原因 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
34 _widget_1693381022925 _widget_1693381022925 门店原因 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
35 _widget_1693381022930 _widget_1693381022930 加盟外部连锁 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
36 _widget_1693381022927 _widget_1693381022927 内部业务影响（包含接车宝会员宝安装服务） radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
37 _widget_1724313867483 _widget_1724313867483 输单原因分类 combo 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
38 _widget_1723603567435 _widget_1723603567435 竞品名称 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
39 _widget_1693381022929 _widget_1693381022929 输单/放弃说明 textarea 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
40 _widget_1708935626093 _widget_1708935626093 线索沟通情况 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
41 _widget_1709019633297 _widget_1709019633297 客户业务需求 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
42 _widget_1708935626085 _widget_1708935626085 客户手机号是否是微信号？ radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
43 _widget_1708935626087 _widget_1708935626087 企微是否已加好友？ radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
44 _widget_1708935626089 _widget_1708935626089 BOSS系统里是否有该客户信息 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
45 _widget_1709027488072 _widget_1709027488072 客户BOSS业务信息 checkboxgroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
46 _widget_1708935626095 _widget_1708935626095 联系人身份 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
47 _widget_1709100220536 _widget_1709100220536 门店业务类型 combo 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
48 _widget_1708935626104 _widget_1708935626104 客户门店工位数 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
49 _widget_1708935626100 _widget_1708935626100 客户是否有需求 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
50 _widget_1708935626102 _widget_1708935626102 客户主要需求功能模块（可多选） checkboxgroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
51 _widget_1708935626107 _widget_1708935626107 客户原系统 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
52 _widget_1708935626091 _widget_1708935626091 客户预算 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
53 _widget_1708935626098 _widget_1708935626098 预计使用时间 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
54 _widget_1709186927667 _widget_1709186927667 门头照片等 image 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
55 _widget_1709100220453 _widget_1709100220453 SDR联系记录 subform [{'name': '_widget_1709100220457', 'widgetName': '_widget_1709100220457', 'label': '日期时间', 'type': 'datetime'}, {'name': '_widget_1709100220455', 'widgetName': '_widget_1709100220455', 'label': '联系情况', 'type': 'text'}] 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
56 _widget_1708935626292 _widget_1708935626292 SDR判断客户是否需要进一步跟进 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
57 _widget_1710292803370 _widget_1710292803370 SDR建议线索跟进时间 combo 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
58 _widget_1710037836605 _widget_1710037836605 线索放弃说明 textarea 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
59 _widget_1709543713740 _widget_1709543713740 SDR放弃意见 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
60 _widget_1725501916821 _widget_1725501916821 提交时间 datetime 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
61 _widget_1725507662927 _widget_1725507662927 提交人 user 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
62 _widget_1690785229279 _widget_1690785229279 城市 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
63 _widget_1692070536228 _widget_1692070536228 区 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
64 _widget_1697423018006 _widget_1697423018006 战区 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
65 _widget_1694076921201 _widget_1694076921201 线上线下 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
66 _widget_1709868059118 _widget_1709868059118 线索跟进角色 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
67 _widget_1709781645383 _widget_1709781645383 客户跟进角色 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
68 _widget_1725875301461 _widget_1725875301461 技术支持提交人 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
69 _widget_1725933630175 _widget_1725933630175 是否有效线索 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
70 _widget_1690785229262 _widget_1690785229262 您的联系方式 phone 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
71 _widget_1723431564839 _widget_1723431564839 线索状态 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
72 _widget_0201002000002 _widget_0201002000002 经销商名称 company 673d8427549d00c3d753c530 020100200000000000000001
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76 _widget_1732095401223 _widget_1732095401223 营业执照名称 text 673d8427549d00c3d753c530 020100200000000000000001
77 _widget_1732153235945 _widget_1732153235945 详细地址 address 673d8427549d00c3d753c530 020100200000000000000001
78 _widget_1732095401224 _widget_1732095401224 负责人姓名 text 673d8427549d00c3d753c530 020100200000000000000001
79 _widget_1732095401225 _widget_1732095401225 负责人手机号 text 673d8427549d00c3d753c530 020100200000000000000001
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81 _widget_1742200662775 _widget_1742200662775 购买年限 combo 673d8427549d00c3d753c530 020100200000000000000001
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83 _widget_1732095401227 _widget_1732095401227 经销商可购买的群数量 text 673d8427549d00c3d753c530 020100200000000000000001
84 _widget_0201002000003 _widget_0201002000003 销售负责人 user 673d8427549d00c3d753c530 020100200000000000000001
85 _widget_1732153235954 _widget_1732153235954 运营顾问 user 673d8427549d00c3d753c530 020100200000000000000001
86 _widget_1732153235955 _widget_1732153235955 运营专家 user 673d8427549d00c3d753c530 020100200000000000000001
87 _widget_1732153235956 _widget_1732153235956 区域经理 user 673d8427549d00c3d753c530 020100200000000000000001
88 _widget_1741165766484 _widget_1741165766484 业务 user 673d8427549d00c3d753c530 020100200000000000000001
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90 _widget_1732180937812 _widget_1732180937812 开通状态 text 673d8427549d00c3d753c530 020100200000000000000001
91 _widget_1732180937811 _widget_1732180937811 开通时间 datetime 673d8427549d00c3d753c530 020100200000000000000001
92 _widget_1741160451740 _widget_1741160451740 系统到期时间 datetime 673d8427549d00c3d753c530 020100200000000000000001
93 _widget_1630862543415 _widget_1630862543415 客户状态 combo 673d8427549d00c3d753c530 020100200000000000000001
94 _widget_1630862543434 _widget_1630862543434 客户级别 combo 673d8427549d00c3d753c530 020100200000000000000001
95 _widget_0201002000001 _widget_0201002000001 客户编码 sn 673d8427549d00c3d753c530 020100200000000000000001
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103 _widget_1663742427957 _widget_1663742427957 客户查重 text 673d8427549d00c3d753c530 020100200000000000000001
104 _widget_1663742427909 _widget_1663742427909 客户查重：客户表内该客户数量 number 673d8427549d00c3d753c530 020100200000000000000001
105 _widget_1709110880998 _widget_1709110880998 结算期限 combo 673d8427549d00c3d753c530 020100200000000000000001
106 _widget_1709110881001 _widget_1709110881001 信用额度/元 number 673d8427549d00c3d753c530 020100200000000000000001
107 _widget_1709110881002 _widget_1709110881002 发票抬头 text 673d8427549d00c3d753c530 020100200000000000000001
108 _widget_1709110881003 _widget_1709110881003 发票税号 text 673d8427549d00c3d753c530 020100200000000000000001
109 _widget_1709110881004 _widget_1709110881004 税种 combo 673d8427549d00c3d753c530 020100200000000000000001
110 _widget_1709110881007 _widget_1709110881007 增值税税率 % number 673d8427549d00c3d753c530 020100200000000000000001
111 _widget_1709110881008 _widget_1709110881008 开户电话 text 673d8427549d00c3d753c530 020100200000000000000001
112 _widget_1709110881009 _widget_1709110881009 开户银行 combo 673d8427549d00c3d753c530 020100200000000000000001
113 _widget_1709110881016 _widget_1709110881016 银行账户 text 673d8427549d00c3d753c530 020100200000000000000001
114 _widget_1734062123070 _widget_1734062123070 门店名称 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
115 _widget_1734062123068 _widget_1734062123068 公司名称 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
116 _widget_1734062123071 _widget_1734062123071 门店编码 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
117 _widget_1734062123072 _widget_1734062123072 公司等级 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
118 _widget_1734062123073 _widget_1734062123073 门店类型 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
119 _widget_1734062123085 _widget_1734062123085 是否主店 number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
120 _widget_1734062123067 _widget_1734062123067 公司id text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
121 _widget_1734062123069 _widget_1734062123069 门店id text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
122 _widget_1734062123169 _widget_1734062123169 经营模式 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
123 _widget_1734062123170 _widget_1734062123170 联系人 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
124 _widget_1734062123172 _widget_1734062123172 手机号码 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
125 _widget_1734062123179 _widget_1734062123179 是否主店 number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
126 _widget_1734062123180 _widget_1734062123180 门店数 number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
127 _widget_1734062123066 _widget_1734062123066 日期 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
128 _widget_1734062123065 _widget_1734062123065 日期批次 number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
129 _widget_1749000071375 _widget_1749000071375 日期（时间字段） datetime 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
130 _widget_1734062123192 _widget_1734062123192 是否加店 number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
131 _widget_1734062123194 _widget_1734062123194 门店规模 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
132 _widget_1734062123196 _widget_1734062123196 经营范围 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
133 _widget_1734062123197 _widget_1734062123197 维修厂类型 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
134 _widget_1734062123199 _widget_1734062123199 工位数 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
135 _widget_1734062123201 _widget_1734062123201 门店阶段 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
136 _widget_1734062123203 _widget_1734062123203 门店分层 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
137 _widget_1742890765211 _widget_1742890765211 门头照片 image 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
138 _widget_1734062123090 _widget_1734062123090 省 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
139 _widget_1734062123092 _widget_1734062123092 市 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
140 _widget_1734062123094 _widget_1734062123094 区 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
141 _widget_1734062123095 _widget_1734062123095 大区 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
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143 _widget_1734062123099 _widget_1734062123099 前置仓名称 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
144 _widget_1734062123102 _widget_1734062123102 区域经理 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
145 _widget_1734062123103 _widget_1734062123103 续约顾问 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
146 _widget_1734062123105 _widget_1734062123105 运营负责人 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
147 _widget_1734062123204 _widget_1734062123204 运营专家 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
148 _widget_1748496855779 _widget_1748496855779 区域经理（成员字段） user 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
149 _widget_1748496855780 _widget_1748496855780 运营负责人（成员字段） user 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
150 _widget_1748496855778 _widget_1748496855778 续约顾问（成员字段） user 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
151 _widget_1751877712235 _widget_1751877712235 运营专家（成员字段） user 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
152 _widget_1734062123075 _widget_1734062123075 ERP操作模式 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
153 _widget_1734062123076 _widget_1734062123076 公众号 number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
154 _widget_1734062123077 _widget_1734062123077 小程序 number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
155 _widget_1734062123078 _widget_1734062123078 微信商城 number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
156 _widget_1734062123079 _widget_1734062123079 洗车摄像头 number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
157 _widget_1734062123106 _widget_1734062123106 有效账户数 number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
158 _widget_1734062123175 _widget_1734062123175 安装服务 number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
159 _widget_1734062123184 _widget_1734062123184 SaaS版本 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
160 _widget_1734062123074 _widget_1734062123074 客户状态 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
161 _widget_1734062123081 _widget_1734062123081 开户日 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
162 _widget_1734062123082 _widget_1734062123082 应续约日 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
163 _widget_1734062123083 _widget_1734062123083 使用天数 number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
164 _widget_1734062123084 _widget_1734062123084 使用年数 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
165 _widget_1734062123176 _widget_1734062123176 上线日期 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
166 _widget_1734062123177 _widget_1734062123177 过期日 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
167 _widget_1734062123178 _widget_1734062123178 实际续约日 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
168 _widget_1749000071377 _widget_1749000071377 开户日（日期字段） datetime 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
169 _widget_1749000071382 _widget_1749000071382 应续约日（日期字段） datetime 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
170 _widget_1749000071384 _widget_1749000071384 上线日期（日期字段） datetime 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
171 _widget_1749000071389 _widget_1749000071389 过期日（日期字段） datetime 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
172 _widget_1749000071391 _widget_1749000071391 实际续约日（日期字段） datetime 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
173 _widget_1734062123111 _widget_1734062123111 G状态 number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
174 _widget_1734062123115 _widget_1734062123115 活跃状态 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
175 _widget_1734062123117 _widget_1734062123117 近30天业务天数 number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
176 _widget_1734062123119 _widget_1734062123119 近7天业务单量 number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
177 _widget_1734062123120 _widget_1734062123120 近7天业务天数 number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
178 _widget_1734062123122 _widget_1734062123122 UV数 number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
179 _widget_1734062123167 _widget_1734062123167 G变化(月) text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
180 _widget_1734062123173 _widget_1734062123173 G月份 number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
181 _widget_1734062123174 _widget_1734062123174 G转化率 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
182 _widget_1734062123182 _widget_1734062123182 G变化类型 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
183 _widget_1734062123183 _widget_1734062123183 G流失天数 number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
184 _widget_1734062123185 _widget_1734062123185 M-1(G) number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
185 _widget_1734062123186 _widget_1734062123186 M-2(G) number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
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322 _widget_1748512176640 _widget_1748512176640 异常跟进情况描述 textarea 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
323 _widget_1748512176641 _widget_1748512176641 异常变化原因 radiogroup 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
324 _widget_1748512176643 _widget_1748512176643 正常使用 radiogroup 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
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329 _widget_1748512176655 _widget_1748512176655 跟进状态 radiogroup 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
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338 _widget_1748241895851 _widget_1748241895851 saas客户类型 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
339 _widget_1748241895852 _widget_1748241895852 门店阶段 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
340 _widget_1748247754304 _widget_1748247754304 关联数据 lookup 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
341 _widget_1751250294777 _widget_1751250294777 姓名1 text 6694d3c4fcb69ca9a111a6c4 6861f5772b0d3575e14eba4a
342 _widget_1751505196330 _widget_1751505196330 图片 image 6694d3c4fcb69ca9a111a6c4 6861f5772b0d3575e14eba4a
343 _widget_1751507507755 _widget_1751507507755 定位 location 6694d3c4fcb69ca9a111a6c4 6861f5772b0d3575e14eba4a
344 _widget_1739951204545 _widget_1739951204545 表单类型 combo 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
345 _widget_1739252804406 _widget_1739252804406 日期 datetime 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
346 _widget_1739258942667 _widget_1739258942667 账号 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
347 _widget_1739252804419 _widget_1739252804419 日分区 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
348 _widget_1739252804397 _widget_1739252804397 产品名称 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
349 _widget_1739252804407 _widget_1739252804407 联系手机号 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
350 _widget_1739252804409 _widget_1739252804409 使用时长 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
351 _widget_1739252804396 _widget_1739252804396 开户日 datetime 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
352 _widget_1739252804408 _widget_1739252804408 到期日 datetime 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
353 _widget_1739252804410 _widget_1739252804410 续约日 datetime 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
354 _widget_1739252804400 _widget_1739252804400 客户状态 combo 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
355 _widget_1739252804413 _widget_1739252804413 近一周开单量 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
356 _widget_1739252804414 _widget_1739252804414 近一周是否活跃 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
357 _widget_1739252804415 _widget_1739252804415 G状态：近30天开单大于等于10天 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
358 _widget_1739252804416 _widget_1739252804416 当月开单天数 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
359 _widget_1739252804417 _widget_1739252804417 近30天开单天数 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
360 _widget_1739252804418 _widget_1739252804418 当月G天数 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
361 _widget_1740036367181 _widget_1740036367181 派发日期 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
362 _widget_1740043340255 _widget_1740043340255 跟进人 user 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
363 _widget_1741252143304 _widget_1741252143304 是否联系上·新签 combo 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
364 _widget_1741252143306 _widget_1741252143306 是否联系上·异常 combo 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
365 _widget_1741252143308 _widget_1741252143308 是否联系上·续约商机 combo 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
366 _widget_1741252143310 _widget_1741252143310 是否联系上·过期召回 combo 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
367 _widget_1741256466947 _widget_1741256466947 未接通原因备注 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
368 _widget_1740721384110 _widget_1740721384110 省市区 address 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
369 _widget_1741312871468 _widget_1741312871468 省市区·续约 address 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
370 _widget_1740721384111 _widget_1740721384111 门店名称 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
371 _widget_1741312871469 _widget_1741312871469 门店名称·续约 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
372 _widget_1740721384112 _widget_1740721384112 负责人姓名 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
373 _widget_1741312871470 _widget_1741312871470 负责人姓名·续约 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
374 _widget_1740721384122 _widget_1740721384122 回访人·新签 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
375 _widget_1740721384117 _widget_1740721384117 未开单原因·新签 textarea 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
376 _widget_1740721384125 _widget_1740721384125 是否愿意继续使用·新签 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
377 _widget_1740721384127 _widget_1740721384127 回访人·异常 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
378 _widget_1740721384128 _widget_1740721384128 未开单原因·异常 textarea 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
379 _widget_1740721384129 _widget_1740721384129 是否愿意继续使用·异常 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
380 _widget_1740721384131 _widget_1740721384131 回访人·续约商机 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
381 _widget_1740721384132 _widget_1740721384132 是否有转化SaaS意愿·续约商机 combo 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
382 _widget_1740721384133 _widget_1740721384133 系统使用情况·续约商机 textarea 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
383 _widget_1749088869175 _widget_1749088869175 SaaS转化结果·续约商机 radiogroup 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
384 _widget_1749088869177 _widget_1749088869177 转化SaaS订单号·续约商机 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
385 _widget_1749088869190 _widget_1749088869190 其他转化结果·续约商机 textarea 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
386 _widget_1740721384135 _widget_1740721384135 回访人·过期召回 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
387 _widget_1740721384136 _widget_1740721384136 未续约单原因·过期召回 textarea 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
388 _widget_1740721384137 _widget_1740721384137 是否有续约意愿·过期召回 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
389 _widget_1749090854370 _widget_1749090854370 沟通跟进结果·过期召回 radiogroup 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
390 _widget_1749090854372 _widget_1749090854372 转化SaaS订单号·过期召回 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
391 _widget_1749090854373 _widget_1749090854373 接车宝续约订单号·过期召回 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
392 _widget_1749090854374 _widget_1749090854374 其他召回情况说明·过期召回 textarea 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
393 _widget_1751356539629 _widget_1751356539629 完成日期时间 datetime 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
394 _widget_1751271771674 _widget_1751271771674 是否完成 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
395 _widget_1751356033346 _widget_1751356033346 流水号 sn 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
396 _widget_1740042824214 _widget_1740042824214 客服人员 user 6717470a0b3975ef583c6df1 67b6f2462f9ac03b783d409a
397 _widget_1740117343937 _widget_1740117343937 开关 combo 6717470a0b3975ef583c6df1 67b6f2462f9ac03b783d409a
398 _widget_1740042824216 _widget_1740042824216 下次开始位置 text 6717470a0b3975ef583c6df1 67b6f2462f9ac03b783d409a
399 _widget_1740723898388 _widget_1740723898388 日期 datetime 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
400 _widget_1740723898389 _widget_1740723898389 产品名称 text 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
401 _widget_1740723898390 _widget_1740723898390 账号 text 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
402 _widget_1740723898391 _widget_1740723898391 联系手机号 number 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
403 _widget_1740723898392 _widget_1740723898392 开户日 datetime 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
404 _widget_1740723898393 _widget_1740723898393 使用时长 number 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
405 _widget_1740723898394 _widget_1740723898394 续约日 text 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
406 _widget_1740723898395 _widget_1740723898395 到期日 datetime 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
407 _widget_1740723898396 _widget_1740723898396 客户状态 text 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
408 _widget_1740723898397 _widget_1740723898397 近一周开单量 number 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
409 _widget_1740723898398 _widget_1740723898398 近一周是否活跃 number 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
410 _widget_1740723898399 _widget_1740723898399 G状态：近30天开单大于等于10天 number 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
411 _widget_1740723898400 _widget_1740723898400 当月开单天数 number 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
412 _widget_1740723898401 _widget_1740723898401 近30天开单天数 number 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
413 _widget_1740723898402 _widget_1740723898402 当月G天数 number 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
414 _widget_1740723898403 _widget_1740723898403 日分区 number 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
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416 _widget_1740723898405 _widget_1740723898405 派发日期 datetime 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
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424 _widget_1746675108119 _widget_1746675108119 原系统名称 combo 673457d6837e60a418e0e56b 020100200000000000000001
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453 _widget_1747133970122 _widget_1747133970122 上线失败原因 combo 673457d6837e60a418e0e56b 020100200000000000000001
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482 _widget_1737092013339 _widget_1737092013339 运营顾问(上线负责人) user 673457d6837e60a418e0e56b 020100200000000000000001
483 _widget_1737092013340 _widget_1737092013340 运营专家 user 673457d6837e60a418e0e56b 020100200000000000000001
484 _widget_1737092013341 _widget_1737092013341 区域经理 user 673457d6837e60a418e0e56b 020100200000000000000001
485 _widget_1750125550901 _widget_1750125550901 状态 text 673457d6837e60a418e0e56b 020100200000000000000001
486 _widget_1663742427909 _widget_1663742427909 客户查重：客户表内该客户数量 number 673457d6837e60a418e0e56b 020100200000000000000001
487 _widget_1709110880998 _widget_1709110880998 结算期限 combo 673457d6837e60a418e0e56b 020100200000000000000001
488 _widget_1709110881001 _widget_1709110881001 信用额度/元 number 673457d6837e60a418e0e56b 020100200000000000000001
489 _widget_1709110881002 _widget_1709110881002 发票抬头 text 673457d6837e60a418e0e56b 020100200000000000000001
490 _widget_1709110881003 _widget_1709110881003 发票税号 text 673457d6837e60a418e0e56b 020100200000000000000001
491 _widget_1709110881004 _widget_1709110881004 税种 combo 673457d6837e60a418e0e56b 020100200000000000000001
492 _widget_1709110881007 _widget_1709110881007 增值税税率 % number 673457d6837e60a418e0e56b 020100200000000000000001
493 _widget_1709110881008 _widget_1709110881008 开户电话 text 673457d6837e60a418e0e56b 020100200000000000000001
494 _widget_1709110881009 _widget_1709110881009 开户银行 combo 673457d6837e60a418e0e56b 020100200000000000000001
495 _widget_1709110881016 _widget_1709110881016 银行账户 text 673457d6837e60a418e0e56b 020100200000000000000001
496 _widget_1742174728275 _widget_1742174728275 指标归属日期 datetime 673457d6837e60a418e0e56b 67d636bb6212b7619a7a4231
497 _widget_1742091963874 _widget_1742091963874 公司ID text 673457d6837e60a418e0e56b 67d636bb6212b7619a7a4231
498 _widget_1742091963875 _widget_1742091963875 公司名称 text 673457d6837e60a418e0e56b 67d636bb6212b7619a7a4231
499 _widget_1742091963876 _widget_1742091963876 门店ID text 673457d6837e60a418e0e56b 67d636bb6212b7619a7a4231
500 _widget_1742091963877 _widget_1742091963877 门店名称 text 673457d6837e60a418e0e56b 67d636bb6212b7619a7a4231
501 _widget_1742091963878 _widget_1742091963878 门店简称 text 673457d6837e60a418e0e56b 67d636bb6212b7619a7a4231
502 _widget_1742091963879 _widget_1742091963879 门店创建时间 datetime 673457d6837e60a418e0e56b 67d636bb6212b7619a7a4231
503 _widget_1742091963880 _widget_1742091963880 指标类型 combo 673457d6837e60a418e0e56b 67d636bb6212b7619a7a4231
504 _widget_1742091963881 _widget_1742091963881 指标子类型 combo 673457d6837e60a418e0e56b 67d636bb6212b7619a7a4231
505 _widget_1742091963882 _widget_1742091963882 指标值 number 673457d6837e60a418e0e56b 67d636bb6212b7619a7a4231
506 _widget_0201002000002 _widget_0201002000002 客户名称 company 675a7f2a54c95e84fb66393e 020100200000000000000001
507 _widget_0201002000001 _widget_0201002000001 客户编码 sn 675a7f2a54c95e84fb66393e 020100200000000000000001
508 _widget_1630862543415 _widget_1630862543415 客户状态 combo 675a7f2a54c95e84fb66393e 020100200000000000000001
509 _widget_1631071964761 _widget_1631071964761 客户来源 text 675a7f2a54c95e84fb66393e 020100200000000000000001
510 _widget_1630862543434 _widget_1630862543434 客户级别 combo 675a7f2a54c95e84fb66393e 020100200000000000000001
511 _widget_0201002000005 _widget_0201002000005 所属公海 account_pool 675a7f2a54c95e84fb66393e 020100200000000000000001
512 _widget_1663742427957 _widget_1663742427957 客户查重 text 675a7f2a54c95e84fb66393e 020100200000000000000001
513 _widget_1630862543637 _widget_1630862543637 所属行业 combo 675a7f2a54c95e84fb66393e 020100200000000000000001
514 _widget_1646826421878 _widget_1646826421878 客户邮箱 text 675a7f2a54c95e84fb66393e 020100200000000000000001
515 _widget_1631071964919 _widget_1631071964919 客户地址 address 675a7f2a54c95e84fb66393e 020100200000000000000001
516 _widget_1631071964934 _widget_1631071964934 客户详情 textarea 675a7f2a54c95e84fb66393e 020100200000000000000001
517 _widget_0201002000003 _widget_0201002000003 销售负责人 user 675a7f2a54c95e84fb66393e 020100200000000000000001
518 _widget_0201002000006 _widget_0201002000006 销售归属部门 dept 675a7f2a54c95e84fb66393e 020100200000000000000001
519 _widget_0201002000004 _widget_0201002000004 协作人 usergroup 675a7f2a54c95e84fb66393e 020100200000000000000001
520 _widget_1663742427909 _widget_1663742427909 客户查重：客户表内该客户数量 number 675a7f2a54c95e84fb66393e 020100200000000000000001
521 _widget_1709110880998 _widget_1709110880998 结算期限 combo 675a7f2a54c95e84fb66393e 020100200000000000000001
522 _widget_1709110881001 _widget_1709110881001 信用额度/元 number 675a7f2a54c95e84fb66393e 020100200000000000000001
523 _widget_1709110881002 _widget_1709110881002 发票抬头 text 675a7f2a54c95e84fb66393e 020100200000000000000001
524 _widget_1709110881003 _widget_1709110881003 发票税号 text 675a7f2a54c95e84fb66393e 020100200000000000000001
525 _widget_1709110881004 _widget_1709110881004 税种 combo 675a7f2a54c95e84fb66393e 020100200000000000000001
526 _widget_1709110881007 _widget_1709110881007 增值税税率 % number 675a7f2a54c95e84fb66393e 020100200000000000000001
527 _widget_1709110881008 _widget_1709110881008 开户电话 text 675a7f2a54c95e84fb66393e 020100200000000000000001
528 _widget_1709110881009 _widget_1709110881009 开户银行 combo 675a7f2a54c95e84fb66393e 020100200000000000000001
529 _widget_1709110881016 _widget_1709110881016 银行账户 text 675a7f2a54c95e84fb66393e 020100200000000000000001
back_ground_module/output/数据快照存储/last_widget_data.csv
+12691
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back_ground_module/output/数据快照存储/snapshot_2025-07-03.csv
+530
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@@ -0,0 +1,530 @@
name,widgetName,label,type,app_id,entry_id,items
_widget_1690785229260,_widget_1690785229260,怎么称呼您,text,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1690785229261,_widget_1690785229261,您门店或公司名称,text,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1693382214358,_widget_1693382214358,您的联系方式,text,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1690785326597,_widget_1690785326597,地址,address,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1690785229266,_widget_1690785229266,备注,text,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1690785229284,_widget_1690785229284,客户概况,textarea,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1690787826014,_widget_1690787826014,门头照片（可上传多张）,image,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1690785229278,_widget_1690785229278,意向书来源,text,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1741837239117,_widget_1741837239117,业务类型,text,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1693381022904,_widget_1693381022904,客户渠道,combo,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1715146829031,_widget_1715146829031,轻连锁类型,text,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1690785229280,_widget_1690785229280,小六,user,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1694154771486,_widget_1694154771486,技术专家,user,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1690785229281,_widget_1690785229281,战区经理,user,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1718855270618,_widget_1718855270618,该养车门店是否已退出？,radiogroup,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1718855270620,_widget_1718855270620,退出情况说明,textarea,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1718855270621,_widget_1718855270621,该养车门店是否有F6系统需求？,radiogroup,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1690785229282,_widget_1690785229282,意向阶段,radiogroup,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1693551051341,_widget_1693551051341,客户门店数,radiogroup,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1690785229283,_widget_1690785229283,意向版本,radiogroup,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1693381022909,_widget_1693381022909,客户沟通记录,subform,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,"[{'name': '_widget_1693381022911', 'widgetName': '_widget_1693381022911', 'label': '跟进日期', 'type': 'datetime'}, {'name': '_widget_1693381022912', 'widgetName': '_widget_1693381022912', 'label': '沟通方式', 'type': 'combo'}, {'name': '_widget_1693381022914', 'widgetName': '_widget_1693381022914', 'label': '沟通概要', 'type': 'textarea'}]"
_widget_1693381022908,_widget_1693381022908,下次跟进日期,datetime,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1696902504775,_widget_1696902504775,理论下次跟进日期,datetime,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1694398435902,_widget_1694398435902,最近一次沟通日期,datetime,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1693381022915,_widget_1693381022915,客户在用系统名称,text,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1693381022916,_widget_1693381022916,预计成交金额（单位：元）,number,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1693381022917,_widget_1693381022917,预计成交日期,datetime,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1699321775702,_widget_1699321775702,实际成交日期,datetime,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1693381022918,_widget_1693381022918,下单手机号,phone,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1693381022919,_widget_1693381022919,放弃原因分类,combo,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1693381022921,_widget_1693381022921,价格原因,radiogroup,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1693381022923,_widget_1693381022923,产品原因,radiogroup,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1693381022925,_widget_1693381022925,门店原因,radiogroup,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1693381022930,_widget_1693381022930,加盟外部连锁,radiogroup,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1693381022927,_widget_1693381022927,内部业务影响（包含接车宝会员宝安装服务）,radiogroup,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1724313867483,_widget_1724313867483,输单原因分类,combo,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1723603567435,_widget_1723603567435,竞品名称,radiogroup,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1693381022929,_widget_1693381022929,输单/放弃说明,textarea,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1708935626093,_widget_1708935626093,线索沟通情况,radiogroup,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1709019633297,_widget_1709019633297,客户业务需求,radiogroup,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1708935626085,_widget_1708935626085,客户手机号是否是微信号？,radiogroup,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1708935626087,_widget_1708935626087,企微是否已加好友？,radiogroup,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1708935626089,_widget_1708935626089,BOSS系统里是否有该客户信息,radiogroup,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1709027488072,_widget_1709027488072,客户BOSS业务信息,checkboxgroup,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1708935626095,_widget_1708935626095,联系人身份,radiogroup,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1709100220536,_widget_1709100220536,门店业务类型,combo,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1708935626104,_widget_1708935626104,客户门店工位数,radiogroup,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1708935626100,_widget_1708935626100,客户是否有需求,radiogroup,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1708935626102,_widget_1708935626102,客户主要需求功能模块（可多选）,checkboxgroup,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1708935626107,_widget_1708935626107,客户原系统,radiogroup,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1708935626091,_widget_1708935626091,客户预算,radiogroup,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1708935626098,_widget_1708935626098,预计使用时间,radiogroup,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1709186927667,_widget_1709186927667,门头照片等,image,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1709100220453,_widget_1709100220453,SDR联系记录,subform,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,"[{'name': '_widget_1709100220457', 'widgetName': '_widget_1709100220457', 'label': '日期时间', 'type': 'datetime'}, {'name': '_widget_1709100220455', 'widgetName': '_widget_1709100220455', 'label': '联系情况', 'type': 'text'}]"
_widget_1708935626292,_widget_1708935626292,SDR判断客户是否需要进一步跟进,radiogroup,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1710292803370,_widget_1710292803370,SDR建议线索跟进时间,combo,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1710037836605,_widget_1710037836605,线索放弃说明,textarea,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1709543713740,_widget_1709543713740,SDR放弃意见,radiogroup,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1725501916821,_widget_1725501916821,提交时间,datetime,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1725507662927,_widget_1725507662927,提交人,user,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1690785229279,_widget_1690785229279,城市,text,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1692070536228,_widget_1692070536228,区,text,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1697423018006,_widget_1697423018006,战区,text,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1694076921201,_widget_1694076921201,线上线下,text,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1709868059118,_widget_1709868059118,线索跟进角色,text,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1709781645383,_widget_1709781645383,客户跟进角色,text,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1725875301461,_widget_1725875301461,技术支持提交人,text,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1725933630175,_widget_1725933630175,是否有效线索,text,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1690785229262,_widget_1690785229262,您的联系方式,phone,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_1723431564839,_widget_1723431564839,线索状态,radiogroup,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd,
_widget_0201002000002,_widget_0201002000002,经销商名称,company,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1732095401220,_widget_1732095401220,经销商简称,text,673d8427549d00c3d753c530,020100200000000000000001,
_widget_0201002000005,_widget_0201002000005,所属公海,account_pool,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1732095401222,_widget_1732095401222,营业执照号,text,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1732095401223,_widget_1732095401223,营业执照名称,text,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1732153235945,_widget_1732153235945,详细地址,address,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1732095401224,_widget_1732095401224,负责人姓名,text,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1732095401225,_widget_1732095401225,负责人手机号,text,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1732095401226,_widget_1732095401226,联系电话,text,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1742200662775,_widget_1742200662775,购买年限,combo,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1742278002584,_widget_1742278002584,购买版本,combo,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1732095401227,_widget_1732095401227,经销商可购买的群数量,text,673d8427549d00c3d753c530,020100200000000000000001,
_widget_0201002000003,_widget_0201002000003,销售负责人,user,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1732153235954,_widget_1732153235954,运营顾问,user,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1732153235955,_widget_1732153235955,运营专家,user,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1732153235956,_widget_1732153235956,区域经理,user,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1741165766484,_widget_1741165766484,业务,user,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1732180937809,_widget_1732180937809,经销商ID,text,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1732180937812,_widget_1732180937812,开通状态,text,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1732180937811,_widget_1732180937811,开通时间,datetime,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1741160451740,_widget_1741160451740,系统到期时间,datetime,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1630862543415,_widget_1630862543415,客户状态,combo,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1630862543434,_widget_1630862543434,客户级别,combo,673d8427549d00c3d753c530,020100200000000000000001,
_widget_0201002000001,_widget_0201002000001,客户编码,sn,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1646826421878,_widget_1646826421878,客户邮箱,text,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1630862543637,_widget_1630862543637,所属行业,combo,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1732178180219,_widget_1732178180219,客户来源表单字段,text,673d8427549d00c3d753c530,020100200000000000000001,
_widget_0201002000006,_widget_0201002000006,销售归属部门,dept,673d8427549d00c3d753c530,020100200000000000000001,
_widget_0201002000004,_widget_0201002000004,协作人,usergroup,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1631071964934,_widget_1631071964934,客户详情,textarea,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1631071964761,_widget_1631071964761,客户来源,text,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1663742427957,_widget_1663742427957,客户查重,text,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1663742427909,_widget_1663742427909,客户查重：客户表内该客户数量,number,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1709110880998,_widget_1709110880998,结算期限,combo,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1709110881001,_widget_1709110881001,信用额度/元,number,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1709110881002,_widget_1709110881002,发票抬头,text,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1709110881003,_widget_1709110881003,发票税号,text,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1709110881004,_widget_1709110881004,税种,combo,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1709110881007,_widget_1709110881007,增值税税率 %,number,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1709110881008,_widget_1709110881008,开户电话,text,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1709110881009,_widget_1709110881009,开户银行,combo,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1709110881016,_widget_1709110881016,银行账户,text,673d8427549d00c3d753c530,020100200000000000000001,
_widget_1734062123070,_widget_1734062123070,门店名称,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123068,_widget_1734062123068,公司名称,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123071,_widget_1734062123071,门店编码,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123072,_widget_1734062123072,公司等级,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123073,_widget_1734062123073,门店类型,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123085,_widget_1734062123085,是否主店,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123067,_widget_1734062123067,公司id,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123069,_widget_1734062123069,门店id,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123169,_widget_1734062123169,经营模式,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123170,_widget_1734062123170,联系人,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123172,_widget_1734062123172,手机号码,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123179,_widget_1734062123179,是否主店,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123180,_widget_1734062123180,门店数,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123066,_widget_1734062123066,日期,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123065,_widget_1734062123065,日期批次,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1749000071375,_widget_1749000071375,日期（时间字段）,datetime,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123192,_widget_1734062123192,是否加店,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123194,_widget_1734062123194,门店规模,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123196,_widget_1734062123196,经营范围,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123197,_widget_1734062123197,维修厂类型,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123199,_widget_1734062123199,工位数,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123201,_widget_1734062123201,门店阶段,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123203,_widget_1734062123203,门店分层,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1742890765211,_widget_1742890765211,门头照片,image,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123090,_widget_1734062123090,省,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123092,_widget_1734062123092,市,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123094,_widget_1734062123094,区,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123095,_widget_1734062123095,大区,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123097,_widget_1734062123097,小区,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123099,_widget_1734062123099,前置仓名称,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123102,_widget_1734062123102,区域经理,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123103,_widget_1734062123103,续约顾问,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123105,_widget_1734062123105,运营负责人,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123204,_widget_1734062123204,运营专家,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1748496855779,_widget_1748496855779,区域经理（成员字段）,user,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1748496855780,_widget_1748496855780,运营负责人（成员字段）,user,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1748496855778,_widget_1748496855778,续约顾问（成员字段）,user,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123075,_widget_1734062123075,ERP操作模式,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123076,_widget_1734062123076,公众号,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123077,_widget_1734062123077,小程序,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123078,_widget_1734062123078,微信商城,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123079,_widget_1734062123079,洗车摄像头,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123106,_widget_1734062123106,有效账户数,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123175,_widget_1734062123175,安装服务,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123184,_widget_1734062123184,SaaS版本,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123074,_widget_1734062123074,客户状态,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123081,_widget_1734062123081,开户日,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123082,_widget_1734062123082,应续约日,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123083,_widget_1734062123083,使用天数,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123084,_widget_1734062123084,使用年数,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123176,_widget_1734062123176,上线日期,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123177,_widget_1734062123177,过期日,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123178,_widget_1734062123178,实际续约日,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1749000071377,_widget_1749000071377,开户日（日期字段）,datetime,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1749000071382,_widget_1749000071382,应续约日（日期字段）,datetime,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1749000071384,_widget_1749000071384,上线日期（日期字段）,datetime,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1749000071389,_widget_1749000071389,过期日（日期字段）,datetime,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1749000071391,_widget_1749000071391,实际续约日（日期字段）,datetime,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123111,_widget_1734062123111,G状态,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123115,_widget_1734062123115,活跃状态,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123117,_widget_1734062123117,近30天业务天数,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123119,_widget_1734062123119,近7天业务单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123120,_widget_1734062123120,近7天业务天数,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123122,_widget_1734062123122,UV数,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123167,_widget_1734062123167,G变化(月),text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123173,_widget_1734062123173,G月份,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123174,_widget_1734062123174,G转化率,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123182,_widget_1734062123182,G变化类型,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123183,_widget_1734062123183,G流失天数,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123185,_widget_1734062123185,M-1(G),number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123186,_widget_1734062123186,M-2(G),number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123187,_widget_1734062123187,M-3(G),number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123188,_widget_1734062123188,M-4(G),number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123189,_widget_1734062123189,M-5(G),number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123190,_widget_1734062123190,M-6(G),number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123191,_widget_1734062123191,G天数,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123202,_widget_1734062123202,本月G天数,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123116,_widget_1734062123116,近30天业务单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123155,_widget_1734062123155,近30天维修单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123156,_widget_1734062123156,近30天洗车单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123157,_widget_1734062123157,近30天维修开单天数,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123158,_widget_1734062123158,近30天洗车开单天数,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123159,_widget_1734062123159,近30天销售单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123160,_widget_1734062123160,近30天销售单开单天数,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123161,_widget_1734062123161,近30天采购单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123162,_widget_1734062123162,近30天采购开单天数,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123163,_widget_1734062123163,近30天卡业务单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123164,_widget_1734062123164,近30天卡业务天数,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123118,_widget_1734062123118,自然月业务天数,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123123,_widget_1734062123123,T_1开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123124,_widget_1734062123124,T_2开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123125,_widget_1734062123125,T_3开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123126,_widget_1734062123126,T_4开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123127,_widget_1734062123127,T_5开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123128,_widget_1734062123128,T_6开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123129,_widget_1734062123129,T_7开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123130,_widget_1734062123130,T_8开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123131,_widget_1734062123131,T_9开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123132,_widget_1734062123132,T_10开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123133,_widget_1734062123133,T_11开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123134,_widget_1734062123134,T_12开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123135,_widget_1734062123135,T_13开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123136,_widget_1734062123136,T_14开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123137,_widget_1734062123137,T_15开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123138,_widget_1734062123138,T_16开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123139,_widget_1734062123139,T_17开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123140,_widget_1734062123140,T_18开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123141,_widget_1734062123141,T_19开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123142,_widget_1734062123142,T_20开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123143,_widget_1734062123143,T_21开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123144,_widget_1734062123144,T_22开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123145,_widget_1734062123145,T_23开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123146,_widget_1734062123146,T_24开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123147,_widget_1734062123147,T_25开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123148,_widget_1734062123148,T_26开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123149,_widget_1734062123149,T_27开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123150,_widget_1734062123150,T_28开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123151,_widget_1734062123151,T_29开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123152,_widget_1734062123152,T_30开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123153,_widget_1734062123153,T_31开单量,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123080,_widget_1734062123080,is_maintenance_service,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123086,_widget_1734062123086,license_code,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123087,_widget_1734062123087,license_name,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123088,_widget_1734062123088,org_crm_id,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123089,_widget_1734062123089,province_id,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123091,_widget_1734062123091,city_id,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123093,_widget_1734062123093,area_id,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123096,_widget_1734062123096,region_short_name,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123098,_widget_1734062123098,carzone_store_id,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123100,_widget_1734062123100,customer_carzone_id,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123101,_widget_1734062123101,salesmen,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123104,_widget_1734062123104,impl_principal,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123107,_widget_1734062123107,active_user_type,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123108,_widget_1734062123108,limit_user_count,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123109,_widget_1734062123109,limit_user_type,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123110,_widget_1734062123110,is_n,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123112,_widget_1734062123112,is_v,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123113,_widget_1734062123113,is_visited,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123114,_widget_1734062123114,is_active,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123121,_widget_1734062123121,pv_count,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123154,_widget_1734062123154,etl_time,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123165,_widget_1734062123165,gd_sales_bill_count_last_30_day,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123166,_widget_1734062123166,gd_sales_bill_day_count_last_30_day,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123168,_widget_1734062123168,saas_package,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123171,_widget_1734062123171,contact_number,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123181,_widget_1734062123181,recent_bill_warning_days,number,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123193,_widget_1734062123193,pt,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123195,_widget_1734062123195,qualification_type_fmt,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123198,_widget_1734062123198,area,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123200,_widget_1734062123200,header_type_fmt,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1734062123205,_widget_1734062123205,tmall_maintain_service_status_desc,text,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1745908548852,_widget_1745908548852,江苏易捷门店归属公司,radiogroup,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4,
_widget_1742795002375,_widget_1742795002375,公司ID,text,675b900991ad2491c69389ca,67e0f0fae622896749ba5087,
_widget_1742795002376,_widget_1742795002376,公众号名称,text,675b900991ad2491c69389ca,67e0f0fae622896749ba5087,
_widget_1742795002377,_widget_1742795002377,小程序模板类型,text,675b900991ad2491c69389ca,67e0f0fae622896749ba5087,
_widget_1742795002378,_widget_1742795002378,是否开通微信商城,number,675b900991ad2491c69389ca,67e0f0fae622896749ba5087,
_widget_1742795002379,_widget_1742795002379,上架商品数,number,675b900991ad2491c69389ca,67e0f0fae622896749ba5087,
_widget_1742795002380,_widget_1742795002380,上架套餐卡数,number,675b900991ad2491c69389ca,67e0f0fae622896749ba5087,
_widget_1742795002381,_widget_1742795002381,上架实体商品数,number,675b900991ad2491c69389ca,67e0f0fae622896749ba5087,
_widget_1742795002382,_widget_1742795002382,上架项目数,number,675b900991ad2491c69389ca,67e0f0fae622896749ba5087,
_widget_1742795002383,_widget_1742795002383,上架套餐数,number,675b900991ad2491c69389ca,67e0f0fae622896749ba5087,
_widget_1742795002384,_widget_1742795002384,微信公众号粉丝数,number,675b900991ad2491c69389ca,67e0f0fae622896749ba5087,
_widget_1742795002385,_widget_1742795002385,微信公众号绑定手机粉丝数,number,675b900991ad2491c69389ca,67e0f0fae622896749ba5087,
_widget_1742795002386,_widget_1742795002386,是否开通微信小程序,number,675b900991ad2491c69389ca,67e0f0fae622896749ba5087,
_widget_1742795002387,_widget_1742795002387,微信小程序绑定用户数,number,675b900991ad2491c69389ca,67e0f0fae622896749ba5087,
_widget_1742795002388,_widget_1742795002388,微信小程序绑定手机用户量,number,675b900991ad2491c69389ca,67e0f0fae622896749ba5087,
_widget_1742795002389,_widget_1742795002389,微信订单数,number,675b900991ad2491c69389ca,67e0f0fae622896749ba5087,
_widget_1742795002390,_widget_1742795002390,微信支付订单量,number,675b900991ad2491c69389ca,67e0f0fae622896749ba5087,
_widget_1742795002391,_widget_1742795002391,线下订单数,number,675b900991ad2491c69389ca,67e0f0fae622896749ba5087,
_widget_1742884710674,_widget_1742884710674,门店id,text,675b900991ad2491c69389ca,67e24f665adf5a8611f3e589,
_widget_1742884710675,_widget_1742884710675,提成类型_二级分类,text,675b900991ad2491c69389ca,67e24f665adf5a8611f3e589,
_widget_1742884710676,_widget_1742884710676,提成基数（本月）,number,675b900991ad2491c69389ca,67e24f665adf5a8611f3e589,
_widget_1742884710677,_widget_1742884710677,提成基数（上月）,number,675b900991ad2491c69389ca,67e24f665adf5a8611f3e589,
_widget_1748930441629,_widget_1748930441629,公司id,text,675b900991ad2491c69389ca,67e24f665adf5a8611f3e589,
_widget_1748931089356,_widget_1748931089356,门店编码,text,675b900991ad2491c69389ca,67e24f665adf5a8611f3e589,
_widget_1748931089357,_widget_1748931089357,门店名称,text,675b900991ad2491c69389ca,67e24f665adf5a8611f3e589,
_widget_1742884829007,_widget_1742884829007,门店id,text,675b900991ad2491c69389ca,67e24fdd8dfcfa918e17c30b,
_widget_1742884829008,_widget_1742884829008,商品名称,text,675b900991ad2491c69389ca,67e24fdd8dfcfa918e17c30b,
_widget_1742884829009,_widget_1742884829009,服务期结束时间,text,675b900991ad2491c69389ca,67e24fdd8dfcfa918e17c30b,
_widget_1748930826642,_widget_1748930826642,公司id,text,675b900991ad2491c69389ca,67e24fdd8dfcfa918e17c30b,
_widget_1748931208852,_widget_1748931208852,门店编码,text,675b900991ad2491c69389ca,67e24fdd8dfcfa918e17c30b,
_widget_1748931208851,_widget_1748931208851,门店名称,text,675b900991ad2491c69389ca,67e24fdd8dfcfa918e17c30b,
_widget_1743065201885,_widget_1743065201885,公司id,text,675b900991ad2491c69389ca,67e5107198ba1b20d5df3974,
_widget_1743065201886,_widget_1743065201886,是否启动短信功能,text,675b900991ad2491c69389ca,67e5107198ba1b20d5df3974,
_widget_1743065201887,_widget_1743065201887,是否购买短信包,text,675b900991ad2491c69389ca,67e5107198ba1b20d5df3974,
_widget_1743065201888,_widget_1743065201888,累计购买总数,text,675b900991ad2491c69389ca,67e5107198ba1b20d5df3974,
_widget_1743065201889,_widget_1743065201889,累计发送成功总人数,text,675b900991ad2491c69389ca,67e5107198ba1b20d5df3974,
_widget_1743065201890,_widget_1743065201890,剩余短信条数,text,675b900991ad2491c69389ca,67e5107198ba1b20d5df3974,
_widget_1743065201891,_widget_1743065201891,第一次短信购买时间,text,675b900991ad2491c69389ca,67e5107198ba1b20d5df3974,
_widget_1743065201892,_widget_1743065201892,最近一次短信购买时间,text,675b900991ad2491c69389ca,67e5107198ba1b20d5df3974,
_widget_1743065201893,_widget_1743065201893,实付总金额,text,675b900991ad2491c69389ca,67e5107198ba1b20d5df3974,
_widget_1743065201894,_widget_1743065201894,短信剩余量是否小于20%,text,675b900991ad2491c69389ca,67e5107198ba1b20d5df3974,
_widget_1748241895830,_widget_1748241895830,门店名称,text,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748241895831,_widget_1748241895831,联系人,text,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748241895839,_widget_1748241895839,开户时间,datetime,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748241895842,_widget_1748241895842,门店编码,text,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748241895832,_widget_1748241895832,联系方式,text,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748241895850,_widget_1748241895850,系统版本,text,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748241895844,_widget_1748241895844,公司名称,text,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748246808679,_widget_1748246808679,运营顾问,user,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748246808682,_widget_1748246808682,区域经理,user,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748241895846,_widget_1748241895846,公司等级,text,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748246808681,_widget_1748246808681,运营专家,user,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748241895853,_widget_1748241895853,操作模式E.L/E.S,text,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748241895829,_widget_1748241895829,活跃健康状态变化,text,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748241895833,_widget_1748241895833,初始日,datetime,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748241895834,_widget_1748241895834,推进日,datetime,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748512176640,_widget_1748512176640,异常跟进情况描述,textarea,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748512176641,_widget_1748512176641,异常变化原因,radiogroup,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748512176643,_widget_1748512176643,正常使用,radiogroup,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748512176645,_widget_1748512176645,门店原因,radiogroup,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748512176647,_widget_1748512176647,服务原因,radiogroup,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748512176649,_widget_1748512176649,产品原因,radiogroup,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748512176651,_widget_1748512176651,未正式切换,radiogroup,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748512176655,_widget_1748512176655,跟进状态,radiogroup,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748246808678,_widget_1748246808678,当前跟进人,user,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748512176654,_widget_1748512176654,跟进时间,datetime,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1751273412737,_widget_1751273412737,是否跟进完成,text,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748246808680,_widget_1748246808680,区域客服,user,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748241895847,_widget_1748241895847,大区,text,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748241895848,_widget_1748241895848,省,text,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748241895855,_widget_1748241895855,城市,text,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748241895849,_widget_1748241895849,门店类型,text,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748241895851,_widget_1748241895851,saas客户类型,text,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748241895852,_widget_1748241895852,门店阶段,text,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1748247754304,_widget_1748247754304,关联数据,lookup,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc,
_widget_1751250294777,_widget_1751250294777,姓名,text,6694d3c4fcb69ca9a111a6c4,6861f5772b0d3575e14eba4a,
_widget_1751250294778,_widget_1751250294778,年纪,number,6694d3c4fcb69ca9a111a6c4,6861f5772b0d3575e14eba4a,
_widget_1751505196330,_widget_1751505196330,图片,image,6694d3c4fcb69ca9a111a6c4,6861f5772b0d3575e14eba4a,
_widget_1751507507755,_widget_1751507507755,定位,location,6694d3c4fcb69ca9a111a6c4,6861f5772b0d3575e14eba4a,
_widget_1751512443179,_widget_1751512443179,单行文本,text,6694d3c4fcb69ca9a111a6c4,6861f5772b0d3575e14eba4a,
_widget_1739951204545,_widget_1739951204545,表单类型,combo,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1739252804406,_widget_1739252804406,日期,datetime,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1739258942667,_widget_1739258942667,账号,text,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1739252804419,_widget_1739252804419,日分区,text,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1739252804397,_widget_1739252804397,产品名称,text,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1739252804407,_widget_1739252804407,联系手机号,text,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1739252804409,_widget_1739252804409,使用时长,text,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1739252804396,_widget_1739252804396,开户日,datetime,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1739252804408,_widget_1739252804408,到期日,datetime,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1739252804410,_widget_1739252804410,续约日,datetime,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1739252804400,_widget_1739252804400,客户状态,combo,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1739252804413,_widget_1739252804413,近一周开单量,text,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1739252804414,_widget_1739252804414,近一周是否活跃,text,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1739252804415,_widget_1739252804415,G状态：近30天开单大于等于10天,text,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1739252804416,_widget_1739252804416,当月开单天数,text,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1739252804417,_widget_1739252804417,近30天开单天数,text,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1739252804418,_widget_1739252804418,当月G天数,text,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1740036367181,_widget_1740036367181,派发日期,text,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1740043340255,_widget_1740043340255,跟进人,user,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1741252143304,_widget_1741252143304,是否联系上·新签,combo,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1741252143306,_widget_1741252143306,是否联系上·异常,combo,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1741252143308,_widget_1741252143308,是否联系上·续约商机,combo,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1741252143310,_widget_1741252143310,是否联系上·过期召回,combo,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1741256466947,_widget_1741256466947,未接通原因备注,text,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1740721384110,_widget_1740721384110,省市区,address,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1741312871468,_widget_1741312871468,省市区·续约,address,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1740721384111,_widget_1740721384111,门店名称,text,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1741312871469,_widget_1741312871469,门店名称·续约,text,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1740721384112,_widget_1740721384112,负责人姓名,text,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1741312871470,_widget_1741312871470,负责人姓名·续约,text,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1740721384122,_widget_1740721384122,回访人·新签,text,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1740721384117,_widget_1740721384117,未开单原因·新签,textarea,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1740721384125,_widget_1740721384125,是否愿意继续使用·新签,text,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1740721384127,_widget_1740721384127,回访人·异常,text,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1740721384128,_widget_1740721384128,未开单原因·异常,textarea,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1740721384129,_widget_1740721384129,是否愿意继续使用·异常,text,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1740721384131,_widget_1740721384131,回访人·续约商机,text,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1740721384132,_widget_1740721384132,是否有转化SaaS意愿·续约商机,combo,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1740721384133,_widget_1740721384133,系统使用情况·续约商机,textarea,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1749088869175,_widget_1749088869175,SaaS转化结果·续约商机,radiogroup,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1749088869177,_widget_1749088869177,转化SaaS订单号·续约商机,text,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1749088869190,_widget_1749088869190,其他转化结果·续约商机,textarea,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1740721384135,_widget_1740721384135,回访人·过期召回,text,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1740721384136,_widget_1740721384136,未续约单原因·过期召回,textarea,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1740721384137,_widget_1740721384137,是否有续约意愿·过期召回,text,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1749090854370,_widget_1749090854370,沟通跟进结果·过期召回,radiogroup,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1749090854372,_widget_1749090854372,转化SaaS订单号·过期召回,text,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1749090854373,_widget_1749090854373,接车宝续约订单号·过期召回,text,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1749090854374,_widget_1749090854374,其他召回情况说明·过期召回,textarea,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1751356539629,_widget_1751356539629,完成日期时间,datetime,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1751271771674,_widget_1751271771674,是否完成,text,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1751356033346,_widget_1751356033346,流水号,sn,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1,
_widget_1740042824214,_widget_1740042824214,客服人员,user,6717470a0b3975ef583c6df1,67b6f2462f9ac03b783d409a,
_widget_1740117343937,_widget_1740117343937,开关,combo,6717470a0b3975ef583c6df1,67b6f2462f9ac03b783d409a,
_widget_1740042824216,_widget_1740042824216,下次开始位置,text,6717470a0b3975ef583c6df1,67b6f2462f9ac03b783d409a,
_widget_1740723898388,_widget_1740723898388,日期,datetime,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110,
_widget_1740723898389,_widget_1740723898389,产品名称,text,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110,
_widget_1740723898390,_widget_1740723898390,账号,text,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110,
_widget_1740723898391,_widget_1740723898391,联系手机号,number,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110,
_widget_1740723898392,_widget_1740723898392,开户日,datetime,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110,
_widget_1740723898393,_widget_1740723898393,使用时长,number,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110,
_widget_1740723898394,_widget_1740723898394,续约日,text,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110,
_widget_1740723898395,_widget_1740723898395,到期日,datetime,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110,
_widget_1740723898396,_widget_1740723898396,客户状态,text,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110,
_widget_1740723898397,_widget_1740723898397,近一周开单量,number,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110,
_widget_1740723898398,_widget_1740723898398,近一周是否活跃,number,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110,
_widget_1740723898399,_widget_1740723898399,G状态：近30天开单大于等于10天,number,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110,
_widget_1740723898400,_widget_1740723898400,当月开单天数,number,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110,
_widget_1740723898401,_widget_1740723898401,近30天开单天数,number,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110,
_widget_1740723898402,_widget_1740723898402,当月G天数,number,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110,
_widget_1740723898403,_widget_1740723898403,日分区,number,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110,
_widget_1740723898404,_widget_1740723898404,表单类型,text,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110,
_widget_1740723898405,_widget_1740723898405,派发日期,datetime,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110,
_widget_0201002000001,_widget_0201002000001,客户编码,sn,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_0201002000002,_widget_0201002000002,门店名称,company,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1630862543434,_widget_1630862543434,客户级别,combo,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1631071964761,_widget_1631071964761,客户来源,text,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_0201002000005,_widget_0201002000005,所属公海,account_pool,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1663742427957,_widget_1663742427957,客户查重,text,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1750126318263,_widget_1750126318263,门店名称（后台传值）,text,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1746675108119,_widget_1746675108119,原系统名称,combo,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1749204198412,_widget_1749204198412,原系统情况描述,text,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1630862543637,_widget_1630862543637,门店类型,combo,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1746675108151,_widget_1746675108151,门店设备,combocheck,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1746675108121,_widget_1746675108121,门店业务,combocheck,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1746675108115,_widget_1746675108115,工位数,number,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1747321321284,_widget_1747321321284,员工数,number,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1746675108123,_widget_1746675108123,系统操作人员,combocheck,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1737097782383,_widget_1737097782383,门店环境,image,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1630862543415,_widget_1630862543415,BD状态,combo,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1747123933309,_widget_1747123933309,客户BD日期,datetime,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1751366502797,_widget_1751366502797,意向程度,combo,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1747661411161,_widget_1747661411161,Test开始日期,datetime,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1747661411178,_widget_1747661411178,Test天数,number,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1747664949166,_widget_1747664949166,Test账号状态,combo,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_0201002000003,_widget_0201002000003,BD负责人,user,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_0201002000004,_widget_0201002000004,BD协作人,usergroup,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_0201002000006,_widget_0201002000006,销售归属部门,dept,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1747133970117,_widget_1747133970117,BD阻塞原因,combo,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1747669642443,_widget_1747669642443,BD阻塞原因分类,combo,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1747133970121,_widget_1747133970121,BD阻塞原因详细描述,textarea,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1749290572780,_widget_1749290572780,签约&上线负责人,user,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1747123933310,_widget_1747123933310,客户签约日期,datetime,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1747123933311,_widget_1747123933311,客户付款日期,datetime,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1749632087678,_widget_1749632087678,付款金额(泰铢),number,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1749632087641,_widget_1749632087641,付款截图,image,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1749632087639,_widget_1749632087639,上传发票附件,upload,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1740460160201,_widget_1740460160201,上线状态,combo,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1747123933312,_widget_1747123933312,上线日期,datetime,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1747133970122,_widget_1747133970122,上线失败原因,combo,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1631071964934,_widget_1631071964934,上线失败原因描述,textarea,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1749108058561,_widget_1749108058561,门店系统使用情况说明,textarea,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1747123507416,_widget_1747123507416,开户门店ID,text,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1737092013289,_widget_1737092013289,公司名称,text,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1737092013291,_widget_1737092013291,主店简称,text,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1737092013292,_widget_1737092013292,营业执照号,text,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1737092013293,_widget_1737092013293,营业执照名称,text,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1737092013300,_widget_1737092013300,门店logo,image,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1737092013301,_widget_1737092013301,pc首页左上角logo,image,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1737092013302,_widget_1737092013302,pc首页左上角logo缩略图,image,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1737092013321,_widget_1737092013321,门头照片,image,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1737097231480,_widget_1737097231480,府,combo,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1737097231482,_widget_1737097231482,县,combo,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1737092013299,_widget_1737092013299,地址（省市区）,text,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1737097782393,_widget_1737097782393,详情地址,text,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1737092013314,_widget_1737092013314,营业开始时间,text,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1737092013313,_widget_1737092013313,营业结束时间,text,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1737092013312,_widget_1737092013312,经度,text,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1737092013311,_widget_1737092013311,纬度,text,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1737092013310,_widget_1737092013310,负责人名字,text,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1737092013308,_widget_1737092013308,负责人手机号,text,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1737092013309,_widget_1737092013309,服务接待固话,text,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1737092013315,_widget_1737092013315,服务接待名称,text,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1737092013316,_widget_1737092013316,服务接待手机号,text,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1737092013320,_widget_1737092013320,账号数上限,text,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1737092013318,_widget_1737092013318,税号,text,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1737092013317,_widget_1737092013317,分支编号,text,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1737092013319,_widget_1737092013319,嘉实多内部门店编码,text,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1737092013339,_widget_1737092013339,运营顾问(上线负责人),user,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1737092013340,_widget_1737092013340,运营专家,user,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1737092013341,_widget_1737092013341,区域经理,user,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1750125550901,_widget_1750125550901,状态,text,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1663742427909,_widget_1663742427909,客户查重：客户表内该客户数量,number,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1709110880998,_widget_1709110880998,结算期限,combo,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1709110881001,_widget_1709110881001,信用额度/元,number,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1709110881002,_widget_1709110881002,发票抬头,text,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1709110881003,_widget_1709110881003,发票税号,text,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1709110881004,_widget_1709110881004,税种,combo,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1709110881007,_widget_1709110881007,增值税税率 %,number,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1709110881008,_widget_1709110881008,开户电话,text,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1709110881009,_widget_1709110881009,开户银行,combo,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1709110881016,_widget_1709110881016,银行账户,text,673457d6837e60a418e0e56b,020100200000000000000001,
_widget_1742174728275,_widget_1742174728275,指标归属日期,datetime,673457d6837e60a418e0e56b,67d636bb6212b7619a7a4231,
_widget_1742091963874,_widget_1742091963874,公司ID,text,673457d6837e60a418e0e56b,67d636bb6212b7619a7a4231,
_widget_1742091963875,_widget_1742091963875,公司名称,text,673457d6837e60a418e0e56b,67d636bb6212b7619a7a4231,
_widget_1742091963876,_widget_1742091963876,门店ID,text,673457d6837e60a418e0e56b,67d636bb6212b7619a7a4231,
_widget_1742091963877,_widget_1742091963877,门店名称,text,673457d6837e60a418e0e56b,67d636bb6212b7619a7a4231,
_widget_1742091963878,_widget_1742091963878,门店简称,text,673457d6837e60a418e0e56b,67d636bb6212b7619a7a4231,
_widget_1742091963879,_widget_1742091963879,门店创建时间,datetime,673457d6837e60a418e0e56b,67d636bb6212b7619a7a4231,
_widget_1742091963880,_widget_1742091963880,指标类型,combo,673457d6837e60a418e0e56b,67d636bb6212b7619a7a4231,
_widget_1742091963881,_widget_1742091963881,指标子类型,combo,673457d6837e60a418e0e56b,67d636bb6212b7619a7a4231,
_widget_1742091963882,_widget_1742091963882,指标值,number,673457d6837e60a418e0e56b,67d636bb6212b7619a7a4231,
_widget_0201002000002,_widget_0201002000002,客户名称,company,675a7f2a54c95e84fb66393e,020100200000000000000001,
_widget_0201002000001,_widget_0201002000001,客户编码,sn,675a7f2a54c95e84fb66393e,020100200000000000000001,
_widget_1630862543415,_widget_1630862543415,客户状态,combo,675a7f2a54c95e84fb66393e,020100200000000000000001,
_widget_1631071964761,_widget_1631071964761,客户来源,text,675a7f2a54c95e84fb66393e,020100200000000000000001,
_widget_1630862543434,_widget_1630862543434,客户级别,combo,675a7f2a54c95e84fb66393e,020100200000000000000001,
_widget_0201002000005,_widget_0201002000005,所属公海,account_pool,675a7f2a54c95e84fb66393e,020100200000000000000001,
_widget_1663742427957,_widget_1663742427957,客户查重,text,675a7f2a54c95e84fb66393e,020100200000000000000001,
_widget_1630862543637,_widget_1630862543637,所属行业,combo,675a7f2a54c95e84fb66393e,020100200000000000000001,
_widget_1646826421878,_widget_1646826421878,客户邮箱,text,675a7f2a54c95e84fb66393e,020100200000000000000001,
_widget_1631071964919,_widget_1631071964919,客户地址,address,675a7f2a54c95e84fb66393e,020100200000000000000001,
_widget_1631071964934,_widget_1631071964934,客户详情,textarea,675a7f2a54c95e84fb66393e,020100200000000000000001,
_widget_0201002000003,_widget_0201002000003,销售负责人,user,675a7f2a54c95e84fb66393e,020100200000000000000001,
_widget_0201002000006,_widget_0201002000006,销售归属部门,dept,675a7f2a54c95e84fb66393e,020100200000000000000001,
_widget_0201002000004,_widget_0201002000004,协作人,usergroup,675a7f2a54c95e84fb66393e,020100200000000000000001,
_widget_1663742427909,_widget_1663742427909,客户查重：客户表内该客户数量,number,675a7f2a54c95e84fb66393e,020100200000000000000001,
_widget_1709110880998,_widget_1709110880998,结算期限,combo,675a7f2a54c95e84fb66393e,020100200000000000000001,
_widget_1709110881001,_widget_1709110881001,信用额度/元,number,675a7f2a54c95e84fb66393e,020100200000000000000001,
_widget_1709110881002,_widget_1709110881002,发票抬头,text,675a7f2a54c95e84fb66393e,020100200000000000000001,
_widget_1709110881003,_widget_1709110881003,发票税号,text,675a7f2a54c95e84fb66393e,020100200000000000000001,
_widget_1709110881004,_widget_1709110881004,税种,combo,675a7f2a54c95e84fb66393e,020100200000000000000001,
_widget_1709110881007,_widget_1709110881007,增值税税率 %,number,675a7f2a54c95e84fb66393e,020100200000000000000001,
_widget_1709110881008,_widget_1709110881008,开户电话,text,675a7f2a54c95e84fb66393e,020100200000000000000001,
_widget_1709110881009,_widget_1709110881009,开户银行,combo,675a7f2a54c95e84fb66393e,020100200000000000000001,
_widget_1709110881016,_widget_1709110881016,银行账户,text,675a7f2a54c95e84fb66393e,020100200000000000000001,
1 name widgetName label type app_id entry_id items
2 _widget_1690785229260 _widget_1690785229260 怎么称呼您 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
3 _widget_1690785229261 _widget_1690785229261 您门店或公司名称 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
4 _widget_1693382214358 _widget_1693382214358 您的联系方式 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
5 _widget_1690785326597 _widget_1690785326597 地址 address 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
6 _widget_1690785229266 _widget_1690785229266 备注 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
7 _widget_1690785229284 _widget_1690785229284 客户概况 textarea 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
8 _widget_1690787826014 _widget_1690787826014 门头照片（可上传多张） image 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
9 _widget_1690785229278 _widget_1690785229278 意向书来源 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
10 _widget_1741837239117 _widget_1741837239117 业务类型 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
11 _widget_1693381022904 _widget_1693381022904 客户渠道 combo 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
12 _widget_1715146829031 _widget_1715146829031 轻连锁类型 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
13 _widget_1690785229280 _widget_1690785229280 小六 user 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
14 _widget_1694154771486 _widget_1694154771486 技术专家 user 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
15 _widget_1690785229281 _widget_1690785229281 战区经理 user 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
16 _widget_1718855270618 _widget_1718855270618 该养车门店是否已退出？ radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
17 _widget_1718855270620 _widget_1718855270620 退出情况说明 textarea 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
18 _widget_1718855270621 _widget_1718855270621 该养车门店是否有F6系统需求？ radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
19 _widget_1690785229282 _widget_1690785229282 意向阶段 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
20 _widget_1693551051341 _widget_1693551051341 客户门店数 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
21 _widget_1690785229283 _widget_1690785229283 意向版本 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
22 _widget_1693381022909 _widget_1693381022909 客户沟通记录 subform 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd [{'name': '_widget_1693381022911', 'widgetName': '_widget_1693381022911', 'label': '跟进日期', 'type': 'datetime'}, {'name': '_widget_1693381022912', 'widgetName': '_widget_1693381022912', 'label': '沟通方式', 'type': 'combo'}, {'name': '_widget_1693381022914', 'widgetName': '_widget_1693381022914', 'label': '沟通概要', 'type': 'textarea'}]
23 _widget_1693381022908 _widget_1693381022908 下次跟进日期 datetime 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
24 _widget_1696902504775 _widget_1696902504775 理论下次跟进日期 datetime 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
25 _widget_1694398435902 _widget_1694398435902 最近一次沟通日期 datetime 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
26 _widget_1693381022915 _widget_1693381022915 客户在用系统名称 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
27 _widget_1693381022916 _widget_1693381022916 预计成交金额（单位：元） number 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
28 _widget_1693381022917 _widget_1693381022917 预计成交日期 datetime 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
29 _widget_1699321775702 _widget_1699321775702 实际成交日期 datetime 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
30 _widget_1693381022918 _widget_1693381022918 下单手机号 phone 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
31 _widget_1693381022919 _widget_1693381022919 放弃原因分类 combo 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
32 _widget_1693381022921 _widget_1693381022921 价格原因 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
33 _widget_1693381022923 _widget_1693381022923 产品原因 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
34 _widget_1693381022925 _widget_1693381022925 门店原因 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
35 _widget_1693381022930 _widget_1693381022930 加盟外部连锁 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
36 _widget_1693381022927 _widget_1693381022927 内部业务影响（包含接车宝会员宝安装服务） radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
37 _widget_1724313867483 _widget_1724313867483 输单原因分类 combo 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
38 _widget_1723603567435 _widget_1723603567435 竞品名称 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
39 _widget_1693381022929 _widget_1693381022929 输单/放弃说明 textarea 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
40 _widget_1708935626093 _widget_1708935626093 线索沟通情况 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
41 _widget_1709019633297 _widget_1709019633297 客户业务需求 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
42 _widget_1708935626085 _widget_1708935626085 客户手机号是否是微信号？ radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
43 _widget_1708935626087 _widget_1708935626087 企微是否已加好友？ radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
44 _widget_1708935626089 _widget_1708935626089 BOSS系统里是否有该客户信息 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
45 _widget_1709027488072 _widget_1709027488072 客户BOSS业务信息 checkboxgroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
46 _widget_1708935626095 _widget_1708935626095 联系人身份 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
47 _widget_1709100220536 _widget_1709100220536 门店业务类型 combo 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
48 _widget_1708935626104 _widget_1708935626104 客户门店工位数 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
49 _widget_1708935626100 _widget_1708935626100 客户是否有需求 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
50 _widget_1708935626102 _widget_1708935626102 客户主要需求功能模块（可多选） checkboxgroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
51 _widget_1708935626107 _widget_1708935626107 客户原系统 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
52 _widget_1708935626091 _widget_1708935626091 客户预算 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
53 _widget_1708935626098 _widget_1708935626098 预计使用时间 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
54 _widget_1709186927667 _widget_1709186927667 门头照片等 image 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
55 _widget_1709100220453 _widget_1709100220453 SDR联系记录 subform 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd [{'name': '_widget_1709100220457', 'widgetName': '_widget_1709100220457', 'label': '日期时间', 'type': 'datetime'}, {'name': '_widget_1709100220455', 'widgetName': '_widget_1709100220455', 'label': '联系情况', 'type': 'text'}]
56 _widget_1708935626292 _widget_1708935626292 SDR判断客户是否需要进一步跟进 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
57 _widget_1710292803370 _widget_1710292803370 SDR建议线索跟进时间 combo 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
58 _widget_1710037836605 _widget_1710037836605 线索放弃说明 textarea 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
59 _widget_1709543713740 _widget_1709543713740 SDR放弃意见 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
60 _widget_1725501916821 _widget_1725501916821 提交时间 datetime 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
61 _widget_1725507662927 _widget_1725507662927 提交人 user 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
62 _widget_1690785229279 _widget_1690785229279 城市 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
63 _widget_1692070536228 _widget_1692070536228 区 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
64 _widget_1697423018006 _widget_1697423018006 战区 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
65 _widget_1694076921201 _widget_1694076921201 线上线下 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
66 _widget_1709868059118 _widget_1709868059118 线索跟进角色 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
67 _widget_1709781645383 _widget_1709781645383 客户跟进角色 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
68 _widget_1725875301461 _widget_1725875301461 技术支持提交人 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
69 _widget_1725933630175 _widget_1725933630175 是否有效线索 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
70 _widget_1690785229262 _widget_1690785229262 您的联系方式 phone 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
71 _widget_1723431564839 _widget_1723431564839 线索状态 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
72 _widget_0201002000002 _widget_0201002000002 经销商名称 company 673d8427549d00c3d753c530 020100200000000000000001
73 _widget_1732095401220 _widget_1732095401220 经销商简称 text 673d8427549d00c3d753c530 020100200000000000000001
74 _widget_0201002000005 _widget_0201002000005 所属公海 account_pool 673d8427549d00c3d753c530 020100200000000000000001
75 _widget_1732095401222 _widget_1732095401222 营业执照号 text 673d8427549d00c3d753c530 020100200000000000000001
76 _widget_1732095401223 _widget_1732095401223 营业执照名称 text 673d8427549d00c3d753c530 020100200000000000000001
77 _widget_1732153235945 _widget_1732153235945 详细地址 address 673d8427549d00c3d753c530 020100200000000000000001
78 _widget_1732095401224 _widget_1732095401224 负责人姓名 text 673d8427549d00c3d753c530 020100200000000000000001
79 _widget_1732095401225 _widget_1732095401225 负责人手机号 text 673d8427549d00c3d753c530 020100200000000000000001
80 _widget_1732095401226 _widget_1732095401226 联系电话 text 673d8427549d00c3d753c530 020100200000000000000001
81 _widget_1742200662775 _widget_1742200662775 购买年限 combo 673d8427549d00c3d753c530 020100200000000000000001
82 _widget_1742278002584 _widget_1742278002584 购买版本 combo 673d8427549d00c3d753c530 020100200000000000000001
83 _widget_1732095401227 _widget_1732095401227 经销商可购买的群数量 text 673d8427549d00c3d753c530 020100200000000000000001
84 _widget_0201002000003 _widget_0201002000003 销售负责人 user 673d8427549d00c3d753c530 020100200000000000000001
85 _widget_1732153235954 _widget_1732153235954 运营顾问 user 673d8427549d00c3d753c530 020100200000000000000001
86 _widget_1732153235955 _widget_1732153235955 运营专家 user 673d8427549d00c3d753c530 020100200000000000000001
87 _widget_1732153235956 _widget_1732153235956 区域经理 user 673d8427549d00c3d753c530 020100200000000000000001
88 _widget_1741165766484 _widget_1741165766484 业务 user 673d8427549d00c3d753c530 020100200000000000000001
89 _widget_1732180937809 _widget_1732180937809 经销商ID text 673d8427549d00c3d753c530 020100200000000000000001
90 _widget_1732180937812 _widget_1732180937812 开通状态 text 673d8427549d00c3d753c530 020100200000000000000001
91 _widget_1732180937811 _widget_1732180937811 开通时间 datetime 673d8427549d00c3d753c530 020100200000000000000001
92 _widget_1741160451740 _widget_1741160451740 系统到期时间 datetime 673d8427549d00c3d753c530 020100200000000000000001
93 _widget_1630862543415 _widget_1630862543415 客户状态 combo 673d8427549d00c3d753c530 020100200000000000000001
94 _widget_1630862543434 _widget_1630862543434 客户级别 combo 673d8427549d00c3d753c530 020100200000000000000001
95 _widget_0201002000001 _widget_0201002000001 客户编码 sn 673d8427549d00c3d753c530 020100200000000000000001
96 _widget_1646826421878 _widget_1646826421878 客户邮箱 text 673d8427549d00c3d753c530 020100200000000000000001
97 _widget_1630862543637 _widget_1630862543637 所属行业 combo 673d8427549d00c3d753c530 020100200000000000000001
98 _widget_1732178180219 _widget_1732178180219 客户来源表单字段 text 673d8427549d00c3d753c530 020100200000000000000001
99 _widget_0201002000006 _widget_0201002000006 销售归属部门 dept 673d8427549d00c3d753c530 020100200000000000000001
100 _widget_0201002000004 _widget_0201002000004 协作人 usergroup 673d8427549d00c3d753c530 020100200000000000000001
101 _widget_1631071964934 _widget_1631071964934 客户详情 textarea 673d8427549d00c3d753c530 020100200000000000000001
102 _widget_1631071964761 _widget_1631071964761 客户来源 text 673d8427549d00c3d753c530 020100200000000000000001
103 _widget_1663742427957 _widget_1663742427957 客户查重 text 673d8427549d00c3d753c530 020100200000000000000001
104 _widget_1663742427909 _widget_1663742427909 客户查重：客户表内该客户数量 number 673d8427549d00c3d753c530 020100200000000000000001
105 _widget_1709110880998 _widget_1709110880998 结算期限 combo 673d8427549d00c3d753c530 020100200000000000000001
106 _widget_1709110881001 _widget_1709110881001 信用额度/元 number 673d8427549d00c3d753c530 020100200000000000000001
107 _widget_1709110881002 _widget_1709110881002 发票抬头 text 673d8427549d00c3d753c530 020100200000000000000001
108 _widget_1709110881003 _widget_1709110881003 发票税号 text 673d8427549d00c3d753c530 020100200000000000000001
109 _widget_1709110881004 _widget_1709110881004 税种 combo 673d8427549d00c3d753c530 020100200000000000000001
110 _widget_1709110881007 _widget_1709110881007 增值税税率 % number 673d8427549d00c3d753c530 020100200000000000000001
111 _widget_1709110881008 _widget_1709110881008 开户电话 text 673d8427549d00c3d753c530 020100200000000000000001
112 _widget_1709110881009 _widget_1709110881009 开户银行 combo 673d8427549d00c3d753c530 020100200000000000000001
113 _widget_1709110881016 _widget_1709110881016 银行账户 text 673d8427549d00c3d753c530 020100200000000000000001
114 _widget_1734062123070 _widget_1734062123070 门店名称 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
115 _widget_1734062123068 _widget_1734062123068 公司名称 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
116 _widget_1734062123071 _widget_1734062123071 门店编码 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
117 _widget_1734062123072 _widget_1734062123072 公司等级 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
118 _widget_1734062123073 _widget_1734062123073 门店类型 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
119 _widget_1734062123085 _widget_1734062123085 是否主店 number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
120 _widget_1734062123067 _widget_1734062123067 公司id text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
121 _widget_1734062123069 _widget_1734062123069 门店id text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
122 _widget_1734062123169 _widget_1734062123169 经营模式 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
123 _widget_1734062123170 _widget_1734062123170 联系人 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
124 _widget_1734062123172 _widget_1734062123172 手机号码 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
125 _widget_1734062123179 _widget_1734062123179 是否主店 number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
126 _widget_1734062123180 _widget_1734062123180 门店数 number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
127 _widget_1734062123066 _widget_1734062123066 日期 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
128 _widget_1734062123065 _widget_1734062123065 日期批次 number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
129 _widget_1749000071375 _widget_1749000071375 日期（时间字段） datetime 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
130 _widget_1734062123192 _widget_1734062123192 是否加店 number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
131 _widget_1734062123194 _widget_1734062123194 门店规模 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
132 _widget_1734062123196 _widget_1734062123196 经营范围 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
133 _widget_1734062123197 _widget_1734062123197 维修厂类型 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
134 _widget_1734062123199 _widget_1734062123199 工位数 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
135 _widget_1734062123201 _widget_1734062123201 门店阶段 text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
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290 _widget_1742884829007 _widget_1742884829007 门店id text 675b900991ad2491c69389ca 67e24fdd8dfcfa918e17c30b
291 _widget_1742884829008 _widget_1742884829008 商品名称 text 675b900991ad2491c69389ca 67e24fdd8dfcfa918e17c30b
292 _widget_1742884829009 _widget_1742884829009 服务期结束时间 text 675b900991ad2491c69389ca 67e24fdd8dfcfa918e17c30b
293 _widget_1748930826642 _widget_1748930826642 公司id text 675b900991ad2491c69389ca 67e24fdd8dfcfa918e17c30b
294 _widget_1748931208852 _widget_1748931208852 门店编码 text 675b900991ad2491c69389ca 67e24fdd8dfcfa918e17c30b
295 _widget_1748931208851 _widget_1748931208851 门店名称 text 675b900991ad2491c69389ca 67e24fdd8dfcfa918e17c30b
296 _widget_1743065201885 _widget_1743065201885 公司id text 675b900991ad2491c69389ca 67e5107198ba1b20d5df3974
297 _widget_1743065201886 _widget_1743065201886 是否启动短信功能 text 675b900991ad2491c69389ca 67e5107198ba1b20d5df3974
298 _widget_1743065201887 _widget_1743065201887 是否购买短信包 text 675b900991ad2491c69389ca 67e5107198ba1b20d5df3974
299 _widget_1743065201888 _widget_1743065201888 累计购买总数 text 675b900991ad2491c69389ca 67e5107198ba1b20d5df3974
300 _widget_1743065201889 _widget_1743065201889 累计发送成功总人数 text 675b900991ad2491c69389ca 67e5107198ba1b20d5df3974
301 _widget_1743065201890 _widget_1743065201890 剩余短信条数 text 675b900991ad2491c69389ca 67e5107198ba1b20d5df3974
302 _widget_1743065201891 _widget_1743065201891 第一次短信购买时间 text 675b900991ad2491c69389ca 67e5107198ba1b20d5df3974
303 _widget_1743065201892 _widget_1743065201892 最近一次短信购买时间 text 675b900991ad2491c69389ca 67e5107198ba1b20d5df3974
304 _widget_1743065201893 _widget_1743065201893 实付总金额 text 675b900991ad2491c69389ca 67e5107198ba1b20d5df3974
305 _widget_1743065201894 _widget_1743065201894 短信剩余量是否小于20% text 675b900991ad2491c69389ca 67e5107198ba1b20d5df3974
306 _widget_1748241895830 _widget_1748241895830 门店名称 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
307 _widget_1748241895831 _widget_1748241895831 联系人 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
308 _widget_1748241895839 _widget_1748241895839 开户时间 datetime 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
309 _widget_1748241895842 _widget_1748241895842 门店编码 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
310 _widget_1748241895832 _widget_1748241895832 联系方式 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
311 _widget_1748241895850 _widget_1748241895850 系统版本 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
312 _widget_1748241895844 _widget_1748241895844 公司名称 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
313 _widget_1748246808679 _widget_1748246808679 运营顾问 user 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
314 _widget_1748246808682 _widget_1748246808682 区域经理 user 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
315 _widget_1748241895846 _widget_1748241895846 公司等级 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
316 _widget_1748246808681 _widget_1748246808681 运营专家 user 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
317 _widget_1748241895853 _widget_1748241895853 操作模式E.L/E.S text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
318 _widget_1748241895829 _widget_1748241895829 活跃健康状态变化 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
319 _widget_1748241895833 _widget_1748241895833 初始日 datetime 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
320 _widget_1748241895834 _widget_1748241895834 推进日 datetime 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
321 _widget_1748512176640 _widget_1748512176640 异常跟进情况描述 textarea 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
322 _widget_1748512176641 _widget_1748512176641 异常变化原因 radiogroup 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
323 _widget_1748512176643 _widget_1748512176643 正常使用 radiogroup 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
324 _widget_1748512176645 _widget_1748512176645 门店原因 radiogroup 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
325 _widget_1748512176647 _widget_1748512176647 服务原因 radiogroup 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
326 _widget_1748512176649 _widget_1748512176649 产品原因 radiogroup 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
327 _widget_1748512176651 _widget_1748512176651 未正式切换 radiogroup 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
328 _widget_1748512176655 _widget_1748512176655 跟进状态 radiogroup 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
329 _widget_1748246808678 _widget_1748246808678 当前跟进人 user 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
330 _widget_1748512176654 _widget_1748512176654 跟进时间 datetime 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
331 _widget_1751273412737 _widget_1751273412737 是否跟进完成 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
332 _widget_1748246808680 _widget_1748246808680 区域客服 user 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
333 _widget_1748241895847 _widget_1748241895847 大区 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
334 _widget_1748241895848 _widget_1748241895848 省 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
335 _widget_1748241895855 _widget_1748241895855 城市 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
336 _widget_1748241895849 _widget_1748241895849 门店类型 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
337 _widget_1748241895851 _widget_1748241895851 saas客户类型 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
338 _widget_1748241895852 _widget_1748241895852 门店阶段 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
339 _widget_1748247754304 _widget_1748247754304 关联数据 lookup 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
340 _widget_1751250294777 _widget_1751250294777 姓名 text 6694d3c4fcb69ca9a111a6c4 6861f5772b0d3575e14eba4a
341 _widget_1751250294778 _widget_1751250294778 年纪 number 6694d3c4fcb69ca9a111a6c4 6861f5772b0d3575e14eba4a
342 _widget_1751505196330 _widget_1751505196330 图片 image 6694d3c4fcb69ca9a111a6c4 6861f5772b0d3575e14eba4a
343 _widget_1751507507755 _widget_1751507507755 定位 location 6694d3c4fcb69ca9a111a6c4 6861f5772b0d3575e14eba4a
344 _widget_1751512443179 _widget_1751512443179 单行文本 text 6694d3c4fcb69ca9a111a6c4 6861f5772b0d3575e14eba4a
345 _widget_1739951204545 _widget_1739951204545 表单类型 combo 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
346 _widget_1739252804406 _widget_1739252804406 日期 datetime 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
347 _widget_1739258942667 _widget_1739258942667 账号 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
348 _widget_1739252804419 _widget_1739252804419 日分区 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
349 _widget_1739252804397 _widget_1739252804397 产品名称 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
350 _widget_1739252804407 _widget_1739252804407 联系手机号 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
351 _widget_1739252804409 _widget_1739252804409 使用时长 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
352 _widget_1739252804396 _widget_1739252804396 开户日 datetime 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
353 _widget_1739252804408 _widget_1739252804408 到期日 datetime 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
354 _widget_1739252804410 _widget_1739252804410 续约日 datetime 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
355 _widget_1739252804400 _widget_1739252804400 客户状态 combo 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
356 _widget_1739252804413 _widget_1739252804413 近一周开单量 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
357 _widget_1739252804414 _widget_1739252804414 近一周是否活跃 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
358 _widget_1739252804415 _widget_1739252804415 G状态：近30天开单大于等于10天 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
359 _widget_1739252804416 _widget_1739252804416 当月开单天数 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
360 _widget_1739252804417 _widget_1739252804417 近30天开单天数 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
361 _widget_1739252804418 _widget_1739252804418 当月G天数 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
362 _widget_1740036367181 _widget_1740036367181 派发日期 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
363 _widget_1740043340255 _widget_1740043340255 跟进人 user 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
364 _widget_1741252143304 _widget_1741252143304 是否联系上·新签 combo 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
365 _widget_1741252143306 _widget_1741252143306 是否联系上·异常 combo 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
366 _widget_1741252143308 _widget_1741252143308 是否联系上·续约商机 combo 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
367 _widget_1741252143310 _widget_1741252143310 是否联系上·过期召回 combo 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
368 _widget_1741256466947 _widget_1741256466947 未接通原因备注 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
369 _widget_1740721384110 _widget_1740721384110 省市区 address 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
370 _widget_1741312871468 _widget_1741312871468 省市区·续约 address 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
371 _widget_1740721384111 _widget_1740721384111 门店名称 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
372 _widget_1741312871469 _widget_1741312871469 门店名称·续约 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
373 _widget_1740721384112 _widget_1740721384112 负责人姓名 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
374 _widget_1741312871470 _widget_1741312871470 负责人姓名·续约 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
375 _widget_1740721384122 _widget_1740721384122 回访人·新签 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
376 _widget_1740721384117 _widget_1740721384117 未开单原因·新签 textarea 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
377 _widget_1740721384125 _widget_1740721384125 是否愿意继续使用·新签 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
378 _widget_1740721384127 _widget_1740721384127 回访人·异常 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
379 _widget_1740721384128 _widget_1740721384128 未开单原因·异常 textarea 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
380 _widget_1740721384129 _widget_1740721384129 是否愿意继续使用·异常 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
381 _widget_1740721384131 _widget_1740721384131 回访人·续约商机 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
382 _widget_1740721384132 _widget_1740721384132 是否有转化SaaS意愿·续约商机 combo 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
383 _widget_1740721384133 _widget_1740721384133 系统使用情况·续约商机 textarea 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
384 _widget_1749088869175 _widget_1749088869175 SaaS转化结果·续约商机 radiogroup 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
385 _widget_1749088869177 _widget_1749088869177 转化SaaS订单号·续约商机 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
386 _widget_1749088869190 _widget_1749088869190 其他转化结果·续约商机 textarea 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
387 _widget_1740721384135 _widget_1740721384135 回访人·过期召回 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
388 _widget_1740721384136 _widget_1740721384136 未续约单原因·过期召回 textarea 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
389 _widget_1740721384137 _widget_1740721384137 是否有续约意愿·过期召回 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
390 _widget_1749090854370 _widget_1749090854370 沟通跟进结果·过期召回 radiogroup 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
391 _widget_1749090854372 _widget_1749090854372 转化SaaS订单号·过期召回 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
392 _widget_1749090854373 _widget_1749090854373 接车宝续约订单号·过期召回 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
393 _widget_1749090854374 _widget_1749090854374 其他召回情况说明·过期召回 textarea 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
394 _widget_1751356539629 _widget_1751356539629 完成日期时间 datetime 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
395 _widget_1751271771674 _widget_1751271771674 是否完成 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
396 _widget_1751356033346 _widget_1751356033346 流水号 sn 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
397 _widget_1740042824214 _widget_1740042824214 客服人员 user 6717470a0b3975ef583c6df1 67b6f2462f9ac03b783d409a
398 _widget_1740117343937 _widget_1740117343937 开关 combo 6717470a0b3975ef583c6df1 67b6f2462f9ac03b783d409a
399 _widget_1740042824216 _widget_1740042824216 下次开始位置 text 6717470a0b3975ef583c6df1 67b6f2462f9ac03b783d409a
400 _widget_1740723898388 _widget_1740723898388 日期 datetime 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
401 _widget_1740723898389 _widget_1740723898389 产品名称 text 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
402 _widget_1740723898390 _widget_1740723898390 账号 text 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
403 _widget_1740723898391 _widget_1740723898391 联系手机号 number 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
404 _widget_1740723898392 _widget_1740723898392 开户日 datetime 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
405 _widget_1740723898393 _widget_1740723898393 使用时长 number 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
406 _widget_1740723898394 _widget_1740723898394 续约日 text 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
407 _widget_1740723898395 _widget_1740723898395 到期日 datetime 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
408 _widget_1740723898396 _widget_1740723898396 客户状态 text 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
409 _widget_1740723898397 _widget_1740723898397 近一周开单量 number 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
410 _widget_1740723898398 _widget_1740723898398 近一周是否活跃 number 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
411 _widget_1740723898399 _widget_1740723898399 G状态：近30天开单大于等于10天 number 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
412 _widget_1740723898400 _widget_1740723898400 当月开单天数 number 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
413 _widget_1740723898401 _widget_1740723898401 近30天开单天数 number 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
414 _widget_1740723898402 _widget_1740723898402 当月G天数 number 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
415 _widget_1740723898403 _widget_1740723898403 日分区 number 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
416 _widget_1740723898404 _widget_1740723898404 表单类型 text 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
417 _widget_1740723898405 _widget_1740723898405 派发日期 datetime 6717470a0b3975ef583c6df1 67c156ba635191b64af8a110
418 _widget_0201002000001 _widget_0201002000001 客户编码 sn 673457d6837e60a418e0e56b 020100200000000000000001
419 _widget_0201002000002 _widget_0201002000002 门店名称 company 673457d6837e60a418e0e56b 020100200000000000000001
420 _widget_1630862543434 _widget_1630862543434 客户级别 combo 673457d6837e60a418e0e56b 020100200000000000000001
421 _widget_1631071964761 _widget_1631071964761 客户来源 text 673457d6837e60a418e0e56b 020100200000000000000001
422 _widget_0201002000005 _widget_0201002000005 所属公海 account_pool 673457d6837e60a418e0e56b 020100200000000000000001
423 _widget_1663742427957 _widget_1663742427957 客户查重 text 673457d6837e60a418e0e56b 020100200000000000000001
424 _widget_1750126318263 _widget_1750126318263 门店名称（后台传值） text 673457d6837e60a418e0e56b 020100200000000000000001
425 _widget_1746675108119 _widget_1746675108119 原系统名称 combo 673457d6837e60a418e0e56b 020100200000000000000001
426 _widget_1749204198412 _widget_1749204198412 原系统情况描述 text 673457d6837e60a418e0e56b 020100200000000000000001
427 _widget_1630862543637 _widget_1630862543637 门店类型 combo 673457d6837e60a418e0e56b 020100200000000000000001
428 _widget_1746675108151 _widget_1746675108151 门店设备 combocheck 673457d6837e60a418e0e56b 020100200000000000000001
429 _widget_1746675108121 _widget_1746675108121 门店业务 combocheck 673457d6837e60a418e0e56b 020100200000000000000001
430 _widget_1746675108115 _widget_1746675108115 工位数 number 673457d6837e60a418e0e56b 020100200000000000000001
431 _widget_1747321321284 _widget_1747321321284 员工数 number 673457d6837e60a418e0e56b 020100200000000000000001
432 _widget_1746675108123 _widget_1746675108123 系统操作人员 combocheck 673457d6837e60a418e0e56b 020100200000000000000001
433 _widget_1737097782383 _widget_1737097782383 门店环境 image 673457d6837e60a418e0e56b 020100200000000000000001
434 _widget_1630862543415 _widget_1630862543415 BD状态 combo 673457d6837e60a418e0e56b 020100200000000000000001
435 _widget_1747123933309 _widget_1747123933309 客户BD日期 datetime 673457d6837e60a418e0e56b 020100200000000000000001
436 _widget_1751366502797 _widget_1751366502797 意向程度 combo 673457d6837e60a418e0e56b 020100200000000000000001
437 _widget_1747661411161 _widget_1747661411161 Test开始日期 datetime 673457d6837e60a418e0e56b 020100200000000000000001
438 _widget_1747661411178 _widget_1747661411178 Test天数 number 673457d6837e60a418e0e56b 020100200000000000000001
439 _widget_1747664949166 _widget_1747664949166 Test账号状态 combo 673457d6837e60a418e0e56b 020100200000000000000001
440 _widget_0201002000003 _widget_0201002000003 BD负责人 user 673457d6837e60a418e0e56b 020100200000000000000001
441 _widget_0201002000004 _widget_0201002000004 BD协作人 usergroup 673457d6837e60a418e0e56b 020100200000000000000001
442 _widget_0201002000006 _widget_0201002000006 销售归属部门 dept 673457d6837e60a418e0e56b 020100200000000000000001
443 _widget_1747133970117 _widget_1747133970117 BD阻塞原因 combo 673457d6837e60a418e0e56b 020100200000000000000001
444 _widget_1747669642443 _widget_1747669642443 BD阻塞原因分类 combo 673457d6837e60a418e0e56b 020100200000000000000001
445 _widget_1747133970121 _widget_1747133970121 BD阻塞原因详细描述 textarea 673457d6837e60a418e0e56b 020100200000000000000001
446 _widget_1749290572780 _widget_1749290572780 签约&上线负责人 user 673457d6837e60a418e0e56b 020100200000000000000001
447 _widget_1747123933310 _widget_1747123933310 客户签约日期 datetime 673457d6837e60a418e0e56b 020100200000000000000001
448 _widget_1747123933311 _widget_1747123933311 客户付款日期 datetime 673457d6837e60a418e0e56b 020100200000000000000001
449 _widget_1749632087678 _widget_1749632087678 付款金额(泰铢) number 673457d6837e60a418e0e56b 020100200000000000000001
450 _widget_1749632087641 _widget_1749632087641 付款截图 image 673457d6837e60a418e0e56b 020100200000000000000001
451 _widget_1749632087639 _widget_1749632087639 上传发票附件 upload 673457d6837e60a418e0e56b 020100200000000000000001
452 _widget_1740460160201 _widget_1740460160201 上线状态 combo 673457d6837e60a418e0e56b 020100200000000000000001
453 _widget_1747123933312 _widget_1747123933312 上线日期 datetime 673457d6837e60a418e0e56b 020100200000000000000001
454 _widget_1747133970122 _widget_1747133970122 上线失败原因 combo 673457d6837e60a418e0e56b 020100200000000000000001
455 _widget_1631071964934 _widget_1631071964934 上线失败原因描述 textarea 673457d6837e60a418e0e56b 020100200000000000000001
456 _widget_1749108058561 _widget_1749108058561 门店系统使用情况说明 textarea 673457d6837e60a418e0e56b 020100200000000000000001
457 _widget_1747123507416 _widget_1747123507416 开户门店ID text 673457d6837e60a418e0e56b 020100200000000000000001
458 _widget_1737092013289 _widget_1737092013289 公司名称 text 673457d6837e60a418e0e56b 020100200000000000000001
459 _widget_1737092013291 _widget_1737092013291 主店简称 text 673457d6837e60a418e0e56b 020100200000000000000001
460 _widget_1737092013292 _widget_1737092013292 营业执照号 text 673457d6837e60a418e0e56b 020100200000000000000001
461 _widget_1737092013293 _widget_1737092013293 营业执照名称 text 673457d6837e60a418e0e56b 020100200000000000000001
462 _widget_1737092013300 _widget_1737092013300 门店logo image 673457d6837e60a418e0e56b 020100200000000000000001
463 _widget_1737092013301 _widget_1737092013301 pc首页左上角logo image 673457d6837e60a418e0e56b 020100200000000000000001
464 _widget_1737092013302 _widget_1737092013302 pc首页左上角logo缩略图 image 673457d6837e60a418e0e56b 020100200000000000000001
465 _widget_1737092013321 _widget_1737092013321 门头照片 image 673457d6837e60a418e0e56b 020100200000000000000001
466 _widget_1737097231480 _widget_1737097231480 府 combo 673457d6837e60a418e0e56b 020100200000000000000001
467 _widget_1737097231482 _widget_1737097231482 县 combo 673457d6837e60a418e0e56b 020100200000000000000001
468 _widget_1737092013299 _widget_1737092013299 地址（省市区） text 673457d6837e60a418e0e56b 020100200000000000000001
469 _widget_1737097782393 _widget_1737097782393 详情地址 text 673457d6837e60a418e0e56b 020100200000000000000001
470 _widget_1737092013314 _widget_1737092013314 营业开始时间 text 673457d6837e60a418e0e56b 020100200000000000000001
471 _widget_1737092013313 _widget_1737092013313 营业结束时间 text 673457d6837e60a418e0e56b 020100200000000000000001
472 _widget_1737092013312 _widget_1737092013312 经度 text 673457d6837e60a418e0e56b 020100200000000000000001
473 _widget_1737092013311 _widget_1737092013311 纬度 text 673457d6837e60a418e0e56b 020100200000000000000001
474 _widget_1737092013310 _widget_1737092013310 负责人名字 text 673457d6837e60a418e0e56b 020100200000000000000001
475 _widget_1737092013308 _widget_1737092013308 负责人手机号 text 673457d6837e60a418e0e56b 020100200000000000000001
476 _widget_1737092013309 _widget_1737092013309 服务接待固话 text 673457d6837e60a418e0e56b 020100200000000000000001
477 _widget_1737092013315 _widget_1737092013315 服务接待名称 text 673457d6837e60a418e0e56b 020100200000000000000001
478 _widget_1737092013316 _widget_1737092013316 服务接待手机号 text 673457d6837e60a418e0e56b 020100200000000000000001
479 _widget_1737092013320 _widget_1737092013320 账号数上限 text 673457d6837e60a418e0e56b 020100200000000000000001
480 _widget_1737092013318 _widget_1737092013318 税号 text 673457d6837e60a418e0e56b 020100200000000000000001
481 _widget_1737092013317 _widget_1737092013317 分支编号 text 673457d6837e60a418e0e56b 020100200000000000000001
482 _widget_1737092013319 _widget_1737092013319 嘉实多内部门店编码 text 673457d6837e60a418e0e56b 020100200000000000000001
483 _widget_1737092013339 _widget_1737092013339 运营顾问(上线负责人) user 673457d6837e60a418e0e56b 020100200000000000000001
484 _widget_1737092013340 _widget_1737092013340 运营专家 user 673457d6837e60a418e0e56b 020100200000000000000001
485 _widget_1737092013341 _widget_1737092013341 区域经理 user 673457d6837e60a418e0e56b 020100200000000000000001
486 _widget_1750125550901 _widget_1750125550901 状态 text 673457d6837e60a418e0e56b 020100200000000000000001
487 _widget_1663742427909 _widget_1663742427909 客户查重：客户表内该客户数量 number 673457d6837e60a418e0e56b 020100200000000000000001
488 _widget_1709110880998 _widget_1709110880998 结算期限 combo 673457d6837e60a418e0e56b 020100200000000000000001
489 _widget_1709110881001 _widget_1709110881001 信用额度/元 number 673457d6837e60a418e0e56b 020100200000000000000001
490 _widget_1709110881002 _widget_1709110881002 发票抬头 text 673457d6837e60a418e0e56b 020100200000000000000001
491 _widget_1709110881003 _widget_1709110881003 发票税号 text 673457d6837e60a418e0e56b 020100200000000000000001
492 _widget_1709110881004 _widget_1709110881004 税种 combo 673457d6837e60a418e0e56b 020100200000000000000001
493 _widget_1709110881007 _widget_1709110881007 增值税税率 % number 673457d6837e60a418e0e56b 020100200000000000000001
494 _widget_1709110881008 _widget_1709110881008 开户电话 text 673457d6837e60a418e0e56b 020100200000000000000001
495 _widget_1709110881009 _widget_1709110881009 开户银行 combo 673457d6837e60a418e0e56b 020100200000000000000001
496 _widget_1709110881016 _widget_1709110881016 银行账户 text 673457d6837e60a418e0e56b 020100200000000000000001
497 _widget_1742174728275 _widget_1742174728275 指标归属日期 datetime 673457d6837e60a418e0e56b 67d636bb6212b7619a7a4231
498 _widget_1742091963874 _widget_1742091963874 公司ID text 673457d6837e60a418e0e56b 67d636bb6212b7619a7a4231
499 _widget_1742091963875 _widget_1742091963875 公司名称 text 673457d6837e60a418e0e56b 67d636bb6212b7619a7a4231
500 _widget_1742091963876 _widget_1742091963876 门店ID text 673457d6837e60a418e0e56b 67d636bb6212b7619a7a4231
501 _widget_1742091963877 _widget_1742091963877 门店名称 text 673457d6837e60a418e0e56b 67d636bb6212b7619a7a4231
502 _widget_1742091963878 _widget_1742091963878 门店简称 text 673457d6837e60a418e0e56b 67d636bb6212b7619a7a4231
503 _widget_1742091963879 _widget_1742091963879 门店创建时间 datetime 673457d6837e60a418e0e56b 67d636bb6212b7619a7a4231
504 _widget_1742091963880 _widget_1742091963880 指标类型 combo 673457d6837e60a418e0e56b 67d636bb6212b7619a7a4231
505 _widget_1742091963881 _widget_1742091963881 指标子类型 combo 673457d6837e60a418e0e56b 67d636bb6212b7619a7a4231
506 _widget_1742091963882 _widget_1742091963882 指标值 number 673457d6837e60a418e0e56b 67d636bb6212b7619a7a4231
507 _widget_0201002000002 _widget_0201002000002 客户名称 company 675a7f2a54c95e84fb66393e 020100200000000000000001
508 _widget_0201002000001 _widget_0201002000001 客户编码 sn 675a7f2a54c95e84fb66393e 020100200000000000000001
509 _widget_1630862543415 _widget_1630862543415 客户状态 combo 675a7f2a54c95e84fb66393e 020100200000000000000001
510 _widget_1631071964761 _widget_1631071964761 客户来源 text 675a7f2a54c95e84fb66393e 020100200000000000000001
511 _widget_1630862543434 _widget_1630862543434 客户级别 combo 675a7f2a54c95e84fb66393e 020100200000000000000001
512 _widget_0201002000005 _widget_0201002000005 所属公海 account_pool 675a7f2a54c95e84fb66393e 020100200000000000000001
513 _widget_1663742427957 _widget_1663742427957 客户查重 text 675a7f2a54c95e84fb66393e 020100200000000000000001
514 _widget_1630862543637 _widget_1630862543637 所属行业 combo 675a7f2a54c95e84fb66393e 020100200000000000000001
515 _widget_1646826421878 _widget_1646826421878 客户邮箱 text 675a7f2a54c95e84fb66393e 020100200000000000000001
516 _widget_1631071964919 _widget_1631071964919 客户地址 address 675a7f2a54c95e84fb66393e 020100200000000000000001
517 _widget_1631071964934 _widget_1631071964934 客户详情 textarea 675a7f2a54c95e84fb66393e 020100200000000000000001
518 _widget_0201002000003 _widget_0201002000003 销售负责人 user 675a7f2a54c95e84fb66393e 020100200000000000000001
519 _widget_0201002000006 _widget_0201002000006 销售归属部门 dept 675a7f2a54c95e84fb66393e 020100200000000000000001
520 _widget_0201002000004 _widget_0201002000004 协作人 usergroup 675a7f2a54c95e84fb66393e 020100200000000000000001
521 _widget_1663742427909 _widget_1663742427909 客户查重：客户表内该客户数量 number 675a7f2a54c95e84fb66393e 020100200000000000000001
522 _widget_1709110880998 _widget_1709110880998 结算期限 combo 675a7f2a54c95e84fb66393e 020100200000000000000001
523 _widget_1709110881001 _widget_1709110881001 信用额度/元 number 675a7f2a54c95e84fb66393e 020100200000000000000001
524 _widget_1709110881002 _widget_1709110881002 发票抬头 text 675a7f2a54c95e84fb66393e 020100200000000000000001
525 _widget_1709110881003 _widget_1709110881003 发票税号 text 675a7f2a54c95e84fb66393e 020100200000000000000001
526 _widget_1709110881004 _widget_1709110881004 税种 combo 675a7f2a54c95e84fb66393e 020100200000000000000001
527 _widget_1709110881007 _widget_1709110881007 增值税税率 % number 675a7f2a54c95e84fb66393e 020100200000000000000001
528 _widget_1709110881008 _widget_1709110881008 开户电话 text 675a7f2a54c95e84fb66393e 020100200000000000000001
529 _widget_1709110881009 _widget_1709110881009 开户银行 combo 675a7f2a54c95e84fb66393e 020100200000000000000001
530 _widget_1709110881016 _widget_1709110881016 银行账户 text 675a7f2a54c95e84fb66393e 020100200000000000000001
back_ground_module/output/数据快照存储/snapshot_2025-07-08.csv
+529
View File
@@ -0,0 +1,529 @@
name,widgetName,label,type,items,app_id,entry_id
_widget_1690785229260,_widget_1690785229260,怎么称呼您,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1690785229261,_widget_1690785229261,您门店或公司名称,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693382214358,_widget_1693382214358,您的联系方式,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1690785326597,_widget_1690785326597,地址,address,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1690785229266,_widget_1690785229266,备注,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1690785229284,_widget_1690785229284,客户概况,textarea,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1690787826014,_widget_1690787826014,门头照片（可上传多张）,image,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1690785229278,_widget_1690785229278,意向书来源,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1741837239117,_widget_1741837239117,业务类型,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693381022904,_widget_1693381022904,客户渠道,combo,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1715146829031,_widget_1715146829031,轻连锁类型,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1690785229280,_widget_1690785229280,小六,user,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1694154771486,_widget_1694154771486,技术专家,user,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1690785229281,_widget_1690785229281,战区经理,user,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1718855270618,_widget_1718855270618,该养车门店是否已退出？,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1718855270620,_widget_1718855270620,退出情况说明,textarea,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1718855270621,_widget_1718855270621,该养车门店是否有F6系统需求？,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1690785229282,_widget_1690785229282,意向阶段,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693551051341,_widget_1693551051341,客户门店数,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1690785229283,_widget_1690785229283,意向版本,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693381022909,_widget_1693381022909,客户沟通记录,subform,"[{'name': '_widget_1693381022911', 'widgetName': '_widget_1693381022911', 'label': '跟进日期', 'type': 'datetime'}, {'name': '_widget_1693381022912', 'widgetName': '_widget_1693381022912', 'label': '沟通方式', 'type': 'combo'}, {'name': '_widget_1693381022914', 'widgetName': '_widget_1693381022914', 'label': '沟通概要', 'type': 'textarea'}]",66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693381022908,_widget_1693381022908,下次跟进日期,datetime,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1696902504775,_widget_1696902504775,理论下次跟进日期,datetime,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1694398435902,_widget_1694398435902,最近一次沟通日期,datetime,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693381022915,_widget_1693381022915,客户在用系统名称,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693381022916,_widget_1693381022916,预计成交金额（单位：元）,number,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693381022917,_widget_1693381022917,预计成交日期,datetime,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1699321775702,_widget_1699321775702,实际成交日期,datetime,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693381022918,_widget_1693381022918,下单手机号,phone,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693381022919,_widget_1693381022919,放弃原因分类,combo,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693381022921,_widget_1693381022921,价格原因,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693381022923,_widget_1693381022923,产品原因,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693381022925,_widget_1693381022925,门店原因,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693381022930,_widget_1693381022930,加盟外部连锁,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693381022927,_widget_1693381022927,内部业务影响（包含接车宝会员宝安装服务）,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1724313867483,_widget_1724313867483,输单原因分类,combo,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1723603567435,_widget_1723603567435,竞品名称,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1693381022929,_widget_1693381022929,输单/放弃说明,textarea,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1708935626093,_widget_1708935626093,线索沟通情况,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1709019633297,_widget_1709019633297,客户业务需求,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1708935626085,_widget_1708935626085,客户手机号是否是微信号？,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1708935626087,_widget_1708935626087,企微是否已加好友？,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1708935626089,_widget_1708935626089,BOSS系统里是否有该客户信息,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1709027488072,_widget_1709027488072,客户BOSS业务信息,checkboxgroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1708935626095,_widget_1708935626095,联系人身份,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1709100220536,_widget_1709100220536,门店业务类型,combo,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1708935626104,_widget_1708935626104,客户门店工位数,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1708935626100,_widget_1708935626100,客户是否有需求,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1708935626102,_widget_1708935626102,客户主要需求功能模块（可多选）,checkboxgroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1708935626107,_widget_1708935626107,客户原系统,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1708935626091,_widget_1708935626091,客户预算,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1708935626098,_widget_1708935626098,预计使用时间,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1709186927667,_widget_1709186927667,门头照片等,image,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1709100220453,_widget_1709100220453,SDR联系记录,subform,"[{'name': '_widget_1709100220457', 'widgetName': '_widget_1709100220457', 'label': '日期时间', 'type': 'datetime'}, {'name': '_widget_1709100220455', 'widgetName': '_widget_1709100220455', 'label': '联系情况', 'type': 'text'}]",66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1708935626292,_widget_1708935626292,SDR判断客户是否需要进一步跟进,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1710292803370,_widget_1710292803370,SDR建议线索跟进时间,combo,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1710037836605,_widget_1710037836605,线索放弃说明,textarea,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1709543713740,_widget_1709543713740,SDR放弃意见,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1725501916821,_widget_1725501916821,提交时间,datetime,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1725507662927,_widget_1725507662927,提交人,user,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1690785229279,_widget_1690785229279,城市,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1692070536228,_widget_1692070536228,区,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1697423018006,_widget_1697423018006,战区,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1694076921201,_widget_1694076921201,线上线下,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1709868059118,_widget_1709868059118,线索跟进角色,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1709781645383,_widget_1709781645383,客户跟进角色,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1725875301461,_widget_1725875301461,技术支持提交人,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1725933630175,_widget_1725933630175,是否有效线索,text,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1690785229262,_widget_1690785229262,您的联系方式,phone,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_1723431564839,_widget_1723431564839,线索状态,radiogroup,,66b9678280b37f8a276b1d01,64c755cd97379b0008bf80dd
_widget_0201002000002,_widget_0201002000002,经销商名称,company,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1732095401220,_widget_1732095401220,经销商简称,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_0201002000005,_widget_0201002000005,所属公海,account_pool,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1732095401222,_widget_1732095401222,营业执照号,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1732095401223,_widget_1732095401223,营业执照名称,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1732153235945,_widget_1732153235945,详细地址,address,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1732095401224,_widget_1732095401224,负责人姓名,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1732095401225,_widget_1732095401225,负责人手机号,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1732095401226,_widget_1732095401226,联系电话,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1742200662775,_widget_1742200662775,购买年限,combo,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1742278002584,_widget_1742278002584,购买版本,combo,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1732095401227,_widget_1732095401227,经销商可购买的群数量,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_0201002000003,_widget_0201002000003,销售负责人,user,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1732153235954,_widget_1732153235954,运营顾问,user,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1732153235955,_widget_1732153235955,运营专家,user,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1732153235956,_widget_1732153235956,区域经理,user,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1741165766484,_widget_1741165766484,业务,user,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1732180937809,_widget_1732180937809,经销商ID,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1732180937812,_widget_1732180937812,开通状态,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1732180937811,_widget_1732180937811,开通时间,datetime,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1741160451740,_widget_1741160451740,系统到期时间,datetime,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1630862543415,_widget_1630862543415,客户状态,combo,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1630862543434,_widget_1630862543434,客户级别,combo,,673d8427549d00c3d753c530,020100200000000000000001
_widget_0201002000001,_widget_0201002000001,客户编码,sn,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1646826421878,_widget_1646826421878,客户邮箱,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1630862543637,_widget_1630862543637,所属行业,combo,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1732178180219,_widget_1732178180219,客户来源表单字段,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_0201002000006,_widget_0201002000006,销售归属部门,dept,,673d8427549d00c3d753c530,020100200000000000000001
_widget_0201002000004,_widget_0201002000004,协作人,usergroup,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1631071964934,_widget_1631071964934,客户详情,textarea,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1631071964761,_widget_1631071964761,客户来源,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1663742427957,_widget_1663742427957,客户查重,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1663742427909,_widget_1663742427909,客户查重：客户表内该客户数量,number,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1709110880998,_widget_1709110880998,结算期限,combo,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1709110881001,_widget_1709110881001,信用额度/元,number,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1709110881002,_widget_1709110881002,发票抬头,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1709110881003,_widget_1709110881003,发票税号,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1709110881004,_widget_1709110881004,税种,combo,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1709110881007,_widget_1709110881007,增值税税率 %,number,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1709110881008,_widget_1709110881008,开户电话,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1709110881009,_widget_1709110881009,开户银行,combo,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1709110881016,_widget_1709110881016,银行账户,text,,673d8427549d00c3d753c530,020100200000000000000001
_widget_1734062123070,_widget_1734062123070,门店名称,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123068,_widget_1734062123068,公司名称,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123071,_widget_1734062123071,门店编码,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123072,_widget_1734062123072,公司等级,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123073,_widget_1734062123073,门店类型,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123085,_widget_1734062123085,是否主店,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123067,_widget_1734062123067,公司id,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123069,_widget_1734062123069,门店id,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123169,_widget_1734062123169,经营模式,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123170,_widget_1734062123170,联系人,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123172,_widget_1734062123172,手机号码,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123179,_widget_1734062123179,是否主店,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123180,_widget_1734062123180,门店数,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123066,_widget_1734062123066,日期,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123065,_widget_1734062123065,日期批次,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1749000071375,_widget_1749000071375,日期（时间字段）,datetime,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123192,_widget_1734062123192,是否加店,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123194,_widget_1734062123194,门店规模,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123196,_widget_1734062123196,经营范围,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123197,_widget_1734062123197,维修厂类型,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123199,_widget_1734062123199,工位数,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123201,_widget_1734062123201,门店阶段,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123203,_widget_1734062123203,门店分层,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1742890765211,_widget_1742890765211,门头照片,image,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123090,_widget_1734062123090,省,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123092,_widget_1734062123092,市,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123094,_widget_1734062123094,区,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123095,_widget_1734062123095,大区,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123097,_widget_1734062123097,小区,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123099,_widget_1734062123099,前置仓名称,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123102,_widget_1734062123102,区域经理,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123103,_widget_1734062123103,续约顾问,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123105,_widget_1734062123105,运营负责人,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123204,_widget_1734062123204,运营专家,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1748496855779,_widget_1748496855779,区域经理（成员字段）,user,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1748496855780,_widget_1748496855780,运营负责人（成员字段）,user,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1748496855778,_widget_1748496855778,续约顾问（成员字段）,user,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1751877712235,_widget_1751877712235,运营专家（成员字段）,user,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123075,_widget_1734062123075,ERP操作模式,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123076,_widget_1734062123076,公众号,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123077,_widget_1734062123077,小程序,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123078,_widget_1734062123078,微信商城,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123079,_widget_1734062123079,洗车摄像头,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123106,_widget_1734062123106,有效账户数,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123175,_widget_1734062123175,安装服务,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123184,_widget_1734062123184,SaaS版本,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123074,_widget_1734062123074,客户状态,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123081,_widget_1734062123081,开户日,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123082,_widget_1734062123082,应续约日,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123083,_widget_1734062123083,使用天数,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123084,_widget_1734062123084,使用年数,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123176,_widget_1734062123176,上线日期,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123177,_widget_1734062123177,过期日,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123178,_widget_1734062123178,实际续约日,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1749000071377,_widget_1749000071377,开户日（日期字段）,datetime,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1749000071382,_widget_1749000071382,应续约日（日期字段）,datetime,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1749000071384,_widget_1749000071384,上线日期（日期字段）,datetime,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1749000071389,_widget_1749000071389,过期日（日期字段）,datetime,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1749000071391,_widget_1749000071391,实际续约日（日期字段）,datetime,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123111,_widget_1734062123111,G状态,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123115,_widget_1734062123115,活跃状态,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123117,_widget_1734062123117,近30天业务天数,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123119,_widget_1734062123119,近7天业务单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123120,_widget_1734062123120,近7天业务天数,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123122,_widget_1734062123122,UV数,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123167,_widget_1734062123167,G变化(月),text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123173,_widget_1734062123173,G月份,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123174,_widget_1734062123174,G转化率,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123182,_widget_1734062123182,G变化类型,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123183,_widget_1734062123183,G流失天数,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123185,_widget_1734062123185,M-1(G),number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123186,_widget_1734062123186,M-2(G),number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123187,_widget_1734062123187,M-3(G),number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123188,_widget_1734062123188,M-4(G),number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123189,_widget_1734062123189,M-5(G),number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123190,_widget_1734062123190,M-6(G),number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123191,_widget_1734062123191,G天数,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123202,_widget_1734062123202,本月G天数,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123116,_widget_1734062123116,近30天业务单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123155,_widget_1734062123155,近30天维修单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123156,_widget_1734062123156,近30天洗车单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123157,_widget_1734062123157,近30天维修开单天数,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123158,_widget_1734062123158,近30天洗车开单天数,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123159,_widget_1734062123159,近30天销售单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123160,_widget_1734062123160,近30天销售单开单天数,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123161,_widget_1734062123161,近30天采购单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123162,_widget_1734062123162,近30天采购开单天数,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123163,_widget_1734062123163,近30天卡业务单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123164,_widget_1734062123164,近30天卡业务天数,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123118,_widget_1734062123118,自然月业务天数,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123123,_widget_1734062123123,T_1开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123124,_widget_1734062123124,T_2开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123125,_widget_1734062123125,T_3开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123126,_widget_1734062123126,T_4开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123127,_widget_1734062123127,T_5开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123128,_widget_1734062123128,T_6开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123129,_widget_1734062123129,T_7开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123130,_widget_1734062123130,T_8开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123131,_widget_1734062123131,T_9开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123132,_widget_1734062123132,T_10开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123133,_widget_1734062123133,T_11开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123134,_widget_1734062123134,T_12开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123135,_widget_1734062123135,T_13开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123136,_widget_1734062123136,T_14开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123137,_widget_1734062123137,T_15开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123138,_widget_1734062123138,T_16开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123139,_widget_1734062123139,T_17开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123140,_widget_1734062123140,T_18开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123141,_widget_1734062123141,T_19开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123142,_widget_1734062123142,T_20开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123143,_widget_1734062123143,T_21开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123144,_widget_1734062123144,T_22开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123145,_widget_1734062123145,T_23开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123146,_widget_1734062123146,T_24开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123147,_widget_1734062123147,T_25开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123148,_widget_1734062123148,T_26开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123149,_widget_1734062123149,T_27开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123150,_widget_1734062123150,T_28开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123151,_widget_1734062123151,T_29开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123152,_widget_1734062123152,T_30开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123153,_widget_1734062123153,T_31开单量,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123080,_widget_1734062123080,is_maintenance_service,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123086,_widget_1734062123086,license_code,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123087,_widget_1734062123087,license_name,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123088,_widget_1734062123088,org_crm_id,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123089,_widget_1734062123089,province_id,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123091,_widget_1734062123091,city_id,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123093,_widget_1734062123093,area_id,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123096,_widget_1734062123096,region_short_name,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123098,_widget_1734062123098,carzone_store_id,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123100,_widget_1734062123100,customer_carzone_id,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123101,_widget_1734062123101,salesmen,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123104,_widget_1734062123104,impl_principal,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123107,_widget_1734062123107,active_user_type,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123108,_widget_1734062123108,limit_user_count,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123109,_widget_1734062123109,limit_user_type,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123110,_widget_1734062123110,is_n,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123112,_widget_1734062123112,is_v,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123113,_widget_1734062123113,is_visited,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123114,_widget_1734062123114,is_active,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123121,_widget_1734062123121,pv_count,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123154,_widget_1734062123154,etl_time,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123165,_widget_1734062123165,gd_sales_bill_count_last_30_day,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123166,_widget_1734062123166,gd_sales_bill_day_count_last_30_day,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123168,_widget_1734062123168,saas_package,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123171,_widget_1734062123171,contact_number,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123181,_widget_1734062123181,recent_bill_warning_days,number,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123193,_widget_1734062123193,pt,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123195,_widget_1734062123195,qualification_type_fmt,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123198,_widget_1734062123198,area,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123200,_widget_1734062123200,header_type_fmt,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1734062123205,_widget_1734062123205,tmall_maintain_service_status_desc,text,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1745908548852,_widget_1745908548852,江苏易捷门店归属公司,radiogroup,,675b900991ad2491c69389ca,675bb02bd2d53c2034c665e4
_widget_1742795002375,_widget_1742795002375,公司ID,text,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002376,_widget_1742795002376,公众号名称,text,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002377,_widget_1742795002377,小程序模板类型,text,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002378,_widget_1742795002378,是否开通微信商城,number,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002379,_widget_1742795002379,上架商品数,number,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002380,_widget_1742795002380,上架套餐卡数,number,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002381,_widget_1742795002381,上架实体商品数,number,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002382,_widget_1742795002382,上架项目数,number,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002383,_widget_1742795002383,上架套餐数,number,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002384,_widget_1742795002384,微信公众号粉丝数,number,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002385,_widget_1742795002385,微信公众号绑定手机粉丝数,number,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002386,_widget_1742795002386,是否开通微信小程序,number,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002387,_widget_1742795002387,微信小程序绑定用户数,number,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002388,_widget_1742795002388,微信小程序绑定手机用户量,number,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002389,_widget_1742795002389,微信订单数,number,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002390,_widget_1742795002390,微信支付订单量,number,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742795002391,_widget_1742795002391,线下订单数,number,,675b900991ad2491c69389ca,67e0f0fae622896749ba5087
_widget_1742884710674,_widget_1742884710674,门店id,text,,675b900991ad2491c69389ca,67e24f665adf5a8611f3e589
_widget_1742884710675,_widget_1742884710675,提成类型_二级分类,text,,675b900991ad2491c69389ca,67e24f665adf5a8611f3e589
_widget_1742884710676,_widget_1742884710676,提成基数（本月）,number,,675b900991ad2491c69389ca,67e24f665adf5a8611f3e589
_widget_1742884710677,_widget_1742884710677,提成基数（上月）,number,,675b900991ad2491c69389ca,67e24f665adf5a8611f3e589
_widget_1748930441629,_widget_1748930441629,公司id,text,,675b900991ad2491c69389ca,67e24f665adf5a8611f3e589
_widget_1748931089356,_widget_1748931089356,门店编码,text,,675b900991ad2491c69389ca,67e24f665adf5a8611f3e589
_widget_1748931089357,_widget_1748931089357,门店名称,text,,675b900991ad2491c69389ca,67e24f665adf5a8611f3e589
_widget_1742884829007,_widget_1742884829007,门店id,text,,675b900991ad2491c69389ca,67e24fdd8dfcfa918e17c30b
_widget_1742884829008,_widget_1742884829008,商品名称,text,,675b900991ad2491c69389ca,67e24fdd8dfcfa918e17c30b
_widget_1742884829009,_widget_1742884829009,服务期结束时间,text,,675b900991ad2491c69389ca,67e24fdd8dfcfa918e17c30b
_widget_1748930826642,_widget_1748930826642,公司id,text,,675b900991ad2491c69389ca,67e24fdd8dfcfa918e17c30b
_widget_1748931208852,_widget_1748931208852,门店编码,text,,675b900991ad2491c69389ca,67e24fdd8dfcfa918e17c30b
_widget_1748931208851,_widget_1748931208851,门店名称,text,,675b900991ad2491c69389ca,67e24fdd8dfcfa918e17c30b
_widget_1743065201885,_widget_1743065201885,公司id,text,,675b900991ad2491c69389ca,67e5107198ba1b20d5df3974
_widget_1743065201886,_widget_1743065201886,是否启动短信功能,text,,675b900991ad2491c69389ca,67e5107198ba1b20d5df3974
_widget_1743065201887,_widget_1743065201887,是否购买短信包,text,,675b900991ad2491c69389ca,67e5107198ba1b20d5df3974
_widget_1743065201888,_widget_1743065201888,累计购买总数,text,,675b900991ad2491c69389ca,67e5107198ba1b20d5df3974
_widget_1743065201889,_widget_1743065201889,累计发送成功总人数,text,,675b900991ad2491c69389ca,67e5107198ba1b20d5df3974
_widget_1743065201890,_widget_1743065201890,剩余短信条数,text,,675b900991ad2491c69389ca,67e5107198ba1b20d5df3974
_widget_1743065201891,_widget_1743065201891,第一次短信购买时间,text,,675b900991ad2491c69389ca,67e5107198ba1b20d5df3974
_widget_1743065201892,_widget_1743065201892,最近一次短信购买时间,text,,675b900991ad2491c69389ca,67e5107198ba1b20d5df3974
_widget_1743065201893,_widget_1743065201893,实付总金额,text,,675b900991ad2491c69389ca,67e5107198ba1b20d5df3974
_widget_1743065201894,_widget_1743065201894,短信剩余量是否小于20%,text,,675b900991ad2491c69389ca,67e5107198ba1b20d5df3974
_widget_1748241895830,_widget_1748241895830,门店名称,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895831,_widget_1748241895831,联系人,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895839,_widget_1748241895839,开户时间,datetime,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895842,_widget_1748241895842,门店编码,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895832,_widget_1748241895832,联系方式,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895850,_widget_1748241895850,系统版本,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895844,_widget_1748241895844,公司名称,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748246808679,_widget_1748246808679,运营顾问,user,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748246808682,_widget_1748246808682,区域经理,user,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895846,_widget_1748241895846,公司等级,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748246808681,_widget_1748246808681,运营专家,user,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895853,_widget_1748241895853,操作模式E.L/E.S,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895829,_widget_1748241895829,活跃健康状态变化,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895833,_widget_1748241895833,初始日,datetime,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895834,_widget_1748241895834,推进日,datetime,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748512176640,_widget_1748512176640,异常跟进情况描述,textarea,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748512176641,_widget_1748512176641,异常变化原因,radiogroup,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748512176643,_widget_1748512176643,正常使用,radiogroup,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748512176645,_widget_1748512176645,门店原因,radiogroup,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748512176647,_widget_1748512176647,服务原因,radiogroup,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748512176649,_widget_1748512176649,产品原因,radiogroup,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748512176651,_widget_1748512176651,未正式切换,radiogroup,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748512176655,_widget_1748512176655,跟进状态,radiogroup,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748246808678,_widget_1748246808678,当前跟进人,user,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748512176654,_widget_1748512176654,跟进时间,datetime,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1751273412737,_widget_1751273412737,是否跟进完成,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748246808680,_widget_1748246808680,区域客服,user,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895847,_widget_1748241895847,大区,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895848,_widget_1748241895848,省,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895855,_widget_1748241895855,城市,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895849,_widget_1748241895849,门店类型,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895851,_widget_1748241895851,saas客户类型,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748241895852,_widget_1748241895852,门店阶段,text,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1748247754304,_widget_1748247754304,关联数据,lookup,,675b900991ad2491c69389ca,68340de79f116c0b66b6b0cc
_widget_1751250294777,_widget_1751250294777,姓名1,text,,6694d3c4fcb69ca9a111a6c4,6861f5772b0d3575e14eba4a
_widget_1751505196330,_widget_1751505196330,图片,image,,6694d3c4fcb69ca9a111a6c4,6861f5772b0d3575e14eba4a
_widget_1751507507755,_widget_1751507507755,定位,location,,6694d3c4fcb69ca9a111a6c4,6861f5772b0d3575e14eba4a
_widget_1739951204545,_widget_1739951204545,表单类型,combo,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739252804406,_widget_1739252804406,日期,datetime,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739258942667,_widget_1739258942667,账号,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739252804419,_widget_1739252804419,日分区,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739252804397,_widget_1739252804397,产品名称,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739252804407,_widget_1739252804407,联系手机号,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739252804409,_widget_1739252804409,使用时长,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739252804396,_widget_1739252804396,开户日,datetime,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739252804408,_widget_1739252804408,到期日,datetime,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739252804410,_widget_1739252804410,续约日,datetime,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739252804400,_widget_1739252804400,客户状态,combo,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739252804413,_widget_1739252804413,近一周开单量,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739252804414,_widget_1739252804414,近一周是否活跃,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739252804415,_widget_1739252804415,G状态：近30天开单大于等于10天,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739252804416,_widget_1739252804416,当月开单天数,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739252804417,_widget_1739252804417,近30天开单天数,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1739252804418,_widget_1739252804418,当月G天数,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740036367181,_widget_1740036367181,派发日期,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740043340255,_widget_1740043340255,跟进人,user,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1741252143304,_widget_1741252143304,是否联系上·新签,combo,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1741252143306,_widget_1741252143306,是否联系上·异常,combo,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1741252143308,_widget_1741252143308,是否联系上·续约商机,combo,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1741252143310,_widget_1741252143310,是否联系上·过期召回,combo,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1741256466947,_widget_1741256466947,未接通原因备注,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740721384110,_widget_1740721384110,省市区,address,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1741312871468,_widget_1741312871468,省市区·续约,address,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740721384111,_widget_1740721384111,门店名称,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1741312871469,_widget_1741312871469,门店名称·续约,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740721384112,_widget_1740721384112,负责人姓名,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1741312871470,_widget_1741312871470,负责人姓名·续约,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740721384122,_widget_1740721384122,回访人·新签,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740721384117,_widget_1740721384117,未开单原因·新签,textarea,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740721384125,_widget_1740721384125,是否愿意继续使用·新签,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740721384127,_widget_1740721384127,回访人·异常,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740721384128,_widget_1740721384128,未开单原因·异常,textarea,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740721384129,_widget_1740721384129,是否愿意继续使用·异常,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740721384131,_widget_1740721384131,回访人·续约商机,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740721384132,_widget_1740721384132,是否有转化SaaS意愿·续约商机,combo,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740721384133,_widget_1740721384133,系统使用情况·续约商机,textarea,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1749088869175,_widget_1749088869175,SaaS转化结果·续约商机,radiogroup,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1749088869177,_widget_1749088869177,转化SaaS订单号·续约商机,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1749088869190,_widget_1749088869190,其他转化结果·续约商机,textarea,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740721384135,_widget_1740721384135,回访人·过期召回,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740721384136,_widget_1740721384136,未续约单原因·过期召回,textarea,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740721384137,_widget_1740721384137,是否有续约意愿·过期召回,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1749090854370,_widget_1749090854370,沟通跟进结果·过期召回,radiogroup,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1749090854372,_widget_1749090854372,转化SaaS订单号·过期召回,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1749090854373,_widget_1749090854373,接车宝续约订单号·过期召回,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1749090854374,_widget_1749090854374,其他召回情况说明·过期召回,textarea,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1751356539629,_widget_1751356539629,完成日期时间,datetime,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1751271771674,_widget_1751271771674,是否完成,text,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1751356033346,_widget_1751356033346,流水号,sn,,6717470a0b3975ef583c6df1,67174710da507490d8ac12c1
_widget_1740042824214,_widget_1740042824214,客服人员,user,,6717470a0b3975ef583c6df1,67b6f2462f9ac03b783d409a
_widget_1740117343937,_widget_1740117343937,开关,combo,,6717470a0b3975ef583c6df1,67b6f2462f9ac03b783d409a
_widget_1740042824216,_widget_1740042824216,下次开始位置,text,,6717470a0b3975ef583c6df1,67b6f2462f9ac03b783d409a
_widget_1740723898388,_widget_1740723898388,日期,datetime,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898389,_widget_1740723898389,产品名称,text,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898390,_widget_1740723898390,账号,text,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898391,_widget_1740723898391,联系手机号,number,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898392,_widget_1740723898392,开户日,datetime,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898393,_widget_1740723898393,使用时长,number,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898394,_widget_1740723898394,续约日,text,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898395,_widget_1740723898395,到期日,datetime,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898396,_widget_1740723898396,客户状态,text,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898397,_widget_1740723898397,近一周开单量,number,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898398,_widget_1740723898398,近一周是否活跃,number,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898399,_widget_1740723898399,G状态：近30天开单大于等于10天,number,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898400,_widget_1740723898400,当月开单天数,number,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898401,_widget_1740723898401,近30天开单天数,number,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898402,_widget_1740723898402,当月G天数,number,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898403,_widget_1740723898403,日分区,number,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898404,_widget_1740723898404,表单类型,text,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_1740723898405,_widget_1740723898405,派发日期,datetime,,6717470a0b3975ef583c6df1,67c156ba635191b64af8a110
_widget_0201002000001,_widget_0201002000001,客户编码,sn,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_0201002000002,_widget_0201002000002,门店名称,company,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1630862543434,_widget_1630862543434,客户级别,combo,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1631071964761,_widget_1631071964761,客户来源,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_0201002000005,_widget_0201002000005,所属公海,account_pool,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1663742427957,_widget_1663742427957,客户查重,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1750126318263,_widget_1750126318263,门店名称（后台传值）,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1746675108119,_widget_1746675108119,原系统名称,combo,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1749204198412,_widget_1749204198412,原系统情况描述,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1630862543637,_widget_1630862543637,门店类型,combo,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1746675108151,_widget_1746675108151,门店设备,combocheck,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1746675108121,_widget_1746675108121,门店业务,combocheck,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1746675108115,_widget_1746675108115,工位数,number,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1747321321284,_widget_1747321321284,员工数,number,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1746675108123,_widget_1746675108123,系统操作人员,combocheck,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737097782383,_widget_1737097782383,门店环境,image,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1630862543415,_widget_1630862543415,BD状态,combo,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1747123933309,_widget_1747123933309,客户BD日期,datetime,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1751366502797,_widget_1751366502797,意向程度,combo,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1747661411161,_widget_1747661411161,Test开始日期,datetime,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1747661411178,_widget_1747661411178,Test天数,number,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1747664949166,_widget_1747664949166,Test账号状态,combo,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_0201002000003,_widget_0201002000003,BD负责人,user,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_0201002000004,_widget_0201002000004,BD协作人,usergroup,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_0201002000006,_widget_0201002000006,销售归属部门,dept,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1747133970117,_widget_1747133970117,BD阻塞原因,combo,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1747669642443,_widget_1747669642443,BD阻塞原因分类,combo,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1747133970121,_widget_1747133970121,BD阻塞原因详细描述,textarea,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1749290572780,_widget_1749290572780,签约&上线负责人,user,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1747123933310,_widget_1747123933310,客户签约日期,datetime,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1747123933311,_widget_1747123933311,客户付款日期,datetime,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1749632087678,_widget_1749632087678,付款金额(泰铢),number,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1749632087641,_widget_1749632087641,付款截图,image,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1749632087639,_widget_1749632087639,上传发票附件,upload,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1740460160201,_widget_1740460160201,上线状态,combo,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1747123933312,_widget_1747123933312,上线日期,datetime,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1747133970122,_widget_1747133970122,上线失败原因,combo,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1631071964934,_widget_1631071964934,上线失败原因描述,textarea,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1749108058561,_widget_1749108058561,门店系统使用情况说明,textarea,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1747123507416,_widget_1747123507416,开户门店ID,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013289,_widget_1737092013289,公司名称,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013291,_widget_1737092013291,主店简称,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013292,_widget_1737092013292,营业执照号,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013293,_widget_1737092013293,营业执照名称,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013300,_widget_1737092013300,门店logo,image,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013301,_widget_1737092013301,pc首页左上角logo,image,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013302,_widget_1737092013302,pc首页左上角logo缩略图,image,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013321,_widget_1737092013321,门头照片,image,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737097231480,_widget_1737097231480,府,combo,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737097231482,_widget_1737097231482,县,combo,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013299,_widget_1737092013299,地址（省市区）,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737097782393,_widget_1737097782393,详情地址,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013314,_widget_1737092013314,营业开始时间,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013313,_widget_1737092013313,营业结束时间,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013312,_widget_1737092013312,经度,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013311,_widget_1737092013311,纬度,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013310,_widget_1737092013310,负责人名字,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013308,_widget_1737092013308,负责人手机号,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013309,_widget_1737092013309,服务接待固话,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013315,_widget_1737092013315,服务接待名称,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013316,_widget_1737092013316,服务接待手机号,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013320,_widget_1737092013320,账号数上限,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013318,_widget_1737092013318,税号,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013317,_widget_1737092013317,分支编号,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013319,_widget_1737092013319,嘉实多内部门店编码,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013339,_widget_1737092013339,运营顾问(上线负责人),user,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013340,_widget_1737092013340,运营专家,user,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1737092013341,_widget_1737092013341,区域经理,user,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1750125550901,_widget_1750125550901,状态,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1663742427909,_widget_1663742427909,客户查重：客户表内该客户数量,number,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1709110880998,_widget_1709110880998,结算期限,combo,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1709110881001,_widget_1709110881001,信用额度/元,number,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1709110881002,_widget_1709110881002,发票抬头,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1709110881003,_widget_1709110881003,发票税号,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1709110881004,_widget_1709110881004,税种,combo,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1709110881007,_widget_1709110881007,增值税税率 %,number,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1709110881008,_widget_1709110881008,开户电话,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1709110881009,_widget_1709110881009,开户银行,combo,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1709110881016,_widget_1709110881016,银行账户,text,,673457d6837e60a418e0e56b,020100200000000000000001
_widget_1742174728275,_widget_1742174728275,指标归属日期,datetime,,673457d6837e60a418e0e56b,67d636bb6212b7619a7a4231
_widget_1742091963874,_widget_1742091963874,公司ID,text,,673457d6837e60a418e0e56b,67d636bb6212b7619a7a4231
_widget_1742091963875,_widget_1742091963875,公司名称,text,,673457d6837e60a418e0e56b,67d636bb6212b7619a7a4231
_widget_1742091963876,_widget_1742091963876,门店ID,text,,673457d6837e60a418e0e56b,67d636bb6212b7619a7a4231
_widget_1742091963877,_widget_1742091963877,门店名称,text,,673457d6837e60a418e0e56b,67d636bb6212b7619a7a4231
_widget_1742091963878,_widget_1742091963878,门店简称,text,,673457d6837e60a418e0e56b,67d636bb6212b7619a7a4231
_widget_1742091963879,_widget_1742091963879,门店创建时间,datetime,,673457d6837e60a418e0e56b,67d636bb6212b7619a7a4231
_widget_1742091963880,_widget_1742091963880,指标类型,combo,,673457d6837e60a418e0e56b,67d636bb6212b7619a7a4231
_widget_1742091963881,_widget_1742091963881,指标子类型,combo,,673457d6837e60a418e0e56b,67d636bb6212b7619a7a4231
_widget_1742091963882,_widget_1742091963882,指标值,number,,673457d6837e60a418e0e56b,67d636bb6212b7619a7a4231
_widget_0201002000002,_widget_0201002000002,客户名称,company,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_0201002000001,_widget_0201002000001,客户编码,sn,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1630862543415,_widget_1630862543415,客户状态,combo,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1631071964761,_widget_1631071964761,客户来源,text,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1630862543434,_widget_1630862543434,客户级别,combo,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_0201002000005,_widget_0201002000005,所属公海,account_pool,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1663742427957,_widget_1663742427957,客户查重,text,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1630862543637,_widget_1630862543637,所属行业,combo,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1646826421878,_widget_1646826421878,客户邮箱,text,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1631071964919,_widget_1631071964919,客户地址,address,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1631071964934,_widget_1631071964934,客户详情,textarea,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_0201002000003,_widget_0201002000003,销售负责人,user,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_0201002000006,_widget_0201002000006,销售归属部门,dept,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_0201002000004,_widget_0201002000004,协作人,usergroup,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1663742427909,_widget_1663742427909,客户查重：客户表内该客户数量,number,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1709110880998,_widget_1709110880998,结算期限,combo,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1709110881001,_widget_1709110881001,信用额度/元,number,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1709110881002,_widget_1709110881002,发票抬头,text,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1709110881003,_widget_1709110881003,发票税号,text,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1709110881004,_widget_1709110881004,税种,combo,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1709110881007,_widget_1709110881007,增值税税率 %,number,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1709110881008,_widget_1709110881008,开户电话,text,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1709110881009,_widget_1709110881009,开户银行,combo,,675a7f2a54c95e84fb66393e,020100200000000000000001
_widget_1709110881016,_widget_1709110881016,银行账户,text,,675a7f2a54c95e84fb66393e,020100200000000000000001
1 name widgetName label type items app_id entry_id
2 _widget_1690785229260 _widget_1690785229260 怎么称呼您 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
3 _widget_1690785229261 _widget_1690785229261 您门店或公司名称 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
4 _widget_1693382214358 _widget_1693382214358 您的联系方式 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
5 _widget_1690785326597 _widget_1690785326597 地址 address 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
6 _widget_1690785229266 _widget_1690785229266 备注 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
7 _widget_1690785229284 _widget_1690785229284 客户概况 textarea 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
8 _widget_1690787826014 _widget_1690787826014 门头照片（可上传多张） image 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
9 _widget_1690785229278 _widget_1690785229278 意向书来源 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
10 _widget_1741837239117 _widget_1741837239117 业务类型 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
11 _widget_1693381022904 _widget_1693381022904 客户渠道 combo 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
12 _widget_1715146829031 _widget_1715146829031 轻连锁类型 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
13 _widget_1690785229280 _widget_1690785229280 小六 user 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
14 _widget_1694154771486 _widget_1694154771486 技术专家 user 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
15 _widget_1690785229281 _widget_1690785229281 战区经理 user 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
16 _widget_1718855270618 _widget_1718855270618 该养车门店是否已退出？ radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
17 _widget_1718855270620 _widget_1718855270620 退出情况说明 textarea 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
18 _widget_1718855270621 _widget_1718855270621 该养车门店是否有F6系统需求？ radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
19 _widget_1690785229282 _widget_1690785229282 意向阶段 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
20 _widget_1693551051341 _widget_1693551051341 客户门店数 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
21 _widget_1690785229283 _widget_1690785229283 意向版本 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
22 _widget_1693381022909 _widget_1693381022909 客户沟通记录 subform [{'name': '_widget_1693381022911', 'widgetName': '_widget_1693381022911', 'label': '跟进日期', 'type': 'datetime'}, {'name': '_widget_1693381022912', 'widgetName': '_widget_1693381022912', 'label': '沟通方式', 'type': 'combo'}, {'name': '_widget_1693381022914', 'widgetName': '_widget_1693381022914', 'label': '沟通概要', 'type': 'textarea'}] 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
23 _widget_1693381022908 _widget_1693381022908 下次跟进日期 datetime 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
24 _widget_1696902504775 _widget_1696902504775 理论下次跟进日期 datetime 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
25 _widget_1694398435902 _widget_1694398435902 最近一次沟通日期 datetime 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
26 _widget_1693381022915 _widget_1693381022915 客户在用系统名称 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
27 _widget_1693381022916 _widget_1693381022916 预计成交金额（单位：元） number 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
28 _widget_1693381022917 _widget_1693381022917 预计成交日期 datetime 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
29 _widget_1699321775702 _widget_1699321775702 实际成交日期 datetime 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
30 _widget_1693381022918 _widget_1693381022918 下单手机号 phone 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
31 _widget_1693381022919 _widget_1693381022919 放弃原因分类 combo 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
32 _widget_1693381022921 _widget_1693381022921 价格原因 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
33 _widget_1693381022923 _widget_1693381022923 产品原因 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
34 _widget_1693381022925 _widget_1693381022925 门店原因 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
35 _widget_1693381022930 _widget_1693381022930 加盟外部连锁 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
36 _widget_1693381022927 _widget_1693381022927 内部业务影响（包含接车宝会员宝安装服务） radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
37 _widget_1724313867483 _widget_1724313867483 输单原因分类 combo 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
38 _widget_1723603567435 _widget_1723603567435 竞品名称 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
39 _widget_1693381022929 _widget_1693381022929 输单/放弃说明 textarea 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
40 _widget_1708935626093 _widget_1708935626093 线索沟通情况 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
41 _widget_1709019633297 _widget_1709019633297 客户业务需求 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
42 _widget_1708935626085 _widget_1708935626085 客户手机号是否是微信号？ radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
43 _widget_1708935626087 _widget_1708935626087 企微是否已加好友？ radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
44 _widget_1708935626089 _widget_1708935626089 BOSS系统里是否有该客户信息 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
45 _widget_1709027488072 _widget_1709027488072 客户BOSS业务信息 checkboxgroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
46 _widget_1708935626095 _widget_1708935626095 联系人身份 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
47 _widget_1709100220536 _widget_1709100220536 门店业务类型 combo 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
48 _widget_1708935626104 _widget_1708935626104 客户门店工位数 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
49 _widget_1708935626100 _widget_1708935626100 客户是否有需求 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
50 _widget_1708935626102 _widget_1708935626102 客户主要需求功能模块（可多选） checkboxgroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
51 _widget_1708935626107 _widget_1708935626107 客户原系统 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
52 _widget_1708935626091 _widget_1708935626091 客户预算 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
53 _widget_1708935626098 _widget_1708935626098 预计使用时间 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
54 _widget_1709186927667 _widget_1709186927667 门头照片等 image 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
55 _widget_1709100220453 _widget_1709100220453 SDR联系记录 subform [{'name': '_widget_1709100220457', 'widgetName': '_widget_1709100220457', 'label': '日期时间', 'type': 'datetime'}, {'name': '_widget_1709100220455', 'widgetName': '_widget_1709100220455', 'label': '联系情况', 'type': 'text'}] 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
56 _widget_1708935626292 _widget_1708935626292 SDR判断客户是否需要进一步跟进 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
57 _widget_1710292803370 _widget_1710292803370 SDR建议线索跟进时间 combo 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
58 _widget_1710037836605 _widget_1710037836605 线索放弃说明 textarea 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
59 _widget_1709543713740 _widget_1709543713740 SDR放弃意见 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
60 _widget_1725501916821 _widget_1725501916821 提交时间 datetime 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
61 _widget_1725507662927 _widget_1725507662927 提交人 user 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
62 _widget_1690785229279 _widget_1690785229279 城市 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
63 _widget_1692070536228 _widget_1692070536228 区 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
64 _widget_1697423018006 _widget_1697423018006 战区 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
65 _widget_1694076921201 _widget_1694076921201 线上线下 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
66 _widget_1709868059118 _widget_1709868059118 线索跟进角色 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
67 _widget_1709781645383 _widget_1709781645383 客户跟进角色 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
68 _widget_1725875301461 _widget_1725875301461 技术支持提交人 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
69 _widget_1725933630175 _widget_1725933630175 是否有效线索 text 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
70 _widget_1690785229262 _widget_1690785229262 您的联系方式 phone 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
71 _widget_1723431564839 _widget_1723431564839 线索状态 radiogroup 66b9678280b37f8a276b1d01 64c755cd97379b0008bf80dd
72 _widget_0201002000002 _widget_0201002000002 经销商名称 company 673d8427549d00c3d753c530 020100200000000000000001
73 _widget_1732095401220 _widget_1732095401220 经销商简称 text 673d8427549d00c3d753c530 020100200000000000000001
74 _widget_0201002000005 _widget_0201002000005 所属公海 account_pool 673d8427549d00c3d753c530 020100200000000000000001
75 _widget_1732095401222 _widget_1732095401222 营业执照号 text 673d8427549d00c3d753c530 020100200000000000000001
76 _widget_1732095401223 _widget_1732095401223 营业执照名称 text 673d8427549d00c3d753c530 020100200000000000000001
77 _widget_1732153235945 _widget_1732153235945 详细地址 address 673d8427549d00c3d753c530 020100200000000000000001
78 _widget_1732095401224 _widget_1732095401224 负责人姓名 text 673d8427549d00c3d753c530 020100200000000000000001
79 _widget_1732095401225 _widget_1732095401225 负责人手机号 text 673d8427549d00c3d753c530 020100200000000000000001
80 _widget_1732095401226 _widget_1732095401226 联系电话 text 673d8427549d00c3d753c530 020100200000000000000001
81 _widget_1742200662775 _widget_1742200662775 购买年限 combo 673d8427549d00c3d753c530 020100200000000000000001
82 _widget_1742278002584 _widget_1742278002584 购买版本 combo 673d8427549d00c3d753c530 020100200000000000000001
83 _widget_1732095401227 _widget_1732095401227 经销商可购买的群数量 text 673d8427549d00c3d753c530 020100200000000000000001
84 _widget_0201002000003 _widget_0201002000003 销售负责人 user 673d8427549d00c3d753c530 020100200000000000000001
85 _widget_1732153235954 _widget_1732153235954 运营顾问 user 673d8427549d00c3d753c530 020100200000000000000001
86 _widget_1732153235955 _widget_1732153235955 运营专家 user 673d8427549d00c3d753c530 020100200000000000000001
87 _widget_1732153235956 _widget_1732153235956 区域经理 user 673d8427549d00c3d753c530 020100200000000000000001
88 _widget_1741165766484 _widget_1741165766484 业务 user 673d8427549d00c3d753c530 020100200000000000000001
89 _widget_1732180937809 _widget_1732180937809 经销商ID text 673d8427549d00c3d753c530 020100200000000000000001
90 _widget_1732180937812 _widget_1732180937812 开通状态 text 673d8427549d00c3d753c530 020100200000000000000001
91 _widget_1732180937811 _widget_1732180937811 开通时间 datetime 673d8427549d00c3d753c530 020100200000000000000001
92 _widget_1741160451740 _widget_1741160451740 系统到期时间 datetime 673d8427549d00c3d753c530 020100200000000000000001
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250 _widget_1734062123110 _widget_1734062123110 is_n number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
251 _widget_1734062123112 _widget_1734062123112 is_v number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
252 _widget_1734062123113 _widget_1734062123113 is_visited number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
253 _widget_1734062123114 _widget_1734062123114 is_active number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
254 _widget_1734062123121 _widget_1734062123121 pv_count number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
255 _widget_1734062123154 _widget_1734062123154 etl_time text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
256 _widget_1734062123165 _widget_1734062123165 gd_sales_bill_count_last_30_day number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
257 _widget_1734062123166 _widget_1734062123166 gd_sales_bill_day_count_last_30_day number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
258 _widget_1734062123168 _widget_1734062123168 saas_package number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
259 _widget_1734062123171 _widget_1734062123171 contact_number text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
260 _widget_1734062123181 _widget_1734062123181 recent_bill_warning_days number 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
261 _widget_1734062123193 _widget_1734062123193 pt text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
262 _widget_1734062123195 _widget_1734062123195 qualification_type_fmt text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
263 _widget_1734062123198 _widget_1734062123198 area text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
264 _widget_1734062123200 _widget_1734062123200 header_type_fmt text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
265 _widget_1734062123205 _widget_1734062123205 tmall_maintain_service_status_desc text 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
266 _widget_1745908548852 _widget_1745908548852 江苏易捷门店归属公司 radiogroup 675b900991ad2491c69389ca 675bb02bd2d53c2034c665e4
267 _widget_1742795002375 _widget_1742795002375 公司ID text 675b900991ad2491c69389ca 67e0f0fae622896749ba5087
268 _widget_1742795002376 _widget_1742795002376 公众号名称 text 675b900991ad2491c69389ca 67e0f0fae622896749ba5087
269 _widget_1742795002377 _widget_1742795002377 小程序模板类型 text 675b900991ad2491c69389ca 67e0f0fae622896749ba5087
270 _widget_1742795002378 _widget_1742795002378 是否开通微信商城 number 675b900991ad2491c69389ca 67e0f0fae622896749ba5087
271 _widget_1742795002379 _widget_1742795002379 上架商品数 number 675b900991ad2491c69389ca 67e0f0fae622896749ba5087
272 _widget_1742795002380 _widget_1742795002380 上架套餐卡数 number 675b900991ad2491c69389ca 67e0f0fae622896749ba5087
273 _widget_1742795002381 _widget_1742795002381 上架实体商品数 number 675b900991ad2491c69389ca 67e0f0fae622896749ba5087
274 _widget_1742795002382 _widget_1742795002382 上架项目数 number 675b900991ad2491c69389ca 67e0f0fae622896749ba5087
275 _widget_1742795002383 _widget_1742795002383 上架套餐数 number 675b900991ad2491c69389ca 67e0f0fae622896749ba5087
276 _widget_1742795002384 _widget_1742795002384 微信公众号粉丝数 number 675b900991ad2491c69389ca 67e0f0fae622896749ba5087
277 _widget_1742795002385 _widget_1742795002385 微信公众号绑定手机粉丝数 number 675b900991ad2491c69389ca 67e0f0fae622896749ba5087
278 _widget_1742795002386 _widget_1742795002386 是否开通微信小程序 number 675b900991ad2491c69389ca 67e0f0fae622896749ba5087
279 _widget_1742795002387 _widget_1742795002387 微信小程序绑定用户数 number 675b900991ad2491c69389ca 67e0f0fae622896749ba5087
280 _widget_1742795002388 _widget_1742795002388 微信小程序绑定手机用户量 number 675b900991ad2491c69389ca 67e0f0fae622896749ba5087
281 _widget_1742795002389 _widget_1742795002389 微信订单数 number 675b900991ad2491c69389ca 67e0f0fae622896749ba5087
282 _widget_1742795002390 _widget_1742795002390 微信支付订单量 number 675b900991ad2491c69389ca 67e0f0fae622896749ba5087
283 _widget_1742795002391 _widget_1742795002391 线下订单数 number 675b900991ad2491c69389ca 67e0f0fae622896749ba5087
284 _widget_1742884710674 _widget_1742884710674 门店id text 675b900991ad2491c69389ca 67e24f665adf5a8611f3e589
285 _widget_1742884710675 _widget_1742884710675 提成类型_二级分类 text 675b900991ad2491c69389ca 67e24f665adf5a8611f3e589
286 _widget_1742884710676 _widget_1742884710676 提成基数（本月） number 675b900991ad2491c69389ca 67e24f665adf5a8611f3e589
287 _widget_1742884710677 _widget_1742884710677 提成基数（上月） number 675b900991ad2491c69389ca 67e24f665adf5a8611f3e589
288 _widget_1748930441629 _widget_1748930441629 公司id text 675b900991ad2491c69389ca 67e24f665adf5a8611f3e589
289 _widget_1748931089356 _widget_1748931089356 门店编码 text 675b900991ad2491c69389ca 67e24f665adf5a8611f3e589
290 _widget_1748931089357 _widget_1748931089357 门店名称 text 675b900991ad2491c69389ca 67e24f665adf5a8611f3e589
291 _widget_1742884829007 _widget_1742884829007 门店id text 675b900991ad2491c69389ca 67e24fdd8dfcfa918e17c30b
292 _widget_1742884829008 _widget_1742884829008 商品名称 text 675b900991ad2491c69389ca 67e24fdd8dfcfa918e17c30b
293 _widget_1742884829009 _widget_1742884829009 服务期结束时间 text 675b900991ad2491c69389ca 67e24fdd8dfcfa918e17c30b
294 _widget_1748930826642 _widget_1748930826642 公司id text 675b900991ad2491c69389ca 67e24fdd8dfcfa918e17c30b
295 _widget_1748931208852 _widget_1748931208852 门店编码 text 675b900991ad2491c69389ca 67e24fdd8dfcfa918e17c30b
296 _widget_1748931208851 _widget_1748931208851 门店名称 text 675b900991ad2491c69389ca 67e24fdd8dfcfa918e17c30b
297 _widget_1743065201885 _widget_1743065201885 公司id text 675b900991ad2491c69389ca 67e5107198ba1b20d5df3974
298 _widget_1743065201886 _widget_1743065201886 是否启动短信功能 text 675b900991ad2491c69389ca 67e5107198ba1b20d5df3974
299 _widget_1743065201887 _widget_1743065201887 是否购买短信包 text 675b900991ad2491c69389ca 67e5107198ba1b20d5df3974
300 _widget_1743065201888 _widget_1743065201888 累计购买总数 text 675b900991ad2491c69389ca 67e5107198ba1b20d5df3974
301 _widget_1743065201889 _widget_1743065201889 累计发送成功总人数 text 675b900991ad2491c69389ca 67e5107198ba1b20d5df3974
302 _widget_1743065201890 _widget_1743065201890 剩余短信条数 text 675b900991ad2491c69389ca 67e5107198ba1b20d5df3974
303 _widget_1743065201891 _widget_1743065201891 第一次短信购买时间 text 675b900991ad2491c69389ca 67e5107198ba1b20d5df3974
304 _widget_1743065201892 _widget_1743065201892 最近一次短信购买时间 text 675b900991ad2491c69389ca 67e5107198ba1b20d5df3974
305 _widget_1743065201893 _widget_1743065201893 实付总金额 text 675b900991ad2491c69389ca 67e5107198ba1b20d5df3974
306 _widget_1743065201894 _widget_1743065201894 短信剩余量是否小于20% text 675b900991ad2491c69389ca 67e5107198ba1b20d5df3974
307 _widget_1748241895830 _widget_1748241895830 门店名称 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
308 _widget_1748241895831 _widget_1748241895831 联系人 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
309 _widget_1748241895839 _widget_1748241895839 开户时间 datetime 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
310 _widget_1748241895842 _widget_1748241895842 门店编码 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
311 _widget_1748241895832 _widget_1748241895832 联系方式 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
312 _widget_1748241895850 _widget_1748241895850 系统版本 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
313 _widget_1748241895844 _widget_1748241895844 公司名称 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
314 _widget_1748246808679 _widget_1748246808679 运营顾问 user 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
315 _widget_1748246808682 _widget_1748246808682 区域经理 user 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
316 _widget_1748241895846 _widget_1748241895846 公司等级 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
317 _widget_1748246808681 _widget_1748246808681 运营专家 user 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
318 _widget_1748241895853 _widget_1748241895853 操作模式E.L/E.S text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
319 _widget_1748241895829 _widget_1748241895829 活跃健康状态变化 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
320 _widget_1748241895833 _widget_1748241895833 初始日 datetime 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
321 _widget_1748241895834 _widget_1748241895834 推进日 datetime 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
322 _widget_1748512176640 _widget_1748512176640 异常跟进情况描述 textarea 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
323 _widget_1748512176641 _widget_1748512176641 异常变化原因 radiogroup 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
324 _widget_1748512176643 _widget_1748512176643 正常使用 radiogroup 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
325 _widget_1748512176645 _widget_1748512176645 门店原因 radiogroup 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
326 _widget_1748512176647 _widget_1748512176647 服务原因 radiogroup 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
327 _widget_1748512176649 _widget_1748512176649 产品原因 radiogroup 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
328 _widget_1748512176651 _widget_1748512176651 未正式切换 radiogroup 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
329 _widget_1748512176655 _widget_1748512176655 跟进状态 radiogroup 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
330 _widget_1748246808678 _widget_1748246808678 当前跟进人 user 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
331 _widget_1748512176654 _widget_1748512176654 跟进时间 datetime 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
332 _widget_1751273412737 _widget_1751273412737 是否跟进完成 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
333 _widget_1748246808680 _widget_1748246808680 区域客服 user 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
334 _widget_1748241895847 _widget_1748241895847 大区 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
335 _widget_1748241895848 _widget_1748241895848 省 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
336 _widget_1748241895855 _widget_1748241895855 城市 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
337 _widget_1748241895849 _widget_1748241895849 门店类型 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
338 _widget_1748241895851 _widget_1748241895851 saas客户类型 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
339 _widget_1748241895852 _widget_1748241895852 门店阶段 text 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
340 _widget_1748247754304 _widget_1748247754304 关联数据 lookup 675b900991ad2491c69389ca 68340de79f116c0b66b6b0cc
341 _widget_1751250294777 _widget_1751250294777 姓名1 text 6694d3c4fcb69ca9a111a6c4 6861f5772b0d3575e14eba4a
342 _widget_1751505196330 _widget_1751505196330 图片 image 6694d3c4fcb69ca9a111a6c4 6861f5772b0d3575e14eba4a
343 _widget_1751507507755 _widget_1751507507755 定位 location 6694d3c4fcb69ca9a111a6c4 6861f5772b0d3575e14eba4a
344 _widget_1739951204545 _widget_1739951204545 表单类型 combo 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
345 _widget_1739252804406 _widget_1739252804406 日期 datetime 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
346 _widget_1739258942667 _widget_1739258942667 账号 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
347 _widget_1739252804419 _widget_1739252804419 日分区 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
348 _widget_1739252804397 _widget_1739252804397 产品名称 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
349 _widget_1739252804407 _widget_1739252804407 联系手机号 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
350 _widget_1739252804409 _widget_1739252804409 使用时长 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
351 _widget_1739252804396 _widget_1739252804396 开户日 datetime 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
352 _widget_1739252804408 _widget_1739252804408 到期日 datetime 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
353 _widget_1739252804410 _widget_1739252804410 续约日 datetime 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
354 _widget_1739252804400 _widget_1739252804400 客户状态 combo 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
355 _widget_1739252804413 _widget_1739252804413 近一周开单量 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
356 _widget_1739252804414 _widget_1739252804414 近一周是否活跃 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
357 _widget_1739252804415 _widget_1739252804415 G状态：近30天开单大于等于10天 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
358 _widget_1739252804416 _widget_1739252804416 当月开单天数 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
359 _widget_1739252804417 _widget_1739252804417 近30天开单天数 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
360 _widget_1739252804418 _widget_1739252804418 当月G天数 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
361 _widget_1740036367181 _widget_1740036367181 派发日期 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
362 _widget_1740043340255 _widget_1740043340255 跟进人 user 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
363 _widget_1741252143304 _widget_1741252143304 是否联系上·新签 combo 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
364 _widget_1741252143306 _widget_1741252143306 是否联系上·异常 combo 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
365 _widget_1741252143308 _widget_1741252143308 是否联系上·续约商机 combo 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
366 _widget_1741252143310 _widget_1741252143310 是否联系上·过期召回 combo 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
367 _widget_1741256466947 _widget_1741256466947 未接通原因备注 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
368 _widget_1740721384110 _widget_1740721384110 省市区 address 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
369 _widget_1741312871468 _widget_1741312871468 省市区·续约 address 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
370 _widget_1740721384111 _widget_1740721384111 门店名称 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
371 _widget_1741312871469 _widget_1741312871469 门店名称·续约 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
372 _widget_1740721384112 _widget_1740721384112 负责人姓名 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
373 _widget_1741312871470 _widget_1741312871470 负责人姓名·续约 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
374 _widget_1740721384122 _widget_1740721384122 回访人·新签 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
375 _widget_1740721384117 _widget_1740721384117 未开单原因·新签 textarea 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
376 _widget_1740721384125 _widget_1740721384125 是否愿意继续使用·新签 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
377 _widget_1740721384127 _widget_1740721384127 回访人·异常 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
378 _widget_1740721384128 _widget_1740721384128 未开单原因·异常 textarea 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
379 _widget_1740721384129 _widget_1740721384129 是否愿意继续使用·异常 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
380 _widget_1740721384131 _widget_1740721384131 回访人·续约商机 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
381 _widget_1740721384132 _widget_1740721384132 是否有转化SaaS意愿·续约商机 combo 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
382 _widget_1740721384133 _widget_1740721384133 系统使用情况·续约商机 textarea 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
383 _widget_1749088869175 _widget_1749088869175 SaaS转化结果·续约商机 radiogroup 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
384 _widget_1749088869177 _widget_1749088869177 转化SaaS订单号·续约商机 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
385 _widget_1749088869190 _widget_1749088869190 其他转化结果·续约商机 textarea 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
386 _widget_1740721384135 _widget_1740721384135 回访人·过期召回 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
387 _widget_1740721384136 _widget_1740721384136 未续约单原因·过期召回 textarea 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
388 _widget_1740721384137 _widget_1740721384137 是否有续约意愿·过期召回 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
389 _widget_1749090854370 _widget_1749090854370 沟通跟进结果·过期召回 radiogroup 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
390 _widget_1749090854372 _widget_1749090854372 转化SaaS订单号·过期召回 text 6717470a0b3975ef583c6df1 67174710da507490d8ac12c1
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back_ground_module/revisit_all_information.py
+853
View File
@@ -0,0 +1,853 @@
import datetime
import os
import time
import requests
from api import API
import re
from back_ground_module import CommonModule
import pandas as pd
from log_config import configure_task_logger, configure_error_task_logger
api_instance = API()
common_module = CommonModule()
# start_time = datetime.datetime.now()
# 获取已经配置好的常规日志记录器
logger = configure_task_logger()
# 获取已经配置好的错误任务日志记录器
error_task_logger = configure_error_task_logger()
class RevisitAllInformation:
"""
日常回访手动触发
"""
def __init__(self):
self.get_feature_usage = None
self.saas_create_time = None
self.index = None
self.date_one = None
self.data_NGV_S = None
self.date_list = None
self.Smart_detection = None
self.service_remind = None
self.NGV_data_list = None
self.permissions_table = None
self.staff_id_list = None
self.json_list = []
self.policy_recognition = None
self.widget_list = None
self.private_domain = None
self.public_domain = None
self.public_domain_list = None
self.different_industries = None
self.different_industries_list = None
self.groupnotification = None
def calculate_date_one(self, start_offset=0):
"""
计算从当前日期（或指定偏移量的日期）开始，往前遍历遇到date_list中日期的次数。
参数:
- start_offset: 从当前日期起始的天数偏移量，默认为0（即今天）。负数表示过去，正数表示未来。
返回:
- date_one: 遍历到date_list中日期的次数。
"""
jdy_date = datetime.datetime.now().strftime("%Y-%m-%d")
jdy_start_time = datetime.datetime.now().strftime("%Y-%m-%d ")
# 设置起始日期
now_time = datetime.datetime.now() + datetime.timedelta(days=start_offset)
# 初始化计数器
date_one = 1
print("当前日期：", now_time.strftime("%Y-%m-%d"))
# 检查起始日期是否在date_list中
if now_time.strftime("%Y-%m-%d") in self.date_list:
date_one = 0
print("开始次数：", date_one)
else:
# 遍历日期
for i in range(1, 10):
new_date = now_time + datetime.timedelta(days=-i)
new_date_str = new_date.strftime("%Y-%m-%d")
print("遍历日期：", new_date_str)
if new_date_str in self.date_list:
date_one += 1
print("节假日期：", new_date_str)
else:
break
print("遍历次数：", date_one)
return date_one
@staticmethod
def download_url_content(url, save_path):
"""
下载指定 URL 的内容并保存到本地文件。
:param url: 要下载内容的 URL
:param save_path: 保存文件的路径
"""
try:
# 发送 GET 请求以获取内容
response = requests.get(url, stream=True)
response.raise_for_status() # 如果响应状态码不是 200，抛出异常
# 确保保存目录存在
os.makedirs(os.path.dirname(save_path), exist_ok=True)
# 将内容写入文件
with open(save_path, 'wb') as file:
for chunk in response.iter_content(chunk_size=8192): # 分块写入，避免占用过多内存
if chunk: # 过滤掉空块
file.write(chunk)
print(f"文件已成功保存到 {save_path}")
except requests.exceptions.RequestException as e:
print(f"下载失败: {e}")
except Exception as e:
print(f"发生错误: {e}")
def load_all_data(self):
"""加载所有必要的数据表"""
# 省市区人员关系表
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "676512ac3e54dc3159460c0a"}
json_dict = api_instance.entry_data_list(payload)
self.json_list = json_dict.get("data")
# 获取简道云员工id
payload = {"api_key": "6694d3c4fcb69ca9a111a6c4",
"entry_id": "6769204a1902c9341340a1bc",
}
staff_id = api_instance.entry_data_list(payload)
self.staff_id_list = staff_id.get("data") # api请求格式，将数据封装在data字典里
# 获取权限表信息
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "675b96c14e839f90fef1647c"}
self.permissions_table = api_instance.entry_data_list(payload).get("data", [])
# 获取NGV数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "675bb02bd2d53c2034c665e4"}
self.NGV_data_list = api_instance.entry_data_list(payload).get("data", [])
# print("NGV获取后的类型：", type(self.NGV_data_list))
# 获取服务提醒-数据支持表单数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "676bb7bda3029720f1083e99"}
self.service_remind = api_instance.entry_data_list(payload).get("data", [])
# 获取智能检测-数据支持表单数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "676bb99649ab3ac975af6e39"}
self.Smart_detection = api_instance.entry_data_list(payload).get("data", [])
# 获取功能使用情况表
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "6763bbf657bd8fb76fcb41b2"}
self.get_feature_usage = api_instance.entry_data_list(payload).get("data", [])
# 获取保单识别表
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "6773a60d30ed87ff9f68d3c5"}
self.policy_recognition = api_instance.entry_data_list(payload).get("data")
# 提取 _widget_1735632397600 的值并存储在列表中
self.widget_list = [item['_widget_1735632397600'] for item in self.policy_recognition]
# 获取私域小程序-数据支持表单数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "67e0f0fae622896749ba5087"}
self.private_domain = api_instance.entry_data_list(payload).get("data", [])
# 提取 _widget_1742795002375 的值并存储在列表中
# self.private_domain = [item['_widget_1742795002375'] for item in self.private_domain]
# 获取公域小程序-数据支持表单数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "67e0c702c8f603b997980999"}
self.public_domain = api_instance.entry_data_list(payload).get("data", [])
# 提取 _widget_1742784257506 的值并存储在列表中
self.public_domain_list = [item['_widget_1742784257506'] for item in self.public_domain]
# 获取异业合作-数据支持表单数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "67e24fdd8dfcfa918e17c30b"}
self.different_industries = api_instance.entry_data_list(payload).get("data", [])
# 提取 _widget_1742784257506 的值并存储在列表中
self.different_industries_list = [item['_widget_1742884829007'] for item in self.different_industries]
# 获取短信-数据支持表单数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "67e5107198ba1b20d5df3974"}
self.groupnotification = api_instance.entry_data_list(payload).get("data", [])
@staticmethod
def build_index(json_list):
index = {}
# print(json_list)
for json_item in json_list:
# json_item = json_item.get("data")
# print(json_item)
try:
key = (json_item['_widget_1734677164861'], json_item['_widget_1734677164862'],
json_item['_widget_1734677164863']) # 省市区
if '_widget_1734677164871' not in json_item: # 日常回访客服
raise KeyError("缺少 '日常回访客服' 键")
index[key] = json_item
except KeyError as e:
print(f"警告：{e}，跳过该条记录: {json_item}")
continue
return index
@staticmethod
def find_customer_service(province_name, city_name, area_name, index):
key = (province_name, city_name, area_name)
# print(index)
if key not in index:
return "数据缺失: 未找到对应的日常回访客服"
return index[key]
@staticmethod
def remove_parentheses(text: str) -> str:
# 使用正则表达式匹配并去除括号及其内容
# \s* 表示匹配零个或多个空白字符（处理括号前后可能存在的空格）
# $ 和 $ 分别表示匹配左括号和右括号
# 中间的 .*? 表示非贪婪地匹配任意数量的字符（包括没有字符的情况）
cleaned_text = re.sub(r'\s*$.*?$\s*', '', text)
# 为了确保同时处理中文括号，再进行一次替换
cleaned_text = re.sub(r'\s*（.*?）\s*', '', cleaned_text)
return cleaned_text.strip() # 去除两端多余的空白字符
@staticmethod
def get_staff_id(row_item, name):
"""辅助函数，用于获取员工ID"""
if str(row_item["_widget_1734942794144"]) == str(name): # 检查姓名是否匹配
return row_item["_widget_1734942794145"] # 返回员工ID
return None
def assign_customer_service(self, province_name, city_name, area_name, index):
"""根据省市区派发给日常回访客服"""
try:
customer_service_info = self.find_customer_service(province_name, city_name, area_name, index)
# 定义一个辅助函数，用于安全地获取多层字段中的 username
def safe_get_username(data, key):
try:
if isinstance(data, dict):
return data.get(key, {}).get('username', "")
return ""
except:
return ""
relationship_manager = safe_get_username(customer_service_info, '_widget_1734677164864')
customer_service = safe_get_username(customer_service_info, '_widget_1734677164871')
technician = safe_get_username(customer_service_info, '_widget_1734677164866')
area_manager = safe_get_username(customer_service_info, '_widget_1734677164865')
return relationship_manager, customer_service, technician, area_manager
except Exception as e:
print(f"Error finding customer service: {e}")
return "分配失败，请检查", "分配失败，请检查", "分配失败，请检查"
def main(self):
task_start_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
global png_url, key, upload_key
self.load_all_data()
self.date_list = common_module.get_holiday_list()
self.data_NGV_S = common_module.get_ngv_details(days_back=1).astype(str) # 获取data_NGV 并转为str
self.date_one = self.calculate_date_one(start_offset=0)
self.index = self.build_index(self.json_list)
self.saas_create_time_180 = 173 # 新签日期
self.saas_create_time_90 = 83 # 新签日期
print("开始运行main")
print(self.date_one)
all_data=[]
for i in range(0, self.date_one): # 从NGV总表过滤
# now_time = datetime.datetime.now() + datetime.timedelta(days=-76)
# now_time = now_time + datetime.timedelta(days=-i)
now_time = datetime.datetime.now() + datetime.timedelta(days=-i)
today = now_time + datetime.timedelta(days=-self.saas_create_time_180)
formatted_today_180 = today.strftime("%Y-%m-%d")
today = now_time + datetime.timedelta(days=-self.saas_create_time_90)
formatted_today_90 = today.strftime("%Y-%m-%d")
print("SaaS开户回访日期：", formatted_today_180, formatted_today_90)
data_NGV = self.data_NGV_S.copy()
def replace_values(series):
# 使用条件判断来进行替换
return series.apply(lambda x: '' if pd.isna(x) or x in ['NA', 'None', ''] else x)
# 对整个DataFrame的所有列应用替换函数
data_NGV = data_NGV.apply(replace_values)
# data_NGV.to_csv("dayinNGV.csv")
# 定义优先级顺序
edition_order = ['皇冠版', '至尊版', '尊享版', '旗舰版', '标准版', '进阶版', '基础版', '入门版']
customer_type_order = ["F", "E", "D", "C", "B", "A"] # 索引越小优先级越高
group_grade_order = ['全国KA（FMVP）', '区域KA（MVP）', '重要客户（SVIP）', '普通客户（VIP）']
# 创建映射字典，并为不在列表中的值设置默认值
edition_map = {edition: idx for idx, edition in enumerate(edition_order)}
customer_type_map = {ctype: idx for idx, ctype in enumerate(customer_type_order)}
group_grade_map = {grade: idx for idx, grade in enumerate(group_grade_order)}
# 添加用于排序的新列，并处理不在映射字典中的值
data_NGV['edition_rank'] = data_NGV['saas_edition_fmt'].map(edition_map).fillna(0).astype(
int) # 缺失值用最高优先级填充
data_NGV['customer_type_rank'] = data_NGV['saas_customer_type'].map(customer_type_map).fillna(0).astype(int)
data_NGV['group_grade_rank'] = data_NGV['group_grade'].map(group_grade_map).fillna(0).astype(int)
# data_NGV.to_csv("88855.csv")
# 找到每组中 edition_rank 最小值对应的行
best_edition_idx = data_NGV.groupby('id_own_group')['edition_rank'].idxmin()
best_edition_rows = data_NGV.loc[best_edition_idx]
best_edition_rows['max_saas_edition'] = best_edition_rows['saas_edition_fmt']
# 找到每组中 customer_type_rank 最小值对应的行
best_customer_type_idx = data_NGV.groupby('id_own_group')['customer_type_rank'].idxmin()
best_customer_type_rows = data_NGV.loc[best_customer_type_idx]
best_customer_type_rows['max_saas_customer_type'] = best_customer_type_rows['customer_type_rank'].apply(
lambda x: customer_type_order[x])
# 找到每组中 group_grade_rank 最小值对应的行
best_group_grade_idx = data_NGV.groupby('id_own_group')['group_grade_rank'].idxmin()
best_group_grade_rows = data_NGV.loc[best_group_grade_idx]
best_group_grade_rows['max_group_grade'] = best_group_grade_rows['group_grade']
# 合并最佳值回到原数据集
best_values = (
best_edition_rows[['id_own_group', 'max_saas_edition']]
.merge(best_customer_type_rows[['id_own_group', 'max_saas_customer_type']], on='id_own_group',
how='outer')
.merge(best_group_grade_rows[['id_own_group', 'max_group_grade']], on='id_own_group', how='outer')
)
# 将最佳值合并回原数据集
data_NGV = data_NGV.merge(best_values, on='id_own_group', how='left')
condition = (data_NGV['is_main_org'] == 1) & (data_NGV['org_status'] == '过期') # 步骤2: 过滤条件
ngvv2 = data_NGV[condition]
# ngvv2.to_excel(r"C:\Users\Administrator.DESKTOP-7IC2USJ\Desktop\NGVV2.xlsx")
data_NGV_V2 = data_NGV.copy() # 步骤3: 检查id_own_group是否存在于ngvv2中
data_NGV_V2['条件'] = (data_NGV_V2['org_type'] == "一般") & (data_NGV_V2['org_status'] == '留存') & (
data_NGV_V2['area_manager'] != '殷昊') & (
data_NGV_V2['area_manager'] != '孙玉蕾') & (
data_NGV_V2['is_main_org'] != 1)
data_NGV_V2 = data_NGV_V2.loc[data_NGV_V2["条件"]]
# 步骤4: 过滤存在的记录
data_NGV_V2['exists_in_ngvv2'] = data_NGV_V2['id_own_group'].isin(ngvv2['id_own_group'])
filtered_data = data_NGV_V2[data_NGV_V2['exists_in_ngvv2']]
fixed_order = ['皇冠版', '至尊版', '尊享版', '旗舰版', '标准版', '进阶版', '基础版', '入门版']
# sorted_items = sorted(filtered_data, key=lambda x: fixed_order.index(x))
fixed_order_map = {edition: index for index, edition in enumerate(fixed_order)}
filtered_data['sort_key'] = filtered_data['saas_edition_fmt'].map(fixed_order_map)
filtered_data = filtered_data.sort_values(by='sort_key').drop('sort_key', axis=1)
result = filtered_data.drop_duplicates(subset='id_own_group', keep='first')
data_NGV['条件'] = (data_NGV['org_type'] == "一般") & (data_NGV['org_status'] == '留存') & (
data_NGV['area_manager'] != '殷昊') & (
data_NGV['area_manager'] != '孙玉蕾') & (
data_NGV['is_main_org'] == "1")
data_NGV = data_NGV.loc[data_NGV["条件"]]
data_NGV = pd.concat([data_NGV, result], axis=0)
print(len(data_NGV), "20250325")
# 定义一个函数，根据 saas_create_time 字段的值设置阶段列和主要目的列的值
def set_columns(row):
if row['saas_create_time'] == formatted_today_180:
row['跟进阶段'] = '新签后180天'
row['主要目的'] = '关怀使用情况，邀约转介绍，跟进增购商机，识别首年续约风险，及时跟进提报。'
elif row['saas_create_time'] == formatted_today_90:
row['跟进阶段'] = '新签后90天'
row['主要目的'] = '关怀使用情况，解答使用问题，强化培训，挖掘增购商机。'
else:
row['跟进阶段'] = "派发异常请联系数据组！" # 返回其他默认值
row['主要目的'] = "派发异常请联系数据组！" # 返回其他默认值
return row
# 使用 apply 方法将函数应用到每一行
data_NGV = data_NGV.apply(set_columns, axis=1)
print("SaaS开户回访人数：", len(data_NGV))
print(data_NGV)
# 重置索引
data_NGV = data_NGV.reset_index(drop=True)
for index_num, row in data_NGV.iterrows(): # 对过滤后的每一条进行派发
try:
# print(row["org_code"]) # 数据验证
# print(row["service_impl_principal"])
# print(row["area_manager"])
# print(row["technician"])
payload_dict = {}
saas_use_year = re.findall(r'第([0-9]+)年', row["saas_use_year"])[0]
NGV_roles = {
'relationship_manager': row['service_impl_principal'], # 运营负责人
# 'relationship_manager': "张阳", # 运营负责人
'area_manager': row['area_manager'], # 区域经理
'technician': row['technician'], # 技术专家
'salesmen': row['salesmen'], # 销售负责人
}
for role, name in NGV_roles.items(): # 寻找对应的员工ID
for row_item in self.staff_id_list:
staff_id = self.get_staff_id(row_item, name)
if staff_id:
NGV_roles[role] = staff_id
break # 找到后退出循环
else:
NGV_roles[role] = None # 如果没有找到对应的员工ID
# 回访人员： 需确认 四年以下 technician
if int(saas_use_year) < 4:
relationship_manager, area_manager, technician, salesmen = [NGV_roles[role] for role in
['relationship_manager',
'area_manager',
'technician', 'salesmen']]
# 如果未找到运营负责人，则根据省市区派发给日常回访客服
if not relationship_manager:
relationship_manager = self.assign_customer_service(
row['province_name'], row['city_name'], row['area_name'], self.index
)[0]
if not technician:
technician = self.assign_customer_service(
row['province_name'], row['city_name'], row['area_name'], self.index
)[2]
if row["group_grade"] == "普通客户（VIP）" or row["group_grade"] == "重要客户（SVIP）":
payload_dict.update({
"_widget_1734590278288": {"value": relationship_manager}, # 跟进人是运营负责人
})
else:
payload_dict.update({
"_widget_1734590278288": {"value": technician}, # 跟进人是技术专家
})
else:
salesmen = [NGV_roles[role] for role in
['salesmen']]
# 直接根据省市区派发给日常回访客服
relationship_manager, customer_service, technician, area_manager = self.assign_customer_service(
row['province_name'], row['city_name'], row['area_name'], self.index
)
if row["group_grade"] == "普通客户（VIP）" or row["group_grade"] == "重要客户（SVIP）":
payload_dict.update({
"_widget_1734590278288": {"value": customer_service} # 跟进人是日常回访客服
})
else:
payload_dict.update({
"_widget_1734590278288": {"value": technician} # 跟进人是技术专家
})
payload_dict.update({
# "_widget_1734590278288": {"value": relationship_manager}, # 跟进人是运营负责人
"_widget_1734590278289": {"value": relationship_manager}, # 运营负责人
"_widget_1734590278290": {"value": area_manager}, # 区域经理
"_widget_1734590278291": {"value": technician}, # 技术专家
"_widget_1735290738545": {"value": salesmen} # 销售负责人
})
if payload_dict.get("_widget_1734590278288") == "02414917880947": # 如果跟进人是殷浩
payload_dict.update({
"_widget_1734590278288": {"value": "051612246035720178"}, # 跟进人是赵柄诚
})
# 输出结果
print("SaaS开户回访人员：", relationship_manager or "未分配")
print("SaaS技术专家：", technician or "未分配")
print("SaaS区域经理：", area_manager or "未分配")
# 判断权限唯一值
# pattern = r'([\u4e00-\u9fa5]+)\（'
# match = re.search(pattern, row['max_group_grade'])
# group_grade = match.group(1)
group_grade = re.sub(r'（[^）]*）', '', row['max_group_grade'])
if not row['saas_customer_type'] or row['saas_customer_type'] == 'NA' or row[
'saas_customer_type'] == 'None':
row['saas_customer_type'] = "F"
NGV_store_level_key = group_grade + row['max_saas_edition'] + row['max_saas_customer_type']
print("权限唯一值：", NGV_store_level_key)
Billing = None
for item in self.permissions_table:
if NGV_store_level_key == item.get("_widget_1734056507963"): # 合并（等级-类型-分层）
print("该门店开单的权限是：", item.get(item.get("_widget_1734055617039")))
Billing = item.get("_widget_1734055617039") # 开单
Service_Alerts = item.get("_widget_1734055617040") # 服务提醒
membership = item.get("_widget_1734055617041") # 会员卡
SMS = item.get("_widget_1734055617042") # 短信
Public_domain_applets = item.get("_widget_1734055617043") # 公域小程序
Private_domain_applets = item.get("_widget_1734055617044") # 私域小程序
Test_sheet = item.get("_widget_1734055617045") # 检测单
AI_poster = item.get("_widget_1734055617046") # AI海报
Business_wallets = item.get("_widget_1734055617047") # 企业钱包
Precision_marketing = item.get("_widget_1734055617049") # 精准营销
Paid_memberships = item.get("_widget_1734055617051") # 付费会员
business_WeCom = item.get("_widget_1734055617052") # 企业微信
Insurance_policy_identification = item.get("_widget_1734055617053") # 保险单识别
Insurance_bots = item.get("_widget_1734055617054") # 保险机器人
Camera_pick_up = item.get("_widget_1734055617055") # 摄像头接车
Camera_billing = item.get("_widget_1734055617056") # 摄像头开单
Transparent_workshop = item.get("_widget_1734055617057") # 透明车间
Cross_industry_cooperation = item.get("_widget_1734055617058") # 异业合作
BI_Insights = item.get("_widget_1734055617059") # BI洞察
payload_dict.update(
{
"_widget_1734073342350": {"value": Billing},
"_widget_1735004315757": {"value": Service_Alerts},
"_widget_1735004315756": {"value": membership},
"_widget_1735004315755": {"value": SMS},
"_widget_1735004315754": {"value": Public_domain_applets},
"_widget_1735004315753": {"value": Private_domain_applets},
"_widget_1735004315752": {"value": Test_sheet},
"_widget_1735004315751": {"value": AI_poster},
"_widget_1735004315750": {"value": Business_wallets},
"_widget_1735004315749": {"value": Precision_marketing},
"_widget_1735004315748": {"value": Paid_memberships},
"_widget_1735004315747": {"value": business_WeCom},
"_widget_1735004315746": {"value": Insurance_policy_identification},
"_widget_1735004315745": {"value": Insurance_bots},
"_widget_1735004315744": {"value": Camera_pick_up},
"_widget_1735004315743": {"value": Camera_billing},
"_widget_1735004315742": {"value": Transparent_workshop},
"_widget_1735004315741": {"value": Cross_industry_cooperation},
"_widget_1734073342352": {"value": BI_Insights},
}
)
feature_dict = {
"开单": "_widget_1734073342350",
"服务提醒": "_widget_1735004315757",
"会员卡": "_widget_1735004315756",
"短信": "_widget_1735004315755",
"公域小程序": "_widget_1735004315754",
"私域小程序": "_widget_1735004315753",
"检测单": "_widget_1735004315752",
"AI海报": "_widget_1735004315751",
"企业钱包": "_widget_1735004315750",
"精准营销": "_widget_1735004315749",
"付费会员": "_widget_1735004315748",
"企业微信": "_widget_1735004315747",
"保险单识别": "_widget_1735004315746",
"保险机器人": "_widget_1735004315745",
"摄像头接车": "_widget_1735004315744",
"摄像头开单": "_widget_1735004315743",
"透明车间": "_widget_1735004315742",
"异业合作": "_widget_1735004315741",
"BI洞察": "_widget_1734073342352",
}
# _widget_1735527329557 下次是否推荐
for new_item in self.get_feature_usage:
for feature_module, feature_value in feature_dict.items(): # 模块
if new_item.get("_widget_1735268263079") == feature_module and new_item.get(
"_widget_1735527329557") == "否" and new_item.get(
"_widget_1735280720550") == \
row["id_own_org"]: # 下次是否推荐 功能使用情况表
print(f"{feature_value}进行了更改")
payload_dict.update({f"{feature_value}": {"value": "×"}})
if new_item.get("_widget_1735268263079") == feature_module and new_item.get(
"_widget_1736414617462") == "否" and new_item.get(
"_widget_1735280720550") == \
row["id_own_org"]: # 下次是否跟进
print(f"{feature_value}进行了更改")
payload_dict.update({f"{feature_value}": {"value": "×"}})
fields_to_check = {
"_widget_1735004315763": Billing, # 开单
"_widget_1735106258016": Service_Alerts, # 服务提醒
"_widget_1735106258036": membership, # 会员卡
"_widget_1735106258086": SMS, # 短信
"_widget_1735106258112": Public_domain_applets, # 公域小程序
"_widget_1735106258141": Private_domain_applets, # 私域小程序
"_widget_1735107354648": Test_sheet, # 检测单
"_widget_1735107354725": AI_poster, # AI海报
"_widget_1735107354811": Business_wallets, # 企业钱包
"_widget_1735107354906": Precision_marketing, # 精准营销
"_widget_1735107354980": Paid_memberships, # 付费会员
"_widget_1735107355093": business_WeCom, # 企业微信
"_widget_1735107355143": Insurance_policy_identification, # 保险单识别
"_widget_1735107355235": Insurance_bots, # 保险机器人
"_widget_1735107355333": Camera_pick_up, # 摄像头接车
"_widget_1735107355392": Camera_billing, # 摄像头开单
"_widget_1735107355502": Transparent_workshop, # 透明车间
"_widget_1735107355618": Cross_industry_cooperation, # 异业合作
"_widget_1735107355740": BI_Insights # BI洞察
}
# 遍历每个字段，检查其值并更新payload_dict
for widget_id, field_name in fields_to_check.items():
if field_name == "√":
payload_dict.update({widget_id: {"value": "是"}})
break
if not Billing:
print(f"权限表请求失败或者权限表无对应关系,权限唯一值是：{NGV_store_level_key}")
if row["active_status_fmt"] == "活跃": # 开单 是否使用
payload_dict.update({"_widget_1735004315765": {"value": "是"}})
else:
payload_dict.update({"_widget_1735004315765": {"value": "否"}})
try:
if row["saas_edition_fmt"] not in ["基础版", "入门版"]: # 会员卡 是否拥有
payload_dict.update({"_widget_1735106258036": {"value": "是"}})
else:
payload_dict.update({"_widget_1735106258036": {"value": "否"}})
except Exception as e:
print(f"会员卡识别：Error finding customer service: {e}")
try:
if row["card_bill_day_count_last_30_day"] != "0": # 会员卡 是否使用
payload_dict.update({"_widget_1735106258038": {"value": "是"}})
else:
payload_dict.update({"_widget_1735106258038": {"value": "否"}})
except Exception as e:
print(f"会员卡识别：Error finding customer service: {e}")
# print(self.service_remind.get("_widget_1735112637045"))
payload_dict["_widget_1735106258018"] = {"value": "否"}
for item in self.service_remind:
if row["id_own_group"] == item.get("_widget_1735112637043"):
if int(item.get("_widget_1735112637045")) < 180 and int(
item.get("_widget_1735112637046")) == 1: # 服务提醒 是否使用
payload_dict.update({"_widget_1735106258018": {"value": "是"}})
break
elif int(item.get("_widget_1735112637048")) > 0:
payload_dict.update({"_widget_1735106258018": {"value": "是"}})
break
keys_to_check = [
"_widget_1735113110155"
] # 智能检测 是否使用
# 初始化默认值为"否"
payload_dict["_widget_1735107354650"] = {"value": "否"}
# 检查每个键，如果有一个大于0，则更新为"是"并停止检查
for key in keys_to_check:
for item in self.Smart_detection:
if row["id_own_org"] == item.get("_widget_1735113110147"):
if int(item.get(key, 0)) > 0: # 使用get方法并提供默认值0防止键不存在的情况
payload_dict["_widget_1735107354650"]["value"] = "是"
break
# 近30天业务单量=0 则其它所有模块均不推荐
try:
for feature_module, feature_value in feature_dict.items(): # 模块
if row["bill_count_last_30_day"] == '0' and payload_dict[feature_value]["value"] == '△':
payload_dict.update({f"{feature_value}": {"value": "×"}})
except Exception as e:
print(f"不开单识别：Error finding customer service: {e}")
# 保单识别：从系统中抽取目标门店，针对门店抽取修改是否推荐
try:
if row["org_code"] in self.widget_list:
payload_dict.update({'_widget_1735004315746': {"value": "△"}})
except Exception as e:
print(f"保单识别：Error finding customer service: {e}")
# 私域小程序：根据是否开通微信小程序判断是否使用，旗舰版及以上算拥有
try:
for item in self.private_domain:
if row["id_own_group"] == item.get("_widget_1742795002375"): # 公司id
if int(item.get("_widget_1742795002379")) > 0: # 上架商品数
payload_dict.update({"_widget_1735106258143": {"value": "是"}}) # DX:是否拥有
break
else:
payload_dict.update({"_widget_1735106258143": {"value": "否"}}) # DX:是否拥有
break
except Exception as e:
print(f"私域小程序：Error finding customer service: {e}")
try:
high_version = ['皇冠版', '至尊版', '尊享版', '旗舰版']
if row["saas_edition_fmt"] in high_version:
payload_dict.update({'_widget_1735106258141': {"value": "是"}}) # SYXCX:是否拥有
else:
payload_dict.update({'_widget_1735106258141': {"value": "否"}}) # SYXCX:是否拥有
except Exception as e:
print(f"私域小程序：Error finding customer service: {e}")
# 公域小程序：根据是否开通微信小程序判断是否使用，旗舰版及以上算拥有
try:
for item in self.public_domain:
if row["id_own_org"] == item.get("_widget_1742784257506"): # 门店id
if int(item.get("_widget_1742784257509")) == 1: # 发布商品数量
payload_dict.update({"_widget_1735106258114": {"value": "是"}}) # GYXCX:是否使用
break
else:
payload_dict.update({"_widget_1735106258114": {"value": "否"}}) # GYXCX:是否使用
break
except Exception as e:
print(f"公域小程序：Error finding customer service: {e}")
try:
if row["id_own_org"] in self.public_domain_list:
payload_dict.update({'_widget_1735106258112': {"value": "是"}}) # GYXCX:是否拥有
else:
payload_dict.update({'_widget_1735106258112': {"value": "否"}}) # GYXCX:是否拥有
except Exception as e:
print(f"公域小程序：Error finding customer service: {e}")
# 异业合作：根据是否存在判断是否拥有，过滤条件 商品名称包含异业两个字
try:
if row["id_own_org"] in self.different_industries_list:
payload_dict.update({'_widget_1735107355618': {"value": "是"}}) # YYHZ:是否拥有
else:
payload_dict.update({'_widget_1735107355618': {"value": "否"}}) # YYHZ:是否拥有
except Exception as e:
print(f"异业合作：Error finding customer service: {e}")
# 短信：根据是否启动短信功能判断是否拥有,根据
try:
for item in self.groupnotification:
if row["id_own_group"] == item.get("_widget_1743065201885"): # 公司id
if int(item.get("_widget_1743065201886")) == 1: # 是否启动短信功能
payload_dict.update({"_widget_1735106258086": {"value": "是"}}) # DX:是否拥有
break
else:
payload_dict.update({"_widget_1735106258086": {"value": "否"}}) # DX:是否拥有
break
except Exception as e:
print(f"短信：Error finding customer service: {e}")
try:
for item in self.groupnotification:
if row["id_own_group"] == item.get("_widget_1743065201885"): # 公司id
if int(item.get("_widget_1743065201889")) > 0: # 累计发送成功总人数
payload_dict.update({"_widget_1735106258088": {"value": "是"}}) # DX:是否使用
break
else:
payload_dict.update({"_widget_1735106258088": {"value": "否"}}) # DX:是否使用
break
except Exception as e:
print(f"短信：Error finding customer service: {e}")
NGV_data_id = None
# 获取关联数据
for NGV_Data in self.NGV_data_list:
# NGV_Data = NGV_Data.get("data")
if row["org_code"] == NGV_Data.get("_widget_1734062123071"): # 门店编码
NGV_data_id = NGV_Data.get("_id")
print(NGV_data_id)
try:
png_url = NGV_Data.get('_widget_1742890765211', {})[0].get('url', "")
except:
png_url = ""
print(png_url)
if not NGV_data_id:
print("未找到数据ID")
distribution_date = datetime.datetime.now(datetime.timezone.utc)
distribution_date = distribution_date.strftime('%Y-%m-%dT%H:%M:%S.%f')[:-3] + 'Z'
upload_key = None
UUid = time.strftime("%Y%m%d%H%M%S", time.localtime())
if png_url:
save_dir = "sampleCloud" # 设置输出目录
# 创建输出目录（如果不存在）
import os
os.makedirs(save_dir, exist_ok=True)
save_path = fr'{save_dir}\png\{time.strftime("%Y%m%d%H%M%S", time.localtime())}.png'
RevisitAllInformation.download_url_content(png_url, save_path)
up_data = api_instance.get_upload_token(
{"api_key": "675b900991ad2491c69389ca", "entry_id": "675b9c63925cd404038a6b86",
"transaction_id": UUid})
upload_url = up_data.get("upload_url")
upload_token = up_data.get("upload_token")
upload_result = api_instance.upload_file(
{"upload_url": upload_url, "upload_token": upload_token, "file_path": save_path})
upload_key = upload_result.get("key")
# print("已上传文件")
# print(upload_result)
# print(upload_key)
payload_dict.update({
"_widget_1734590278279": {"value": row["group_name"]}, # 公司名称
"_widget_1735112931760": {"value": row["id_own_group"]}, # 公司id
"_widget_1735112931761": {"value": row["id_own_org"]}, # 门店id
"_widget_1734590278281": {"value": row['org_name']}, # 门店名称
"_widget_1734590278292": {"value": row["跟进阶段"]}, # 跟进阶段
"_widget_1734321349021": {"value": NGV_data_id}, # 关data_get联数据
"_widget_1742548684369": {"value": row['主要目的']}, # 主要目的
"_widget_1734590278266": {"value": row['region_name']}, # 大区
"_widget_1734590278285": {"value": row['branch_name']}, # 小区
"_widget_1734590278284": {"value": row['province_name']}, # 省
"_widget_1734590278283": {"value": row['city_name']}, # 市
"_widget_1734590278282": {"value": row['area_name']}, # 区
"_widget_1734590278278": {"value": row['saas_customer_type']}, # 门店分层
"_widget_1734590278277": {"value": row['group_grade']}, # 公司等级
"_widget_1734590278276": {"value": row['limit_user_type']}, # 限制账户类型
"_widget_1734590278275": {"value": row['active_user_type']}, # 有效账户类型
"_widget_1734590278274": {"value": row['saas_version']}, # ERP操作模式
"_widget_1734590278273": {"value": row['saas_use_year']}, # 使用时长
"_widget_1734590278272": {"value": row['org_stage']}, # 门店阶段
"_widget_1734590278271": {"value": row['manage_model']}, # 经营模式
"_widget_1734590278267": {"value": row['contacts']}, # 联系人
"_widget_1734590278287": {"value": row['contact_mobile']}, # 联系手机号
"_widget_1734590278286": {"value": row['saas_edition_fmt']}, # SaaS版本
"_widget_1734590278280": {"value": row['org_code']}, # 门店编码
"_widget_1735096489244": {"value": distribution_date}, # 派发时间
"_widget_1742895342914": {"value": row['business_scope_fmt']}, # 经营范围
"_widget_1742895342915": {"value": row['station_number']}, # 工位数
"_widget_1742895342916": {"value": [upload_key]} # 门头照片
})
# 以上部分删除重新从日常回访新签回访复制 , 增加all_data=[] ，去除日期条件过滤
all_data.append(payload_dict)
except:
pass
break
routine_follow_up_payload = {
"api_key": "675b900991ad2491c69389ca",
"entry_id": "682eea70f81d67dc6c95a7a9",
"is_start_workflow": "true",
"data_list": all_data,
"transaction_id": UUid
}
# print(routine_follow_up_payload)
# 获取id
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "682eea70f81d67dc6c95a7a9"}
get_ids = api_instance.entry_data_list(payload).get("data", [])
delete_ids = [id["_id"] for id in get_ids]
payload ={"api_key":"675b900991ad2491c69389ca","entry_id":"682eea70f81d67dc6c95a7a9",
"data_ids":delete_ids,
}
api_instance.entry_data_batch_delete(payload)
res = api_instance.entry_data_batch_create(routine_follow_up_payload)
logger.info(f"创建结果：{res}")
common_module.send_task_status(task_start_time, "手动添加日常回访")
if __name__ == '__main__':
start = RevisitAllInformation()
start.main()
back_ground_module/revisit_key_customer.py
+547
View File
@@ -0,0 +1,547 @@
from api import API
from back_ground_module import CommonModule
import datetime
import re
import pandas as pd
from log_config import configure_task_logger, configure_error_task_logger
api_instance = API()
common_module = CommonModule()
start_time = datetime.datetime.now()
# 获取已经配置好的常规日志记录器
logger = configure_task_logger()
# 获取已经配置好的错误任务日志记录器
error_task_logger = configure_error_task_logger()
class KeyCustomerRevisit:
"""大客户回访"""
def __init__(self):
self.index = None
self.data_NGV = None
self.date_list = None
self.Smart_detection = None
self.service_remind = None
self.json_list = []
self.NGV_data_list = None
self.permissions_table = None
self.staff_id_list = None
self.get_feature_usage = None
self.policy_recognition = None
self.widget_list = None
self.private_domain = None
self.public_domain = None
self.public_domain_list = None
self.different_industries = None
self.different_industries_list = None
def load_all_data(self):
"""加载所有必要的数据表"""
# 省市区人员关系表
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "676512ac3e54dc3159460c0a"}
json_dict = api_instance.entry_data_list(payload)
self.json_list = json_dict.get("data")
# 获取简道云员工id
payload = {"api_key": "6694d3c4fcb69ca9a111a6c4",
"entry_id": "6769204a1902c9341340a1bc",
}
staff_id = api_instance.entry_data_list(payload)
self.staff_id_list = staff_id.get("data") # api请求格式，将数据封装在data字典里
# 获取权限表信息
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "675b96c14e839f90fef1647c"}
self.permissions_table = api_instance.entry_data_list(payload).get("data")
# 获取NGV数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "675bb02bd2d53c2034c665e4"}
self.NGV_data_list = api_instance.entry_data_list(payload).get("data")
# print("NGV获取后的类型：", type(self.NGV_data_list))
# 获取服务提醒-数据支持表单数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "676bb7bda3029720f1083e99"}
self.service_remind = api_instance.entry_data_list(payload).get("data")
# 获取智能检测-数据支持表单数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "676bb99649ab3ac975af6e39"}
self.Smart_detection = api_instance.entry_data_list(payload).get("data")
# 获取功能使用情况表
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "6763bbf657bd8fb76fcb41b2"}
self.get_feature_usage = api_instance.entry_data_list(payload).get("data", [])
# 获取保单识别表
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "6773a60d30ed87ff9f68d3c5"}
self.policy_recognition = api_instance.entry_data_list(payload).get("data")
# 提取 _widget_1735632397600 的值并存储在列表中
self.widget_list = [item['_widget_1735632397600'] for item in self.policy_recognition]
# 获取私域小程序-数据支持表单数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "67e0f0fae622896749ba5087"}
self.private_domain = api_instance.entry_data_list(payload).get("data", [])
# 提取 _widget_1742795002375 的值并存储在列表中
self.private_domain = [item['_widget_1742795002375'] for item in self.private_domain]
# 获取公域小程序-数据支持表单数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "67e0c702c8f603b997980999"}
self.public_domain = api_instance.entry_data_list(payload).get("data", [])
# 提取 _widget_1742784257506 的值并存储在列表中
self.public_domain_list = [item['_widget_1742784257506'] for item in self.private_domain]
# 获取异业合作-数据支持表单数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "67e24fdd8dfcfa918e17c30b"}
self.different_industries = api_instance.entry_data_list(payload).get("data", [])
# 提取 _widget_1742784257506 的值并存储在列表中
self.different_industries_list = [item['_widget_1742784257506'] for item in self.different_industries]
@staticmethod
def remove_parentheses(text: str) -> str:
# 使用正则表达式匹配并去除括号及其内容
# \s* 表示匹配零个或多个空白字符（处理括号前后可能存在的空格）
# $ 和 $ 分别表示匹配左括号和右括号
# 中间的 .*? 表示非贪婪地匹配任意数量的字符（包括没有字符的情况）
cleaned_text = re.sub(r'\s*$.*?$\s*', '', text)
# 为了确保同时处理中文括号，再进行一次替换
cleaned_text = re.sub(r'\s*（.*?）\s*', '', cleaned_text)
return cleaned_text.strip() # 去除两端多余的空白字符
@staticmethod
def get_staff_id(row_item, name):
"""辅助函数，用于获取员工ID"""
if str(row_item["_widget_1734942794144"]) == str(name): # 检查姓名是否匹配
return row_item["_widget_1734942794145"] # 返回员工ID
return None
def main(self):
task_start_time =datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
self.load_all_data()
self.date_list = common_module.get_holiday_list() # 获取一年中的节假日
self.data_NGV = common_module.get_ngv_details(days_back=1) # 获取data_NGV 并转为str
# self.index = self.build_index(self.json_list)
data_NGV = self.data_NGV.copy()
def replace_values(series):
# 使用条件判断来进行替换
return series.apply(lambda x: '' if pd.isna(x) or x in ['NA', 'None', ''] else x)
# 对整个DataFrame的所有列应用替换函数
data_NGV = data_NGV.apply(replace_values)
# data_NGV.to_csv("dayinNGV.csv")
# 定义优先级顺序
edition_order = ['皇冠版', '至尊版', '尊享版', '旗舰版', '标准版', '进阶版', '基础版', '入门版']
customer_type_order = ["F", "E", "D", "C", "B", "A"] # 索引越小优先级越高
group_grade_order = ['全国KA（FMVP）', '区域KA（MVP）', '重要客户（SVIP）', '普通客户（VIP）']
# 创建映射字典，并为不在列表中的值设置默认值
edition_map = {edition: idx for idx, edition in enumerate(edition_order)}
customer_type_map = {ctype: idx for idx, ctype in enumerate(customer_type_order)}
group_grade_map = {grade: idx for idx, grade in enumerate(group_grade_order)}
# 添加用于排序的新列，并处理不在映射字典中的值
data_NGV['edition_rank'] = data_NGV['saas_edition_fmt'].map(edition_map).fillna(0).astype(int) # 缺失值用最高优先级填充
data_NGV['customer_type_rank'] = data_NGV['saas_customer_type'].map(customer_type_map).fillna(0).astype(int)
data_NGV['group_grade_rank'] = data_NGV['group_grade'].map(group_grade_map).fillna(0).astype(int)
# data_NGV.to_csv("88855.csv")
# 找到每组中 edition_rank 最小值对应的行
best_edition_idx = data_NGV.groupby('id_own_group')['edition_rank'].idxmin()
best_edition_rows = data_NGV.loc[best_edition_idx]
best_edition_rows['max_saas_edition'] = best_edition_rows['saas_edition_fmt']
# 找到每组中 customer_type_rank 最小值对应的行
best_customer_type_idx = data_NGV.groupby('id_own_group')['customer_type_rank'].idxmin()
best_customer_type_rows = data_NGV.loc[best_customer_type_idx]
best_customer_type_rows['max_saas_customer_type'] = best_customer_type_rows['customer_type_rank'].apply(
lambda x: customer_type_order[x])
# 找到每组中 group_grade_rank 最小值对应的行
best_group_grade_idx = data_NGV.groupby('id_own_group')['group_grade_rank'].idxmin()
best_group_grade_rows = data_NGV.loc[best_group_grade_idx]
best_group_grade_rows['max_group_grade'] = best_group_grade_rows['group_grade']
# 合并最佳值回到原数据集
best_values = (
best_edition_rows[['id_own_group', 'max_saas_edition']]
.merge(best_customer_type_rows[['id_own_group', 'max_saas_customer_type']], on='id_own_group', how='outer')
.merge(best_group_grade_rows[['id_own_group', 'max_group_grade']], on='id_own_group', how='outer')
)
# 将最佳值合并回原数据集
data_NGV = data_NGV.merge(best_values, on='id_own_group', how='left')
condition = (data_NGV['is_main_org'] == 1) & (data_NGV['org_status'] == '过期') # 步骤2: 过滤条件
ngvv2 = data_NGV[condition]
# ngvv2.to_excel(r"C:\Users\Administrator.DESKTOP-7IC2USJ\Desktop\NGVV2.xlsx")
data_NGV_V2 = data_NGV.copy() # 步骤3: 检查id_own_group是否存在于ngvv2中
data_NGV_V2['条件'] = (data_NGV['org_type'] == "一般") & (data_NGV['org_status'] == '留存') & (
data_NGV['group_grade'].isin(['全国KA（FMVP）', '区域KA（MVP）'])) & (data_NGV['is_main_org'] != 1)
data_NGV_V2 = data_NGV_V2.loc[data_NGV_V2["条件"]]
# 步骤4: 过滤存在的记录
data_NGV_V2['exists_in_ngvv2'] = data_NGV_V2['id_own_group'].isin(ngvv2['id_own_group'])
filtered_data = data_NGV_V2[data_NGV_V2['exists_in_ngvv2']]
fixed_order = ['皇冠版', '至尊版', '尊享版', '旗舰版', '标准版', '进阶版', '基础版', '入门版']
# sorted_items = sorted(filtered_data, key=lambda x: fixed_order.index(x))
fixed_order_map = {edition: index for index, edition in enumerate(fixed_order)}
filtered_data['sort_key'] = filtered_data['saas_edition_fmt'].map(fixed_order_map)
filtered_data = filtered_data.sort_values(by='sort_key').drop('sort_key', axis=1)
result = filtered_data.drop_duplicates(subset='id_own_group', keep='first')
data_NGV['条件'] = (data_NGV['org_type'] == "一般") & (data_NGV['org_status'] == '留存') & (
data_NGV['group_grade'].isin(['全国KA（FMVP）', '区域KA（MVP）'])) & (data_NGV['is_main_org'] == 1)
data_NGV = data_NGV.loc[data_NGV["条件"]]
data_NGV = pd.concat([data_NGV, result], axis=0)
# 重置索引
data_NGV = data_NGV.reset_index(drop=True)
print(f'读取NGV大客户回访 {len(data_NGV)} 条数据！')
# data_NGV.to_csv("大客户回访数据.csv")
data_NGV = data_NGV.copy()
for index_num, row in data_NGV.iterrows(): # 对过滤后的每一条进行派发
print(row["org_code"]) # 数据验证
print(row["service_impl_principal"])
print(row["area_manager"])
print(row["technician"])
print(row["group_grade"])
payload_dict = {}
# saas_use_year = re.findall(r'第([0-9]+)年', row["saas_use_year"])[0]
NGV_roles = {
'relationship_manager': row['service_impl_principal'], # 运营负责人
# 'relationship_manager': "张阳", # 运营负责人
'area_manager': row['area_manager'], # 区域经理
'technician': row['technician'], # 技术专家
'salesmen': row['salesmen'], # 技术专家
}
for role, name in NGV_roles.items():
for row_item in self.staff_id_list:
staff_id = self.get_staff_id(row_item, name)
if staff_id:
NGV_roles[role] = staff_id
break # 找到后退出循环
else:
NGV_roles[role] = None # 如果没有找到对应的员工ID
relationship_manager, area_manager, technician, salesmen = [NGV_roles[role] for role in
['relationship_manager', 'area_manager',
'technician', 'salesmen']]
payload_dict.update({
"_widget_1734590278288": {"value": technician} # 跟进人是技术专家
})
payload_dict.update({
"_widget_1734590278289": {"value": relationship_manager}, # 运营负责人
"_widget_1734590278290": {"value": area_manager}, # 区域经理
"_widget_1734590278291": {"value": technician}, # 技术专家
"_widget_1735290738545": {"value": salesmen}} # 销售负责人
)
# 输出结果
print("SaaS开户回访人员：", relationship_manager or "未分配")
print("SaaS技术专家：", technician or "未分配")
print("SaaS区域经理：", area_manager or "未分配")
# 判断权限唯一值
pattern = r'(.+)\（'
match = re.search(pattern, row['max_group_grade'])
group_grade = match.group(1)
if not row['saas_customer_type'] or row['saas_customer_type'] == 'NA' or row[
'saas_customer_type'] == 'None':
row['saas_customer_type'] = "F"
NGV_store_level_key = group_grade + row['max_saas_edition'] + row['max_saas_customer_type']
print("权限唯一值：", NGV_store_level_key)
data_NGV.at[index_num, 'NGV_store_level_key'] = NGV_store_level_key
Billing = None
for item in self.permissions_table:
if NGV_store_level_key == item.get("_widget_1734056507963"): # 合并（等级-类型-分层）
print("该门店开单的权限是：", item.get("_widget_1734055617039"))
Billing = item.get("_widget_1734055617039") # 开单
Service_Alerts = item.get("_widget_1734055617040") # 服务提醒
membership = item.get("_widget_1734055617041") # 会员卡
SMS = item.get("_widget_1734055617042") # 短信
Public_domain_applets = item.get("_widget_1734055617043") # 公域小程序
Private_domain_applets = item.get("_widget_1734055617044") # 私域小程序
Test_sheet = item.get("_widget_1734055617045") # 检测单
AI_poster = item.get("_widget_1734055617046") # AI海报
Business_wallets = item.get("_widget_1734055617047") # 企业钱包
Precision_marketing = item.get("_widget_1734055617049") # 精准营销
Paid_memberships = item.get("_widget_1734055617051") # 付费会员
business_WeCom = item.get("_widget_1734055617052") # 企业微信
Insurance_policy_identification = item.get("_widget_1734055617053") # 保险单识别
Insurance_bots = item.get("_widget_1734055617054") # 保险机器人
Camera_pick_up = item.get("_widget_1734055617055") # 摄像头接车
Camera_billing = item.get("_widget_1734055617056") # 摄像头开单
Transparent_workshop = item.get("_widget_1734055617057") # 透明车间
Cross_industry_cooperation = item.get("_widget_1734055617058") # 异业合作
BI_Insights = item.get("_widget_1734055617059") # BI洞察
payload_dict.update(
{
"_widget_1734073342350": {"value": Billing},
"_widget_1735004315757": {"value": Service_Alerts},
"_widget_1735004315756": {"value": membership},
"_widget_1735004315755": {"value": SMS},
"_widget_1735004315754": {"value": Public_domain_applets},
"_widget_1735004315753": {"value": Private_domain_applets},
"_widget_1735004315752": {"value": Test_sheet},
"_widget_1735004315751": {"value": AI_poster},
"_widget_1735004315750": {"value": Business_wallets},
"_widget_1735004315749": {"value": Precision_marketing},
"_widget_1735004315748": {"value": Paid_memberships},
"_widget_1735004315747": {"value": business_WeCom},
"_widget_1735004315746": {"value": Insurance_policy_identification},
"_widget_1735004315745": {"value": Insurance_bots},
"_widget_1735004315744": {"value": Camera_pick_up},
"_widget_1735004315743": {"value": Camera_billing},
"_widget_1735004315742": {"value": Transparent_workshop},
"_widget_1735004315741": {"value": Cross_industry_cooperation},
"_widget_1734073342352": {"value": BI_Insights},
}
)
feature_dict = {
"开单": "_widget_1734073342350",
"服务提醒": "_widget_1735004315757",
"会员卡": "_widget_1735004315756",
"短信": "_widget_1735004315755",
"公域小程序": "_widget_1735004315754",
"私域小程序": "_widget_1735004315753",
"检测单": "_widget_1735004315752",
"AI海报": "_widget_1735004315751",
"企业钱包": "_widget_1735004315750",
"精准营销": "_widget_1735004315749",
"付费会员": "_widget_1735004315748",
"企业微信": "_widget_1735004315747",
"保险单识别": "_widget_1735004315746",
"保险机器人": "_widget_1735004315745",
"摄像头接车": "_widget_1735004315744",
"摄像头开单": "_widget_1735004315743",
"透明车间": "_widget_1735004315742",
"异业合作": "_widget_1735004315741",
"BI洞察": "_widget_1734073342352",
}
# _widget_1735527329557 下次是否推荐
for new_item in self.get_feature_usage:
for feature_module, feature_value in feature_dict.items(): # 模块
if new_item.get("_widget_1735268263079") == feature_module and new_item.get(
"_widget_1735527329557") == "否" and new_item.get("_widget_1735280720550") == \
row["id_own_org"]: # 下次是否推荐 功能使用情况表
print(f"{feature_value}进行了更改")
payload_dict.update({f"{feature_value}": {"value": "×"}})
if new_item.get("_widget_1735268263079") == feature_module and new_item.get(
"_widget_1736414617462") == "否" and new_item.get("_widget_1735280720550") == \
row["id_own_org"]: # 下次是否跟进
print(f"{feature_value}进行了更改")
payload_dict.update({f"{feature_value}": {"value": "×"}})
fields_to_check = {
"_widget_1735004315763": Billing, # 开单
"_widget_1735106258016": Service_Alerts, # 服务提醒
"_widget_1735106258036": membership, # 会员卡
"_widget_1735106258086": SMS, # 短信
"_widget_1735106258112": Public_domain_applets, # 公域小程序
"_widget_1735106258141": Private_domain_applets, # 私域小程序
"_widget_1735107354648": Test_sheet, # 检测单
"_widget_1735107354725": AI_poster, # AI海报
"_widget_1735107354811": Business_wallets, # 企业钱包
"_widget_1735107354906": Precision_marketing, # 精准营销
"_widget_1735107354980": Paid_memberships, # 付费会员
"_widget_1735107355093": business_WeCom, # 企业微信
"_widget_1735107355143": Insurance_policy_identification, # 保险单识别
"_widget_1735107355235": Insurance_bots, # 保险机器人
"_widget_1735107355333": Camera_pick_up, # 摄像头接车
"_widget_1735107355392": Camera_billing, # 摄像头开单
"_widget_1735107355502": Transparent_workshop, # 透明车间
"_widget_1735107355618": Cross_industry_cooperation, # 异业合作
"_widget_1735107355740": BI_Insights # BI洞察
}
# 遍历每个字段，检查其值并更新payload_dict
for widget_id, field_name in fields_to_check.items():
if field_name == "√":
payload_dict.update({widget_id: {"value": "是"}})
break
if row["active_status_fmt"] == "活跃": # 开单 是否使用
payload_dict.update({"_widget_1735004315765": {"value": "是"}})
else:
payload_dict.update({"_widget_1735004315765": {"value": "否"}})
try:
if row["card_bill_day_count_last_30_day"] != "0": # 会员卡 是否使用
payload_dict.update({"_widget_1735106258038": {"value": "是"}})
else:
payload_dict.update({"_widget_1735106258038": {"value": "否"}})
except Exception as e:
print(f"会员卡识别：Error finding customer service: {e}")
# print(self.service_remind.get("_widget_1735112637045"))
payload_dict["_widget_1735106258018"] = {"value": "否"}
for item in self.service_remind:
if row["id_own_group"] == item.get("_widget_1735112637043"):
if int(item.get("_widget_1735112637045")) < 180 and int(
item.get("_widget_1735112637046")) == 1: # 服务提醒 是否使用
payload_dict.update({"_widget_1735106258018": {"value": "是"}})
break
elif int(item.get("_widget_1735112637048")) > 0:
payload_dict.update({"_widget_1735106258018": {"value": "是"}})
break
keys_to_check = [
"_widget_1735113110155"
] # 智能检测 是否使用
# 初始化默认值为"否"
payload_dict["_widget_1735107354650"] = {"value": "否"}
# 检查每个键，如果有一个大于0，则更新为"是"并停止检查
for key in keys_to_check:
for item in self.Smart_detection:
if row["id_own_org"] == item.get("_widget_1735113110147"):
if int(item.get(key, 0)) > 0: # 使用get方法并提供默认值0防止键不存在的情况
payload_dict["_widget_1735107354650"]["value"] = "是"
break
# 近30天业务单量=0 则其它所有模块均不推荐
try:
for feature_module, feature_value in feature_dict.items(): # 模块
if row["bill_count_last_30_day"] == '0' and payload_dict[feature_value]["value"] == '△':
payload_dict.update({f"{feature_value}": {"value": "×"}})
except Exception as e:
print(f"不开单识别：Error finding customer service: {e}")
# 保单识别：从系统中抽取目标门店，针对门店抽取修改是否推荐
try:
if row["org_code"] in self.widget_list:
payload_dict.update({'_widget_1735004315746': {"value": "△"}})
except Exception as e:
print(f"保单识别：Error finding customer service: {e}")
# 私域小程序：根据是否开通微信小程序判断是否使用，旗舰版及以上算拥有
try:
if row["id_own_group"] in self.private_domain:
payload_dict.update({'_widget_1735106258143': {"value": "是"}}) # SYXCX:是否使用
else:
payload_dict.update({'_widget_1735106258143': {"value": "否"}}) # SYXCX:是否使用
except Exception as e:
print(f"私域小程序：Error finding customer service: {e}")
try:
high_version = ['皇冠版', '至尊版', '尊享版', '旗舰版']
if row["saas_edition_fmt"] in high_version:
payload_dict.update({'_widget_1735106258141': {"value": "是"}}) # SYXCX:是否拥有
else:
payload_dict.update({'_widget_1735106258141': {"value": "否"}}) # SYXCX:是否拥有
except Exception as e:
print(f"私域小程序：Error finding customer service: {e}")
# 公域小程序：根据是否开通微信小程序判断是否使用，旗舰版及以上算拥有
try:
for item in self.public_domain:
if row["id_own_org"] == item.get("_widget_1742784257506"): # 门店id
if int(item.get("_widget_1742784257509")) > 0 : # 发布商品数量
payload_dict.update({"_widget_1735106258114": {"value": "是"}}) # GYXCX:是否使用
break
else :
payload_dict.update({"_widget_1735106258114": {"value": "否"}}) # GYXCX:是否使用
break
except Exception as e:
print(f"公域小程序：Error finding customer service: {e}")
try:
if row["id_own_org"] in self.public_domain_list:
payload_dict.update({'_widget_1735106258112': {"value": "是"}}) # GYXCX:是否拥有
else:
payload_dict.update({'_widget_1735106258112': {"value": "否"}}) # GYXCX:是否拥有
except Exception as e:
print(f"公域小程序：Error finding customer service: {e}")
# 异业合作：根据是否存在判断是否拥有，过滤条件 商品名称包含异业两个字
try:
if row["id_own_org"] in self.different_industries_list:
payload_dict.update({'_widget_1735107355618': {"value": "是"}}) # YYHZ:是否拥有
else:
payload_dict.update({'_widget_1735107355618': {"value": "否"}}) # YYHZ:是否拥有
except Exception as e:
print(f"异业合作：Error finding customer service: {e}")
NGV_data_id = None
# 获取关联数据
for NGV_Data in self.NGV_data_list:
# NGV_Data = NGV_Data.get("data")
if row["org_code"] == NGV_Data.get("_widget_1734062123071"): # 门店编码
NGV_data_id = NGV_Data.get("_id")
print(NGV_data_id)
if not NGV_data_id:
print("未找到数据ID")
distribution_date = datetime.datetime.now(datetime.timezone.utc)
distribution_date = distribution_date.strftime('%Y-%m-%dT%H:%M:%S.%f')[:-3] + 'Z'
payload_dict.update({
"_widget_1734590278279": {"value": row["group_name"]}, # 公司名称
"_widget_1735112931760": {"value": row["id_own_group"]}, # 公司id
"_widget_1735112931761": {"value": row["id_own_org"]}, # 门店id
"_widget_1734590278281": {"value": row['org_name']}, # 门店名称
"_widget_1734590278292": {"value": "2025第一季度大客户回访"}, # 跟进阶段
"_widget_1734321349021": {"value": NGV_data_id}, # 关data_get联数据
"_widget_1742548684369": {"value": "定期维护，了解业务变化，保持客户满意度的同时挖掘增购机会。"}, # 主要目的
"_widget_1734590278266": {"value": row['region_name']}, # 大区
"_widget_1734590278285": {"value": row['branch_name']}, # 小区
"_widget_1734590278284": {"value": row['province_name']}, # 省
"_widget_1734590278283": {"value": row['city_name']}, # 市
"_widget_1734590278282": {"value": row['area_name']}, # 区
"_widget_1734590278278": {"value": row['saas_customer_type']}, # 门店分层
"_widget_1734590278277": {"value": row['group_grade']}, # 公司等级
"_widget_1734590278276": {"value": row['limit_user_type']}, # 限制账户类型
"_widget_1734590278275": {"value": row['active_user_type']}, # 有效账户类型
"_widget_1734590278274": {"value": row['saas_version']}, # ERP操作模式
"_widget_1734590278273": {"value": row['saas_use_year']}, # 使用时长
"_widget_1734590278272": {"value": row['org_stage']}, # 门店阶段
"_widget_1734590278271": {"value": row['manage_model']}, # 经营模式
"_widget_1734590278267": {"value": row['contacts']}, # 联系人
"_widget_1734590278287": {"value": row['contact_mobile']}, # 联系手机号
"_widget_1734590278286": {"value": row['saas_edition_fmt']}, # SaaS版本
"_widget_1734590278280": {"value": row['org_code']}, # 门店编码
"_widget_1735287791875": {"value": row['salesmen']}, # 销售负责人
"_widget_1735096489244": {"value": distribution_date}, # 派发时间
})
routine_follow_up_payload = {
"api_key": "675b900991ad2491c69389ca",
"entry_id": "675b9c63925cd404038a6b86",
"is_start_workflow": "true",
"data": payload_dict,
}
print(routine_follow_up_payload)
res = api_instance.data_batch_create(routine_follow_up_payload)
logger.info(f"创建结果：{res}")
print(res)
# data_NGV.to_csv("final_data_NGV.csv", index=False)
common_module.send_task_status(task_start_time, "大客户回访")
if __name__ == '__main__':
start = KeyCustomerRevisit()
start.main()
back_ground_module/revisit_new_services_180.py
+852
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import datetime
import os
import time
import requests
from api import API
import re
from back_ground_module import CommonModule
import pandas as pd
from log_config import configure_task_logger, configure_error_task_logger
api_instance = API()
common_module = CommonModule()
# start_time = datetime.datetime.now()
# 获取已经配置好的常规日志记录器
logger = configure_task_logger()
# 获取已经配置好的错误任务日志记录器
error_task_logger = configure_error_task_logger()
class NewServicesRevisit:
"""
新签回访180天
"""
def __init__(self):
self.get_feature_usage = None
self.saas_create_time = None
self.index = None
self.date_one = None
self.data_NGV_S = None
self.date_list = None
self.Smart_detection = None
self.service_remind = None
self.NGV_data_list = None
self.permissions_table = None
self.staff_id_list = None
self.json_list = []
self.policy_recognition = None
self.widget_list = None
self.private_domain = None
self.public_domain = None
self.public_domain_list = None
self.different_industries = None
self.different_industries_list = None
self.groupnotification = None
def calculate_date_one(self, start_offset=0):
"""
计算从当前日期（或指定偏移量的日期）开始，往前遍历遇到date_list中日期的次数。
参数:
- start_offset: 从当前日期起始的天数偏移量，默认为0（即今天）。负数表示过去，正数表示未来。
返回:
- date_one: 遍历到date_list中日期的次数。
"""
jdy_date = datetime.datetime.now().strftime("%Y-%m-%d")
jdy_start_time = datetime.datetime.now().strftime("%Y-%m-%d ")
# 设置起始日期
now_time = datetime.datetime.now() + datetime.timedelta(days=start_offset)
# 初始化计数器
date_one = 1
print("当前日期：", now_time.strftime("%Y-%m-%d"))
# 检查起始日期是否在date_list中
if now_time.strftime("%Y-%m-%d") in self.date_list:
date_one = 0
print("开始次数：", date_one)
else:
# 遍历日期
for i in range(1, 10):
new_date = now_time + datetime.timedelta(days=-i)
new_date_str = new_date.strftime("%Y-%m-%d")
print("遍历日期：", new_date_str)
if new_date_str in self.date_list:
date_one += 1
print("节假日期：", new_date_str)
else:
break
print("遍历次数：", date_one)
return date_one
@staticmethod
def download_url_content(url, save_path):
"""
下载指定 URL 的内容并保存到本地文件。
:param url: 要下载内容的 URL
:param save_path: 保存文件的路径
"""
try:
# 发送 GET 请求以获取内容
response = requests.get(url, stream=True)
response.raise_for_status() # 如果响应状态码不是 200，抛出异常
# 确保保存目录存在
os.makedirs(os.path.dirname(save_path), exist_ok=True)
# 将内容写入文件
with open(save_path, 'wb') as file:
for chunk in response.iter_content(chunk_size=8192): # 分块写入，避免占用过多内存
if chunk: # 过滤掉空块
file.write(chunk)
print(f"文件已成功保存到 {save_path}")
except requests.exceptions.RequestException as e:
print(f"下载失败: {e}")
except Exception as e:
print(f"发生错误: {e}")
def load_all_data(self):
"""加载所有必要的数据表"""
# 省市区人员关系表
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "676512ac3e54dc3159460c0a"}
json_dict = api_instance.entry_data_list(payload)
self.json_list = json_dict.get("data")
# 获取简道云员工id
payload = {"api_key": "6694d3c4fcb69ca9a111a6c4",
"entry_id": "6769204a1902c9341340a1bc",
}
staff_id = api_instance.entry_data_list(payload)
self.staff_id_list = staff_id.get("data") # api请求格式，将数据封装在data字典里
# 获取权限表信息
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "675b96c14e839f90fef1647c"}
self.permissions_table = api_instance.entry_data_list(payload).get("data", [])
# 获取NGV数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "675bb02bd2d53c2034c665e4"}
self.NGV_data_list = api_instance.entry_data_list(payload).get("data", [])
# print("NGV获取后的类型：", type(self.NGV_data_list))
# 获取服务提醒-数据支持表单数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "676bb7bda3029720f1083e99"}
self.service_remind = api_instance.entry_data_list(payload).get("data", [])
# 获取智能检测-数据支持表单数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "676bb99649ab3ac975af6e39"}
self.Smart_detection = api_instance.entry_data_list(payload).get("data", [])
# 获取功能使用情况表
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "6763bbf657bd8fb76fcb41b2"}
self.get_feature_usage = api_instance.entry_data_list(payload).get("data", [])
# 获取保单识别表
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "6773a60d30ed87ff9f68d3c5"}
self.policy_recognition = api_instance.entry_data_list(payload).get("data")
# 提取 _widget_1735632397600 的值并存储在列表中
self.widget_list = [item['_widget_1735632397600'] for item in self.policy_recognition]
# 获取私域小程序-数据支持表单数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "67e0f0fae622896749ba5087"}
self.private_domain = api_instance.entry_data_list(payload).get("data", [])
# 提取 _widget_1742795002375 的值并存储在列表中
# self.private_domain = [item['_widget_1742795002375'] for item in self.private_domain]
# 获取公域小程序-数据支持表单数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "67e0c702c8f603b997980999"}
self.public_domain = api_instance.entry_data_list(payload).get("data", [])
# 提取 _widget_1742784257506 的值并存储在列表中
self.public_domain_list = [item['_widget_1742784257506'] for item in self.public_domain]
# 获取异业合作-数据支持表单数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "67e24fdd8dfcfa918e17c30b"}
self.different_industries = api_instance.entry_data_list(payload).get("data", [])
# 提取 _widget_1742784257506 的值并存储在列表中
self.different_industries_list = [item['_widget_1742884829007'] for item in self.different_industries]
# 获取短信-数据支持表单数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "67e5107198ba1b20d5df3974"}
self.groupnotification = api_instance.entry_data_list(payload).get("data", [])
@staticmethod
def build_index(json_list):
index = {}
# print(json_list)
for json_item in json_list:
# json_item = json_item.get("data")
# print(json_item)
try:
key = (json_item['_widget_1734677164861'], json_item['_widget_1734677164862'],
json_item['_widget_1734677164863']) # 省市区
if '_widget_1734677164871' not in json_item: # 日常回访客服
raise KeyError("缺少 '日常回访客服' 键")
index[key] = json_item
except KeyError as e:
print(f"警告：{e}，跳过该条记录: {json_item}")
continue
return index
@staticmethod
def find_customer_service(province_name, city_name, area_name, index):
key = (province_name, city_name, area_name)
# print(index)
if key not in index:
return "数据缺失: 未找到对应的日常回访客服"
return index[key]
@staticmethod
def remove_parentheses(text: str) -> str:
# 使用正则表达式匹配并去除括号及其内容
# \s* 表示匹配零个或多个空白字符（处理括号前后可能存在的空格）
# $ 和 $ 分别表示匹配左括号和右括号
# 中间的 .*? 表示非贪婪地匹配任意数量的字符（包括没有字符的情况）
cleaned_text = re.sub(r'\s*$.*?$\s*', '', text)
# 为了确保同时处理中文括号，再进行一次替换
cleaned_text = re.sub(r'\s*（.*?）\s*', '', cleaned_text)
return cleaned_text.strip() # 去除两端多余的空白字符
@staticmethod
def get_staff_id(row_item, name):
"""辅助函数，用于获取员工ID"""
if str(row_item["_widget_1734942794144"]) == str(name): # 检查姓名是否匹配
return row_item["_widget_1734942794145"] # 返回员工ID
return None
def assign_customer_service(self, province_name, city_name, area_name, index):
"""根据省市区派发给日常回访客服"""
try:
customer_service_info = self.find_customer_service(province_name, city_name, area_name, index)
# 定义一个辅助函数，用于安全地获取多层字段中的 username
def safe_get_username(data, key):
try:
if isinstance(data, dict):
return data.get(key, {}).get('username', "")
return ""
except:
return ""
relationship_manager = safe_get_username(customer_service_info, '_widget_1734677164864')
customer_service = safe_get_username(customer_service_info, '_widget_1734677164871')
technician = safe_get_username(customer_service_info, '_widget_1734677164866')
area_manager = safe_get_username(customer_service_info, '_widget_1734677164865')
return relationship_manager, customer_service, technician, area_manager
except Exception as e:
print(f"Error finding customer service: {e}")
return "分配失败，请检查", "分配失败，请检查", "分配失败，请检查"
def main(self):
task_start_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
global png_url, key, upload_key
self.load_all_data()
self.date_list = common_module.get_holiday_list()
self.data_NGV_S = common_module.get_ngv_details(days_back=1).astype(str) # 获取data_NGV 并转为str
self.date_one = self.calculate_date_one(start_offset=0)
self.index = self.build_index(self.json_list)
self.saas_create_time_180 = 173 # 新签日期
self.saas_create_time_90 = 83 # 新签日期
print("开始运行main")
print(self.date_one)
for i in range(0, self.date_one): # 从NGV总表过滤
# now_time = datetime.datetime.now() + datetime.timedelta(days=-76)
# now_time = now_time + datetime.timedelta(days=-i)
now_time = datetime.datetime.now() + datetime.timedelta(days=-i)
today = now_time + datetime.timedelta(days=-self.saas_create_time_180)
formatted_today_180 = today.strftime("%Y-%m-%d")
today = now_time + datetime.timedelta(days=-self.saas_create_time_90)
formatted_today_90 = today.strftime("%Y-%m-%d")
print("SaaS开户回访日期：", formatted_today_180, formatted_today_90)
data_NGV = self.data_NGV_S.copy()
def replace_values(series):
# 使用条件判断来进行替换
return series.apply(lambda x: '' if pd.isna(x) or x in ['NA', 'None', ''] else x)
# 对整个DataFrame的所有列应用替换函数
data_NGV = data_NGV.apply(replace_values)
# data_NGV.to_csv("dayinNGV.csv")
# 定义优先级顺序
edition_order = ['皇冠版', '至尊版', '尊享版', '旗舰版', '标准版', '进阶版', '基础版', '入门版']
customer_type_order = ["F", "E", "D", "C", "B", "A"] # 索引越小优先级越高
group_grade_order = ['全国KA（FMVP）', '区域KA（MVP）', '重要客户（SVIP）', '普通客户（VIP）']
# 创建映射字典，并为不在列表中的值设置默认值
edition_map = {edition: idx for idx, edition in enumerate(edition_order)}
customer_type_map = {ctype: idx for idx, ctype in enumerate(customer_type_order)}
group_grade_map = {grade: idx for idx, grade in enumerate(group_grade_order)}
# 添加用于排序的新列，并处理不在映射字典中的值
data_NGV['edition_rank'] = data_NGV['saas_edition_fmt'].map(edition_map).fillna(0).astype(
int) # 缺失值用最高优先级填充
data_NGV['customer_type_rank'] = data_NGV['saas_customer_type'].map(customer_type_map).fillna(0).astype(int)
data_NGV['group_grade_rank'] = data_NGV['group_grade'].map(group_grade_map).fillna(0).astype(int)
# data_NGV.to_csv("88855.csv")
# 找到每组中 edition_rank 最小值对应的行
best_edition_idx = data_NGV.groupby('id_own_group')['edition_rank'].idxmin()
best_edition_rows = data_NGV.loc[best_edition_idx]
best_edition_rows['max_saas_edition'] = best_edition_rows['saas_edition_fmt']
# 找到每组中 customer_type_rank 最小值对应的行
best_customer_type_idx = data_NGV.groupby('id_own_group')['customer_type_rank'].idxmin()
best_customer_type_rows = data_NGV.loc[best_customer_type_idx]
best_customer_type_rows['max_saas_customer_type'] = best_customer_type_rows['customer_type_rank'].apply(
lambda x: customer_type_order[x])
# 找到每组中 group_grade_rank 最小值对应的行
best_group_grade_idx = data_NGV.groupby('id_own_group')['group_grade_rank'].idxmin()
best_group_grade_rows = data_NGV.loc[best_group_grade_idx]
best_group_grade_rows['max_group_grade'] = best_group_grade_rows['group_grade']
# 合并最佳值回到原数据集
best_values = (
best_edition_rows[['id_own_group', 'max_saas_edition']]
.merge(best_customer_type_rows[['id_own_group', 'max_saas_customer_type']], on='id_own_group',
how='outer')
.merge(best_group_grade_rows[['id_own_group', 'max_group_grade']], on='id_own_group', how='outer')
)
# 将最佳值合并回原数据集
data_NGV = data_NGV.merge(best_values, on='id_own_group', how='left')
condition = (data_NGV['is_main_org'] == 1) & (data_NGV['org_status'] == '过期') # 步骤2: 过滤条件
ngvv2 = data_NGV[condition]
# ngvv2.to_excel(r"C:\Users\Administrator.DESKTOP-7IC2USJ\Desktop\NGVV2.xlsx")
data_NGV_V2 = data_NGV.copy() # 步骤3: 检查id_own_group是否存在于ngvv2中
data_NGV_V2['条件'] = (data_NGV_V2['org_type'] == "一般") & (data_NGV_V2['org_status'] == '留存') & (
data_NGV_V2['area_manager'] != '殷昊') & (
data_NGV_V2['area_manager'] != '孙玉蕾') & (
data_NGV_V2['is_main_org'] != 1)
data_NGV_V2 = data_NGV_V2.loc[data_NGV_V2["条件"]]
# 步骤4: 过滤存在的记录
data_NGV_V2['exists_in_ngvv2'] = data_NGV_V2['id_own_group'].isin(ngvv2['id_own_group'])
filtered_data = data_NGV_V2[data_NGV_V2['exists_in_ngvv2']]
fixed_order = ['皇冠版', '至尊版', '尊享版', '旗舰版', '标准版', '进阶版', '基础版', '入门版']
# sorted_items = sorted(filtered_data, key=lambda x: fixed_order.index(x))
fixed_order_map = {edition: index for index, edition in enumerate(fixed_order)}
filtered_data['sort_key'] = filtered_data['saas_edition_fmt'].map(fixed_order_map)
filtered_data = filtered_data.sort_values(by='sort_key').drop('sort_key', axis=1)
result = filtered_data.drop_duplicates(subset='id_own_group', keep='first')
data_NGV['条件'] = (data_NGV['org_type'] == "一般") & (data_NGV['org_status'] == '留存') & (
data_NGV['area_manager'] != '殷昊') & (
data_NGV['area_manager'] != '孙玉蕾') & (
(data_NGV['saas_create_time'] == formatted_today_180) | (
data_NGV['saas_create_time'] == formatted_today_90)) & (
data_NGV['is_main_org'] == "1")
data_NGV = data_NGV.loc[data_NGV["条件"]]
data_NGV = pd.concat([data_NGV, result], axis=0)
print(len(data_NGV), "20250325")
# 定义一个函数，根据 saas_create_time 字段的值设置阶段列和主要目的列的值
def set_columns(row):
if row['saas_create_time'] == formatted_today_180:
row['跟进阶段'] = '新签后180天'
row['主要目的'] = '关怀使用情况，邀约转介绍，跟进增购商机，识别首年续约风险，及时跟进提报。'
elif row['saas_create_time'] == formatted_today_90:
row['跟进阶段'] = '新签后90天'
row['主要目的'] = '关怀使用情况，解答使用问题，强化培训，挖掘增购商机。'
else:
row['跟进阶段'] = "派发异常请联系数据组！" # 返回其他默认值
row['主要目的'] = "派发异常请联系数据组！" # 返回其他默认值
return row
# 使用 apply 方法将函数应用到每一行
data_NGV = data_NGV.apply(set_columns, axis=1)
print("SaaS开户回访人数：", len(data_NGV))
print(data_NGV)
# 重置索引
data_NGV = data_NGV.reset_index(drop=True)
for index_num, row in data_NGV.iterrows(): # 对过滤后的每一条进行派发
try:
# print(row["org_code"]) # 数据验证
# print(row["service_impl_principal"])
# print(row["area_manager"])
# print(row["technician"])
payload_dict = {}
saas_use_year = re.findall(r'第([0-9]+)年', row["saas_use_year"])[0]
NGV_roles = {
'relationship_manager': row['service_impl_principal'], # 运营负责人
# 'relationship_manager': "张阳", # 运营负责人
'area_manager': row['area_manager'], # 区域经理
'technician': row['technician'], # 技术专家
'salesmen': row['salesmen'], # 销售负责人
}
for role, name in NGV_roles.items(): # 寻找对应的员工ID
for row_item in self.staff_id_list:
staff_id = self.get_staff_id(row_item, name)
if staff_id:
NGV_roles[role] = staff_id
break # 找到后退出循环
else:
NGV_roles[role] = None # 如果没有找到对应的员工ID
# 回访人员： 需确认 四年以下 technician
if int(saas_use_year) < 4:
relationship_manager, area_manager, technician, salesmen = [NGV_roles[role] for role in
['relationship_manager',
'area_manager',
'technician', 'salesmen']]
# 如果未找到运营负责人，则根据省市区派发给日常回访客服
if not relationship_manager:
relationship_manager = self.assign_customer_service(
row['province_name'], row['city_name'], row['area_name'], self.index
)[0]
if not technician:
technician = self.assign_customer_service(
row['province_name'], row['city_name'], row['area_name'], self.index
)[2]
if row["group_grade"] == "普通客户（VIP）" or row["group_grade"] == "重要客户（SVIP）":
payload_dict.update({
"_widget_1734590278288": {"value": relationship_manager}, # 跟进人是运营负责人
})
else:
payload_dict.update({
"_widget_1734590278288": {"value": technician}, # 跟进人是技术专家
})
else:
salesmen = [NGV_roles[role] for role in
['salesmen']]
# 直接根据省市区派发给日常回访客服
relationship_manager, customer_service, technician, area_manager = self.assign_customer_service(
row['province_name'], row['city_name'], row['area_name'], self.index
)
if row["group_grade"] == "普通客户（VIP）" or row["group_grade"] == "重要客户（SVIP）":
payload_dict.update({
"_widget_1734590278288": {"value": customer_service} # 跟进人是日常回访客服
})
else:
payload_dict.update({
"_widget_1734590278288": {"value": technician} # 跟进人是技术专家
})
payload_dict.update({
# "_widget_1734590278288": {"value": relationship_manager}, # 跟进人是运营负责人
"_widget_1734590278289": {"value": relationship_manager}, # 运营负责人
"_widget_1734590278290": {"value": area_manager}, # 区域经理
"_widget_1734590278291": {"value": technician}, # 技术专家
"_widget_1735290738545": {"value": salesmen} # 销售负责人
})
if payload_dict.get("_widget_1734590278288") == "02414917880947": # 如果跟进人是殷浩
payload_dict.update({
"_widget_1734590278288": {"value": "051612246035720178"}, # 跟进人是赵柄诚
})
# 输出结果
print("SaaS开户回访人员：", relationship_manager or "未分配")
print("SaaS技术专家：", technician or "未分配")
print("SaaS区域经理：", area_manager or "未分配")
# 判断权限唯一值
# pattern = r'([\u4e00-\u9fa5]+)\（'
# match = re.search(pattern, row['max_group_grade'])
# group_grade = match.group(1)
group_grade = re.sub(r'（[^）]*）', '', row['max_group_grade'])
if not row['saas_customer_type'] or row['saas_customer_type'] == 'NA' or row[
'saas_customer_type'] == 'None':
row['saas_customer_type'] = "F"
NGV_store_level_key = group_grade + row['max_saas_edition'] + row['max_saas_customer_type']
print("权限唯一值：", NGV_store_level_key)
Billing = None
for item in self.permissions_table:
if NGV_store_level_key == item.get("_widget_1734056507963"): # 合并（等级-类型-分层）
print("该门店开单的权限是：", item.get(item.get("_widget_1734055617039")))
Billing = item.get("_widget_1734055617039") # 开单
Service_Alerts = item.get("_widget_1734055617040") # 服务提醒
membership = item.get("_widget_1734055617041") # 会员卡
SMS = item.get("_widget_1734055617042") # 短信
Public_domain_applets = item.get("_widget_1734055617043") # 公域小程序
Private_domain_applets = item.get("_widget_1734055617044") # 私域小程序
Test_sheet = item.get("_widget_1734055617045") # 检测单
AI_poster = item.get("_widget_1734055617046") # AI海报
Business_wallets = item.get("_widget_1734055617047") # 企业钱包
Precision_marketing = item.get("_widget_1734055617049") # 精准营销
Paid_memberships = item.get("_widget_1734055617051") # 付费会员
business_WeCom = item.get("_widget_1734055617052") # 企业微信
Insurance_policy_identification = item.get("_widget_1734055617053") # 保险单识别
Insurance_bots = item.get("_widget_1734055617054") # 保险机器人
Camera_pick_up = item.get("_widget_1734055617055") # 摄像头接车
Camera_billing = item.get("_widget_1734055617056") # 摄像头开单
Transparent_workshop = item.get("_widget_1734055617057") # 透明车间
Cross_industry_cooperation = item.get("_widget_1734055617058") # 异业合作
BI_Insights = item.get("_widget_1734055617059") # BI洞察
payload_dict.update(
{
"_widget_1734073342350": {"value": Billing},
"_widget_1735004315757": {"value": Service_Alerts},
"_widget_1735004315756": {"value": membership},
"_widget_1735004315755": {"value": SMS},
"_widget_1735004315754": {"value": Public_domain_applets},
"_widget_1735004315753": {"value": Private_domain_applets},
"_widget_1735004315752": {"value": Test_sheet},
"_widget_1735004315751": {"value": AI_poster},
"_widget_1735004315750": {"value": Business_wallets},
"_widget_1735004315749": {"value": Precision_marketing},
"_widget_1735004315748": {"value": Paid_memberships},
"_widget_1735004315747": {"value": business_WeCom},
"_widget_1735004315746": {"value": Insurance_policy_identification},
"_widget_1735004315745": {"value": Insurance_bots},
"_widget_1735004315744": {"value": Camera_pick_up},
"_widget_1735004315743": {"value": Camera_billing},
"_widget_1735004315742": {"value": Transparent_workshop},
"_widget_1735004315741": {"value": Cross_industry_cooperation},
"_widget_1734073342352": {"value": BI_Insights},
}
)
feature_dict = {
"开单": "_widget_1734073342350",
"服务提醒": "_widget_1735004315757",
"会员卡": "_widget_1735004315756",
"短信": "_widget_1735004315755",
"公域小程序": "_widget_1735004315754",
"私域小程序": "_widget_1735004315753",
"检测单": "_widget_1735004315752",
"AI海报": "_widget_1735004315751",
"企业钱包": "_widget_1735004315750",
"精准营销": "_widget_1735004315749",
"付费会员": "_widget_1735004315748",
"企业微信": "_widget_1735004315747",
"保险单识别": "_widget_1735004315746",
"保险机器人": "_widget_1735004315745",
"摄像头接车": "_widget_1735004315744",
"摄像头开单": "_widget_1735004315743",
"透明车间": "_widget_1735004315742",
"异业合作": "_widget_1735004315741",
"BI洞察": "_widget_1734073342352",
}
# _widget_1735527329557 下次是否推荐
for new_item in self.get_feature_usage:
for feature_module, feature_value in feature_dict.items(): # 模块
if new_item.get("_widget_1735268263079") == feature_module and new_item.get(
"_widget_1735527329557") == "否" and new_item.get(
"_widget_1735280720550") == \
row["id_own_org"]: # 下次是否推荐 功能使用情况表
print(f"{feature_value}进行了更改")
payload_dict.update({f"{feature_value}": {"value": "×"}})
if new_item.get("_widget_1735268263079") == feature_module and new_item.get(
"_widget_1736414617462") == "否" and new_item.get(
"_widget_1735280720550") == \
row["id_own_org"]: # 下次是否跟进
print(f"{feature_value}进行了更改")
payload_dict.update({f"{feature_value}": {"value": "×"}})
fields_to_check = {
"_widget_1735004315763": Billing, # 开单
"_widget_1735106258016": Service_Alerts, # 服务提醒
"_widget_1735106258036": membership, # 会员卡
"_widget_1735106258086": SMS, # 短信
"_widget_1735106258112": Public_domain_applets, # 公域小程序
"_widget_1735106258141": Private_domain_applets, # 私域小程序
"_widget_1735107354648": Test_sheet, # 检测单
"_widget_1735107354725": AI_poster, # AI海报
"_widget_1735107354811": Business_wallets, # 企业钱包
"_widget_1735107354906": Precision_marketing, # 精准营销
"_widget_1735107354980": Paid_memberships, # 付费会员
"_widget_1735107355093": business_WeCom, # 企业微信
"_widget_1735107355143": Insurance_policy_identification, # 保险单识别
"_widget_1735107355235": Insurance_bots, # 保险机器人
"_widget_1735107355333": Camera_pick_up, # 摄像头接车
"_widget_1735107355392": Camera_billing, # 摄像头开单
"_widget_1735107355502": Transparent_workshop, # 透明车间
"_widget_1735107355618": Cross_industry_cooperation, # 异业合作
"_widget_1735107355740": BI_Insights # BI洞察
}
# 遍历每个字段，检查其值并更新payload_dict
for widget_id, field_name in fields_to_check.items():
if field_name == "√":
payload_dict.update({widget_id: {"value": "是"}})
break
is_continue = False
# 如果门店倒闭则不派发
for store in self.NGV_data_list:
if row["id_own_org"] == store.get("_widget_1734062123069") and store.get(
"_widget_1752027386523") == "门店倒闭":
is_continue = True
print(f"门店已关闭，不派发")
break
if is_continue:
continue
if not Billing:
print(f"权限表请求失败或者权限表无对应关系,权限唯一值是：{NGV_store_level_key}")
if row["active_status_fmt"] == "活跃": # 开单 是否使用
payload_dict.update({"_widget_1735004315765": {"value": "是"}})
else:
payload_dict.update({"_widget_1735004315765": {"value": "否"}})
try:
if row["saas_edition_fmt"] not in ["基础版", "入门版"]: # 会员卡 是否拥有
payload_dict.update({"_widget_1735106258036": {"value": "是"}})
else:
payload_dict.update({"_widget_1735106258036": {"value": "否"}})
except Exception as e:
print(f"会员卡识别：Error finding customer service: {e}")
try:
if row["card_bill_day_count_last_30_day"] != "0": # 会员卡 是否使用
payload_dict.update({"_widget_1735106258038": {"value": "是"}})
else:
payload_dict.update({"_widget_1735106258038": {"value": "否"}})
except Exception as e:
print(f"会员卡识别：Error finding customer service: {e}")
# print(self.service_remind.get("_widget_1735112637045"))
payload_dict["_widget_1735106258018"] = {"value": "否"}
for item in self.service_remind:
if row["id_own_group"] == item.get("_widget_1735112637043"):
if int(item.get("_widget_1735112637045")) < 180 and int(
item.get("_widget_1735112637046")) == 1: # 服务提醒 是否使用
payload_dict.update({"_widget_1735106258018": {"value": "是"}})
break
elif int(item.get("_widget_1735112637048")) > 0:
payload_dict.update({"_widget_1735106258018": {"value": "是"}})
break
keys_to_check = [
"_widget_1735113110155"
] # 智能检测 是否使用
# 初始化默认值为"否"
payload_dict["_widget_1735107354650"] = {"value": "否"}
# 检查每个键，如果有一个大于0，则更新为"是"并停止检查
for key in keys_to_check:
for item in self.Smart_detection:
if row["id_own_org"] == item.get("_widget_1735113110147"):
if int(item.get(key, 0)) > 0: # 使用get方法并提供默认值0防止键不存在的情况
payload_dict["_widget_1735107354650"]["value"] = "是"
break
# 近30天业务单量=0 则其它所有模块均不推荐
try:
for feature_module, feature_value in feature_dict.items(): # 模块
if row["bill_count_last_30_day"] == '0' and payload_dict[feature_value]["value"] == '△':
payload_dict.update({f"{feature_value}": {"value": "×"}})
except Exception as e:
print(f"不开单识别：Error finding customer service: {e}")
# 保单识别：从系统中抽取目标门店，针对门店抽取修改是否推荐
try:
if row["org_code"] in self.widget_list:
payload_dict.update({'_widget_1735004315746': {"value": "△"}})
except Exception as e:
print(f"保单识别：Error finding customer service: {e}")
# 私域小程序：根据是否开通微信小程序判断是否使用，旗舰版及以上算拥有
try:
for item in self.private_domain:
if row["id_own_group"] == item.get("_widget_1742795002375"): # 公司id
if int(item.get("_widget_1742795002379")) > 0: # 上架商品数
payload_dict.update({"_widget_1735106258143": {"value": "是"}}) # DX:是否拥有
break
else:
payload_dict.update({"_widget_1735106258143": {"value": "否"}}) # DX:是否拥有
break
except Exception as e:
print(f"私域小程序：Error finding customer service: {e}")
try:
high_version = ['皇冠版', '至尊版', '尊享版', '旗舰版']
if row["saas_edition_fmt"] in high_version:
payload_dict.update({'_widget_1735106258141': {"value": "是"}}) # SYXCX:是否拥有
else:
payload_dict.update({'_widget_1735106258141': {"value": "否"}}) # SYXCX:是否拥有
except Exception as e:
print(f"私域小程序：Error finding customer service: {e}")
# 公域小程序：根据是否开通微信小程序判断是否使用，旗舰版及以上算拥有
try:
for item in self.public_domain:
if row["id_own_org"] == item.get("_widget_1742784257506"): # 门店id
if int(item.get("_widget_1742784257509")) == 1: # 发布商品数量
payload_dict.update({"_widget_1735106258114": {"value": "是"}}) # GYXCX:是否使用
break
else:
payload_dict.update({"_widget_1735106258114": {"value": "否"}}) # GYXCX:是否使用
break
except Exception as e:
print(f"公域小程序：Error finding customer service: {e}")
try:
if row["id_own_org"] in self.public_domain_list:
payload_dict.update({'_widget_1735106258112': {"value": "是"}}) # GYXCX:是否拥有
else:
payload_dict.update({'_widget_1735106258112': {"value": "否"}}) # GYXCX:是否拥有
except Exception as e:
print(f"公域小程序：Error finding customer service: {e}")
# 异业合作：根据是否存在判断是否拥有，过滤条件 商品名称包含异业两个字
try:
if row["id_own_org"] in self.different_industries_list:
payload_dict.update({'_widget_1735107355618': {"value": "是"}}) # YYHZ:是否拥有
else:
payload_dict.update({'_widget_1735107355618': {"value": "否"}}) # YYHZ:是否拥有
except Exception as e:
print(f"异业合作：Error finding customer service: {e}")
# 短信：根据是否启动短信功能判断是否拥有,根据
try:
for item in self.groupnotification:
if row["id_own_group"] == item.get("_widget_1743065201885"): # 公司id
if int(item.get("_widget_1743065201886")) == 1: # 是否启动短信功能
payload_dict.update({"_widget_1735106258086": {"value": "是"}}) # DX:是否拥有
break
else:
payload_dict.update({"_widget_1735106258086": {"value": "否"}}) # DX:是否拥有
break
except Exception as e:
print(f"短信：Error finding customer service: {e}")
try:
for item in self.groupnotification:
if row["id_own_group"] == item.get("_widget_1743065201885"): # 公司id
if int(item.get("_widget_1743065201889")) > 0: # 累计发送成功总人数
payload_dict.update({"_widget_1735106258088": {"value": "是"}}) # DX:是否使用
break
else:
payload_dict.update({"_widget_1735106258088": {"value": "否"}}) # DX:是否使用
break
except Exception as e:
print(f"短信：Error finding customer service: {e}")
NGV_data_id = None
# 获取关联数据
for NGV_Data in self.NGV_data_list:
# NGV_Data = NGV_Data.get("data")
if row["org_code"] == NGV_Data.get("_widget_1734062123071"): # 门店编码
NGV_data_id = NGV_Data.get("_id")
print(NGV_data_id)
try:
png_url = NGV_Data.get('_widget_1742890765211', {})[0].get('url', "")
except:
png_url = ""
print(png_url)
if not NGV_data_id:
print("未找到数据ID")
distribution_date = datetime.datetime.now(datetime.timezone.utc)
distribution_date = distribution_date.strftime('%Y-%m-%dT%H:%M:%S.%f')[:-3] + 'Z'
upload_key = None
UUid = time.strftime("%Y%m%d%H%M%S", time.localtime())
if png_url:
save_dir = "sampleCloud" # 设置输出目录
# 创建输出目录（如果不存在）
import os
os.makedirs(save_dir, exist_ok=True)
save_path = fr'{save_dir}\png\{time.strftime("%Y%m%d%H%M%S", time.localtime())}.png'
NewServicesRevisit.download_url_content(png_url, save_path)
up_data = api_instance.get_upload_token(
{"api_key": "675b900991ad2491c69389ca", "entry_id": "675b9c63925cd404038a6b86",
"transaction_id": UUid})
upload_url = up_data.get("upload_url")
upload_token = up_data.get("upload_token")
upload_result = api_instance.upload_file(
{"upload_url": upload_url, "upload_token": upload_token, "file_path": save_path})
upload_key = upload_result.get("key")
# print("已上传文件")
# print(upload_result)
# print(upload_key)
payload_dict.update({
"_widget_1734590278279": {"value": row["group_name"]}, # 公司名称
"_widget_1735112931760": {"value": row["id_own_group"]}, # 公司id
"_widget_1735112931761": {"value": row["id_own_org"]}, # 门店id
"_widget_1734590278281": {"value": row['org_name']}, # 门店名称
"_widget_1734590278292": {"value": row["跟进阶段"]}, # 跟进阶段
"_widget_1734321349021": {"value": NGV_data_id}, # 关data_get联数据
"_widget_1742548684369": {"value": row['主要目的']}, # 主要目的
"_widget_1734590278266": {"value": row['region_name']}, # 大区
"_widget_1734590278285": {"value": row['branch_name']}, # 小区
"_widget_1734590278284": {"value": row['province_name']}, # 省
"_widget_1734590278283": {"value": row['city_name']}, # 市
"_widget_1734590278282": {"value": row['area_name']}, # 区
"_widget_1734590278278": {"value": row['saas_customer_type']}, # 门店分层
"_widget_1734590278277": {"value": row['group_grade']}, # 公司等级
"_widget_1734590278276": {"value": row['limit_user_type']}, # 限制账户类型
"_widget_1734590278275": {"value": row['active_user_type']}, # 有效账户类型
"_widget_1734590278274": {"value": row['saas_version']}, # ERP操作模式
"_widget_1734590278273": {"value": row['saas_use_year']}, # 使用时长
"_widget_1734590278272": {"value": row['org_stage']}, # 门店阶段
"_widget_1734590278271": {"value": row['manage_model']}, # 经营模式
"_widget_1734590278267": {"value": row['contacts']}, # 联系人
"_widget_1734590278287": {"value": row['contact_mobile']}, # 联系手机号
"_widget_1734590278286": {"value": row['saas_edition_fmt']}, # SaaS版本
"_widget_1734590278280": {"value": row['org_code']}, # 门店编码
"_widget_1735096489244": {"value": distribution_date}, # 派发时间
"_widget_1742895342914": {"value": row['business_scope_fmt']}, # 经营范围
"_widget_1742895342915": {"value": row['station_number']}, # 工位数
"_widget_1742895342916": {"value": [upload_key]} # 门头照片
})
routine_follow_up_payload = {
"api_key": "675b900991ad2491c69389ca",
"entry_id": "675b9c63925cd404038a6b86",
"is_start_workflow": "true",
"data": payload_dict,
"transaction_id": UUid
}
print(routine_follow_up_payload)
res = api_instance.data_batch_create(routine_follow_up_payload)
logger.info(f"创建结果：{res}")
time.sleep(1)
except:
pass
common_module.send_task_status(task_start_time, "新签客户回访")
if __name__ == '__main__':
start = NewServicesRevisit()
start.main()
back_ground_module/revisit_renew_services_90_120_180.py
+946
View File
@@ -0,0 +1,946 @@
import os
import time
import requests
from api import API
from back_ground_module import CommonModule
import pandas as pd
import datetime
import re
from log_config import configure_task_logger, configure_error_task_logger
api_instance = API()
common_module = CommonModule()
# start_time = datetime.datetime.now()
# 获取已经配置好的常规日志记录器
logger = configure_task_logger()
# 获取已经配置好的错误任务日志记录器
error_task_logger = configure_error_task_logger()
class RenewServicesRevisit:
"""续约回访90-180"""
def __init__(self):
self.index = None
self.data_NGV = None
self.date_list = None
self.Smart_detection = None
self.service_remind = None
self.json_list = []
self.NGV_data_list = None
self.permissions_table = None
self.staff_id_list = None
self.get_feature_usage = None
self.policy_recognition = None
self.widget_list = None
self.private_domain = None
self.public_domain = None
self.public_domain_list = None
self.different_industries = None
self.different_industries_list = None
self.groupnotification = None
def load_all_data(self):
"""加载所有必要的数据表"""
# 省市区人员关系表
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "676512ac3e54dc3159460c0a"}
json_dict = api_instance.entry_data_list(payload)
if json_dict and "data" in json_dict:
self.json_list = json_dict.get("data")
else:
print("加载省市区人员关系表失败")
self.json_list = []
# 获取简道云员工id
payload = {"api_key": "6694d3c4fcb69ca9a111a6c4",
"entry_id": "6769204a1902c9341340a1bc",
}
staff_id = api_instance.entry_data_list(payload)
self.staff_id_list = staff_id.get("data") # api请求格式，将数据封装在data字典里
# 获取权限表信息
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "675b96c14e839f90fef1647c"}
self.permissions_table = api_instance.entry_data_list(payload).get("data")
# 获取NGV数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "675bb02bd2d53c2034c665e4"}
self.NGV_data_list = api_instance.entry_data_list(payload).get("data")
# print("NGV获取后的类型：", type(self.NGV_data_list))
# 获取服务提醒-数据支持表单数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "676bb7bda3029720f1083e99"}
self.service_remind = api_instance.entry_data_list(payload).get("data")
# 获取智能检测-数据支持表单数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "676bb99649ab3ac975af6e39"}
self.Smart_detection = api_instance.entry_data_list(payload).get("data")
# 获取功能使用情况表
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "6763bbf657bd8fb76fcb41b2"}
self.get_feature_usage = api_instance.entry_data_list(payload).get("data", [])
# 获取保单识别表
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "6773a60d30ed87ff9f68d3c5"}
self.policy_recognition = api_instance.entry_data_list(payload).get("data")
# 提取 _widget_1735632397600 的值并存储在列表中
self.widget_list = [item['_widget_1735632397600'] for item in self.policy_recognition]
# 获取私域小程序-数据支持表单数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "67e0f0fae622896749ba5087"}
self.private_domain = api_instance.entry_data_list(payload).get("data", [])
# 提取 _widget_1742795002375 的值并存储在列表中
# self.private_domain_list = [item['_widget_1742795002375'] for item in self.private_domain]
# 获取公域小程序-数据支持表单数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "67e0c702c8f603b997980999"}
self.public_domain = api_instance.entry_data_list(payload).get("data", [])
# 提取 _widget_1742784257506 的值并存储在列表中
self.public_domain_list = [item['_widget_1742784257506'] for item in self.public_domain]
# 获取异业合作-数据支持表单数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "67e24fdd8dfcfa918e17c30b"}
self.different_industries = api_instance.entry_data_list(payload).get("data", [])
# 提取 _widget_1742784257506 的值并存储在列表中
self.different_industries_list = [item['_widget_1742884829007'] for item in self.different_industries]
# 获取短信-数据支持表单数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "67e5107198ba1b20d5df3974"}
self.groupnotification = api_instance.entry_data_list(payload).get("data", [])
@staticmethod
def download_url_content(url, save_path):
"""
下载指定 URL 的内容并保存到本地文件。
:param url: 要下载内容的 URL
:param save_path: 保存文件的路径
"""
try:
# 发送 GET 请求以获取内容
response = requests.get(url, stream=True)
response.raise_for_status() # 如果响应状态码不是 200，抛出异常
# 确保保存目录存在
os.makedirs(os.path.dirname(save_path), exist_ok=True)
# 将内容写入文件
with open(save_path, 'wb') as file:
for chunk in response.iter_content(chunk_size=8192): # 分块写入，避免占用过多内存
if chunk: # 过滤掉空块
file.write(chunk)
print(f"文件已成功保存到 {save_path}")
except requests.exceptions.RequestException as e:
print(f"下载失败: {e}")
except Exception as e:
print(f"发生错误: {e}")
@staticmethod
def build_index(json_list):
index = {}
for json_item in json_list:
try:
key = (json_item['_widget_1734677164861'], json_item['_widget_1734677164862'],
json_item['_widget_1734677164863']) # 省市区
if '_widget_1734677164871' not in json_item: # 日常回访客服
raise KeyError("缺少 '日常回访客服' 键")
index[key] = json_item
except KeyError as e:
print(f"警告：{e}，跳过该条记录: {json_item}")
continue
return index
@staticmethod
def find_customer_service(province_name, city_name, area_name, index):
key = (province_name, city_name, area_name)
# print(index)
if key not in index:
return "数据缺失: 未找到对应的日常回访客服"
return index[key]
@staticmethod
def remove_parentheses(text: str) -> str:
# 使用正则表达式匹配并去除括号及其内容
# \s* 表示匹配零个或多个空白字符（处理括号前后可能存在的空格）
# $ 和 $ 分别表示匹配左括号和右括号
# 中间的 .*? 表示非贪婪地匹配任意数量的字符（包括没有字符的情况）
cleaned_text = re.sub(r'\s*$.*?$\s*', '', text)
# 为了确保同时处理中文括号，再进行一次替换
cleaned_text = re.sub(r'\s*（.*?）\s*', '', cleaned_text)
return cleaned_text.strip() # 去除两端多余的空白字符
@staticmethod
def get_staff_id(row_item, name):
"""辅助函数，用于获取员工ID"""
if str(row_item["_widget_1734942794144"]) == str(name): # 检查姓名是否匹配
return row_item["_widget_1734942794145"] # 返回员工ID
return None
def assign_customer_service(self, province_name, city_name, area_name, index):
"""根据省市区派发给日常回访客服"""
try:
customer_service_info = self.find_customer_service(province_name, city_name, area_name, index)
# 定义一个辅助函数，用于安全地获取多层字段中的 username
def safe_get_username(data, key):
try:
if isinstance(data, dict):
return data.get(key, {}).get('username', "")
return ""
except:
return ""
relationship_manager = safe_get_username(customer_service_info, '_widget_1734677164864')
customer_service = safe_get_username(customer_service_info, '_widget_1734677164871')
technician = safe_get_username(customer_service_info, '_widget_1734677164866')
area_manager = safe_get_username(customer_service_info, '_widget_1734677164865')
return relationship_manager, customer_service, technician, area_manager
except Exception as e:
print(f"Error finding customer service: {e}")
return "分配失败，请检查", "分配失败，请检查", "分配失败，请检查"
def calculate_date_one(self, start_offset=0):
"""
计算从当前日期（或指定偏移量的日期）开始，往前遍历遇到date_list中日期的次数。
参数:
- start_offset: 从当前日期起始的天数偏移量，默认为0（即今天）。负数表示过去，正数表示未来。
返回:
- date_one: 遍历到date_list中日期的次数。
"""
# 设置起始日期
now_time = datetime.datetime.now() + datetime.timedelta(days=start_offset)
# 初始化计数器
date_one = 1
print("当前日期：", now_time.strftime("%Y-%m-%d"))
# 检查起始日期是否在date_list中
if now_time.strftime("%Y-%m-%d") in self.date_list:
date_one = 0
print("开始次数：", date_one)
else:
# 遍历日期
for i in range(1, 10):
new_date = now_time + datetime.timedelta(days=-i)
new_date_str = new_date.strftime("%Y-%m-%d")
print("遍历日期：", new_date_str)
if new_date_str in self.date_list:
date_one += 1
print("节假日期：", new_date_str)
else:
break
print("遍历次数：", date_one)
return date_one
def main(self):
import datetime
task_start_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
# 主店过期，分店设置为主店
global png_url, upload_key
self.load_all_data()
self.date_list = common_module.get_holiday_list() # 获取一年中的节假日
self.date_one = self.calculate_date_one(start_offset=0)
print(self.date_one)
self.data_NGV = common_module.get_ngv_details(days_back=1) # 获取data_NGV 并转为str
self.index = self.build_index(self.json_list)
# 将A列和B列的日期字符串转换为日期格式
data_NGV = self.data_NGV.copy()
# data_NGV.to_csv("dayin.csv")
data_NGV['A'] = pd.to_datetime(data_NGV['expiry_time'])
data_NGV['B'] = pd.to_datetime(data_NGV['renew_date'])
def replace_values(series):
# 使用条件判断来进行替换
return series.apply(lambda x: '' if pd.isna(x) or x in ['NA', 'None', ''] else x)
# 对整个DataFrame的所有列应用替换函数
# 处理字符串数据并显式指定数据类型
data_NGV = data_NGV.apply(replace_values)
# data_NGV.to_csv("dayinNGV.csv")
# 定义优先级顺序
edition_order = ['皇冠版', '至尊版', '尊享版', '旗舰版', '标准版', '进阶版', '基础版', '入门版']
customer_type_order = ["F", "E", "D", "C", "B", "A"] # 索引越小优先级越高
group_grade_order = ['全国KA（FMVP）', '区域KA（MVP）', '重要客户（SVIP）', '普通客户（VIP）']
# 创建映射字典，并为不在列表中的值设置默认值
edition_map = {edition: idx for idx, edition in enumerate(edition_order)}
customer_type_map = {ctype: idx for idx, ctype in enumerate(customer_type_order)}
group_grade_map = {grade: idx for idx, grade in enumerate(group_grade_order)}
# 添加用于排序的新列，并处理不在映射字典中的值
data_NGV['edition_rank'] = data_NGV['saas_edition_fmt'].map(edition_map).fillna(0).astype(
int) # 缺失值用最高优先级填充
data_NGV['customer_type_rank'] = data_NGV['saas_customer_type'].map(customer_type_map).fillna(0).astype(int)
data_NGV['group_grade_rank'] = data_NGV['group_grade'].map(group_grade_map).fillna(0).astype(int)
# data_NGV.to_csv("88855.csv")
# 找到每组中 edition_rank 最小值对应的行
best_edition_idx = data_NGV.groupby('id_own_group')['edition_rank'].idxmin()
best_edition_rows = data_NGV.loc[best_edition_idx]
best_edition_rows['max_saas_edition'] = best_edition_rows['saas_edition_fmt']
# 找到每组中 customer_type_rank 最小值对应的行
best_customer_type_idx = data_NGV.groupby('id_own_group')['customer_type_rank'].idxmin()
best_customer_type_rows = data_NGV.loc[best_customer_type_idx]
best_customer_type_rows['max_saas_customer_type'] = best_customer_type_rows['customer_type_rank'].apply(
lambda x: customer_type_order[x])
# 找到每组中 group_grade_rank 最小值对应的行
best_group_grade_idx = data_NGV.groupby('id_own_group')['group_grade_rank'].idxmin()
best_group_grade_rows = data_NGV.loc[best_group_grade_idx]
best_group_grade_rows['max_group_grade'] = best_group_grade_rows['group_grade']
# 合并最佳值回到原数据集
best_values = (
best_edition_rows[['id_own_group', 'max_saas_edition']]
.merge(best_customer_type_rows[['id_own_group', 'max_saas_customer_type']], on='id_own_group',
how='outer')
.merge(best_group_grade_rows[['id_own_group', 'max_group_grade']], on='id_own_group', how='outer')
)
# 将最佳值合并回原数据集
data_NGV = data_NGV.merge(best_values, on='id_own_group', how='left')
condition = (data_NGV['is_main_org'] == 1) & (data_NGV['org_status'] == '过期') # 步骤2: 过滤条件
ngvv2 = data_NGV[condition]
# ngvv2.to_excel(r"C:\Users\Administrator.DESKTOP-7IC2USJ\Desktop\NGVV2.xlsx")
data_NGV_V2 = data_NGV.copy() # 步骤3: 检查id_own_group是否存在于ngvv2中
data_NGV_V2['条件'] = ((data_NGV_V2['org_type'] == "一般") & (data_NGV_V2['org_status'] == '留存') &
(data_NGV_V2['area_manager'] != '殷昊') & (data_NGV_V2['area_manager'] != '孙玉蕾') & (
data_NGV_V2['is_main_org'] != 1))
data_NGV_V2 = data_NGV_V2.loc[data_NGV_V2["条件"]]
# 步骤4: 过滤存在的记录
data_NGV_V2['exists_in_ngvv2'] = data_NGV_V2['id_own_group'].isin(ngvv2['id_own_group'])
filtered_data = data_NGV_V2[data_NGV_V2['exists_in_ngvv2']]
fixed_order = ['皇冠版', '至尊版', '尊享版', '旗舰版', '标准版', '进阶版', '基础版', '入门版']
# sorted_items = sorted(filtered_data, key=lambda x: fixed_order.index(x))
fixed_order_map = {edition: index for index, edition in enumerate(fixed_order)}
filtered_data['sort_key'] = filtered_data['saas_edition_fmt'].map(fixed_order_map)
filtered_data = filtered_data.sort_values(by='sort_key').drop('sort_key', axis=1)
result = filtered_data.drop_duplicates(subset='id_own_group', keep='first')
data_NGV['条件'] = (data_NGV['org_type'] == "一般") & (data_NGV['org_status'] == '留存') & (
data_NGV['area_manager'] != '殷昊') & (
data_NGV['area_manager'] != '孙玉蕾') & (
data_NGV['is_main_org'] == 1)
data_NGV = data_NGV.loc[data_NGV["条件"]]
data_NGV = pd.concat([data_NGV, result], axis=0)
# data_NGV.to_csv("dayin1.csv")
data_details = data_NGV.copy()
# data_details.to_excel(r"C:\Users\admin\Downloads\1.xlsx")
# 重置索引
data_details = data_details.reset_index(drop=True)
# data_details.to_csv("dayin.csv")
# 判断A列的日期是否大于B列的日期730天，如果是的话，将B列的值设置为1
data_details['条件'] = data_details.apply(
lambda row: (
(pd.to_datetime(row['A']) - pd.to_datetime(row['B'])).days
if pd.to_datetime(row['A']) - pd.to_datetime(row['B']) >= pd.Timedelta(days=730)
else 0
),
axis=1
)
data_details = data_details.loc[data_details["条件"] > 0]
# 定义一个函数，用于将数字除以365并取整数
def divide_by_365(x):
if isinstance(x, (int, float)):
return int(x / 365)
else:
return x
# 使用applymap()函数将divide_by_365函数应用到DataFrame的每个元素
data_details['年'] = data_details['条件'].apply(divide_by_365)
# 重置索引
data_details = data_details.reset_index(drop=True)
# data_details.to_excel(r"C:\Users\admin\Downloads\2.xlsx")
# 创建一个新的空的DataFrame
new_df = pd.DataFrame()
# 遍历原始DataFrame的每一行
from datetime import datetime
for index, row in data_details.iterrows():
# 根据A列的值来决定复制的次数
if row["renew_date"] != "2024-02-29":
for i_new in range(1, row['年']):
# 修改日期
row_new = row.copy()
c = row_new["renew_date"]
date_obj = datetime.strptime(c, "%Y-%m-%d")
new_year = date_obj.year + i_new
new_date_obj = date_obj.replace(year=new_year)
new_c = new_date_obj.strftime("%Y-%m-%d")
row_new["renew_date"] = new_c
# 将当前行添加到新的DataFrame中
# new_df = new_df.append(row_new, ignore_index=True)
new_df = pd.concat([new_df, pd.DataFrame([row_new])], ignore_index=True)
# 合并两个DataFrame
# new_df.to_excel(r"C:\Users\admin\Downloads\3.xlsx")
merged_df = pd.concat([data_NGV, new_df], axis=0, ignore_index=True)
data_details = merged_df.copy() # 替换名称
data_details_not_null = data_details[data_details['renew_date'].notnull()]
# data_details_not_null = data_details_not_null[data_details_not_null['renew_date'].str.contains('2023')]
# data_details_not_null = data_details_not_null.sort_values(by='renew_date', ascending=True).drop_duplicates(
# subset='id_own_group') 重置索引
data_details_not_null = data_details_not_null.reset_index(drop=True)
data_details = data_details_not_null.copy() # 替换名称 v2
data_details['saas_create_time'] = data_details['saas_create_time'].str[:4] # 截取前10位
data_details['renew_date_new'] = data_details['renew_date'].str[:4] # 截取前10位
data_details = data_details[
data_details['saas_create_time'] != data_details['renew_date_new']] # 过滤掉等于renew_date的行
data_details = data_details.reset_index(drop=True)
print(data_details)
# data_details.to_excel(r"C:\Users\admin\Downloads\4.xlsx")
import datetime
start_time = datetime.datetime.now()
date_90 = 83
date_120 = 113
date_180 = 173
# self.date_one = 1
now_time = start_time.replace()
if now_time.strftime("%Y-%m-%d") in self.date_list:
self.date_one = 0
print("开始次数：", self.date_one)
print("当前日期：", now_time)
# for i in range(1, 10):
# new_date = now_time + datetime.timedelta(days=-i)
# new_date = new_date.strftime("%Y-%m-%d")
# print("遍历日期：", new_date)
# if new_date in self.date_list:
# date_one = date_one + 1
# print("节假日期：", new_date)
# else:
# break
print("遍历次数：", self.date_one)
now_time = start_time.replace()
for i in range(0, self.date_one):
print(f"这是第{i}次遍历")
import datetime
now_time = datetime.datetime.now() + datetime.timedelta(days=-(i + 1))
today = now_time + datetime.timedelta(days=-date_90)
formatted_today_90 = today.strftime("%Y-%m-%d")
today = now_time + datetime.timedelta(days=-date_120)
formatted_today_120 = today.strftime("%Y-%m-%d")
today = now_time + datetime.timedelta(days=-date_180)
formatted_today_180 = today.strftime("%Y-%m-%d")
print(formatted_today_90, formatted_today_120, formatted_today_180)
# 获取数据
data_details_90 = data_details.copy()
data_details_90['条件'] = (data_details_90['renew_date'] == formatted_today_90) & (data_details_90[
'group_grade'] != "普通客户（VIP）") # & (data_details_90['saas_edition_fmt'] != '基础版') & (data_details_90['saas_edition_fmt'] != '入门版')
data_details_90 = data_details_90.loc[data_details_90["条件"]]
data_details_120 = data_details.copy()
data_details_120['条件'] = (data_details_120['renew_date'] == formatted_today_120) & (
(data_details_120['saas_edition_fmt'] == '基础版') | (
data_details_120['saas_edition_fmt'] == '入门版'))
data_details_120 = data_details_120.loc[data_details_120["条件"]]
data_details_180 = data_details.copy()
data_details_180['条件'] = (data_details_180[
'renew_date'] == formatted_today_180) # & (data_details_180[
# 'saas_edition_fmt'] != '基础版') & (data_details_180['saas_edition_fmt'] != '入门版')
data_details_180 = data_details_180.loc[data_details_180["条件"]]
data_details_90["跟进阶段"] = "续约后90天回访"
data_details_90["主要目的"] = "关怀使用情况，促进更多功能使用，提升系统使用深度。"
data_details_120["跟进阶段"] = "续约后120天回访"
data_details_120["主要目的"] = "暂无"
data_details_180["跟进阶段"] = "续约后180天回访"
data_details_180["主要目的"] = "关怀使用情况，促进增购商机转化，识别潜在风险，及时提报。"
# 合并三个DataFrame
data_result = pd.concat([data_details_90, data_details_180],
ignore_index=True) # 去除续约120天回访 data_details_120
print(len(data_result))
data_result = data_result.astype(str)
data_NGV = data_result.copy()
for index_num, row in data_NGV.iterrows(): # 对过滤后的每一条进行派发
try:
# print(row["org_code"]) # 数据验证
# print(row["service_impl_principal"])
# print(row["area_manager"])
# print(row["technician"])
print("销售负责人是：", row["salesmen"])
payload_dict = {}
saas_use_year = re.findall(r'第([0-9]+)年', row["saas_use_year"])[0]
NGV_roles = {
'relationship_manager': row['service_impl_principal'], # 运营负责人
# 'relationship_manager': "张阳", # 运营负责人
'area_manager': row['area_manager'], # 区域经理
'technician': row['technician'], # 技术专家
'salesmen': row['salesmen'], # 销售负责人
}
for role, name in NGV_roles.items():
for row_item in self.staff_id_list:
staff_id = self.get_staff_id(row_item, name)
if staff_id:
NGV_roles[role] = staff_id
break # 找到后退出循环
else:
NGV_roles[role] = None # 如果没有找到对应的员工ID
# 回访人员： 需确认 四年以下 technician
if int(saas_use_year) < 4:
relationship_manager, area_manager, technician, salesmen = [NGV_roles[role] for role in
['relationship_manager',
'area_manager',
'technician', 'salesmen']]
# 如果未找到运营负责人，则根据省市区派发给日常回访客服
if not relationship_manager:
relationship_manager = self.assign_customer_service(
row['province_name'], row['city_name'], row['area_name'], self.index
)[0]
if not technician:
technician = self.assign_customer_service(
row['province_name'], row['city_name'], row['area_name'], self.index
)[2]
if row["group_grade"] == "普通客户（VIP）" or row["group_grade"] == "重要客户（SVIP）":
payload_dict.update({
"_widget_1734590278288": {"value": relationship_manager}, # 跟进人是运营负责人
})
else:
payload_dict.update({
"_widget_1734590278288": {"value": technician}, # 跟进人是技术专家
})
else:
salesmen = [NGV_roles[role] for role in ['salesmen']][0]
# print(salesmen)
# salesmen = [NGV_roles[role] for role in
# ['salesmen']]
# 直接根据省市区派发给日常回访客服
relationship_manager, customer_service, technician, area_manager = self.assign_customer_service(
row['province_name'], row['city_name'], row['area_name'], self.index
)
if row["group_grade"] == "普通客户（VIP）" or row["group_grade"] == "重要客户（SVIP）":
payload_dict.update({
"_widget_1734590278288": {"value": customer_service} # 跟进人是日常回访客服
})
else:
payload_dict.update({
"_widget_1734590278288": {"value": technician} # 跟进人是技术专家
})
payload_dict.update({
# "_widget_1734590278288": {"value": relationship_manager}, # 跟进人是运营负责人
"_widget_1734590278289": {"value": relationship_manager}, # 运营负责人
"_widget_1734590278290": {"value": area_manager}, # 区域经理
"_widget_1734590278291": {"value": technician}, # 技术专家
"_widget_1735290738545": {"value": salesmen} # 销售负责人
})
if payload_dict.get("_widget_1734590278288") == "02414917880947": # 如果跟进人是殷浩
payload_dict.update({
"_widget_1734590278288": {"value": "051612246035720178"}, # 跟进人是赵柄诚
})
# 输出结果
print("SaaS开户回访人员：", relationship_manager or "未分配")
print("SaaS技术专家：", technician or "未分配")
print("SaaS区域经理：", area_manager or "未分配")
# 判断权限唯一值
# pattern = r'([\u4e00-\u9fa5]+)\（'
# match = re.search(pattern, row['max_group_grade'])
# group_grade = match.group(1)
group_grade = re.sub(r'（[^）]*）', '', row['max_group_grade'])
if not row['saas_customer_type'] or row['saas_customer_type'] == 'NA' or row[
'saas_customer_type'] == 'None':
row['saas_customer_type'] = "F"
NGV_store_level_key = group_grade + row['max_saas_edition'] + row['max_saas_customer_type']
print("权限唯一值：", NGV_store_level_key)
Billing = None
for item in self.permissions_table:
if NGV_store_level_key == item.get("_widget_1734056507963"): # 合并（等级-类型-分层）
print("该门店开单的权限是：", item.get("_widget_1734055617039"))
Billing = item.get("_widget_1734055617039") # 开单
Service_Alerts = item.get("_widget_1734055617040") # 服务提醒
membership = item.get("_widget_1734055617041") # 会员卡
SMS = item.get("_widget_1734055617042") # 短信
Public_domain_applets = item.get("_widget_1734055617043") # 公域小程序
Private_domain_applets = item.get("_widget_1734055617044") # 私域小程序
Test_sheet = item.get("_widget_1734055617045") # 检测单
AI_poster = item.get("_widget_1734055617046") # AI海报
Business_wallets = item.get("_widget_1734055617047") # 企业钱包
Precision_marketing = item.get("_widget_1734055617049") # 精准营销
Paid_memberships = item.get("_widget_1734055617051") # 付费会员
business_WeCom = item.get("_widget_1734055617052") # 企业微信
Insurance_policy_identification = item.get("_widget_1734055617053") # 保险单识别
Insurance_bots = item.get("_widget_1734055617054") # 保险机器人
Camera_pick_up = item.get("_widget_1734055617055") # 摄像头接车
Camera_billing = item.get("_widget_1734055617056") # 摄像头开单
Transparent_workshop = item.get("_widget_1734055617057") # 透明车间
Cross_industry_cooperation = item.get("_widget_1734055617058") # 异业合作
BI_Insights = item.get("_widget_1734055617059") # BI洞察
payload_dict.update(
{
"_widget_1734073342350": {"value": Billing},
"_widget_1735004315757": {"value": Service_Alerts},
"_widget_1735004315756": {"value": membership},
"_widget_1735004315755": {"value": SMS},
"_widget_1735004315754": {"value": Public_domain_applets},
"_widget_1735004315753": {"value": Private_domain_applets},
"_widget_1735004315752": {"value": Test_sheet},
"_widget_1735004315751": {"value": AI_poster},
"_widget_1735004315750": {"value": Business_wallets},
"_widget_1735004315749": {"value": Precision_marketing},
"_widget_1735004315748": {"value": Paid_memberships},
"_widget_1735004315747": {"value": business_WeCom},
"_widget_1735004315746": {"value": Insurance_policy_identification},
"_widget_1735004315745": {"value": Insurance_bots},
"_widget_1735004315744": {"value": Camera_pick_up},
"_widget_1735004315743": {"value": Camera_billing},
"_widget_1735004315742": {"value": Transparent_workshop},
"_widget_1735004315741": {"value": Cross_industry_cooperation},
"_widget_1734073342352": {"value": BI_Insights},
}
)
feature_dict = {
"开单": "_widget_1734073342350",
"服务提醒": "_widget_1735004315757",
"会员卡": "_widget_1735004315756",
"短信": "_widget_1735004315755",
"公域小程序": "_widget_1735004315754",
"私域小程序": "_widget_1735004315753",
"检测单": "_widget_1735004315752",
"AI海报": "_widget_1735004315751",
"企业钱包": "_widget_1735004315750",
"精准营销": "_widget_1735004315749",
"付费会员": "_widget_1735004315748",
"企业微信": "_widget_1735004315747",
"保险单识别": "_widget_1735004315746",
"保险机器人": "_widget_1735004315745",
"摄像头接车": "_widget_1735004315744",
"摄像头开单": "_widget_1735004315743",
"透明车间": "_widget_1735004315742",
"异业合作": "_widget_1735004315741",
"BI洞察": "_widget_1734073342352",
}
# _widget_1735527329557 下次是否推荐
for new_item in self.get_feature_usage:
for feature_module, feature_value in feature_dict.items(): # 模块
if new_item.get("_widget_1735268263079") == feature_module and new_item.get(
"_widget_1735527329557") == "否" and new_item.get(
"_widget_1735280720550") == \
row["id_own_org"]: # 下次是否推荐 功能使用情况表
print(f"{feature_value}进行了更改")
payload_dict.update({f"{feature_value}": {"value": "×"}})
if new_item.get("_widget_1735268263079") == feature_module and new_item.get(
"_widget_1736414617462") == "否" and new_item.get(
"_widget_1735280720550") == \
row["id_own_org"]: # 下次是否跟进
print(f"{feature_value}进行了更改")
payload_dict.update({f"{feature_value}": {"value": "×"}})
fields_to_check = {
"_widget_1735004315763": Billing, # 开单
"_widget_1735106258016": Service_Alerts, # 服务提醒
"_widget_1735106258036": membership, # 会员卡
"_widget_1735106258086": SMS, # 短信
"_widget_1735106258112": Public_domain_applets, # 公域小程序
"_widget_1735106258141": Private_domain_applets, # 私域小程序
"_widget_1735107354648": Test_sheet, # 检测单
"_widget_1735107354725": AI_poster, # AI海报
"_widget_1735107354811": Business_wallets, # 企业钱包
"_widget_1735107354906": Precision_marketing, # 精准营销
"_widget_1735107354980": Paid_memberships, # 付费会员
"_widget_1735107355093": business_WeCom, # 企业微信
"_widget_1735107355143": Insurance_policy_identification, # 保险单识别
"_widget_1735107355235": Insurance_bots, # 保险机器人
"_widget_1735107355333": Camera_pick_up, # 摄像头接车
"_widget_1735107355392": Camera_billing, # 摄像头开单
"_widget_1735107355502": Transparent_workshop, # 透明车间
"_widget_1735107355618": Cross_industry_cooperation, # 异业合作
"_widget_1735107355740": BI_Insights # BI洞察
}
# 遍历每个字段，检查其值并更新payload_dict
for widget_id, field_name in fields_to_check.items():
if field_name == "√":
payload_dict.update({widget_id: {"value": "是"}})
break
is_continue = False
# 如果门店倒闭则不派发
for store in self.NGV_data_list:
if row["id_own_org"] == store.get("_widget_1734062123069") and store.get(
"_widget_1752027386523") == "门店倒闭":
is_continue = True
print(f"门店已关闭，不派发")
break
if is_continue:
continue
if not Billing:
print(f"权限表请求失败或者权限表无对应关系,权限唯一值是：{NGV_store_level_key}")
if row["active_status_fmt"] == "活跃": # 开单 是否使用
payload_dict.update({"_widget_1735004315765": {"value": "是"}})
else:
payload_dict.update({"_widget_1735004315765": {"value": "否"}})
try:
if row["saas_edition_fmt"] not in ["基础版", "入门版"]: # 会员卡 是否拥有
payload_dict.update({"_widget_1735106258036": {"value": "是"}})
else:
payload_dict.update({"_widget_1735106258036": {"value": "否"}})
except Exception as e:
print(f"会员卡识别：Error finding customer service: {e}")
try:
if row["card_bill_day_count_last_30_day"] != "0": # 会员卡 是否使用
payload_dict.update({"_widget_1735106258038": {"value": "是"}})
else:
payload_dict.update({"_widget_1735106258038": {"value": "否"}})
except Exception as e:
print(f"会员卡识别：Error finding customer service: {e}")
# print(self.service_remind.get("_widget_1735112637045"))
payload_dict["_widget_1735106258018"] = {"value": "否"}
for item in self.service_remind:
if row["id_own_group"] == item.get("_widget_1735112637043"):
if int(item.get("_widget_1735112637045")) < 180 and int(
item.get("_widget_1735112637046")) == 1: # 服务提醒 是否使用
payload_dict.update({"_widget_1735106258018": {"value": "是"}})
break
elif int(item.get("_widget_1735112637048")) > 0:
payload_dict.update({"_widget_1735106258018": {"value": "是"}})
break
keys_to_check = [
"_widget_1735113110155"
] # 智能检测 是否使用
# 初始化默认值为"否"
payload_dict["_widget_1735107354650"] = {"value": "否"}
# 检查每个键，如果有一个大于0，则更新为"是"并停止检查
for key in keys_to_check:
for item in self.Smart_detection:
if row["id_own_org"] == item.get("_widget_1735113110147"):
if int(item.get(key, 0)) > 0: # 使用get方法并提供默认值0防止键不存在的情况
payload_dict["_widget_1735107354650"]["value"] = "是"
break
# 近30天业务单量=0 则其它所有模块均不推荐
try:
for feature_module, feature_value in feature_dict.items(): # 模块
if row["bill_count_last_30_day"] == '0' and payload_dict[feature_value]["value"] == '△':
payload_dict.update({f"{feature_value}": {"value": "×"}})
except Exception as e:
print(f"不开单识别：Error finding customer service: {e}")
# 保单识别：从系统中抽取目标门店，针对门店抽取修改是否推荐
try:
if row["org_code"] in self.widget_list:
payload_dict.update({'_widget_1735004315746': {"value": "△"}})
except Exception as e:
print(f"保单识别：Error finding customer service: {e}")
# 私域小程序：根据是否开通微信小程序判断是否使用，旗舰版及以上算拥有
try:
for item in self.private_domain:
if row["id_own_group"] == item.get("_widget_1742795002375"): # 公司id
if int(item.get("_widget_1742795002379")) > 0: # 上架商品数
payload_dict.update({"_widget_1735106258143": {"value": "是"}}) # DX:是否拥有
break
else:
payload_dict.update({"_widget_1735106258143": {"value": "否"}}) # DX:是否拥有
break
except Exception as e:
print(f"私域小程序：Error finding customer service: {e}")
try:
high_version = ['皇冠版', '至尊版', '尊享版', '旗舰版']
if row["saas_edition_fmt"] in high_version:
payload_dict.update({'_widget_1735106258141': {"value": "是"}}) # SYXCX:是否拥有
else:
payload_dict.update({'_widget_1735106258141': {"value": "否"}}) # SYXCX:是否拥有
except Exception as e:
print(f"私域小程序：Error finding customer service: {e}")
# 公域小程序：根据是否开通微信小程序判断是否使用，旗舰版及以上算拥有
try:
for item in self.public_domain:
if row["id_own_org"] == item.get("_widget_1742784257506"): # 门店id
if int(item.get("_widget_1742784257509")) == 1: # 发布商品数量
payload_dict.update({"_widget_1735106258114": {"value": "是"}}) # GYXCX:是否使用
break
else:
payload_dict.update({"_widget_1735106258114": {"value": "否"}}) # GYXCX:是否使用
break
except Exception as e:
print(f"公域小程序：Error finding customer service: {e}")
try:
if row["id_own_org"] in self.public_domain_list:
payload_dict.update({'_widget_1735106258112': {"value": "是"}}) # GYXCX:是否拥有
else:
payload_dict.update({'_widget_1735106258112': {"value": "否"}}) # GYXCX:是否拥有
except Exception as e:
print(f"公域小程序：Error finding customer service: {e}")
# 异业合作：根据是否存在判断是否拥有，过滤条件 商品名称包含异业两个字
try:
if row["id_own_org"] in self.different_industries_list:
payload_dict.update({'_widget_1735107355618': {"value": "是"}}) # YYHZ:是否拥有
else:
payload_dict.update({'_widget_1735107355618': {"value": "否"}}) # YYHZ:是否拥有
except Exception as e:
print(f"异业合作：Error finding customer service: {e}")
# 短信：根据是否启动短信功能判断是否拥有,根据
try:
for item in self.groupnotification:
if row["id_own_group"] == item.get("_widget_1743065201885"): # 公司id
if int(item.get("_widget_1743065201886")) == 1: # 是否启动短信功能
payload_dict.update({"_widget_1735106258086": {"value": "是"}}) # DX:是否拥有
break
else:
payload_dict.update({"_widget_1735106258086": {"value": "否"}}) # DX:是否拥有
break
except Exception as e:
print(f"短信：Error finding customer service: {e}")
try:
for item in self.groupnotification:
if row["id_own_group"] == item.get("_widget_1743065201885"): # 公司id
if int(item.get("_widget_1743065201889")) > 0: # 累计发送成功总人数
payload_dict.update({"_widget_1735106258088": {"value": "是"}}) # DX:是否使用
break
else:
payload_dict.update({"_widget_1735106258088": {"value": "否"}}) # DX:是否使用
break
except Exception as e:
print(f"短信：Error finding customer service: {e}")
NGV_data_id = None
# 获取关联数据
for NGV_Data in self.NGV_data_list:
# NGV_Data = NGV_Data.get("data")
if row["org_code"] == NGV_Data.get("_widget_1734062123071"): # 门店编码
NGV_data_id = NGV_Data.get("_id")
print(NGV_data_id)
try:
png_url = NGV_Data.get('_widget_1742890765211', {})[0].get('url', "")
except:
png_url = ""
print(png_url)
if not NGV_data_id:
print("未找到数据ID")
distribution_date = datetime.datetime.now(datetime.timezone.utc)
distribution_date = distribution_date.strftime('%Y-%m-%dT%H:%M:%S.%f')[:-3] + 'Z'
upload_key = None
UUid = time.strftime("%Y%m%d%H%M%S", time.localtime())
if png_url:
save_dir = "sampleCloud" # 设置输出目录
# 创建输出目录（如果不存在）
import os
os.makedirs(save_dir, exist_ok=True)
save_path = fr'{save_dir}\png\{time.strftime("%Y%m%d%H%M%S", time.localtime())}.png'
RenewServicesRevisit.download_url_content(png_url, save_path)
up_data = api_instance.get_upload_token(
{"api_key": "675b900991ad2491c69389ca", "entry_id": "675b9c63925cd404038a6b86",
"transaction_id": UUid})
upload_url = up_data.get("upload_url")
upload_token = up_data.get("upload_token")
upload_result = api_instance.upload_file(
{"upload_url": upload_url, "upload_token": upload_token, "file_path": save_path})
upload_key = upload_result.get("key")
payload_dict.update({
"_widget_1734590278279": {"value": row["group_name"]}, # 公司名称
"_widget_1735112931760": {"value": row["id_own_group"]}, # 公司id
"_widget_1735112931761": {"value": row["id_own_org"]}, # 门店id
"_widget_1734590278281": {"value": row['org_name']}, # 门店名称
"_widget_1734590278292": {"value": row["跟进阶段"]}, # 跟进阶段
"_widget_1734321349021": {"value": NGV_data_id}, # 关data_get联数据
"_widget_1742548684369": {"value": row['主要目的']}, # 主要目的
"_widget_1734590278266": {"value": row['region_name']}, # 大区
"_widget_1734590278285": {"value": row['branch_name']}, # 小区
"_widget_1734590278284": {"value": row['province_name']}, # 省
"_widget_1734590278283": {"value": row['city_name']}, # 市
"_widget_1734590278282": {"value": row['area_name']}, # 区
"_widget_1734590278278": {"value": row['saas_customer_type']}, # 门店分层
"_widget_1734590278277": {"value": row['group_grade']}, # 公司等级
"_widget_1734590278276": {"value": row['limit_user_type']}, # 限制账户类型
"_widget_1734590278275": {"value": row['active_user_type']}, # 有效账户类型
"_widget_1734590278274": {"value": row['saas_version']}, # ERP操作模式
"_widget_1734590278273": {"value": row['saas_use_year']}, # 使用时长
"_widget_1734590278272": {"value": row['org_stage']}, # 门店阶段
"_widget_1734590278271": {"value": row['manage_model']}, # 经营模式
"_widget_1734590278267": {"value": row['contacts']}, # 联系人
"_widget_1734590278287": {"value": row['contact_mobile']}, # 联系手机号
"_widget_1734590278286": {"value": row['saas_edition_fmt']}, # SaaS版本
"_widget_1734590278280": {"value": row['org_code']}, # 门店编码
# "_widget_1735287791875": {"value": row['salesmen']}, # 销售负责人
"_widget_1735096489244": {"value": distribution_date}, # 派发时间
"_widget_1742895342914": {"value": row['business_scope_fmt']}, # 经营范围
"_widget_1742895342915": {"value": row['station_number']}, # 工位数
"_widget_1742895342916": {"value": [upload_key]} # 门头照片
})
routine_follow_up_payload = {
"api_key": "675b900991ad2491c69389ca",
"entry_id": "675b9c63925cd404038a6b86",
"is_start_workflow": "true",
"data": payload_dict,
"transaction_id": UUid
}
print(routine_follow_up_payload)
res = api_instance.data_batch_create(routine_follow_up_payload)
logger.info(f"创建结果：{res}")
time.sleep(1)
# print(res)
except:
pass
common_module.send_task_status(task_start_time, "续约客户回访")
if __name__ == '__main__':
start = RenewServicesRevisit()
start.main()
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back_ground_module/update_BI_CRM_info.py
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import pandas as pd
import mysql.connector
from mysql.connector import Error
from api import API
import ast
from datetime import datetime, timedelta
from dateutil.parser import parse
from back_ground_module import CommonModule
import numpy as np
from config import Config
common_module = CommonModule()
class CRMDataProcessor:
"""泰国CRM数据迁移到BI"""
def __init__(self):
"""
初始化CRM数据处理类
"""
api_key = Config.OVERSEAS_PROJECT_CRM_APP_ID
entry_id = Config.OVERSEAS_PROJECT_FOLLOW_UP_PLAN_ENTRY_ID
self.api_key = api_key
self.entry_id = entry_id
self.db_config = Config.HS_DB_Config
self.api_instance = API()
self.connection = None
self.cursor = None
# 字段映射字典
self.id_to_name_mapping = {
'_widget_0201002000001': '客户编码',
'_widget_0201002000002': '门店名称',
'_widget_1630862543434': '客户级别',
'_widget_1630862543415': 'BD状态',
'_widget_1631071964761': '客户来源',
'_widget_0201002000005': '所属公海',
'_widget_1663742427957': '客户查重',
'_widget_1747123933309': '客户BD日期',
'_widget_1747661411161': 'Test开始日期',
'_widget_1747661411178': 'Test天数',
'_widget_1747664949166': 'Test账号状态',
'_widget_1747123933310': '客户签约日期',
'_widget_1747123933311': '客户付款日期',
'_widget_0201002000003': 'BD负责人',
'_widget_0201002000006': '销售归属部门',
'_widget_0201002000004': 'BD协作人',
'_widget_1747133970117': 'BD阻塞原因',
'_widget_1747669642443': 'BD阻塞原因分类',
'_widget_1747133970121': 'BD阻塞原因详细描述',
'_widget_1746675108119': '原系统名称',
'_widget_1746675108151': '门店设备',
'_widget_1630862543637': '门店类型',
'_widget_1746675108121': '门店业务',
'_widget_1746675108115': '工位数',
'_widget_1747321321284': '员工数',
'_widget_1746675108123': '系统操作人员',
'_widget_1747123507416': '开户门店ID',
'_widget_1737092013289': '公司名称',
'_widget_1737092013291': '主店简称',
'_widget_1737092013292': '营业执照号',
'_widget_1737092013293': '营业执照名称',
'_widget_1737097231480': '府',
'_widget_1737097231482': '县',
'_widget_1737092013299': '地址_省市区',
'_widget_1737097782393': '详情地址',
'_widget_1737092013314': '营业开始时间',
'_widget_1737092013313': '营业结束时间',
'_widget_1737092013312': '经度',
'_widget_1737092013311': '纬度',
'_widget_1737092013310': '负责人名字',
'_widget_1737092013308': '负责人手机号',
'_widget_1737092013309': '服务接待固话',
'_widget_1737092013315': '服务接待名称',
'_widget_1737092013316': '服务接待手机号',
'_widget_1737092013320': '账号数上限',
'_widget_1737092013318': '税号',
'_widget_1737092013317': '分支编号',
'_widget_1737092013319': '嘉实多内部门店编码',
'_widget_1737092013339': '运营顾问_上线负责人',
'_widget_1747123933312': '客户上线日期',
'_widget_1740460160201': '上线阶段',
'_widget_1747133970122': '上线失败原因',
'_widget_1631071964934': '上线失败原因描述',
'_widget_1749108058561': '门店系统使用情况说明',
'_widget_1737092013340': '运营专家',
'_widget_1737092013341': '区域经理',
'_widget_1663742427909': '客户查重_客户表内该客户数量',
'_widget_0201002000007': '领取时间',
'_widget_0201002000009': '客户退回原因',
'_widget_0201002000008': '最后跟进时间',
'plan_recycle_time': "预计回收时间",
'_widget_1709110880998': '结算期限',
'_widget_1709110881001': '信用额度_元',
'_widget_1709110881002': '发票抬头',
'_widget_1709110881003': '发票税号',
'_widget_1709110881004': '税种',
'_widget_1709110881007': '增值税税率_',
'_widget_1709110881008': '开户电话',
'_widget_1709110881009': '开户银行',
'_widget_1709110881016': '银行账户',
"_widget_1749204198412": "原系统情况描述",
"_widget_1749632087678": "付款金额_泰铢",
'creator': '提交人',
'createTime': '提交时间',
'updateTime': '更新时间'
}
# 需要处理的列
self.list_columns_to_process = [
'_widget_1746675108123',
'_widget_1746675108121',
'_widget_1746675108151'
]
self.columns_to_process = [
'_widget_0201002000005',
'_widget_0201002000003',
'_widget_0201002000006',
'_widget_0201002000004',
'_widget_1737092013339',
'_widget_1737092013340',
'_widget_1737092013341'
]
self.columns_to_drop = [
'_widget_1737097782383',
'_widget_1737092013321',
'_widget_1737092013300',
'_widget_1737092013301',
'_widget_1737092013302'
]
self.datetime_columns = [
'_widget_1747123933309', # 客户BD日期
'_widget_1747123933310', # 客户签约日期
'_widget_1747123933311', # 客户付款日期
'_widget_0201002000007', # 领取时间
'_widget_0201002000008' # 最后跟进时间
]
def connect_db(self):
"""连接数据库"""
try:
self.connection = mysql.connector.connect(
host=self.db_config['host'],
user=self.db_config['user'],
password=self.db_config['password'],
database=self.db_config['database']
)
self.cursor = self.connection.cursor()
print(f"成功连接数据库 {self.db_config['database']}")
except Error as e:
print(f"连接数据库时发生错误: {e}")
raise
def close_db(self):
"""关闭数据库连接"""
if self.connection and self.connection.is_connected():
if self.cursor:
self.cursor.close()
self.connection.close()
print("数据库连接已关闭")
def fetch_crm_data(self):
"""从API获取CRM数据"""
payload = {"api_key": self.api_key, "entry_id": self.entry_id}
CRM_data_list = self.api_instance.entry_data_list(payload).get("data")
CRM_data = pd.DataFrame(CRM_data_list)
print("成功从API获取CRM数据")
CRM_data.to_csv("CRM.csv")
return CRM_data
def process_data(self, df):
"""处理CRM数据"""
# 去掉前六列和后两列
df = df.iloc[:, 6:-2]
# del df["creator"]
# del df["createTime"]
# del df["updateTime"]
# del df["updater"]
# del df["deleter"]
# del df["deleteTime"]
# 生成URL
base_url = f"https://www.jiandaoyun.com/dashboard/app/{self.api_key}/form/{self.entry_id}/data/"
df['url'] = base_url + df['_id'].astype(str) + "/qr_link"
del df['_id']
# 处理列表格式列
for col in self.list_columns_to_process:
if col in df.columns:
df[col] = df[col].apply(self._join_list_items)
# 处理字典格式列
for col in self.columns_to_process:
if col in df.columns:
if col == '_widget_0201002000004':
df[col] = df[col].apply(self._extract_names_from_list)
else:
df[col] = df[col].apply(self._extract_name_from_dict)
# 删除不需要的列
for col in self.columns_to_drop:
if col in df.columns:
df.drop(columns=[col], inplace=True)
# 处理时间列
for col in self.datetime_columns:
if col in df.columns:
df[col] = df[col].apply(self._add_8_hours)
# 重命名列
df.rename(columns=self.id_to_name_mapping, inplace=True)
# 只保留映射后的列和URL字段
mapped_columns = list(self.id_to_name_mapping.values()) + ['url']
df = df[[col for col in mapped_columns if col in df.columns]]
#df.replace([np.nan, None, r'^\s*$'], "", regex=True, inplace=True)
# 修改替换空值的实现方式
df = df.fillna("") # 先替换NaN和None
df = df.replace(r'^\s*$', "", regex=True) # 再替换空字符串
print("数据处理完成")
df.to_csv('DF.csv', index=False)
return df
def _join_list_items(self, cell_value):
"""将列表中的内容用逗号分隔"""
if pd.api.types.is_list_like(cell_value):
return ', '.join(map(str, cell_value))
if pd.isna(cell_value) or cell_value == '':
return ""
try:
cell_list = ast.literal_eval(cell_value)
return ', '.join(cell_list)
except (ValueError, SyntaxError):
return str(cell_value)
def _extract_name_from_dict(self, cell_value):
"""提取字典中的'name'值"""
if pd.isna(cell_value):
return ""
if isinstance(cell_value, str):
try:
cell_dict = ast.literal_eval(cell_value)
except (ValueError, SyntaxError):
return str(cell_value)
else:
cell_dict = cell_value
return cell_dict.get('name', '')
def _extract_names_from_list(self, cell_value):
"""提取列表中所有字典的'name'值"""
if isinstance(cell_value, (pd.Series, np.ndarray)):
return cell_value.apply(self._extract_names_from_list)
if pd.isna(cell_value).any() if hasattr(cell_value, '__iter__') else pd.isna(cell_value):
return ""
try:
cell_list = ast.literal_eval(cell_value) if isinstance(cell_value, str) else cell_value
names = [item.get('name', '') for item in cell_list if isinstance(item, dict)]
return ', '.join(names)
except (ValueError, SyntaxError, TypeError):
return str(cell_value)
def _add_8_hours(self, dt_str):
"""为时间添加8小时"""
if pd.isna(dt_str) or dt_str == '':
return None
try:
dt = parse(dt_str)
dt += timedelta(hours=8)
return dt.strftime('%Y-%m-%dT%H:%M:%S.000Z')
except Exception as e:
print(f"Error processing datetime {dt_str}: {e}")
return dt_str
def clear_table(self, table_name):
"""清空数据库表"""
try:
self.connect_db()
self.cursor.execute(f"TRUNCATE TABLE {table_name}")
self.connection.commit()
print(f"成功清空表 {table_name} 中的所有数据")
except Error as e:
print(f"清空表时发生错误: {e}")
if self.connection and self.connection.is_connected():
self.connection.rollback()
raise
finally:
self.close_db()
def import_data(self, df, table_name):
try:
self.connect_db()
# 处理空值 - 将NaN/NaT/空字符串统一转为None
df = df.map(lambda x: None if pd.isna(x) or str(x).strip() == '' else x)
# # 确保所有空值（包括NaN、None、空字符串）转为None
df = df.replace([np.nan, None, r'^\s*$'], None, regex=True)
# 检查表结构是否匹配
self.cursor.execute(f"DESCRIBE {table_name}")
table_columns = [col[0] for col in self.cursor.fetchall()]
# 只保留表中存在的列
df = df[[col for col in df.columns if col in table_columns]]
# 生成插入语句
columns = ', '.join(df.columns)
placeholders = ', '.join(['%s'] * len(df.columns))
insert_query = f"INSERT INTO {table_name} ({columns}) VALUES ({placeholders})"
# 批量插入数据
records = [tuple(row) for row in df.values]
self.cursor.executemany(insert_query, records)
self.connection.commit()
print(f"成功导入 {self.cursor.rowcount} 条记录到 {table_name} 表")
except Error as e:
print(f"导入数据时发生错误: {e}")
if self.connection and self.connection.is_connected():
self.connection.rollback()
raise
finally:
self.close_db()
# # 批量插入数据
# records = [tuple(None if pd.isna(x) else x for x in row) for row in df.values]
# self.cursor.executemany(insert_query, records)
# self.connection.commit()
# print(f"成功导入 {self.cursor.rowcount} 条记录到 {table_name} 表")
# except Error as e:
# print(f"导入数据时发生错误: {e}")
# raise
# finally:
# self.close_db()
def main(self):
"""运行完整的数据处理流程"""
table_name = "jiandaoyun_crm_customer_profile"
task_start_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
try:
# 获取数据
raw_data = self.fetch_crm_data()
# 处理数据
processed_data = self.process_data(raw_data)
# 清空表
self.clear_table(table_name)
# 导入数据
self.import_data(processed_data, table_name)
print("数据处理流程完成")
except Exception as e:
print(f"数据处理流程出错: {e}")
raise
common_module.send_task_status(task_start_time, "简道云海外项目CRM客户档案迁移BI")
# 使用示例
if __name__ == "__main__":
# 配置信息
# 创建处理器实例并运行流程
processor = CRMDataProcessor()
processor.main()
back_ground_module/update_ID_form.py
+113
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import requests
import json
import pandas as pd
from api import API
from config import Config
from log_config import configure_task_logger, configure_error_task_logger
from back_ground_module import CommonModule
from datetime import datetime
# 初始化API实例
api_instance = API()
# 获取已经配置好的常规日志记录器
logger = configure_task_logger()
# 获取已经配置好的错误任务日志记录器
error_task_logger = configure_error_task_logger()
common_module = CommonModule()
class update_ID_form:
"""更新简道云员工ID表"""
def __init__(self):
self.headers = {
'Authorization': Config.JIANDAOYUN_API_TOKEN, # 曹伟应用api测试 app_key
'Content-Type': 'application/json'
}
self.url = "https://api.jiandaoyun.com/api/v5/corp/department/user/list"
self.payload1 = {
"api_key": "6694d3c4fcb69ca9a111a6c4",
"entry_id": "6769204a1902c9341340a1bc",
}
self.delete_payload = {
"api_key": "6694d3c4fcb69ca9a111a6c4",
"entry_id": "6769204a1902c9341340a1bc",
}
self.update_payload = {
"api_key": "6694d3c4fcb69ca9a111a6c4",
"entry_id": "6769204a1902c9341340a1bc",
}
def get_department_members(self):
"""获取部门成员及ID表"""
try:
payload = json.dumps({
"dept_no": 1,
"has_child": True
})
response = requests.request("POST", self.url, headers=self.headers, data=payload)
search_department_member = response.json()
departments_members = search_department_member.get('users')
df1 = pd.DataFrame(departments_members)
logger.info("部门成员及ID表已成功获取")
return df1
except Exception as e:
error_task_logger.error(f"获取部门成员及ID表失败：{e}")
return None
def get_existing_id_form(self):
"""读取现有的ID表"""
try:
now_ID_form = api_instance.entry_data_list(self.payload1).get('data')
df = pd.DataFrame(now_ID_form)
logger.info("现有的ID表已成功读取")
return df
except Exception as e:
error_task_logger.error(f"读取现有的ID表失败：{e}")
return None
def delete_existing_data(self, df):
"""批量删除现有数据"""
try:
all_data = []
for index, i in df.iterrows():
all_data.append(i["_id"])
self.delete_payload["data_ids"] = all_data
api_instance.entry_data_batch_delete(self.delete_payload)
logger.info("现有数据已成功删除")
except Exception as e:
error_task_logger.error(f"批量删除现有数据失败：{e}")
def update_data(self, df1):
"""批量写入新数据"""
try:
all_data1 = []
for index, i in df1.iterrows():
all_data1.append({
"_widget_1734942794144": {"value": i["name"]},
"_widget_1734942794145": {"value": i["username"]},
})
self.update_payload["data_list"] = all_data1
api_instance.entry_data_batch_create(self.update_payload)
logger.info("新数据已成功写入")
except Exception as e:
error_task_logger.error(f"批量写入新数据失败：{e}")
def main(self):
"""主函数"""
task_start_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
logger.info("每日任务开始执行")
df1 = self.get_department_members()
if df1 is not None:
df = self.get_existing_id_form()
if df is not None:
self.delete_existing_data(df)
self.update_data(df1)
logger.info("每日任务执行完成")
common_module.send_task_status(task_start_time, "简道云员工ID表更新")
if __name__ == '__main__':
daily_task = update_ID_form()
daily_task.main()
back_ground_module/update_NGV_data.py
+228
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# -*- coding: utf-8 -*-
import pandas as pd
import datetime
from config import Config
from api import API
from back_ground_module import CommonModule
start_time = datetime.datetime.now()
api_instance = API()
common_module = CommonModule()
class UpdateNGVData:
"""NGV数据每日新增"""
def __init__(self):
self.staff_id_list = None
self.field_mapping = {}
self.fields()
def load_all_data(self):
# 获取简道云员工id
payload = {"api_key": "6694d3c4fcb69ca9a111a6c4",
"entry_id": "6769204a1902c9341340a1bc",
}
staff_id = api_instance.entry_data_list(payload)
self.staff_id_list = staff_id.get("data") # api请求格式，将数据封装在data字典里
@staticmethod
def get_staff_id(row_item, name):
"""辅助函数，用于获取员工ID"""
if str(row_item["_widget_1734942794144"]) == str(name): # 检查姓名是否匹配
return row_item["_widget_1734942794145"] # 返回员工ID
return None
def main(self):
self.load_all_data()
task_start_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
data_NGV_j = common_module.get_ngv_details(days_back=1)
data_NGV_j1 = common_module.get_ngv_details(days_back=2)
# 找出在 data_NGV_j 中存在但在 data_NGV_j1 中不存在的 data_id
unique_data_ids = data_NGV_j[~data_NGV_j['org_code'].isin(data_NGV_j1['org_code'])]
# 创建一个新的 DataFrame 保存这些唯一的 data_id 及其对应的数据
new_df = data_NGV_j[data_NGV_j['org_code'].isin(unique_data_ids['org_code'])]
# 对 new_df 进行进一步的过滤，只保留 org_type 为 "一般" 的记录
data_NGV_j = data_NGV_j[data_NGV_j['org_type'] == '一般']
data_NGV_j1 = data_NGV_j1[data_NGV_j1['org_type'] == '一般']
filtered_df = new_df[new_df['org_type'] == '一般']
# 日期字段转换为日期格式
time_columns = ['date_fmt', 'saas_create_time', 'expiry_time', 'install_create_time', "last_end_date",
"renew_date"]
new_filtered_df = filtered_df.copy() # 复制df，以调整时间
for col in time_columns:
# 1. 转换为datetime类型（带错误处理）
# 使用.loc安全赋值
new_filtered_df[col] = pd.to_datetime(filtered_df[col], errors='coerce', utc=False)
# 2. 优化后的时区转换（高效向量化操作）
filtered_df[col + '_date'] = (
new_filtered_df[col]
# 本地化为北京时间（东八区）
.dt.tz_localize('Asia/Shanghai', ambiguous='infer', nonexistent='NaT')
# 转换为UTC时区
.dt.tz_convert('UTC')
# 格式化为ISO8601字符串
.dt.strftime('%Y-%m-%dT%H:%M:%SZ')
)
# 人员字段转换为人员字段
staff_columns = ['area_manager', 'service_impl_principal', "service_salesmen","technician"]
# 将员工列表转为DataFrame
# 三重循环临时方案（确保可写入）
for col in staff_columns:
staff_ids = []
for _, row in filtered_df.iterrows():
matched = False
for staff in self.staff_id_list:
if str(staff['_widget_1734942794144']) == str(row[col]):
staff_ids.append(staff['_widget_1734942794145'])
matched = True
break
if not matched:
staff_ids.append(None)
filtered_df[col + "_staff_id"] = staff_ids
# filtered_df.to_csv(r"D:\Idea Project\SaaS_V1.3\back_ground_module\output\NGV.csv")
# 生成包含所有行转换后的字典列表
# all_data = [self.row_to_dict(row, self.field_mapping) for index, row in data_NGV_j1.iterrows()] # 前两天的全部数据
# all_data = [self.row_to_dict(row, self.field_mapping) for index, row in data_NGV_j.iterrows()] # 前一天的全部数据
all_data = [self.row_to_dict(row, self.field_mapping) for index, row in filtered_df.iterrows()] # 增量数据
#
data = {'api_key': Config.SaaS_Tasks_APP_ID, 'entry_id': Config.NGV_TASKS_ENTRY_ID, "data_list": all_data}
result = api_instance.entry_data_batch_create(data)
# result_str = str(result)
# print(result_str[:500])
# 保存到Excel文件
# output_path = r'D:\Idea Project\F6+宜搭+其它(1)\new\文件输出\ngv明细1.xlsx'
# filtered_df.to_excel(output_path, index=False)
# data_NGV_j1.to_excel( r'D:\Idea Project\F6+宜搭+其它(1)\new\文件输出\ngv明细j1.xlsx', index=False)
# data_NGV_j.to_excel( r'D:\Idea Project\F6+宜搭+其它(1)\new\文件输出\ngv明细j.xlsx', index=False)
# new_df.to_excel(r'D:\Idea Project\F6+宜搭+其它(1)\new\文件输出\ngv明细ndf.xlsx', index=False)
end_time = datetime.datetime.now()
time_diff = end_time - start_time
# 打印天数、秒数和微秒数
print(f"执行时间: {time_diff.days} 天, {time_diff.seconds} 秒, {time_diff.microseconds} 微秒")
common_module.send_task_status(task_start_time, "NGV新增数据")
@staticmethod
def row_to_dict(row, field_mapping):
"""将一行数据转换为指定格式的字典"""
result = {}
for col_name, widget_id in field_mapping.items():
if col_name in row:
value = row[col_name]
clean_value = None if pd.isna(value) else value
result[widget_id] = {"value": clean_value}
return result
def fields(self):
self.field_mapping = dict(date_id='_widget_1734062123065', date_fmt='_widget_1734062123066',
id_own_group='_widget_1734062123067', group_name='_widget_1734062123068',
id_own_org='_widget_1734062123069', org_name='_widget_1734062123070',
org_code='_widget_1734062123071', group_grade='_widget_1734062123072',
org_type='_widget_1734062123073', org_status='_widget_1734062123074',
saas_version='_widget_1734062123075', is_wechat='_widget_1734062123076',
is_mini_app='_widget_1734062123077', is_wx_shop='_widget_1734062123078',
is_camera_service='_widget_1734062123079',
is_maintenance_service='_widget_1734062123080',
saas_create_time='_widget_1734062123081', expiry_time='_widget_1734062123082',
saas_use_days='_widget_1734062123083', saas_use_year='_widget_1734062123084',
is_main_org='_widget_1734062123085', license_code='_widget_1734062123086',
license_name='_widget_1734062123087', org_crm_id='_widget_1734062123088',
province_id='_widget_1734062123089', province_name='_widget_1734062123090',
city_id='_widget_1734062123091', city_name='_widget_1734062123092',
area_id='_widget_1734062123093', area_name='_widget_1734062123094',
region_name='_widget_1734062123095', region_short_name='_widget_1734062123096',
branch_name='_widget_1734062123097', carzone_store_id='_widget_1734062123098',
carzone_store_name='_widget_1734062123099',
customer_carzone_id='_widget_1734062123100', salesmen='_widget_1734062123101',
area_manager='_widget_1734062123102', service_salesmen='_widget_1734062123103',
impl_principal='_widget_1734062123104',
service_impl_principal='_widget_1734062123105',
active_user_count='_widget_1734062123106', active_user_type='_widget_1734062123107',
limit_user_count='_widget_1734062123108', limit_user_type='_widget_1734062123109',
is_n='_widget_1734062123110', is_g='_widget_1734062123111',
is_v='_widget_1734062123112', is_visited='_widget_1734062123113',
is_active='_widget_1734062123114', active_status_fmt='_widget_1734062123115',
bill_count_last_30_day='_widget_1734062123116',
bill_day_count_last_30_day='_widget_1734062123117',
bill_day_count_this_month='_widget_1734062123118',
bill_count_last_7_day='_widget_1734062123119',
bill_day_count_last_7_day='_widget_1734062123120', pv_count='_widget_1734062123121',
uv_count='_widget_1734062123122', bill_count_1d='_widget_1734062123123',
bill_count_2d='_widget_1734062123124', bill_count_3d='_widget_1734062123125',
bill_count_4d='_widget_1734062123126', bill_count_5d='_widget_1734062123127',
bill_count_6d='_widget_1734062123128', bill_count_7d='_widget_1734062123129',
bill_count_8d='_widget_1734062123130', bill_count_9d='_widget_1734062123131',
bill_count_10d='_widget_1734062123132', bill_count_11d='_widget_1734062123133',
bill_count_12d='_widget_1734062123134', bill_count_13d='_widget_1734062123135',
bill_count_14d='_widget_1734062123136', bill_count_15d='_widget_1734062123137',
bill_count_16d='_widget_1734062123138', bill_count_17d='_widget_1734062123139',
bill_count_18d='_widget_1734062123140', bill_count_19d='_widget_1734062123141',
bill_count_20d='_widget_1734062123142', bill_count_21d='_widget_1734062123143',
bill_count_22d='_widget_1734062123144', bill_count_23d='_widget_1734062123145',
bill_count_24d='_widget_1734062123146', bill_count_25d='_widget_1734062123147',
bill_count_26d='_widget_1734062123148', bill_count_27d='_widget_1734062123149',
bill_count_28d='_widget_1734062123150', bill_count_29d='_widget_1734062123151',
bill_count_30d='_widget_1734062123152', bill_count_31d='_widget_1734062123153',
etl_time='_widget_1734062123154',
maintain_bill_count_last_30_day='_widget_1734062123155',
washing_bill_count_last_30_day='_widget_1734062123156',
maintain_bill_day_count_last_30_day='_widget_1734062123157',
washing_bill_day_count_last_30_day='_widget_1734062123158',
retail_bill_count_last_30_day='_widget_1734062123159',
retail_bill_day_count_last_30_day='_widget_1734062123160',
purchase_bill_count_last_30_day='_widget_1734062123161',
purchase_bill_day_count_last_30_day='_widget_1734062123162',
card_bill_count_last_30_day='_widget_1734062123163',
card_bill_day_count_last_30_day='_widget_1734062123164',
gd_sales_bill_count_last_30_day='_widget_1734062123165',
gd_sales_bill_day_count_last_30_day='_widget_1734062123166',
g_change_flag='_widget_1734062123167', saas_package='_widget_1734062123168',
manage_model='_widget_1734062123169', contacts='_widget_1734062123170',
contact_number='_widget_1734062123171', contact_mobile='_widget_1734062123172',
g_month_count='_widget_1734062123173', g_month_percentage='_widget_1734062123174',
is_install_service='_widget_1734062123175',
install_create_time='_widget_1734062123176', last_end_date='_widget_1734062123177',
renew_date='_widget_1734062123178', is_chain_owner='_widget_1734062123179',
group_org_count='_widget_1734062123180',
recent_bill_warning_days='_widget_1734062123181',
g_change_flag_d='_widget_1734062123182', g_lost_warning_days='_widget_1734062123183',
saas_edition_fmt='_widget_1734062123184', g_flag_1m='_widget_1734062123185',
g_flag_2m='_widget_1734062123186', g_flag_3m='_widget_1734062123187',
g_flag_4m='_widget_1734062123188', g_flag_5m='_widget_1734062123189',
g_flag_6m='_widget_1734062123190', g_flag_day_count='_widget_1734062123191',
add_org_flag='_widget_1734062123192', pt='_widget_1734062123193',
org_size='_widget_1734062123194', qualification_type_fmt='_widget_1734062123195',
business_scope_fmt='_widget_1734062123196', store_type_fmt='_widget_1734062123197',
area='_widget_1734062123198', station_number='_widget_1734062123199',
header_type_fmt='_widget_1734062123200', org_stage='_widget_1734062123201',
g_count_this_month='_widget_1734062123202',
saas_customer_type='_widget_1734062123203', technician='_widget_1734062123204',
tmall_maintain_service_status_desc='_widget_1734062123205',
date_fmt_date='_widget_1749000071375',
area_manager_staff_id='_widget_1748496855779',
service_impl_principal_staff_id="_widget_1748496855780",
service_salesmen_staff_id="_widget_1748496855778",
technician_staff_id="_widget_1751877712235",
saas_create_time_date="_widget_1749000071377",
expiry_time_date="_widget_1749000071382",
install_create_time_date="_widget_1749000071384",
last_end_date_date="_widget_1749000071389", renew_date_date="_widget_1749000071391")
if __name__ == '__main__':
start = UpdateNGVData()
start.main()
back_ground_module/update_all_NGV_data_daily.py
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# -*- coding: utf-8 -*-
import pandas as pd
import datetime
from config import Config
from api import API
from back_ground_module import CommonModule
from log_config import configure_task_logger, configure_error_task_logger
import concurrent.futures
# 获取已经配置好的常规日志记录器
logger = configure_task_logger()
# 获取已经配置好的错误任务日志记录器
error_task_logger = configure_error_task_logger()
start_time = datetime.datetime.now()
api_instance = API()
common_module = CommonModule()
class UpdateAllNGVDataDaily:
"""NGV数据每日更新"""
def __init__(self):
self.field_mapping = {}
self.fields()
def main(self):
# 保存为CSV文件
output_dir = "output" # 设置输出目录
# 创建输出目录（如果不存在）
import os
os.makedirs(output_dir, exist_ok=True)
task_start_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
# 获取NGV数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "675bb02bd2d53c2034c665e4"}
NGV_data_list = api_instance.entry_data_list(payload).get("data", [])
jdy_NGV_data = pd.DataFrame(NGV_data_list)
payload = {"api_key": "6694d3c4fcb69ca9a111a6c4",
"entry_id": "6769204a1902c9341340a1bc",
}
staff_id = api_instance.entry_data_list(payload)
staff_id_list = staff_id.get("data") # api请求格式，将数据封装在data字典里
# for i in range(1,2):
data_NGV_j = common_module.get_ngv_details(days_back=1)
data_NGV_j.to_csv(os.path.join(output_dir, f"data_NGV_j.csv"), index=False)
data_NGV_j1 = common_module.get_ngv_details(days_back=2)
# 对 data_NGV 进行进一步的过滤，只保留 org_type 为 "一般" 的记录
data_NGV_j = data_NGV_j[data_NGV_j['org_type'] == '一般']
data_NGV_j1 = data_NGV_j1[data_NGV_j1['org_type'] == '一般']
# 去除不需要的列
columns_to_remove = {'date_id', 'date_fmt', 'pt', 'etl_time'}
# 获取所有列名并计算要保留的列
columns_to_keep_df1 = list(set(data_NGV_j.columns) - columns_to_remove)
columns_to_keep_df2 = list(set(data_NGV_j1.columns) - columns_to_remove)
# 过滤DataFrame以去除指定列
df1_filtered = data_NGV_j[columns_to_keep_df1]
df2_filtered = data_NGV_j1[columns_to_keep_df2]
# 设置唯一标识列作为索引
df1_set_index = df1_filtered.set_index('id_own_org')
df2_set_index = df2_filtered.set_index('id_own_org')
df1_set_index = df1_set_index.astype(str).replace(['nan', 'None'], '', ).fillna("")
df2_set_index = df2_set_index.astype(str).replace(['nan', 'None'], '', ).fillna("")
# 找到两个DataFrame共有的索引
common_index = df1_set_index.index.intersection(df2_set_index.index)
# 使用共同的索引来重新索引两个DataFrame
df1_common = df1_set_index.reindex(common_index).fillna('')
df2_common = df2_set_index.reindex(common_index).fillna('')
# 确保两个DataFrame有相同的列顺序
common_columns = df1_common.columns.intersection(df2_common.columns)
df1_common = df1_common[common_columns]
df2_common = df2_common[common_columns]
# 比较两个DataFrame的内容
comparison_column = 'match_status'
# 创建一个布尔Series，指示每一行是否完全相同
matches = (df1_common == df2_common).all(axis=1)
# 添加新列到第一个DataFrame，标记是否匹配
df1_common[comparison_column] = matches.map({True: '一致', False: '不一致'})
# df1_common.to_csv(os.path.join(output_dir, f"df1_common.csv"))
# 如果需要也可以添加到第二个DataFrame（这里假设只需要处理df1_common）
# df2_common[comparison_column] = matches.map({True: '一致', False: '不一致'})
# 提取只在一个DataFrame中存在的索引对应的行
df1_only_index = df1_set_index.index.difference(df2_set_index.index)
df2_only_index = df2_set_index.index.difference(df1_set_index.index)
df1_only_rows = df1_set_index.loc[df1_only_index].copy()
df2_only_rows = df2_set_index.loc[df2_only_index].copy()
# 保存匹配结果
# df1_common.to_csv(os.path.join(output_dir, 'matched_results.csv'), index_label='id_own_org')
# 保存仅在df1中的行
# df1_only_rows.to_csv(os.path.join(output_dir, 'df1_only_rows.csv'), index_label='id_own_org')
# 保存仅在df2中的行
# df2_only_rows.to_csv(os.path.join(output_dir, 'df2_only_rows.csv'), index_label='id_own_org')
# data_NGV_j.to_csv(os.path.join(output_dir, 'data_NGV_j.csv'), index_label='id_own_org')
# data_NGV_j1.to_csv(os.path.join(output_dir, 'data_NGV_j1.csv'), index_label='id_own_org')
# jdy_NGV_data.to_csv(os.path.join(output_dir, 'jdy_NGV_data.csv'), index_label='id_own_org')
# print(f"\nCSV文件已保存到目录: {output_dir}")
temp_jdy_NGV_data = jdy_NGV_data.copy()
# temp_jdy_NGV_data.to_csv(os.path.join(output_dir, 'jdy_NGV_data.csv'), index=False)
temp_jdy_NGV_data.reset_index(inplace=True) # 如果 '门店id' 是索引，则先将其转换为普通列
# temp_jdy_NGV_data.to_csv(os.path.join(output_dir, 'jdy_NGV_data1.csv'), index=False)
if '_widget_1734062123069' not in temp_jdy_NGV_data.columns:
print("列 '门店id' 不存在")
temp_jdy_NGV_data.rename(columns={'_widget_1734062123069': 'id_own_org'}, inplace=True)
temp_jdy_NGV_data.set_index('id_own_org', inplace=True)
# 如果简道云存在，NGV不存在则标记NGV已删除
# 找出在 temp_jdy_NGV_data 中存在，但在 df1_common 中不存在的索引
ids_in_jdy_not_in_df1 = temp_jdy_NGV_data.index[~temp_jdy_NGV_data.index.isin(df1_common.index)]
# 提取这些行，形成新的 DataFrame
only_in_temp_jdy = temp_jdy_NGV_data.loc[ids_in_jdy_not_in_df1]
# 对数据源已经去掉的门店进行标记
for index, only_row in only_in_temp_jdy.iterrows():
result = {}
if '_id' in only_in_temp_jdy.columns:
_id_value = str(only_row['_id']) if not pd.isna(only_row['_id']) else None
result["_id"] = _id_value
if result["_id"]:
data = {
'api_key': Config.SaaS_Tasks_APP_ID,
'entry_id': Config.NGV_TASKS_ENTRY_ID,
"data_id": result["_id"],
"data": {"_widget_1754285499851": {"value": "已删除"}}
}
api_instance.entry_data_update(data=data, max_retries=20)
# 简道云与ngv不一致的数据做关联
df1_common = df1_common.join(temp_jdy_NGV_data["_id"], how='left')
df1_common = df1_common[df1_common['match_status'] == '不一致']
# 日期字段转换为日期格式
time_columns = ['saas_create_time', 'expiry_time', 'install_create_time', "last_end_date",
"renew_date"]
new_filtered_df = df1_common.copy() # 复制df，以调整时间
for col in time_columns:
# 1. 转换为datetime类型（带错误处理）
# 使用.loc安全赋值
new_filtered_df[col] = pd.to_datetime(df1_common[col], errors='coerce', utc=False)
# 2. 优化后的时区转换（高效向量化操作）
df1_common[col + '_date'] = (
new_filtered_df[col]
# 本地化为北京时间（东八区）
.dt.tz_localize('Asia/Shanghai', ambiguous='infer', nonexistent='NaT')
# 转换为UTC时区
.dt.tz_convert('UTC')
# 格式化为ISO8601字符串
.dt.strftime('%Y-%m-%dT%H:%M:%SZ')
)
# 人员字段转换为人员字段
staff_columns = ['area_manager', 'service_impl_principal', "service_salesmen", "technician"]
# 将员工列表转为DataFrame
# 三重循环临时方案（确保可写入）
for col in staff_columns:
staff_ids = []
for _, row in df1_common.iterrows():
matched = False
for staff in staff_id_list:
if str(staff['_widget_1734942794144']) == str(row[col]):
staff_ids.append(staff['_widget_1734942794145'])
matched = True
break
if not matched:
staff_ids.append(None)
df1_common[col + "_staff_id"] = staff_ids
# 并发请求
futures = []
all_data = []
for idx, row in df1_common.iterrows():
result = {}
data_dict = {}
# 根据 field_mapping 进行字段替换
for col_name, widget_id in self.field_mapping.items():
if col_name in df1_common.columns:
value = row[col_name]
clean_value = None if pd.isna(value) else value
data_dict[widget_id] = {"value": clean_value}
# 单独处理 _id 列，并将其转换为字符串
if '_id' in df1_common.columns:
_id_value = str(row['_id']) if not pd.isna(row['_id']) else None
result["_id"] = _id_value
# 组装最终结果
if result["_id"]:
data = {
'api_key': Config.SaaS_Tasks_APP_ID,
'entry_id': Config.NGV_TASKS_ENTRY_ID,
"data_id": result["_id"],
"data": data_dict
}
api_instance.entry_data_update(data=data, max_retries=20)
else:
# continue
data1 = {'api_key': Config.SaaS_Tasks_APP_ID, 'entry_id': Config.NGV_TASKS_ENTRY_ID,
"data": data_dict}
api_instance.data_batch_create(data=data1, max_retries=20)
# all_data.append(data_dict)
# 收集所有结果
for future in concurrent.futures.as_completed(futures):
try:
result = future.result()
print("请求结果:", result)
except Exception as exc:
print(f"请求发生异常: {exc}")
end_time = datetime.datetime.now()
# df11 = pd.DataFrame(all_data)
# df11.to_csv(f"all_data.csv")
time_diff = end_time - start_time
# 打印天数、秒数和微秒数
print(f"执行时间: {time_diff.days} 天, {time_diff.seconds} 秒, {time_diff.microseconds} 微秒")
common_module.send_task_status(task_start_time, "NGV更新数据")
@staticmethod
def row_to_dict(row, field_mapping):
"""将一行数据转换为指定格式的字典"""
result = {}
for col_name, widget_id in field_mapping.items():
if col_name in row:
value = row[col_name]
clean_value = None if pd.isna(value) else value
result[widget_id] = {"value": clean_value}
return result
def fields(self):
self.field_mapping = dict(date_id='_widget_1734062123065', date_fmt='_widget_1734062123066',
id_own_group='_widget_1734062123067', group_name='_widget_1734062123068',
id_own_org='_widget_1734062123069', org_name='_widget_1734062123070',
org_code='_widget_1734062123071', group_grade='_widget_1734062123072',
org_type='_widget_1734062123073', org_status='_widget_1734062123074',
saas_version='_widget_1734062123075', is_wechat='_widget_1734062123076',
is_mini_app='_widget_1734062123077', is_wx_shop='_widget_1734062123078',
is_camera_service='_widget_1734062123079',
is_maintenance_service='_widget_1734062123080',
saas_create_time='_widget_1734062123081', expiry_time='_widget_1734062123082',
saas_use_days='_widget_1734062123083', saas_use_year='_widget_1734062123084',
is_main_org='_widget_1734062123085', license_code='_widget_1734062123086',
license_name='_widget_1734062123087', org_crm_id='_widget_1734062123088',
province_id='_widget_1734062123089', province_name='_widget_1734062123090',
city_id='_widget_1734062123091', city_name='_widget_1734062123092',
area_id='_widget_1734062123093', area_name='_widget_1734062123094',
region_name='_widget_1734062123095', region_short_name='_widget_1734062123096',
branch_name='_widget_1734062123097', carzone_store_id='_widget_1734062123098',
carzone_store_name='_widget_1734062123099',
customer_carzone_id='_widget_1734062123100', salesmen='_widget_1734062123101',
area_manager='_widget_1734062123102', service_salesmen='_widget_1734062123103',
impl_principal='_widget_1734062123104',
service_impl_principal='_widget_1734062123105',
active_user_count='_widget_1734062123106', active_user_type='_widget_1734062123107',
limit_user_count='_widget_1734062123108', limit_user_type='_widget_1734062123109',
is_n='_widget_1734062123110', is_g='_widget_1734062123111',
is_v='_widget_1734062123112', is_visited='_widget_1734062123113',
is_active='_widget_1734062123114', active_status_fmt='_widget_1734062123115',
bill_count_last_30_day='_widget_1734062123116',
bill_day_count_last_30_day='_widget_1734062123117',
bill_day_count_this_month='_widget_1734062123118',
bill_count_last_7_day='_widget_1734062123119',
bill_day_count_last_7_day='_widget_1734062123120', pv_count='_widget_1734062123121',
uv_count='_widget_1734062123122', bill_count_1d='_widget_1734062123123',
bill_count_2d='_widget_1734062123124', bill_count_3d='_widget_1734062123125',
bill_count_4d='_widget_1734062123126', bill_count_5d='_widget_1734062123127',
bill_count_6d='_widget_1734062123128', bill_count_7d='_widget_1734062123129',
bill_count_8d='_widget_1734062123130', bill_count_9d='_widget_1734062123131',
bill_count_10d='_widget_1734062123132', bill_count_11d='_widget_1734062123133',
bill_count_12d='_widget_1734062123134', bill_count_13d='_widget_1734062123135',
bill_count_14d='_widget_1734062123136', bill_count_15d='_widget_1734062123137',
bill_count_16d='_widget_1734062123138', bill_count_17d='_widget_1734062123139',
bill_count_18d='_widget_1734062123140', bill_count_19d='_widget_1734062123141',
bill_count_20d='_widget_1734062123142', bill_count_21d='_widget_1734062123143',
bill_count_22d='_widget_1734062123144', bill_count_23d='_widget_1734062123145',
bill_count_24d='_widget_1734062123146', bill_count_25d='_widget_1734062123147',
bill_count_26d='_widget_1734062123148', bill_count_27d='_widget_1734062123149',
bill_count_28d='_widget_1734062123150', bill_count_29d='_widget_1734062123151',
bill_count_30d='_widget_1734062123152', bill_count_31d='_widget_1734062123153',
etl_time='_widget_1734062123154',
maintain_bill_count_last_30_day='_widget_1734062123155',
washing_bill_count_last_30_day='_widget_1734062123156',
maintain_bill_day_count_last_30_day='_widget_1734062123157',
washing_bill_day_count_last_30_day='_widget_1734062123158',
retail_bill_count_last_30_day='_widget_1734062123159',
retail_bill_day_count_last_30_day='_widget_1734062123160',
purchase_bill_count_last_30_day='_widget_1734062123161',
purchase_bill_day_count_last_30_day='_widget_1734062123162',
card_bill_count_last_30_day='_widget_1734062123163',
card_bill_day_count_last_30_day='_widget_1734062123164',
gd_sales_bill_count_last_30_day='_widget_1734062123165',
gd_sales_bill_day_count_last_30_day='_widget_1734062123166',
g_change_flag='_widget_1734062123167', saas_package='_widget_1734062123168',
manage_model='_widget_1734062123169', contacts='_widget_1734062123170',
contact_number='_widget_1734062123171', contact_mobile='_widget_1734062123172',
g_month_count='_widget_1734062123173', g_month_percentage='_widget_1734062123174',
is_install_service='_widget_1734062123175',
install_create_time='_widget_1734062123176', last_end_date='_widget_1734062123177',
renew_date='_widget_1734062123178', is_chain_owner='_widget_1734062123179',
group_org_count='_widget_1734062123180',
recent_bill_warning_days='_widget_1734062123181',
g_change_flag_d='_widget_1734062123182', g_lost_warning_days='_widget_1734062123183',
saas_edition_fmt='_widget_1734062123184', g_flag_1m='_widget_1734062123185',
g_flag_2m='_widget_1734062123186', g_flag_3m='_widget_1734062123187',
g_flag_4m='_widget_1734062123188', g_flag_5m='_widget_1734062123189',
g_flag_6m='_widget_1734062123190', g_flag_day_count='_widget_1734062123191',
add_org_flag='_widget_1734062123192', pt='_widget_1734062123193',
org_size='_widget_1734062123194', qualification_type_fmt='_widget_1734062123195',
business_scope_fmt='_widget_1734062123196', store_type_fmt='_widget_1734062123197',
area='_widget_1734062123198', station_number='_widget_1734062123199',
header_type_fmt='_widget_1734062123200', org_stage='_widget_1734062123201',
g_count_this_month='_widget_1734062123202',
saas_customer_type='_widget_1734062123203', technician='_widget_1734062123204',
tmall_maintain_service_status_desc='_widget_1734062123205',
date_fmt_date='_widget_1749000071375',
area_manager_staff_id='_widget_1748496855779',
service_impl_principal_staff_id="_widget_1748496855780",
service_salesmen_staff_id="_widget_1748496855778",
technician_staff_id="_widget_1751877712235",
saas_create_time_date="_widget_1749000071377",
expiry_time_date="_widget_1749000071382",
install_create_time_date="_widget_1749000071384",
last_end_date_date="_widget_1749000071389", renew_date_date="_widget_1749000071391")
if __name__ == '__main__':
start = UpdateAllNGVDataDaily()
start.main()
back_ground_module/update_denominator_reporting_adjustment_to_bi.py
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import mysql.connector
from mysql.connector import Error
import numpy as np
import pandas as pd
from yd_api import YDAPI
from api import API
import pandas as pd
from tqdm import tqdm
import time
from datetime import datetime, timedelta
from config import Config
from back_ground_module import CommonModule
import logging
from log_config import configure_task_logger, configure_error_task_logger
import mysql.connector
from mysql.connector import Error
import re
import json
logger = configure_task_logger()
# 获取已经配置好的错误任务日志记录器
error_task_logger = configure_error_task_logger()
# 初始化 API 实例和 Token
yd_api_instance = YDAPI()
api_instance = API()
common_module = CommonModule()
TOKEN = yd_api_instance.generateToken()
# 配置常量
FORMID = "FORM-WV866IC119W8BZC7AKHAR7VT3FI52W4Q1VBFLD1" # FPO需求提交
appType = "APP_UYZ0KG6L0CCNV80GZ66O" # F6客户服务
systemToken = "XA966F81JAJOFCVVVKO64E9MIIZV1EWE5SFMKJ2" # 密钥
BASE_URL = "https://f6car.aliwork.com" # 基础URL
print(TOKEN)
DB_CONFIG = Config.HS_DB_Config
# 数据库配置
class DenominatorReportingAdjustment:
"""分母报备调整"""
def __init__(self):
self.structures = None
self.denominator_data_list = None
self.field_map = {
"门店编码": "textField_pl5p5a3",
"门店名称": "textField_fcl5xg6",
"公司名称": "textField_bdlfhio",
"大区": "textField_urgu3fr",
"小区": "textField_dro2c5y",
"战区": "textField_e3pkxp1",
"技术专家": "employeeField_mca5shp0",
"区域客成": "employeeField_mca5shp1",
"运营负责人": "textField_j9uxos9",
"SaaS版本": "textField_0hbyovw",
"开户日期": "dateField_dnj8hop",
"开始时间": "dateField_ppr0d3a",
"结束时间": "dateField_jvsr6ef",
"原分母金额": "numberField_l4bcg80",
"调整后金额": "numberField_9bjyfzj",
"分母调整理由": "textField_niczt1b",
"对应订单编码": "textField_2ubszzt",
"转养车后门店编码": "textField_q14ebff",
"总部调整备注": "textareaField_lfrnbtbu",
"总部调整结果": "selectField_lfqwg05y",
"总部核对结果": "selectField_lfqwg05x",
"是否上传衡石": "selectField_mca5shoz",
"是否计入应续约数": "selectField_mdnwwvyo"
}
def get_yida_data(self):
# 获取分母报备数据
denominator_data = yd_api_instance.read_processes(token=TOKEN, formUuid=FORMID, page=1, n=100,
appType=appType, systemToken=systemToken)
self.denominator_data_list = []
print(denominator_data)
PAGES_two = denominator_data.get('totalCount') // 100 + 1
parentheses_pattern = re.compile(r'$[^)]*$')
for a in range(1, PAGES_two + 1):
denominator_data = yd_api_instance.read_processes(token=TOKEN, formUuid=FORMID, page=a, n=100,
appType=appType, systemToken=systemToken)
for item in denominator_data.get("data", []):
form_data = item.get("formData", {})
# Transform the keys using field_map
transformed_data = {}
for field_key in ['employeeField_mca5shp1', 'employeeField_mca5shp0']:
if field_key in form_data and isinstance(form_data[field_key], list) and len(form_data[field_key]) > 0:
# 取第一个元素
raw_value = form_data[field_key][0]
# 去除括号及其中的内容
cleaned_value = parentheses_pattern.sub('', raw_value).strip()
# 更新 formData 中的值
form_data[field_key] = cleaned_value
for field_id, value in form_data.items():
# Find the display name in field_map
for display_name, id_in_map in self.field_map.items():
if id_in_map == field_id:
transformed_data[display_name] = value
break
# print(transformed_data.get("是否上传衡石"))
# if transformed_data.get("是否上传衡石") == "否" or transformed_data.get("是否上传衡石") is None:
# continue
self.denominator_data_list.append(transformed_data)
def execute_sql(self, sql, params=None, fetch=False, many=False):
"""执行SQL语句"""
conn = None
try:
conn = mysql.connector.connect(**DB_CONFIG)
cursor = conn.cursor()
if many:
cursor.executemany(sql, params)
else:
cursor.execute(sql, params or ())
conn.commit()
return cursor.fetchall() if fetch else cursor
except Error as e:
print(f"执行失败: {sql}\n错误: {e}")
if conn: conn.rollback()
return None
finally:
if conn and conn.is_connected():
cursor.close()
conn.close()
def write_to_bi(self, df):
# 数据库连接信息
table_name = "f6_denominator_adjustment" # 替换为你的实际表名
# 建立数据库连接
connection = mysql.connector.connect(
host=DB_CONFIG["host"],
user=DB_CONFIG["user"],
password=DB_CONFIG["password"],
database=DB_CONFIG["database"]
)
cursor = connection.cursor()
try:
# 查询表列名
cursor.execute(f"SHOW COLUMNS FROM {table_name}")
columns_info = cursor.fetchall()
db_columns = [col[0] for col in columns_info] # 提取列名
df = df.replace([None, np.nan, pd.NA, 'nan', 'NaN', 'NAN', ''], None)
# 保留 DataFrame 中与数据库列名匹配的列
filtered_df = df[df.columns.intersection(db_columns)]
# 如果没有匹配的列，直接返回
if filtered_df.empty:
print("DataFrame 中没有与数据库表结构匹配的列。")
return
# 筛选列之后，插入前处理 dict 类型
filtered_df = filtered_df.copy()
for col in filtered_df.columns:
if filtered_df[col].apply(lambda x: isinstance(x, (dict, list)) if x is not None else False).any():
filtered_df.loc[:, col] = filtered_df[col].apply(
lambda x: json.dumps(x, ensure_ascii=False) if x is not None else x
)
# 构建插入语句
placeholders = ', '.join(['%s'] * len(filtered_df.columns))
# 使用反引号避免特殊列明
columns = ', '.join([f"`{col}`" for col in filtered_df.columns])
insert_sql = f"INSERT INTO {table_name} ({columns}) VALUES ({placeholders})"
# 将 DataFrame 写入数据库
for _, row in filtered_df.iterrows():
cursor.execute(insert_sql, tuple(row))
connection.commit()
print(f"成功写入 {len(filtered_df)} 条记录到 {table_name} 表中。")
except Exception as e:
print("写入数据库时发生错误：", e)
connection.rollback()
finally:
cursor.close()
connection.close()
def clear_table(self):
"""清空表数据"""
if self.execute_sql("TRUNCATE TABLE f6_denominator_adjustment"):
print("✅ 成功清空表数据")
def main(self):
task_start_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
# step1:获取宜搭数据
self.get_yida_data()
df = pd.DataFrame(self.denominator_data_list)
df['开户日期'] = df['开户日期'].astype('Int64')
df['开户日期'] = pd.to_datetime(df['开户日期'], unit='ms')
df['结束时间'] = df['结束时间'].astype('Int64')
df['结束时间'] = pd.to_datetime(df['结束时间'], unit='ms')
df['开始时间'] = df['开始时间'].astype('Int64')
df['开始时间'] = pd.to_datetime(df['开始时间'], unit='ms')
# step2:清空BI数据表
self.clear_table()
# # step3:写入BI数据库
self.write_to_bi(df)
common_module.send_task_status(task_start_time, "分母报备调整")
if __name__ == '__main__':
denominator_reporting_adjustment = DenominatorReportingAdjustment()
denominator_reporting_adjustment.main()
back_ground_module/update_email_to_store_daily_use.py
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import os
import poplib
import time
import pandas as pd
from email.parser import Parser
from email.header import decode_header
from email.utils import parseaddr
from datetime import datetime
from config import Config
from api import API
from back_ground_module import CommonModule
import pandas as pd
import pymysql
from pymysql import Error
api_instance = API()
common_module = CommonModule()
class EmailProcessor:
"""泰国CRM每日邮件写入简道云与BI"""
def __init__(self):
# 配置信息
self.user_email_address = 'caowei@f6car.cn'
self.user_password = 'Cw@340826'
self.pop_server_host = 'pop.qiye.aliyun.com'
self.pop_server_port = '995'
self.send_name = "f6car"
self.send_addr = 'noreplay@notice.f6car.com'
# 创建输出目录（如果不存在）
output_dir = "email"
os.makedirs(output_dir, exist_ok=True)
nowtime = datetime.now().strftime("%Y%m%d%H%M%S")
self.write_path = os.path.join(output_dir, f'email_data.xlsx')
# 初始化字段映射
self.field_mapping = {
"指标归属日期": "_widget_1742174728275",
"公司ID": "_widget_1742091963874",
"公司名称": "_widget_1742091963875",
"门店ID": "_widget_1742091963876",
"门店名称": "_widget_1742091963877",
"门店简称": "_widget_1742091963878",
"门店创建时间": "_widget_1742091963879",
"指标类型": "_widget_1742091963880",
"指标值": "_widget_1742091963882",
"指标子类型": "_widget_1742091963881",
"指标值": "_widget_1742091963882"
}
def connect_email_by_pop3(self):
try:
# 连接到POP服务器
email_server = poplib.POP3_SSL(
host=self.pop_server_host,
port=self.pop_server_port,
timeout=10
)
print("POP服务器连接成功，开始用户邮箱验证")
except Exception as e:
print(f"POP服务器连接失败。错误: {str(e)}")
exit(1)
try:
# 验证用户邮箱
email_server.user(self.user_email_address)
print("用户邮箱验证成功，开始授权码验证")
except Exception as e:
print(f"用户邮箱验证失败。错误: {str(e)}")
exit(1)
try:
# 验证密码/授权码
email_server.pass_(self.user_password)
print("授权码验证成功，开始处理邮件")
except Exception as e:
print(f"授权码验证失败。错误: {str(e)}")
exit(1)
# 处理邮件
self.parse_email_server(email_server)
def parse_email_server(self, email_server):
# 获取所有邮件列表
resp, mails, octets = email_server.list()
index = len(mails)
# 获取今天的零点时间戳
now = datetime.now()
today_start = datetime(now.year, now.month, now.day) # 当天零点
today_start_timestamp = int(today_start.timestamp()) # 转换为时间戳
# 按逆序处理邮件（最新的先处理）
for i in range(index, 0, -1):
# print(f"正在处理邮件 {i},{index}")
try:
# 获取邮件内容
resp, lines, octets = email_server.retr(i)
msg_content = b'\r\n'.join(lines).decode('utf-8', errors='ignore') # 避免解码错误
msg = Parser().parsestr(msg_content)
# 处理邮件时间
mail_datetime = self.parse_mail_time(msg.get("date"))
if not mail_datetime: # 如果邮件时间解析失败，跳过
# logging.warning(f"Failed to parse date for email {i}. Skipping...")
continue
# 将邮件时间转换为时间戳
mail_timestamp = int(mail_datetime.timestamp())
# 如果邮件不是今天的，跳过
if mail_timestamp < today_start_timestamp:
# logging.info(f"Skipping email {i} as it is not from today.")
# continue
break
# 打印邮件接收时间
mail_time_str = datetime.strftime(mail_datetime, '%Y-%m-%d %H:%M:%S')
print(f"邮件接收时间: {mail_time_str}")
# 处理邮件内容
self.parser_content(msg, 0)
except Exception as e:
# logging.error(f"Error processing email {i}: {e}")
print(f"Error processing email {i}: {e}")
continue
# 退出服务器
email_server.quit()
def parser_content(self, msg, indent):
print("邮件处理")
if indent == 0:
self.parser_email_header(msg)
# 解析发件人信息
hdr, addr = parseaddr(msg['From'])
name, charset = decode_header(hdr)[0]
if charset:
name = name.decode(charset)
print(f'发件人姓名: {name}, 发件人邮箱: {addr}')
if name == self.send_name:
# 下载附件
for part in msg.walk():
file_name = part.get_filename()
if file_name is None:
continue
filename = self.decode_str(file_name)
data = part.get_payload(decode=True)
try:
with open(self.write_path, 'wb') as att_file:
att_file.write(data)
print(f"附件保存成功: {self.write_path}+{filename}")
except Exception as e:
print(f"附件保存失败: {str(e)}")
if msg.is_multipart():
parts = msg.get_payload()
for part in parts:
self.parser_content(part, indent + 1)
else:
# 解析邮件正文
content_type = msg.get_content_type()
if content_type in ['text/plain', 'text/html']:
content = msg.get_payload(decode=True)
charset = self.guess_charset(msg)
if charset:
content = content.decode(charset)
print(f"{' ' * indent}邮件内容: {content}")
def parser_email_header(self, msg):
# 解析邮件主题
subject = msg['Subject']
value, charset = decode_header(subject)[0]
if charset:
value = value.decode(charset)
print(f'邮件主题: {value}')
# 解析发件人信息
hdr, addr = parseaddr(msg['From'])
name, charset = decode_header(hdr)[0]
if charset:
name = name.decode(charset)
print(f'发件人姓名: {name}, 发件人邮箱: {addr}')
# 解析收件人信息
hdr, addr = parseaddr(msg['To'])
name, charset = decode_header(hdr)[0]
if charset:
name = name.decode(charset)
print(f'收件人姓名: {name}, 收件人邮箱: {addr}')
@staticmethod
def decode_str(s):
value, charset = decode_header(s)[0]
if charset:
value = value.decode(charset)
return value
@staticmethod
def guess_charset(msg):
charset = msg.get_charset()
if charset is None:
content_type = msg.get('Content-Type', '').lower()
for item in content_type.split(';'):
item = item.strip()
if item.startswith('charset'):
charset = item.split('=')[1]
break
return charset
@staticmethod
def parse_mail_time(mail_datetime):
GMT_FORMAT = "%a, %d %b %Y %H:%M:%S"
GMT_FORMAT2 = "%d %b %Y %H:%M:%S"
index = mail_datetime.find(' +0')
if index > 0:
mail_datetime = mail_datetime[:index] # 移除时区信息
formats = [GMT_FORMAT, GMT_FORMAT2]
for ft in formats:
try:
mail_datetime = datetime.strptime(mail_datetime, ft)
return mail_datetime
except:
pass
raise Exception("邮件时间格式解析错误")
@staticmethod
def row_to_dict(row, field_mapping):
"""将一行数据转换为格式化字典"""
result = {}
for col_name, widget_id in field_mapping.items():
if col_name in row:
value = row[col_name]
clean_value = None if pd.isna(value) else value
result[widget_id] = {"value": clean_value}
return result
def update_email(self):
# try:
print(self.write_path)
email_df = pd.read_excel(self.write_path, sheet_name="Sheet0")
print(email_df.head())
email_df['公司ID'] = email_df['公司ID'].astype(str)
email_df['门店ID'] = email_df['门店ID'].astype(str)
email_df['指标归属日期'] = pd.to_datetime(email_df['指标归属日期'], format="%Y/%m/%d").dt.strftime("%Y-%m-%d")
email_df["门店创建时间"] = pd.to_datetime(email_df['门店创建时间'], format="%Y-%m-%d %H:%M:%S")
new_email_df = email_df.copy() # 拷贝传参
for index, row in email_df.iterrows():
email_df.loc[index, '指标归属日期'] = common_module.time_to_UTC(row['指标归属日期'])
email_df.loc[index, '门店创建时间'] = common_module.time_to_UTC(row['门店创建时间'])
email_data = [self.row_to_dict(row, self.field_mapping) for index, row in email_df.iterrows()]
new_email_data = {'api_key': "673457d6837e60a418e0e56b",
'entry_id': "67d636bb6212b7619a7a4231",
# 'entry_id': "684157deab0c4c9ec636ed36", # 测试
"data_list": email_data}
api_instance.entry_data_batch_create(new_email_data)
os.remove(self.write_path)
return new_email_df
def up_to_BI(self, df):
# 连接信息
HS_DB_Config = Config.HS_DB_Config
table_name = "thailand_store_data_email"
try:
# 连接
connection = pymysql.connect(
host=HS_DB_Config["host"],
user=HS_DB_Config["user"],
password=HS_DB_Config["password"],
database=HS_DB_Config["database"],
charset='utf8mb4',
)
print(f"成功连接 {HS_DB_Config["database"]}")
with connection.cursor() as cursor:
# 处理数据
df = df.where(pd.notna(df), None) # 将NaN转换为None
# 生成插入语句
columns = ', '.join(df.columns)
placeholders = ', '.join(['%s'] * len(df.columns))
insert_query = f"INSERT INTO {table_name} ({columns}) VALUES ({placeholders})"
# 批量插入数据
records = [tuple(row) for row in df.values]
cursor.executemany(insert_query, records)
connection.commit()
print(f"成功导入 {cursor.rowcount} 条记录到 {table_name} 表")
except Error as e:
print(f"数据库操作出错: {e}")
if connection:
connection.rollback()
finally:
if connection:
connection.close()
@classmethod
def main(cls):
"""邮件处理器的主入口点"""
task_start_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
processor = cls()
processor.connect_email_by_pop3()
email_df = processor.update_email()
processor.up_to_BI(email_df) # 发送到BI
common_module.send_task_status(task_start_time, "海外邮件推送")
if __name__ == "__main__":
EmailProcessor.main()
back_ground_module/update_molecule_reporting_adjustment_to_bi.py
+196
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import mysql.connector
from mysql.connector import Error
import numpy as np
import pandas as pd
from yd_api import YDAPI
from api import API
import pandas as pd
from tqdm import tqdm
import time
from datetime import datetime, timedelta
from config import Config
from back_ground_module import CommonModule
import logging
from log_config import configure_task_logger, configure_error_task_logger
import mysql.connector
from mysql.connector import Error
import json
logger = configure_task_logger()
# 获取已经配置好的错误任务日志记录器
error_task_logger = configure_error_task_logger()
# 初始化 API 实例和 Token
yd_api_instance = YDAPI()
api_instance = API()
common_module = CommonModule()
TOKEN = yd_api_instance.generateToken()
print(TOKEN)
# 配置常量
FORMID = "FORM-VJ866081CVI9E7ALB7WOO7BHPPQW25R99AWFL0" # 分子报备调整
appType = "APP_UYZ0KG6L0CCNV80GZ66O" # F6客户服务
systemToken = "XA966F81JAJOFCVVVKO64E9MIIZV1EWE5SFMKJ2" # 密钥
# 数据库配置
DB_CONFIG = Config.HS_DB_Config
class MoleculeReportingAdjustment:
"""分子报备调整"""
def __init__(self):
self.molecule_data_list = None
self.structures = None
self.denominator_data_list = None
self.field_map = {
"归属月份": "dateField_264kcmw",
"门店编码": "textField_9rqmwyy",
"门店名称": "textField_oxuvyp2",
"公司名称": "textField_dqmsvkl",
"续约后saas版本": "textField_1oil7le",
"运营负责人": "textField_lxouajj",
"区域经理": "textField_udayebj",
"技术专家": "textField_49x98hm",
"大区": "textField_a4niy40",
"小区": "textField_s98potv",
"省份": "textField_526wca0",
"城市": "textField_pvk89jn",
"收入类型": "selectField_alb3qo9",
"关联订单编码": "textField_mtynj7n",
"调整金额": "numberField_knq1ssd",
"调整理由说明": "textField_6ysqrxw",
"总部核对结果": "selectField_lfwb7dnn",
"分子调整结果": "selectField_lfwb7dno",
"是否上传衡石": "selectField_mceh174n",
"总部调整备注": "textField_lfwb7dnp",
}
def get_yida_data(self):
# 获取分母报备数据
molecule_data = yd_api_instance.read_processes(token=TOKEN, formUuid=FORMID, page=1, n=100,
appType=appType, systemToken=systemToken)
self.molecule_data_list = []
PAGES_two = molecule_data.get('totalCount') // 100 + 1
for a in range(1, PAGES_two + 1):
molecule_data = yd_api_instance.read_processes(token=TOKEN, formUuid=FORMID, page=a, n=100,
appType=appType, systemToken=systemToken)
for item in molecule_data.get("data", []):
form_data = item.get("formData", {})
# Transform the keys using field_map
transformed_data = {}
for field_id, value in form_data.items():
# Find the display name in field_map
for display_name, id_in_map in self.field_map.items():
if id_in_map == field_id :
transformed_data[display_name] = value
break
# if transformed_data.get("是否上传衡石") == "否" or transformed_data.get("是否上传衡石") is None:
# continue
self.molecule_data_list.append(transformed_data)
def execute_sql(self, sql, params=None, fetch=False, many=False):
"""执行SQL语句"""
conn = None
try:
conn = mysql.connector.connect(**DB_CONFIG)
cursor = conn.cursor()
if many:
cursor.executemany(sql, params)
else:
cursor.execute(sql, params or ())
conn.commit()
return cursor.fetchall() if fetch else cursor
except Error as e:
print(f"执行失败: {sql}\n错误: {e}")
if conn: conn.rollback()
return None
finally:
if conn and conn.is_connected():
cursor.close()
conn.close()
def write_to_bi(self, df):
# 数据库连接信息
table_name = "f6_molecule_adjustment" # 替换为你的实际表名
# 建立数据库连接
connection = mysql.connector.connect(
host=DB_CONFIG["host"],
user=DB_CONFIG["user"],
password=DB_CONFIG["password"],
database=DB_CONFIG["database"]
)
cursor = connection.cursor()
try:
# 查询表列名
cursor.execute(f"SHOW COLUMNS FROM {table_name}")
columns_info = cursor.fetchall()
db_columns = [col[0] for col in columns_info] # 提取列名
df = df.replace([None, np.nan, pd.NA, 'nan', 'NaN', 'NAN', ''], None)
# 保留 DataFrame 中与数据库列名匹配的列
filtered_df = df[df.columns.intersection(db_columns)]
# 如果没有匹配的列，直接返回
if filtered_df.empty:
print("DataFrame 中没有与数据库表结构匹配的列。")
return
# 筛选列之后，插入前处理 dict 类型
filtered_df = filtered_df.copy()
for col in filtered_df.columns:
if filtered_df[col].apply(lambda x: isinstance(x, (dict, list)) if x is not None else False).any():
filtered_df.loc[:, col] = filtered_df[col].apply(
lambda x: json.dumps(x, ensure_ascii=False) if x is not None else x
)
# 构建插入语句
placeholders = ', '.join(['%s'] * len(filtered_df.columns))
# 使用反引号避免特殊列明
columns = ', '.join([f"`{col}`" for col in filtered_df.columns])
insert_sql = f"INSERT INTO {table_name} ({columns}) VALUES ({placeholders})"
# 将 DataFrame 写入数据库
for _, row in filtered_df.iterrows():
cursor.execute(insert_sql, tuple(row))
connection.commit()
print(f"成功写入 {len(filtered_df)} 条记录到 {table_name} 表中。")
except Exception as e:
print("写入数据库时发生错误：", e)
connection.rollback()
finally:
cursor.close()
connection.close()
def clear_table(self):
"""清空表数据"""
if self.execute_sql("TRUNCATE TABLE f6_molecule_adjustment"):
print("✅ 成功清空表数据")
def main(self):
task_start_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
# step1:获取宜搭数据
self.get_yida_data()
df = pd.DataFrame(self.molecule_data_list)
df['归属月份'] = df['归属月份'].astype('Int64')
df['归属月份'] = pd.to_datetime(df['归属月份'], unit='ms')
# step2:清空BI数据表
self.clear_table()
# # step3:写入BI数据库
self.write_to_bi(df)
common_module.send_task_status(task_start_time, "分子报备调整")
if __name__ == '__main__':
molecule_reporting_adjustment = MoleculeReportingAdjustment()
molecule_reporting_adjustment.main()
back_ground_module/yida_Fpo_Jandaoyun.py
+388
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from yd_api import YDAPI
from api import API
import pandas as pd
from tqdm import tqdm
import time
from datetime import datetime, timedelta
from config import Config
from back_ground_module import CommonModule
import logging
from log_config import configure_task_logger, configure_error_task_logger
# 配置日志
# logging.basicConfig(
# level=logging.INFO,
# format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
# handlers=[
# logging.FileHandler("process.log"),
# logging.StreamHandler()
# ]
# )
# logger = logging.getLogger(__name__)
# 获取已经配置好的常规日志记录器
logger = configure_task_logger()
# 获取已经配置好的错误任务日志记录器
error_task_logger = configure_error_task_logger()
# 初始化 API 实例和 Token
api_instanceyd = YDAPI()
api_instance = API()
common_module = CommonModule()
TOKEN = api_instanceyd.generateToken()
# 配置常量
FORMID = "FORM-JD8668C1O2MV388PX5YIQGKMBEPS1EXV0UCWK0" # FPO需求提交
appType = "APP_FE5IWP670JPRC5ZA6HK0" # FPO产品运营
systemToken = "HP666C71ZLASJ0MPWC5ZOUA4AGDP17QU7TPRK92" # FPO产品运营
BASE_URL = "https://f6car.aliwork.com" # 基础URL
# 目标表单配置
TARGET_API_KEY = "675b900991ad2491c69389ca"
TARGET_ENTRY_ID = "683fa187aeaf99ebb29faa63"
class YDFpoJiandaoyun:
"""
宜搭FPO迁移到简道云
"""
def __init__(self):
self.all_dict = pd.DataFrame() # 存储流程实例数据
self.data_NGV = pd.DataFrame() # 存储NGV数据
self.all_data = [] # 存储需要派发的数据
self.success_count = 0
self.fail_count = 0
self.max_retries = 3 # API请求最大重试次数
self.retry_delay = 1 # 重试延迟(秒)
def fetch_process_data(self):
"""获取所有流程实例数据"""
try:
# 获取时间范围
today_midnight = datetime.now().replace(hour=0, minute=0, second=0, microsecond=0)
yesterday_midnight = today_midnight - timedelta(days=1)
start_time = yesterday_midnight.strftime("%Y-%m-%d") # 昨天0点
end_time = today_midnight.strftime("%Y-%m-%d") # 今天0点
logger.info(f"开始时间: {start_time}, 结束时间: {end_time}")
# 创建DataFrame
columns = ["超链接", "门店名称", "需求编号", "需求类型", "场景描述", "需求描述",
"需求解决状态", "需求评审意见", "需求提出日期", "计划解决日期", "实际解决日期"]
all_dict = pd.DataFrame(columns=columns)
# 获取总页数
form_data = self._api_request_with_retry(
api_instanceyd.read_processes,
token=TOKEN,
formUuid=FORMID,
page=1,
n=100,
appType=appType,
systemToken=systemToken
)
if not form_data:
error_task_logger.error("获取流程实例数据失败")
return pd.DataFrame()
total_count = form_data.get('totalCount', 0)
total_pages = total_count // 100 + (1 if total_count % 100 > 0 else 0)
logger.info(f"总共有 {total_count} 条记录，分为 {total_pages} 页")
# 分页获取数据
for page in tqdm(range(1, total_pages + 1)):
form_data = self._api_request_with_retry(
api_instanceyd.read_processes,
token=TOKEN,
formUuid=FORMID,
page=page,
n=100,
appType=appType,
systemToken=systemToken
)
if not form_data:
error_task_logger.error(f"获取第 {page} 页数据失败")
continue
self._process_page_data(form_data, all_dict)
logger.info(f"成功获取 {len(all_dict)} 条流程实例数据")
return all_dict
except Exception as e:
error_task_logger.error(f"获取流程实例数据时发生错误: {e}", exc_info=True)
return pd.DataFrame()
def _process_page_data(self, form_data, all_dict):
"""处理单页流程实例数据"""
for file in form_data.get("data", []):
try:
# 构建URL
url = f"{BASE_URL}/{appType}/formDetail/{FORMID}?formInstId={file['formInstanceId']}"
# 添加新行
new_row = pd.Series([
url,
file['formData'].get('selectField_kwcxm069', ''),
file['formData'].get('textField_krydg6af', ''),
file['formData'].get('selectField_kwd5rp7s', ''),
file['formData'].get('textareaField_krrhmeuc', ''),
file['formData'].get('textareaField_krrhmeud', ''),
file['formData'].get('selectField_krrhmevo', ''),
file['formData'].get('textareaField_krrhmevm', ''),
file['formData'].get('dateField_krrhmeue', ''),
file['formData'].get('dateField_krrhmex6', ''),
file['formData'].get('dateField_krrhmex9', '')
], index=all_dict.columns)
all_dict.loc[len(all_dict)] = new_row
except KeyError as e:
error_task_logger.error(f"处理记录时缺少字段: {e}")
except Exception as e:
error_task_logger.error(f"处理记录时出错: {e}")
def NGV_data(self):
"""获取NGV数据"""
try:
logger.info("开始获取NGV数据")
data_NGV = common_module.get_ngv_details(days_back=1)
logger.info(f"成功获取 {len(data_NGV)} 条NGV数据")
return data_NGV
except Exception as e:
error_task_logger.error(f"获取NGV数据时发生错误: {e}", exc_info=True)
return pd.DataFrame()
def match_and_update(self):
"""根据门店名称匹配两个DataFrame，并更新all_dict"""
try:
if self.all_dict.empty or self.data_NGV.empty:
logger.warning("all_dict 或 data_NGV 为空，无法进行匹配")
return self.all_dict
# 创建一个映射字典，键是org_name，值是(id_own_org, id_own_group)元组
mapping_dict = {}
for _, row in self.data_NGV.iterrows():
mapping_dict[row['org_name']] = (row['id_own_org'], row['id_own_group'])
# 创建新的列来存储匹配结果
self.all_dict['id_own_org'] = None
self.all_dict['id_own_group'] = None
# 匹配计数
match_count = 0
# 遍历all_dict，根据门店名称查找对应的id
for idx, row in self.all_dict.iterrows():
store_name = row['门店名称']
if store_name in mapping_dict:
org_id, group_id = mapping_dict[store_name]
self.all_dict.at[idx, 'id_own_org'] = org_id
self.all_dict.at[idx, 'id_own_group'] = group_id
match_count += 1
logger.info(f"匹配完成: 共 {len(self.all_dict)} 条记录，成功匹配 {match_count} 条")
return self.all_dict
except Exception as e:
error_task_logger.error(f"匹配数据时发生错误: {e}", exc_info=True)
return self.all_dict
def write_in(self):
"""将处理后的数据写入表单"""
if self.all_dict.empty:
logger.warning("all_dict 为空，没有数据可写入")
return
self.success_count = 0
self.fail_count = 0
for index_num, row in tqdm(self.all_dict.iterrows(), total=len(self.all_dict)):
try:
payload_dict = self._build_payload_dict(row)
self.all_data.append(payload_dict)
self.success_count += 1
except Exception as e:
self.fail_count += 1
error_task_logger.error(f"处理记录 #{index_num} 时发生错误: {e}", exc_info=True)
return self.all_data
def _build_payload_dict(self, row):
"""构建请求数据字典"""
return {
"_widget_1749000583446": {"value": row["门店名称"]},
"_widget_1749000583447": {"value": row["超链接"]},
"_widget_1749006049130": {"value": row["需求编号"]},
"_widget_1749006049131": {"value": row["需求类型"]},
"_widget_1749006049132": {"value": row["场景描述"]},
"_widget_1749006049133": {"value": row["需求描述"]},
"_widget_1749006049134": {"value": row["需求解决状态"]},
"_widget_1749006049135": {"value": row["id_own_org"]},
"_widget_1749006049136": {"value": row["id_own_group"]},
"_widget_1749019791181": {"value": row["需求评审意见"]},
"_widget_1749019791182": {"value": row["需求提出日期"]},
"_widget_1749019791183": {"value": row["计划解决日期"]},
"_widget_1749019791184": {"value": row["实际解决日期"]}
}
def _build_request_payload(self, payload_dict):
"""构建完整请求负载"""
UUid = time.strftime("%Y%m%d%H%M%S", time.localtime())
return {
"api_key": TARGET_API_KEY,
"entry_id": TARGET_ENTRY_ID,
"is_start_workflow": "true",
"data": payload_dict,
"transaction_id": UUid
}
def _api_request_with_retry(self, api_func, *args, **kwargs):
"""API请求重试机制"""
for attempt in range(self.max_retries):
try:
result = api_func(*args, **kwargs)
return result
except Exception as e:
if attempt < self.max_retries - 1:
logger.warning(f"API请求失败，正在重试 ({attempt + 1}/{self.max_retries}): {e}")
# time.sleep(self.retry_delay)
self.retry_delay *= 2 # 指数退避
else:
error_task_logger.error(f"API请求失败，已达到最大重试次数: {e}", exc_info=True)
return None
def clear_existing_data(self):
"""清除目标表单中的现有数据"""
try:
logger.info("开始清除现有数据")
# 获取现有数据ID
payload = {"api_key": TARGET_API_KEY, "entry_id": TARGET_ENTRY_ID}
get_ids = self._api_request_with_retry(
api_instance.entry_data_list,
payload
)
if not get_ids:
logger.warning("获取现有数据ID失败")
return
data_list = get_ids.get("data", [])
if not data_list:
logger.info("目标表单中没有现有数据")
return
delete_ids = [item["_id"] for item in data_list]
logger.info(f"将删除 {len(delete_ids)} 条现有记录")
# 批量删除
delete_payload = {
"api_key": TARGET_API_KEY,
"entry_id": TARGET_ENTRY_ID,
"data_ids": delete_ids
}
delete_result = self._api_request_with_retry(
api_instance.entry_data_batch_delete,
delete_payload
)
if delete_result and delete_result.get("success", False):
logger.info("成功清除现有数据")
else:
error_msg = delete_result.get('message', '未知错误') if delete_result else '无响应'
error_task_logger.error(f"清除现有数据失败: {error_msg}")
except Exception as e:
error_task_logger.error(f"清除现有数据时发生错误: {e}", exc_info=True)
def batch_create_entries(self,task_start_time):
"""批量创建条目"""
try:
if not self.all_data:
logger.warning("没有数据可创建条目")
return False
UUid = time.strftime("%Y%m%d%H%M%S", time.localtime())
# task_start_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
routine_follow_up_payload = {
"api_key": TARGET_API_KEY,
"entry_id": TARGET_ENTRY_ID,
"is_start_workflow": "true",
"data_list": self.all_data,
"transaction_id": UUid
}
res = api_instance.entry_data_batch_create(routine_follow_up_payload)
logger.info(f"创建结果：{res}")
# 发送任务状态
common_module.send_task_status(task_start_time, "宜搭FPO实例同步简道云")
return True
except Exception as e:
error_task_logger.error(f"批量创建条目时发生错误: {e}", exc_info=True)
return False
def main(self):
"""主函数，协调各个处理步骤"""
task_start_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
logger.info("=" * 50)
logger.info("开始执行时间消耗流程处理")
logger.info("=" * 50)
try:
# Step 1: 获取流程实例
logger.info("步骤1: 获取流程实例数据")
self.all_dict = self.fetch_process_data()
if self.all_dict.empty:
logger.warning("未获取到流程实例数据，终止执行")
return
# Step 2: 获取NGV数据
logger.info("步骤2: 获取NGV数据")
self.data_NGV = self.NGV_data()
if self.data_NGV.empty:
logger.warning("未获取到NGV数据，终止执行")
return
# Step 3: 匹配数据
logger.info("步骤3: 匹配流程实例与NGV数据")
self.all_dict = self.match_and_update()
# Step 4: 清除之前的数据
logger.info("步骤4: 清除目标表单中的现有数据")
self.clear_existing_data()
# Step 5: 写入表单
logger.info("步骤5: 将处理后的数据写入表单")
self.write_in()
# Step 6: 批量创建条目
logger.info("步骤6: 批量创建条目")
success = self.batch_create_entries(task_start_time)
logger.info("=" * 50)
logger.info(
f"处理完成: 共处理 {len(self.all_dict)} 条记录，成功 {self.success_count} 条，失败 {self.fail_count} 条")
logger.info(f"批量创建结果: {'成功' if success else '失败'}")
logger.info("=" * 50)
except Exception as e:
error_task_logger.error(f"执行过程中发生错误: {e}", exc_info=True)
if __name__ == '__main__':
processor = YDFpoJiandaoyun()
processor.main()
back_ground_module/新签180天重构.py
+820
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@@ -0,0 +1,820 @@
import datetime
import os
import time
import requests
from api import API
import re
from back_ground_module import CommonModule
import pandas as pd
from log_config import configure_task_logger, configure_error_task_logger
api_instance = API()
common_module = CommonModule()
logger = configure_task_logger()
error_task_logger = configure_error_task_logger()
class NewServicesRevisitTest:
"""
用于处理新签服务回访的类。
"""
def __init__(self):
# 初始化所有数据属性
self.get_feature_usage = None
self.saas_create_time = None
self.index = None
self.date_one = None
self.data_NGV_S = None
self.date_list = None
self.Smart_detection = None
self.service_remind = None
self.NGV_data_list = None
self.permissions_table = None
self.staff_id_list = None
self.json_list = []
self.policy_recognition = None
self.widget_list = None
self.private_domain = None
self.public_domain = None
self.public_domain_list = None
self.different_industries = None
self.different_industries_list = None
self.groupnotification = None
def calculate_date_one(self, start_offset=0):
"""
计算从当前日期（或指定偏移量的日期）开始，往前遍历遇到date_list中日期的次数。
参数:
- start_offset: 从当前日期起始的天数偏移量，默认为0（即今天）。负数表示过去，正数表示未来。
返回:
- date_one: 遍历到date_list中日期的次数。
"""
jdy_date = datetime.datetime.now().strftime("%Y-%m-%d")
jdy_start_time = datetime.datetime.now().strftime("%Y-%m-%d ")
# 设置起始日期
now_time = datetime.datetime.now() + datetime.timedelta(days=start_offset)
# 初始化计数器
date_one = 1
print("当前日期：", now_time.strftime("%Y-%m-%d"))
# 检查起始日期是否在date_list中
if now_time.strftime("%Y-%m-%d") in self.date_list:
date_one = 0
print("开始次数：", date_one)
else:
# 遍历日期
for i in range(1, 10):
new_date = now_time + datetime.timedelta(days=-i)
new_date_str = new_date.strftime("%Y-%m-%d")
print("遍历日期：", new_date_str)
if new_date_str in self.date_list:
date_one += 1
print("节假日期：", new_date_str)
else:
break
print("遍历次数：", date_one)
return date_one
@staticmethod
def download_url_content(url, save_path):
"""
下载指定 URL 的内容并保存到本地文件。简道云图片下载
:param url: 要下载内容的 URL
:param save_path: 保存文件的路径
"""
try:
# 发送 GET 请求以获取内容
response = requests.get(url, stream=True)
response.raise_for_status() # 如果响应状态码不是 200，抛出异常
# 确保保存目录存在
os.makedirs(os.path.dirname(save_path), exist_ok=True)
# 将内容写入文件
with open(save_path, 'wb') as file:
for chunk in response.iter_content(chunk_size=8192): # 分块写入，避免占用过多内存
if chunk: # 过滤掉空块
file.write(chunk)
print(f"文件已成功保存到 {save_path}")
except requests.exceptions.RequestException as e:
print(f"下载失败: {e}")
except Exception as e:
print(f"发生错误: {e}")
def load_all_data(self):
"""加载所有必要的数据表"""
# 省市区人员关系表
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "676512ac3e54dc3159460c0a"}
json_dict = api_instance.entry_data_list(payload)
self.json_list = json_dict.get("data")
# 获取简道云员工id
payload = {"api_key": "6694d3c4fcb69ca9a111a6c4",
"entry_id": "6769204a1902c9341340a1bc",
}
staff_id = api_instance.entry_data_list(payload)
self.staff_id_list = staff_id.get("data") # api请求格式，将数据封装在data字典里
# 获取权限表信息
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "675b96c14e839f90fef1647c"}
self.permissions_table = api_instance.entry_data_list(payload).get("data", [])
# 获取NGV数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "675bb02bd2d53c2034c665e4"}
self.NGV_data_list = api_instance.entry_data_list(payload).get("data", [])
# print("NGV获取后的类型：", type(self.NGV_data_list))
# 获取服务提醒-数据支持表单数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "676bb7bda3029720f1083e99"}
self.service_remind = api_instance.entry_data_list(payload).get("data", [])
# 获取智能检测-数据支持表单数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "676bb99649ab3ac975af6e39"}
self.Smart_detection = api_instance.entry_data_list(payload).get("data", [])
# 获取功能使用情况表
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "6763bbf657bd8fb76fcb41b2"}
self.get_feature_usage = api_instance.entry_data_list(payload).get("data", [])
# 获取保单识别表
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "6773a60d30ed87ff9f68d3c5"}
self.policy_recognition = api_instance.entry_data_list(payload).get("data")
# 提取 _widget_1735632397600 的值并存储在列表中
self.widget_list = [item['_widget_1735632397600'] for item in self.policy_recognition]
# 获取私域小程序-数据支持表单数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "67e0f0fae622896749ba5087"}
self.private_domain = api_instance.entry_data_list(payload).get("data", [])
# 提取 _widget_1742795002375 的值并存储在列表中
# self.private_domain = [item['_widget_1742795002375'] for item in self.private_domain]
# 获取公域小程序-数据支持表单数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "67e0c702c8f603b997980999"}
self.public_domain = api_instance.entry_data_list(payload).get("data", [])
# 提取 _widget_1742784257506 的值并存储在列表中
self.public_domain_list = [item['_widget_1742784257506'] for item in self.public_domain]
# 获取异业合作-数据支持表单数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "67e24fdd8dfcfa918e17c30b"}
self.different_industries = api_instance.entry_data_list(payload).get("data", [])
# 提取 _widget_1742784257506 的值并存储在列表中
self.different_industries_list = [item['_widget_1742884829007'] for item in self.different_industries]
# 获取短信-数据支持表单数据
payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "67e5107198ba1b20d5df3974"}
self.groupnotification = api_instance.entry_data_list(payload).get("data", [])
@staticmethod
def build_index(json_list):
"""构建省市区人员索引"""
index = {}
# print(json_list)
for json_item in json_list:
# json_item = json_item.get("data")
# print(json_item)
try:
key = (json_item['_widget_1734677164861'], json_item['_widget_1734677164862'],
json_item['_widget_1734677164863']) # 省市区
if '_widget_1734677164871' not in json_item: # 日常回访客服
raise KeyError("缺少 '日常回访客服' 键")
index[key] = json_item
except KeyError as e:
print(f"警告：{e}，跳过该条记录: {json_item}")
continue
return index
@staticmethod
def find_customer_service(province_name, city_name, area_name, index):
"""根据省市区查找客服"""
key = (province_name, city_name, area_name)
# print(index)
if key not in index:
return "数据缺失: 未找到对应的日常回访客服"
return index[key]
@staticmethod
def remove_parentheses(text: str) -> str:
"""使用正则表达式匹配并去除括号及其内容"""
# \s* 表示匹配零个或多个空白字符（处理括号前后可能存在的空格）
# $ 和 $ 分别表示匹配左括号和右括号
# 中间的 .*? 表示非贪婪地匹配任意数量的字符（包括没有字符的情况）
cleaned_text = re.sub(r'\s*$.*?$\s*', '', text)
# 为了确保同时处理中文括号，再进行一次替换
cleaned_text = re.sub(r'\s*（.*?）\s*', '', cleaned_text)
return cleaned_text.strip() # 去除两端多余的空白字符
@staticmethod
def get_staff_id(row_item, name):
"""辅助函数，用于获取员工ID"""
if str(row_item["_widget_1734942794144"]) == str(name): # 检查姓名是否匹配
return row_item["_widget_1734942794145"] # 返回员工ID
return None
def assign_customer_service(self, province_name, city_name, area_name, index):
"""根据省市区派发给日常回访客服"""
try:
customer_service_info = self.find_customer_service(province_name, city_name, area_name, index)
# 定义一个辅助函数，用于安全地获取多层字段中的 username
def safe_get_username(data, key):
try:
if isinstance(data, dict):
return data.get(key, {}).get('username', "")
return ""
except:
return ""
relationship_manager = safe_get_username(customer_service_info, '_widget_1734677164864')
customer_service = safe_get_username(customer_service_info, '_widget_1734677164871')
technician = safe_get_username(customer_service_info, '_widget_1734677164866')
area_manager = safe_get_username(customer_service_info, '_widget_1734677164865')
return relationship_manager, customer_service, technician, area_manager
except Exception as e:
print(f"Error finding customer service: {e}")
return "分配失败，请检查", "分配失败，请检查", "分配失败，请检查"
def prepare_data(self):
"""准备基础数据"""
# Step 1: 加载所有数据表
self.load_all_data()
# Step 2: 获取节假日列表
self.date_list = common_module.get_holiday_list()
# Step 3: 获取NGV数据
self.data_NGV_S = common_module.get_ngv_details(days_back=1).astype(str)
# Step 4: 计算日期偏移
self.date_one = self.calculate_date_one(start_offset=0)
# Step 5: 构建索引
self.index = self.build_index(self.json_list)
# Step 6: 设置时间偏移常量
self.saas_create_time_180 = 173
self.saas_create_time_90 = 83
def filter_and_process_data(self):
"""过滤和处理数据"""
# Step 1: 准备数据
self.prepare_data()
print("开始运行主流程")
for i in range(0, self.date_one):
# Step 2: 计算当前处理日期
now_time = datetime.datetime.now() + datetime.timedelta(days=-i)
today_180 = now_time + datetime.timedelta(days=-self.saas_create_time_180)
formatted_today_180 = today_180.strftime("%Y-%m-%d")
today_90 = now_time + datetime.timedelta(days=-self.saas_create_time_90)
formatted_today_90 = today_90.strftime("%Y-%m-%d")
print("SaaS开户回访日期：", formatted_today_180, formatted_today_90)
# Step 3: 数据预处理
data_NGV = self.data_NGV_S.copy()
data_NGV = data_NGV.apply(lambda series: series.apply(
lambda x: '' if pd.isna(x) or x in ['NA', 'None', ''] else x))
# Step 4: 计算最佳版本、分层和等级
edition_order = ['皇冠版', '至尊版', '尊享版', '旗舰版', '标准版', '进阶版', '基础版', '入门版']
customer_type_order = ["F", "E", "D", "C", "B", "A"]
group_grade_order = ['全国KA（FMVP）', '区域KA（MVP）', '重要客户（SVIP）', '普通客户（VIP）']
# 创建映射字典
edition_map = {edition: idx for idx, edition in enumerate(edition_order)}
customer_type_map = {ctype: idx for idx, ctype in enumerate(customer_type_order)}
group_grade_map = {grade: idx for idx, grade in enumerate(group_grade_order)}
# 添加排序列
data_NGV['edition_rank'] = data_NGV['saas_edition_fmt'].map(edition_map).fillna(0).astype(int)
data_NGV['customer_type_rank'] = data_NGV['saas_customer_type'].map(customer_type_map).fillna(0).astype(int)
data_NGV['group_grade_rank'] = data_NGV['group_grade'].map(group_grade_map).fillna(0).astype(int)
# 找到最佳值
best_edition_idx = data_NGV.groupby('id_own_group')['edition_rank'].idxmin()
best_edition_rows = data_NGV.loc[best_edition_idx]
best_edition_rows['max_saas_edition'] = best_edition_rows['saas_edition_fmt']
best_customer_type_idx = data_NGV.groupby('id_own_group')['customer_type_rank'].idxmin()
best_customer_type_rows = data_NGV.loc[best_customer_type_idx]
best_customer_type_rows['max_saas_customer_type'] = best_customer_type_rows['customer_type_rank'].apply(
lambda x: customer_type_order[x])
best_group_grade_idx = data_NGV.groupby('id_own_group')['group_grade_rank'].idxmin()
best_group_grade_rows = data_NGV.loc[best_group_grade_idx]
best_group_grade_rows['max_group_grade'] = best_group_grade_rows['group_grade']
# 合并最佳值
best_values = (
best_edition_rows[['id_own_group', 'max_saas_edition']]
.merge(best_customer_type_rows[['id_own_group', 'max_saas_customer_type']], on='id_own_group',
how='outer')
.merge(best_group_grade_rows[['id_own_group', 'max_group_grade']], on='id_own_group', how='outer')
)
data_NGV = data_NGV.merge(best_values, on='id_own_group', how='left')
# Step 5: 过滤数据
condition = (data_NGV['is_main_org'] == 1) & (data_NGV['org_status'] == '过期')
ngvv2 = data_NGV[condition]
data_NGV_V2 = data_NGV.copy()
data_NGV_V2['条件'] = (
(data_NGV_V2['org_type'] == "一般") &
(data_NGV_V2['org_status'] == '留存') &
(data_NGV_V2['area_manager'] != '殷昊') &
(data_NGV_V2['area_manager'] != '孙玉蕾') &
(data_NGV_V2['is_main_org'] != 1)
)
data_NGV_V2 = data_NGV_V2.loc[data_NGV_V2["条件"]]
data_NGV_V2['exists_in_ngvv2'] = data_NGV_V2['id_own_group'].isin(ngvv2['id_own_group'])
filtered_data = data_NGV_V2[data_NGV_V2['exists_in_ngvv2']]
# 排序
fixed_order_map = {edition: index for index, edition in enumerate(edition_order)}
filtered_data['sort_key'] = filtered_data['saas_edition_fmt'].map(fixed_order_map)
filtered_data = filtered_data.sort_values(by='sort_key').drop('sort_key', axis=1)
result = filtered_data.drop_duplicates(subset='id_own_group', keep='first')
data_NGV['条件'] = (
(data_NGV['org_type'] == "一般") &
(data_NGV['org_status'] == '留存') &
(data_NGV['area_manager'] != '殷昊') &
(data_NGV['area_manager'] != '孙玉蕾') &
((data_NGV['saas_create_time'] == formatted_today_180) |
(data_NGV['saas_create_time'] == formatted_today_90)) &
(data_NGV['is_main_org'] == "1")
)
data_NGV = data_NGV.loc[data_NGV["条件"]]
data_NGV = pd.concat([data_NGV, result], axis=0)
# Step 6: 设置跟进阶段和主要目的
def set_columns(row):
if row['saas_create_time'] == formatted_today_180:
row['跟进阶段'] = '新签后180天'
row['主要目的'] = '关怀使用情况，邀约转介绍，跟进增购商机，识别首年续约风险，及时跟进提报。'
elif row['saas_create_time'] == formatted_today_90:
row['跟进阶段'] = '新签后90天'
row['主要目的'] = '关怀使用情况，解答使用问题，强化培训，挖掘增购商机。'
else:
row['跟进阶段'] = "派发异常请联系数据组！"
row['主要目的'] = "派发异常请联系数据组！"
return row
data_NGV = data_NGV.apply(set_columns, axis=1)
print("SaaS开户回访人数：", len(data_NGV))
# Step 7: 重置索引
data_NGV = data_NGV.reset_index(drop=True)
# Step 8: 处理每个门店数据
self.process_shop_data(data_NGV, formatted_today_180, formatted_today_90)
def process_shop_data(self, data_NGV, formatted_today_180, formatted_today_90):
"""处理每个门店的数据"""
for index_num, row in data_NGV.iterrows():
try:
# Step 1: 准备基础数据
payload_dict = {}
saas_use_year = re.findall(r'第([0-9]+)年', row["saas_use_year"])[0]
# Step 2: 获取员工ID
NGV_roles = {
'relationship_manager': row['service_impl_principal'],
'area_manager': row['area_manager'],
'technician': row['technician'],
'salesmen': row['salesmen'],
}
for role, name in NGV_roles.items():
for row_item in self.staff_id_list:
staff_id = self.get_staff_id(row_item, name)
if staff_id:
NGV_roles[role] = staff_id
break
else:
NGV_roles[role] = None
# Step 3: 分配回访人员
if int(saas_use_year) < 4:
relationship_manager, area_manager, technician, salesmen = [
NGV_roles[role] for role in ['relationship_manager', 'area_manager', 'technician', 'salesmen']
]
# 如果未找到运营负责人，则根据省市区派发给日常回访客服
if not relationship_manager or not technician:
relationship_manager, _, technician, _ = self.assign_customer_service(
row['province_name'], row['city_name'], row['area_name'], self.index
)
if row["group_grade"] in ["普通客户（VIP）", "重要客户（SVIP）"]:
payload_dict["_widget_1734590278288"] = {"value": relationship_manager} # 跟进人是运营负责人
else:
payload_dict["_widget_1734590278288"] = {"value": technician} # 跟进人是技术专家
else:
salesmen = NGV_roles['salesmen']
relationship_manager, customer_service, technician, area_manager = self.assign_customer_service(
row['province_name'], row['city_name'], row['area_name'], self.index
)
if row["group_grade"] in ["普通客户（VIP）", "重要客户（SVIP）"]:
payload_dict["_widget_1734590278288"] = {"value": customer_service}
else:
payload_dict["_widget_1734590278288"] = {"value": technician}
# 其他成员字段赋值
payload_dict.update({
"_widget_1734590278289": {"value": relationship_manager}, # 运营负责人
"_widget_1734590278290": {"value": area_manager}, # 区域经理
"_widget_1734590278291": {"value": technician}, # 技术专家
"_widget_1735290738545": {"value": salesmen} # 销售负责人
})
# Step 4: 处理特殊逻辑
if payload_dict.get("_widget_1734590278288") == "02414917880947": # 如果跟进人是殷浩
payload_dict["_widget_1734590278288"] = {"value": "051612246035720178"} # 跟进人是赵柄诚
# Step 5: 获取权限信息
group_grade = re.sub(r'（[^）]*）', '', row['max_group_grade'])
if not row['saas_customer_type'] or row['saas_customer_type'] in ['NA', 'None']:
row['saas_customer_type'] = "F"
NGV_store_level_key = group_grade + row['max_saas_edition'] + row['max_saas_customer_type']
# Step 6: 处理权限表逻辑...
print("权限唯一值：", NGV_store_level_key)
Billing = None
for item in self.permissions_table:
if NGV_store_level_key == item.get("_widget_1734056507963"): # 合并（等级-类型-分层）
print("该门店开单的权限是：", item.get(item.get("_widget_1734055617039")))
Billing = item.get("_widget_1734055617039") # 开单
Service_Alerts = item.get("_widget_1734055617040") # 服务提醒
membership = item.get("_widget_1734055617041") # 会员卡
SMS = item.get("_widget_1734055617042") # 短信
Public_domain_applets = item.get("_widget_1734055617043") # 公域小程序
Private_domain_applets = item.get("_widget_1734055617044") # 私域小程序
Test_sheet = item.get("_widget_1734055617045") # 检测单
AI_poster = item.get("_widget_1734055617046") # AI海报
Business_wallets = item.get("_widget_1734055617047") # 企业钱包
Precision_marketing = item.get("_widget_1734055617049") # 精准营销
Paid_memberships = item.get("_widget_1734055617051") # 付费会员
business_WeCom = item.get("_widget_1734055617052") # 企业微信
Insurance_policy_identification = item.get("_widget_1734055617053") # 保险单识别
Insurance_bots = item.get("_widget_1734055617054") # 保险机器人
Camera_pick_up = item.get("_widget_1734055617055") # 摄像头接车
Camera_billing = item.get("_widget_1734055617056") # 摄像头开单
Transparent_workshop = item.get("_widget_1734055617057") # 透明车间
Cross_industry_cooperation = item.get("_widget_1734055617058") # 异业合作
BI_Insights = item.get("_widget_1734055617059") # BI洞察
payload_dict.update(
{
"_widget_1734073342350": {"value": Billing},
"_widget_1735004315757": {"value": Service_Alerts},
"_widget_1735004315756": {"value": membership},
"_widget_1735004315755": {"value": SMS},
"_widget_1735004315754": {"value": Public_domain_applets},
"_widget_1735004315753": {"value": Private_domain_applets},
"_widget_1735004315752": {"value": Test_sheet},
"_widget_1735004315751": {"value": AI_poster},
"_widget_1735004315750": {"value": Business_wallets},
"_widget_1735004315749": {"value": Precision_marketing},
"_widget_1735004315748": {"value": Paid_memberships},
"_widget_1735004315747": {"value": business_WeCom},
"_widget_1735004315746": {"value": Insurance_policy_identification},
"_widget_1735004315745": {"value": Insurance_bots},
"_widget_1735004315744": {"value": Camera_pick_up},
"_widget_1735004315743": {"value": Camera_billing},
"_widget_1735004315742": {"value": Transparent_workshop},
"_widget_1735004315741": {"value": Cross_industry_cooperation},
"_widget_1734073342352": {"value": BI_Insights},
}
)
feature_dict = {
"开单": "_widget_1734073342350",
"服务提醒": "_widget_1735004315757",
"会员卡": "_widget_1735004315756",
"短信": "_widget_1735004315755",
"公域小程序": "_widget_1735004315754",
"私域小程序": "_widget_1735004315753",
"检测单": "_widget_1735004315752",
"AI海报": "_widget_1735004315751",
"企业钱包": "_widget_1735004315750",
"精准营销": "_widget_1735004315749",
"付费会员": "_widget_1735004315748",
"企业微信": "_widget_1735004315747",
"保险单识别": "_widget_1735004315746",
"保险机器人": "_widget_1735004315745",
"摄像头接车": "_widget_1735004315744",
"摄像头开单": "_widget_1735004315743",
"透明车间": "_widget_1735004315742",
"异业合作": "_widget_1735004315741",
"BI洞察": "_widget_1734073342352",
}
# _widget_1735527329557 下次是否推荐
for new_item in self.get_feature_usage:
for feature_module, feature_value in feature_dict.items(): # 模块
if new_item.get("_widget_1735268263079") == feature_module and new_item.get(
"_widget_1735527329557") == "否" and new_item.get(
"_widget_1735280720550") == \
row["id_own_org"]: # 下次是否推荐 功能使用情况表
print(f"{feature_value}进行了更改")
payload_dict.update({f"{feature_value}": {"value": "×"}})
if new_item.get("_widget_1735268263079") == feature_module and new_item.get(
"_widget_1736414617462") == "否" and new_item.get(
"_widget_1735280720550") == \
row["id_own_org"]: # 下次是否跟进
print(f"{feature_value}进行了更改")
payload_dict.update({f"{feature_value}": {"value": "×"}})
fields_to_check = {
"_widget_1735004315763": Billing, # 开单
"_widget_1735106258016": Service_Alerts, # 服务提醒
"_widget_1735106258036": membership, # 会员卡
"_widget_1735106258086": SMS, # 短信
"_widget_1735106258112": Public_domain_applets, # 公域小程序
"_widget_1735106258141": Private_domain_applets, # 私域小程序
"_widget_1735107354648": Test_sheet, # 检测单
"_widget_1735107354725": AI_poster, # AI海报
"_widget_1735107354811": Business_wallets, # 企业钱包
"_widget_1735107354906": Precision_marketing, # 精准营销
"_widget_1735107354980": Paid_memberships, # 付费会员
"_widget_1735107355093": business_WeCom, # 企业微信
"_widget_1735107355143": Insurance_policy_identification, # 保险单识别
"_widget_1735107355235": Insurance_bots, # 保险机器人
"_widget_1735107355333": Camera_pick_up, # 摄像头接车
"_widget_1735107355392": Camera_billing, # 摄像头开单
"_widget_1735107355502": Transparent_workshop, # 透明车间
"_widget_1735107355618": Cross_industry_cooperation, # 异业合作
"_widget_1735107355740": BI_Insights # BI洞察
}
# 遍历每个字段，检查其值并更新payload_dict
for widget_id, field_name in fields_to_check.items():
if field_name == "√":
payload_dict.update({widget_id: {"value": "是"}})
break
if not Billing:
print(f"权限表请求失败或者权限表无对应关系,权限唯一值是：{NGV_store_level_key}")
# 根据NGV内容给出默认值
if row["active_status_fmt"] == "活跃": # 开单 是否使用
payload_dict.update({"_widget_1735004315765": {"value": "是"}})
else:
payload_dict.update({"_widget_1735004315765": {"value": "否"}})
try:
if row["saas_edition_fmt"] not in ["基础版", "入门版"]: # 会员卡 是否拥有
payload_dict.update({"_widget_1735106258036": {"value": "是"}})
else:
payload_dict.update({"_widget_1735106258036": {"value": "否"}})
except Exception as e:
print(f"会员卡识别：Error finding customer service: {e}")
try:
if row["card_bill_day_count_last_30_day"] != "0": # 会员卡 是否使用
payload_dict.update({"_widget_1735106258038": {"value": "是"}})
else:
payload_dict.update({"_widget_1735106258038": {"value": "否"}})
except Exception as e:
print(f"会员卡识别：Error finding customer service: {e}")
# print(self.service_remind.get("_widget_1735112637045"))
payload_dict["_widget_1735106258018"] = {"value": "否"}
for item in self.service_remind:
if row["id_own_group"] == item.get("_widget_1735112637043"):
if int(item.get("_widget_1735112637045")) < 180 and int(
item.get("_widget_1735112637046")) == 1: # 服务提醒 是否使用
payload_dict.update({"_widget_1735106258018": {"value": "是"}})
break
elif int(item.get("_widget_1735112637048")) > 0:
payload_dict.update({"_widget_1735106258018": {"value": "是"}})
break
keys_to_check = [
"_widget_1735113110155"
] # 智能检测 是否使用
# 初始化默认值为"否"
payload_dict["_widget_1735107354650"] = {"value": "否"}
# 检查每个键，如果有一个大于0，则更新为"是"并停止检查
for key in keys_to_check:
for item in self.Smart_detection:
if row["id_own_org"] == item.get("_widget_1735113110147"):
if int(item.get(key, 0)) > 0: # 使用get方法并提供默认值0防止键不存在的情况
payload_dict["_widget_1735107354650"]["value"] = "是"
break
# 近30天业务单量=0 则其它所有模块均不推荐
try:
for feature_module, feature_value in feature_dict.items(): # 模块
if row["bill_count_last_30_day"] == '0' and payload_dict[feature_value]["value"] == '△':
payload_dict.update({f"{feature_value}": {"value": "×"}})
except Exception as e:
print(f"不开单识别：Error finding customer service: {e}")
# 保单识别：从系统中抽取目标门店，针对门店抽取修改是否推荐
try:
if row["org_code"] in self.widget_list:
payload_dict.update({'_widget_1735004315746': {"value": "△"}})
except Exception as e:
print(f"保单识别：Error finding customer service: {e}")
# 私域小程序：根据是否开通微信小程序判断是否使用，旗舰版及以上算拥有
try:
for item in self.private_domain:
if row["id_own_group"] == item.get("_widget_1742795002375"): # 公司id
if int(item.get("_widget_1742795002379")) > 0: # 上架商品数
payload_dict.update({"_widget_1735106258143": {"value": "是"}}) # DX:是否拥有
break
else:
payload_dict.update({"_widget_1735106258143": {"value": "否"}}) # DX:是否拥有
break
except Exception as e:
print(f"私域小程序：Error finding customer service: {e}")
try:
high_version = ['皇冠版', '至尊版', '尊享版', '旗舰版']
if row["saas_edition_fmt"] in high_version:
payload_dict.update({'_widget_1735106258141': {"value": "是"}}) # SYXCX:是否拥有
else:
payload_dict.update({'_widget_1735106258141': {"value": "否"}}) # SYXCX:是否拥有
except Exception as e:
print(f"私域小程序：Error finding customer service: {e}")
# 公域小程序：根据是否开通微信小程序判断是否使用，旗舰版及以上算拥有
try:
for item in self.public_domain:
if row["id_own_org"] == item.get("_widget_1742784257506"): # 门店id
if int(item.get("_widget_1742784257509")) == 1: # 发布商品数量
payload_dict.update({"_widget_1735106258114": {"value": "是"}}) # GYXCX:是否使用
break
else:
payload_dict.update({"_widget_1735106258114": {"value": "否"}}) # GYXCX:是否使用
break
except Exception as e:
print(f"公域小程序：Error finding customer service: {e}")
try:
if row["id_own_org"] in self.public_domain_list:
payload_dict.update({'_widget_1735106258112': {"value": "是"}}) # GYXCX:是否拥有
else:
payload_dict.update({'_widget_1735106258112': {"value": "否"}}) # GYXCX:是否拥有
except Exception as e:
print(f"公域小程序：Error finding customer service: {e}")
# 异业合作：根据是否存在判断是否拥有，过滤条件 商品名称包含异业两个字
try:
if row["id_own_org"] in self.different_industries_list:
payload_dict.update({'_widget_1735107355618': {"value": "是"}}) # YYHZ:是否拥有
else:
payload_dict.update({'_widget_1735107355618': {"value": "否"}}) # YYHZ:是否拥有
except Exception as e:
print(f"异业合作：Error finding customer service: {e}")
# 短信：根据是否启动短信功能判断是否拥有,根据
try:
for item in self.groupnotification:
if row["id_own_group"] == item.get("_widget_1743065201885"): # 公司id
if int(item.get("_widget_1743065201886")) == 1: # 是否启动短信功能
payload_dict.update({"_widget_1735106258086": {"value": "是"}}) # DX:是否拥有
break
else:
payload_dict.update({"_widget_1735106258086": {"value": "否"}}) # DX:是否拥有
break
except Exception as e:
print(f"短信：Error finding customer service: {e}")
try:
for item in self.groupnotification:
if row["id_own_group"] == item.get("_widget_1743065201885"): # 公司id
if int(item.get("_widget_1743065201889")) > 0: # 累计发送成功总人数
payload_dict.update({"_widget_1735106258088": {"value": "是"}}) # DX:是否使用
break
else:
payload_dict.update({"_widget_1735106258088": {"value": "否"}}) # DX:是否使用
break
except Exception as e:
print(f"短信：Error finding customer service: {e}")
# Step 7: 创建回访记录
self.create_revisit_record(row, payload_dict)
except Exception as e:
error_task_logger.error(f"处理门店数据时出错: {e}")
continue
def create_revisit_record(self, row, payload_dict):
"""创建回访记录"""
# Step 1: 获取关联数据
NGV_data_id = None
for NGV_Data in self.NGV_data_list:
if row["org_code"] == NGV_Data.get("_widget_1734062123071"):
NGV_data_id = NGV_Data.get("_id")
try:
png_url = NGV_Data.get('_widget_1742890765211', {})[0].get('url', "")
except:
png_url = ""
# Step 2: 处理图片上传
upload_key = None
UUid = time.strftime("%Y%m%d%H%M%S", time.localtime())
if png_url:
save_dir = "sampleCloud"
os.makedirs(save_dir, exist_ok=True)
save_path = fr'{save_dir}\png\{UUid}.png'
self.download_url_content(png_url, save_path)
up_data = api_instance.get_upload_token(
{"api_key": "675b900991ad2491c69389ca",
"entry_id": "675b9c63925cd404038a6b86",
"transaction_id": UUid})
upload_url = up_data.get("upload_url")
upload_token = up_data.get("upload_token")
upload_result = api_instance.upload_file(
{"upload_url": upload_url,
"upload_token": upload_token,
"file_path": save_path})
upload_key = upload_result.get("key")
# Step 3: 设置分发时间
distribution_date = datetime.datetime.now(datetime.timezone.utc)
distribution_date = distribution_date.strftime('%Y-%m-%dT%H:%M:%S.%f')[:-3] + 'Z'
# Step 4: 完善payload
payload_dict.update({
"_widget_1734590278279": {"value": row["group_name"]}, # 公司名称
"_widget_1735112931760": {"value": row["id_own_group"]}, # 公司id
"_widget_1735112931761": {"value": row["id_own_org"]}, # 门店id
"_widget_1734590278281": {"value": row['org_name']}, # 门店名称
"_widget_1734590278292": {"value": row["跟进阶段"]}, # 跟进阶段
"_widget_1734321349021": {"value": NGV_data_id}, # 关data_get联数据
"_widget_1742548684369": {"value": row['主要目的']}, # 主要目的
"_widget_1734590278266": {"value": row['region_name']}, # 大区
"_widget_1734590278285": {"value": row['branch_name']}, # 小区
"_widget_1734590278284": {"value": row['province_name']}, # 省
"_widget_1734590278283": {"value": row['city_name']}, # 市
"_widget_1734590278282": {"value": row['area_name']}, # 区
"_widget_1734590278278": {"value": row['saas_customer_type']}, # 门店分层
"_widget_1734590278277": {"value": row['group_grade']}, # 公司等级
"_widget_1734590278276": {"value": row['limit_user_type']}, # 限制账户类型
"_widget_1734590278275": {"value": row['active_user_type']}, # 有效账户类型
"_widget_1734590278274": {"value": row['saas_version']}, # ERP操作模式
"_widget_1734590278273": {"value": row['saas_use_year']}, # 使用时长
"_widget_1734590278272": {"value": row['org_stage']}, # 门店阶段
"_widget_1734590278271": {"value": row['manage_model']}, # 经营模式
"_widget_1734590278267": {"value": row['contacts']}, # 联系人
"_widget_1734590278287": {"value": row['contact_mobile']}, # 联系手机号
"_widget_1734590278286": {"value": row['saas_edition_fmt']}, # SaaS版本
"_widget_1734590278280": {"value": row['org_code']}, # 门店编码
"_widget_1735096489244": {"value": distribution_date}, # 派发时间
"_widget_1742895342914": {"value": row['business_scope_fmt']}, # 经营范围
"_widget_1742895342915": {"value": row['station_number']}, # 工位数
"_widget_1742895342916": {"value": [upload_key]} # 门头照片
})
# Step 5: 创建记录
routine_follow_up_payload = {
"api_key": "675b900991ad2491c69389ca",
# "entry_id": "675b9c63925cd404038a6b86", # 日常回访表单
"entry_id": "6850e88ebdfde576a2e91a59", # 测试表单
"is_start_workflow": "true",
"data": payload_dict,
"transaction_id": UUid
}
res = api_instance.data_batch_create(routine_follow_up_payload)
logger.info(f"创建结果：{res}")
def main(self):
"""主入口方法"""
# Step 1: 记录任务开始时间
task_start_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
try:
# Step 2: 过滤和处理数据
self.filter_and_process_data()
# Step 3: 发送任务状态通知
common_module.send_task_status(task_start_time, "新签客户回访测试")
logger.info("任务执行成功")
except Exception as e:
error_task_logger.error(f"任务执行失败: {e}")
pass
if __name__ == '__main__':
start = NewServicesRevisitTest()
start.main()