Files
saas/back_ground_module/revisit_key_customer.py
2025-08-12 13:43:10 +08:00

548 lines
31 KiB
Python
Raw Permalink Blame History

This file contains ambiguous Unicode characters
This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.
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KAFMVP', '区域KAMVP', '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KAFMVP', '区域KAMVP'])) & (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KAFMVP', '区域KAMVP'])) & (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") == "" 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") == "" 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": ""}})
break
if row["active_status_fmt"] == "活跃": # 开单 是否使用
payload_dict.update({"_widget_1735004315765": {"value": ""}})
else:
payload_dict.update({"_widget_1735004315765": {"value": ""}})
try:
if row["card_bill_day_count_last_30_day"] != "0": # 会员卡 是否使用
payload_dict.update({"_widget_1735106258038": {"value": ""}})
else:
payload_dict.update({"_widget_1735106258038": {"value": ""}})
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": ""}
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": ""}})
break
elif int(item.get("_widget_1735112637048")) > 0:
payload_dict.update({"_widget_1735106258018": {"value": ""}})
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": ""}
# 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"] = ""
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": ""}}) # SYXCX:是否使用
else:
payload_dict.update({'_widget_1735106258143': {"value": ""}}) # 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": ""}}) # SYXCX:是否拥有
else:
payload_dict.update({'_widget_1735106258141': {"value": ""}}) # 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": ""}}) # GYXCX:是否使用
break
else :
payload_dict.update({"_widget_1735106258114": {"value": ""}}) # 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": ""}}) # GYXCX:是否拥有
else:
payload_dict.update({'_widget_1735106258112': {"value": ""}}) # 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": ""}}) # YYHZ:是否拥有
else:
payload_dict.update({'_widget_1735107355618': {"value": ""}}) # 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()