# -*- 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 time 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() 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) 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): task_start_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S") try: self.load_all_data() logger.info(f"数据加载完成") data_NGV_j = common_module.get_ngv_details(days_back=1) data_NGV_j1 = common_module.get_ngv_details(days_back=2) timestamp = time.time() data_NGV_j.to_csv(os.path.join(output_dir, f"up_NGV_j.csv")) data_NGV_j1.to_csv(os.path.join(output_dir, f"up_NGV_j1.csv")) # 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'] filtered_df = filtered_df.copy() # 默认未删除 filtered_df['源NGV是否已删除'] = '未删除' # 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') ) logger.info(f"时间转换完成") # 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 logger.info(f"人员转换完成") # 数字保留3位小数 filtered_df['g_month_percentage'] = ( pd.to_numeric(filtered_df['g_month_percentage'], errors='coerce') .round(3) .apply(lambda x: f"{x:.3f}" if pd.notna(x) else '') ) # 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 # try: # filtered_df.to_csv(os.path.join(output_dir, f"{timestamp}NGV.csv")) # except Exception as e: # error_task_logger.error(f"NGV过滤后数据保存异常: {e}") # pass # data = {'api_key': Config.SaaS_Tasks_APP_ID, 'entry_id': Config.NGV_TASKS_ENTRY_ID, "data_list": all_data, "is_start_trigger": "true"} result = api_instance.entry_data_batch_create(data) logger.info(f"数据已推送:{result}") # result_str = str(result) # print(result_str[:500]) # 保存到Excel文件 # output_path = r'D:\Idea Project\SaaS_V1.7\back_ground_module\output\ngv明细1.xlsx' # filtered_df.to_excel(output_path, index=False) # data_NGV_j1.to_excel( r'D:\Idea Project\SaaS_V1.7\back_ground_module\output\ngv明细j1.xlsx', index=False) # data_NGV_j.to_excel( r'D:\Idea Project\SaaS_V1.7\back_ground_module\output\ngv明细j.xlsx', index=False) # new_df.to_excel(r'D:\Idea Project\SaaS_V1.7\back_ground_module\output\ngv明细ndf.xlsx', index=False) common_module.send_task_status(task_start_time, "NGV新增数据") logger.info(f"任务完成。") except Exception as e: error_task_logger.error(f"任务执行时发生异常: {e}") common_module.send_task_error(task_start_time, "NGV新增数据", str(e)) # pass @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" , 源NGV是否已删除="_widget_1754285499851") if __name__ == '__main__': start = UpdateNGVData() start.main()