saas1.6
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# -*- coding: utf-8 -*-
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import pandas as pd
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import datetime
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from config import Config
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from api import API
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from back_ground_module import CommonModule
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start_time = datetime.datetime.now()
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api_instance = API()
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common_module = CommonModule()
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class UpdateNGVData:
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"""NGV数据每日新增"""
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def __init__(self):
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self.staff_id_list = None
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self.field_mapping = {}
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self.fields()
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def load_all_data(self):
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# 获取简道云员工id
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payload = {"api_key": "6694d3c4fcb69ca9a111a6c4",
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"entry_id": "6769204a1902c9341340a1bc",
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}
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staff_id = api_instance.entry_data_list(payload)
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self.staff_id_list = staff_id.get("data") # api请求格式，将数据封装在data字典里
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@staticmethod
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def get_staff_id(row_item, name):
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"""辅助函数，用于获取员工ID"""
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if str(row_item["_widget_1734942794144"]) == str(name): # 检查姓名是否匹配
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return row_item["_widget_1734942794145"] # 返回员工ID
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return None
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def main(self):
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self.load_all_data()
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task_start_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
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data_NGV_j = common_module.get_ngv_details(days_back=1)
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data_NGV_j1 = common_module.get_ngv_details(days_back=2)
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# 找出在 data_NGV_j 中存在但在 data_NGV_j1 中不存在的 data_id
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unique_data_ids = data_NGV_j[~data_NGV_j['org_code'].isin(data_NGV_j1['org_code'])]
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# 创建一个新的 DataFrame 保存这些唯一的 data_id 及其对应的数据
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new_df = data_NGV_j[data_NGV_j['org_code'].isin(unique_data_ids['org_code'])]
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# 对 new_df 进行进一步的过滤，只保留 org_type 为 "一般" 的记录
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data_NGV_j = data_NGV_j[data_NGV_j['org_type'] == '一般']
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data_NGV_j1 = data_NGV_j1[data_NGV_j1['org_type'] == '一般']
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filtered_df = new_df[new_df['org_type'] == '一般']
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# 日期字段转换为日期格式
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time_columns = ['date_fmt', 'saas_create_time', 'expiry_time', 'install_create_time', "last_end_date",
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"renew_date"]
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new_filtered_df = filtered_df.copy() # 复制df，以调整时间
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for col in time_columns:
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# 1. 转换为datetime类型（带错误处理）
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# 使用.loc安全赋值
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new_filtered_df[col] = pd.to_datetime(filtered_df[col], errors='coerce', utc=False)
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# 2. 优化后的时区转换（高效向量化操作）
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filtered_df[col + '_date'] = (
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new_filtered_df[col]
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# 本地化为北京时间（东八区）
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.dt.tz_localize('Asia/Shanghai', ambiguous='infer', nonexistent='NaT')
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# 转换为UTC时区
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.dt.tz_convert('UTC')
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# 格式化为ISO8601字符串
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.dt.strftime('%Y-%m-%dT%H:%M:%SZ')
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)
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# 人员字段转换为人员字段
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staff_columns = ['area_manager', 'service_impl_principal', "service_salesmen","technician"]
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# 将员工列表转为DataFrame
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# 三重循环临时方案（确保可写入）
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for col in staff_columns:
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staff_ids = []
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for _, row in filtered_df.iterrows():
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matched = False
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for staff in self.staff_id_list:
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if str(staff['_widget_1734942794144']) == str(row[col]):
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staff_ids.append(staff['_widget_1734942794145'])
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matched = True
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break
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if not matched:
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staff_ids.append(None)
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filtered_df[col + "_staff_id"] = staff_ids
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# filtered_df.to_csv(r"D:\Idea Project\SaaS_V1.3\back_ground_module\output\NGV.csv")
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# 生成包含所有行转换后的字典列表
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# 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
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# 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
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all_data = [self.row_to_dict(row, self.field_mapping) for index, row in filtered_df.iterrows()] # 增量数据
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#
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data = {'api_key': Config.SaaS_Tasks_APP_ID, 'entry_id': Config.NGV_TASKS_ENTRY_ID, "data_list": all_data}
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result = api_instance.entry_data_batch_create(data)
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# result_str = str(result)
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# print(result_str[:500])
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# 保存到Excel文件
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# output_path = r'D:\Idea Project\F6+宜搭+其它(1)\new\文件输出\ngv明细1.xlsx'
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# filtered_df.to_excel(output_path, index=False)
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# 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)
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# 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)
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# 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)
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end_time = datetime.datetime.now()
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time_diff = end_time - start_time
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# 打印天数、秒数和微秒数
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print(f"执行时间: {time_diff.days} 天, {time_diff.seconds} 秒, {time_diff.microseconds} 微秒")
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common_module.send_task_status(task_start_time, "NGV新增数据")
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@staticmethod
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def row_to_dict(row, field_mapping):
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"""将一行数据转换为指定格式的字典"""
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result = {}
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for col_name, widget_id in field_mapping.items():
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if col_name in row:
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value = row[col_name]
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clean_value = None if pd.isna(value) else value
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result[widget_id] = {"value": clean_value}
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return result
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def fields(self):
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self.field_mapping = dict(date_id='_widget_1734062123065', date_fmt='_widget_1734062123066',
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id_own_group='_widget_1734062123067', group_name='_widget_1734062123068',
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id_own_org='_widget_1734062123069', org_name='_widget_1734062123070',
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org_code='_widget_1734062123071', group_grade='_widget_1734062123072',
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org_type='_widget_1734062123073', org_status='_widget_1734062123074',
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saas_version='_widget_1734062123075', is_wechat='_widget_1734062123076',
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is_mini_app='_widget_1734062123077', is_wx_shop='_widget_1734062123078',
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is_camera_service='_widget_1734062123079',
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is_maintenance_service='_widget_1734062123080',
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saas_create_time='_widget_1734062123081', expiry_time='_widget_1734062123082',
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saas_use_days='_widget_1734062123083', saas_use_year='_widget_1734062123084',
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is_main_org='_widget_1734062123085', license_code='_widget_1734062123086',
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license_name='_widget_1734062123087', org_crm_id='_widget_1734062123088',
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province_id='_widget_1734062123089', province_name='_widget_1734062123090',
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city_id='_widget_1734062123091', city_name='_widget_1734062123092',
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area_id='_widget_1734062123093', area_name='_widget_1734062123094',
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region_name='_widget_1734062123095', region_short_name='_widget_1734062123096',
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branch_name='_widget_1734062123097', carzone_store_id='_widget_1734062123098',
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carzone_store_name='_widget_1734062123099',
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customer_carzone_id='_widget_1734062123100', salesmen='_widget_1734062123101',
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area_manager='_widget_1734062123102', service_salesmen='_widget_1734062123103',
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impl_principal='_widget_1734062123104',
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service_impl_principal='_widget_1734062123105',
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active_user_count='_widget_1734062123106', active_user_type='_widget_1734062123107',
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limit_user_count='_widget_1734062123108', limit_user_type='_widget_1734062123109',
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is_n='_widget_1734062123110', is_g='_widget_1734062123111',
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is_v='_widget_1734062123112', is_visited='_widget_1734062123113',
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is_active='_widget_1734062123114', active_status_fmt='_widget_1734062123115',
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bill_count_last_30_day='_widget_1734062123116',
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bill_day_count_last_30_day='_widget_1734062123117',
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bill_day_count_this_month='_widget_1734062123118',
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bill_count_last_7_day='_widget_1734062123119',
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bill_day_count_last_7_day='_widget_1734062123120', pv_count='_widget_1734062123121',
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uv_count='_widget_1734062123122', bill_count_1d='_widget_1734062123123',
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bill_count_2d='_widget_1734062123124', bill_count_3d='_widget_1734062123125',
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bill_count_4d='_widget_1734062123126', bill_count_5d='_widget_1734062123127',
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bill_count_6d='_widget_1734062123128', bill_count_7d='_widget_1734062123129',
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bill_count_8d='_widget_1734062123130', bill_count_9d='_widget_1734062123131',
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bill_count_10d='_widget_1734062123132', bill_count_11d='_widget_1734062123133',
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bill_count_12d='_widget_1734062123134', bill_count_13d='_widget_1734062123135',
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bill_count_14d='_widget_1734062123136', bill_count_15d='_widget_1734062123137',
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bill_count_16d='_widget_1734062123138', bill_count_17d='_widget_1734062123139',
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bill_count_18d='_widget_1734062123140', bill_count_19d='_widget_1734062123141',
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bill_count_20d='_widget_1734062123142', bill_count_21d='_widget_1734062123143',
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bill_count_22d='_widget_1734062123144', bill_count_23d='_widget_1734062123145',
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bill_count_24d='_widget_1734062123146', bill_count_25d='_widget_1734062123147',
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bill_count_26d='_widget_1734062123148', bill_count_27d='_widget_1734062123149',
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bill_count_28d='_widget_1734062123150', bill_count_29d='_widget_1734062123151',
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bill_count_30d='_widget_1734062123152', bill_count_31d='_widget_1734062123153',
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etl_time='_widget_1734062123154',
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maintain_bill_count_last_30_day='_widget_1734062123155',
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washing_bill_count_last_30_day='_widget_1734062123156',
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maintain_bill_day_count_last_30_day='_widget_1734062123157',
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washing_bill_day_count_last_30_day='_widget_1734062123158',
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retail_bill_count_last_30_day='_widget_1734062123159',
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retail_bill_day_count_last_30_day='_widget_1734062123160',
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purchase_bill_count_last_30_day='_widget_1734062123161',
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purchase_bill_day_count_last_30_day='_widget_1734062123162',
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card_bill_count_last_30_day='_widget_1734062123163',
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card_bill_day_count_last_30_day='_widget_1734062123164',
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gd_sales_bill_count_last_30_day='_widget_1734062123165',
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gd_sales_bill_day_count_last_30_day='_widget_1734062123166',
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g_change_flag='_widget_1734062123167', saas_package='_widget_1734062123168',
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manage_model='_widget_1734062123169', contacts='_widget_1734062123170',
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contact_number='_widget_1734062123171', contact_mobile='_widget_1734062123172',
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g_month_count='_widget_1734062123173', g_month_percentage='_widget_1734062123174',
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is_install_service='_widget_1734062123175',
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install_create_time='_widget_1734062123176', last_end_date='_widget_1734062123177',
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renew_date='_widget_1734062123178', is_chain_owner='_widget_1734062123179',
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group_org_count='_widget_1734062123180',
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recent_bill_warning_days='_widget_1734062123181',
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g_change_flag_d='_widget_1734062123182', g_lost_warning_days='_widget_1734062123183',
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saas_edition_fmt='_widget_1734062123184', g_flag_1m='_widget_1734062123185',
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g_flag_2m='_widget_1734062123186', g_flag_3m='_widget_1734062123187',
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g_flag_4m='_widget_1734062123188', g_flag_5m='_widget_1734062123189',
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g_flag_6m='_widget_1734062123190', g_flag_day_count='_widget_1734062123191',
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add_org_flag='_widget_1734062123192', pt='_widget_1734062123193',
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org_size='_widget_1734062123194', qualification_type_fmt='_widget_1734062123195',
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business_scope_fmt='_widget_1734062123196', store_type_fmt='_widget_1734062123197',
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area='_widget_1734062123198', station_number='_widget_1734062123199',
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header_type_fmt='_widget_1734062123200', org_stage='_widget_1734062123201',
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g_count_this_month='_widget_1734062123202',
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saas_customer_type='_widget_1734062123203', technician='_widget_1734062123204',
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tmall_maintain_service_status_desc='_widget_1734062123205',
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date_fmt_date='_widget_1749000071375',
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area_manager_staff_id='_widget_1748496855779',
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service_impl_principal_staff_id="_widget_1748496855780",
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service_salesmen_staff_id="_widget_1748496855778",
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technician_staff_id="_widget_1751877712235",
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saas_create_time_date="_widget_1749000071377",
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expiry_time_date="_widget_1749000071382",
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install_create_time_date="_widget_1749000071384",
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last_end_date_date="_widget_1749000071389", renew_date_date="_widget_1749000071391")
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if __name__ == '__main__':
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start = UpdateNGVData()
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start.main()
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