DataMining/export/exportProject.py

#encoding:GBK
import sys
import os
sys.path.append("../")

import pandas as pd
from dataSource.source import *
import json
from utils.multiThread import MultiThreadHandler
import queue
from utils.Utils import *
from dataSource.pool import ConnectorPool
import re
from tablestore import *
import traceback
from utils.hashUtil import aesCipher
from export.exportEnterprise import getDictEnterprise,getOneContact
from export.exportUtils import generateBoolShouldQuery
from queue import Queue


data_path = "../data/"

set_columns = set()
list_df_columns = []

def set_dict_item(_dict,name,v):
    _dict[name] = getLegal_str(v)
    if name not in set_columns:
        set_columns.add(name)
        list_df_columns.append(getLegal_str(name))

def getDict_docchannel():
    conn = getConnection_mysql()
    cursor = conn.cursor()
    sql  = "select channel_id,chnlname from sys_channel "
    cursor.execute(sql)
    rows = cursor.fetchall()
    _dict = dict()
    for row in rows:
        _dict[row[0]] = row[1]
    return _dict

def exportProject_by_pagetime():
    # filename = "../data/重复公告.xlsx"
    # df = pd.read_excel(filename)
    ots_client = getConnect_ots()


    set_enter = set()
    str_enter = '''
    成都四方伟业软件股份有限公司
    北京数字冰雹信息技术有限公司
    北京睿呈时代信息科技有限公司
    北京五一视界数字孪生科技股份有限公司
    易达云图(深圳)科技有限公司
    北京优锘科技有限公司
    深圳市鸿普森科技股份有限公司
    厦门图扑软件科技有限公司
    四川相数科技有限公司
    '''
    for a in re.split("\s+",str_enter):
        if a.strip()!="":
            set_enter.add(a.strip())

    columns = ["docids","doctitle","docchannel","bidway","province","city","district","info_type","page_time","crtime","project_code","tenderee","project_name","agency","sub_docs_json","tenderee_contact","tenderee_phone","doctextcon","product","moneysource","win_bid_price","win_tenderer","bidding_budget"]
    columns = ["page_time","province","city","win_tenderer"]
    dict_channel = getDict_docchannel()
    def getData(df_data,rows,set_line):
        list_data = getRow_ots(rows)
        for row in list_data:
            item = {}
            _dict = row
            set_dict_item(item,"docids",_dict.get("docids",""))
            set_dict_item(item,"项目名称",_dict.get("project_name",""))
            set_dict_item(item,"项目编号",_dict.get("project_code",""))
            # set_dict_item(item,"公告标题",_dict.get("doctitle",""))
            # set_dict_item(item,"公告类别",dict_channel.get(_dict.get("docchannel",""),""))
            set_dict_item(item,"省份",_dict.get("province",""))
            # item["区域"] = "%s-%s-%s"%(_dict.get("province",""),_dict.get("city",""),_dict.get("district",""))
            set_dict_item(item,"城市",_dict.get("city",""))
            set_dict_item(item,"发布时间",_dict.get("page_time",""))

            set_dict_item(item,"公告标题_refine",re.sub(r'工程|服务|询价|比价|谈判|竞争性|磋商|结果|中标|招标|采购|的|公示|公开|成交|公告|评标|候选人|交易|通知|废标|流标|终止|中止|一笔|预告|单一来源|询价|竞价|合同', '',  _dict.get("doctitle","")))


            set_dict_item(item,"招标单位",_dict.get("tenderee",""))
            set_dict_item(item,"招标联系人",_dict.get("tenderee_contact",""))
            set_dict_item(item,"招标联系人电话",_dict.get("tenderee_phone",""))
            set_dict_item(item,"代理单位",_dict.get("agency",""))
            set_dict_item(item,"代理联系人",_dict.get("agency_contact",""))
            set_dict_item(item,"代理联系人电话",_dict.get("agency_phone",""))
            # set_dict_item(item,"比地招标公告地址","http://www.bidizhaobiao.com/excel_detail.do?code=%s"%(str(aesCipher.encrypt('{"docid":%d}'%_dict.get("docid")))))

            set_dict_item(item,"招标金额",_dict.get("bidding_budget",""))
            set_dict_item(item,"中标金额",_dict.get("win_bid_price",""))
            set_dict_item(item,"中标单位",_dict.get("win_tenderer",""))

            sub_docs_json = _dict.get("sub_docs_json")
            if sub_docs_json is not None:
                for _doc in json.loads(sub_docs_json):
                    if "win_tenderer" in _doc:
                        set_dict_item(item,"中标单位",_doc["win_tenderer"])
                    if "win_tenderee_manager" in _doc:
                        set_dict_item(item,"中标单位联系人",_doc["win_tenderee_manager"])
                    if "win_tenderee_phone" in _doc:
                        set_dict_item(item,"中标单位联系电话",_doc["win_tenderee_phone"])
                    if "win_bid_price" in _doc and float(0 if _doc["win_bid_price"]=="" else _doc["win_bid_price"])>0:
                        set_dict_item(item,"中标金额",_doc["win_bid_price"])
                    if "bidding_budget" in _doc and float(0 if _doc["bidding_budget"]=="" else _doc["bidding_budget"])>0:
                        set_dict_item(item,"招标金额",_doc["bidding_budget"])


            if "招标金额" not in item:
                set_dict_item(item,"招标金额","")
            if "中标金额" not in item:
                set_dict_item(item,"中标金额","")
            if "中标单位" not in item:
                set_dict_item(item,"中标单位","")

            if "中标单位联系人" not in item:
                set_dict_item(item,"中标单位联系人","")
            if "中标单位联系电话" not in item:
                set_dict_item(item,"中标单位联系电话","")

            # if item["中标单位"] not in set_enter:
            #     continue

            _line = "%s-%s-%s-%s-%s-%s"%(item["省份"],item["城市"],item["项目编号"],item["招标单位"],item["招标联系人"],str(item["招标金额"]))
            # if _line in set_line:
            #     continue
            # if item["招标金额"]=="":
            #     continue

            # set_line.add(_line)
            for k,v in item.items():
                if k not in df_data:
                    df_data[k] = []
                df_data[k].append(v)

    # list_province = ["江西","湖南","四川","安徽"]
    list_province = ["全国"]
    for _province in list_province:
        df_data = {}

        str_p = '''
        家具

            '''
        # str_p = '''
        # 教育信息化 教学设备 智慧校园 互联网教育
        # '''
        list_prov = re.split("\s|、",str_p)
        list_mu = []
        for _p in list_prov:
            if _p.strip()=="":
                continue
            print(_p)
            list_mu.append(MatchPhraseQuery('doctextcon', '%s'%_p.strip()))

        s_tenderee = '教育局、中学、小学'
        list_should_ten = []
        for _p in re.split("、",s_tenderee):
            if _p.split()=="":
                continue
            list_should_ten.append(WildcardQuery("tenderee","*%s*"%_p.strip()))
            # list_should_ten.append(MatchPhraseQuery('doctextcon', '%s'%_p.strip()))

        list_should_chan = []
        list_should_chan.append(TermQuery("docchannel",101))
        # list_should_chan.append(TermQuery("docchannel",101))
        # list_should_chan.append(TermQuery("docchannel",102))

        should_q1 = BoolQuery(should_queries=list_mu)
        should_q2 = BoolQuery(should_queries=list_should_ten)
        should_q3 = BoolQuery(should_queries=list_should_chan)
        bool_query = BoolQuery(must_queries=[
            generateBoolShouldQuery(["doctextcon"],["家具"],MatchPhraseQuery),
            generateBoolShouldQuery(["province"],["广东","安徽","江苏","浙江","四川","北京"],TermQuery),
            WildcardQuery("win_tenderer","*"),
            ])


        table_name = "project2"

        rows, next_token, total_count, is_all_succeed = ots_client.search(table_name, "%s_index"%table_name,
                                                                          SearchQuery(bool_query ,sort=Sort(sorters=[FieldSort("page_time",SortOrder.ASC)]), limit=100, get_total_count=True),
                                                                          ColumnsToGet(columns,return_type=ColumnReturnType.SPECIFIED))

        print(total_count)
        set_line = set()
        _count = len(rows)
        getData(df_data,rows,set_line)
        while next_token:
            print("%d/%d"%(_count,total_count))
            rows, next_token, total_count, is_all_succeed = ots_client.search(table_name, "%s_index"%table_name,
                                                                              SearchQuery(bool_query ,next_token=next_token, limit=100, get_total_count=True),
                                                                              ColumnsToGet(columns,return_type=ColumnReturnType.SPECIFIED))
            getData(df_data,rows,set_line)
            _count += len(rows)
            # if len(df_data[list(df_data.keys())[0]])>=300:
            #     break

        set_enterprise = set()
        for _tenderee,_agency,_win_tenderer in zip(df_data["招标单位"],df_data["代理单位"],df_data["中标单位"]):
            set_enterprise.add(_tenderee)
            set_enterprise.add(_agency)
            set_enterprise.add(_win_tenderer)
        if "" in set_enterprise:
            set_enterprise.remove("")
        if None in set_enterprise:
            set_enterprise.remove(None)
        # dict_enterprise = getDictEnterprise(list(set_enterprise))
        # if len(set_enterprise)>0:
        #     for _i in range(len(df_data["招标单位"])):
        #         _enterprise_name = df_data["招标单位"][_i]
        #         if df_data["招标联系人电话"][_i]=="":
        #             contacts = dict_enterprise.get(_enterprise_name,{}).get("contacts")
        #             if contacts is not None:
        #                 _person,_phone = getOneContact(contacts)
        #                 df_data["招标联系人"][_i] = _person
        #                 df_data["招标联系人电话"][_i] = _phone
        #
        #         _enterprise_name = df_data["代理单位"][_i]
        #         if df_data["代理联系人电话"][_i]=="":
        #             contacts = dict_enterprise.get(_enterprise_name,{}).get("contacts")
        #             if contacts is not None:
        #                 _person,_phone = getOneContact(contacts)
        #                 df_data["代理联系人"][_i] = _person
        #                 df_data["代理联系人电话"][_i] = _phone
        #
        #         _enterprise_name = df_data["中标单位"][_i]
        #         if df_data["中标单位联系电话"][_i]=="":
        #             contacts = dict_enterprise.get(_enterprise_name,{}).get("contacts")
        #             if contacts is not None:
        #                 _person,_phone = getOneContact(contacts)
        #                 df_data["中标单位联系人"][_i] = _person
        #                 df_data["中标单位联系电话"][_i] = _phone

        # print(df_data)
        df1 = pd.DataFrame(df_data)
        df1.to_excel("../data/%s_数据导出.xlsx"%(getCurrent_date('%Y-%m-%d_%H%M%S')),columns=list_df_columns)

def exportProjectWithOneDocid():
    ots_client = getConnect_ots()

    list_data = []
    bool_query = BoolQuery(must_queries=[TermQuery("page_time","2021-05-28")])
    columns = ["docids","project_name"]

    rows,next_token,total_count,is_all_succeed = ots_client.search("project2","project2_index",
                                                                   SearchQuery(bool_query,sort=Sort(sorters=[FieldSort("page_time",SortOrder.ASC)]),get_total_count=True,limit=100),
                                                                   columns_to_get=ColumnsToGet(columns,ColumnReturnType.SPECIFIED))
    list_dict = getRow_ots(rows)
    for _dict in list_dict:
        if len(_dict["docids"].split(","))==1:
            list_data.append(_dict)
    _count = len(list_dict)
    while True:
        if not next_token:
            break
        rows,next_token,total_count,is_all_succeed = ots_client.search("project2","project2_index",
                                                                       SearchQuery(bool_query,next_token=next_token,limit=100,get_total_count=True),
                                                                       columns_to_get=ColumnsToGet(columns,ColumnReturnType.SPECIFIED))
        list_dict = getRow_ots(rows)
        _count += len(list_dict)
        print("%d/%d"%(_count,total_count))
        for _dict in list_dict:
            if len(_dict["docids"].split(","))==1:
                list_data.append(_dict)
    _index = 0

    task_queue = queue.Queue()
    for _dict in list_data:
        task_queue.put(_dict)

    def _handle(_dict,result_queue):
        docid = _dict["docids"]
        project_name = _dict["project_name"]
        _dict["candidate"] = []
        _dict["total_count"] = 0
        if len(project_name)>0:
            doc_query = BoolQuery(must_queries=[MatchPhraseQuery("doctextcon",project_name)
                                                ,RangeQuery("status",201,300,True,True)],
                                  must_not_queries=[TermQuery("docid",docid)])
            rows,next_token,total_count,is_all_succeed = ots_client.search("document","document_index",
                                                                           SearchQuery(doc_query,sort=Sort(sorters=[FieldSort("page_time",SortOrder.DESC)]),limit=10,get_total_count=True),
                                                                           columns_to_get=ColumnsToGet(["doctitle"],ColumnReturnType.SPECIFIED))
            l_d = getRow_ots(rows)
            for _d in l_d:
                _dict["candidate"].append(_d["docid"])
        _dict["total_count"] = total_count

    mt = MultiThreadHandler(task_queue,_handle,None,30)
    mt.run()

    df_data = {}
    for _d in list_data:
        for k,v in _d.items():
            if k not in df_data:
                df_data[k] = []
            df_data[k].append(v)
    df = pd.DataFrame(df_data)
    df.to_excel("../data/%s_未合并.xlsx"%(getCurrent_date("%Y-%m-%d %H%M%S")))

def getPayStaffName():
    conn = getConnection_mysql()
    cursor = conn.cursor()
    sql = " select company,userid,phone,contactname,aftermarket from bxkc.b2c_mall_staff_basic_info where MEMBERLEVELID is not null and MEMBERLEVELID <> 81"
    cursor.execute(sql)
    rows = cursor.fetchall()
    dict_staff = {}
    for row in rows:
        company,userid,phone,contactname,aftermarket = row
        if company is not None:
            dict_staff[company] = {"userid":userid,"phone":phone,"contactname":contactname,"aftermarket":aftermarket}
    return dict_staff

def exportCompanyByCycleProduct():
    filename = "../data/周期项目识别.csv"
    df = pd.read_csv(filename,encoding='gbk')
    task_queue = queue.Queue()
    result_queue = queue.Queue()
    pool_conn = ConnectorPool(init_num=10,max_num=30,method_init=getConnection_mysql)
    _count = 0
    for tenderee,product,last_time,avg_period,min_period,max_period,json_docid in zip(df["tenderee"],df["product"],df["last_time"],df["avg_period"],df["min_period"],df["max_period"],df["json_docid"]):
        _dict = {"tenderee":tenderee,"product":product,"last_time":last_time,"avg_period":avg_period,"min_period":min_period,
                 "max_period":max_period,"json_docid":json_docid}
        task_queue.put(_dict)
        _count += 1

    sstr_staff = getPayStaffName()
    ots_client = getConnect_ots()

    def _comsumer(_dict,result_queue,ots_client,sstr_staff,pool_conn):
        new_dict = {"招标人":_dict["tenderee"],"产品":_dict["product"],"上次招标":_dict["last_time"],
                    "预计招标范围":"%s-%s"%(timeAdd(_dict["last_time"],_dict["min_period"]),timeAdd(_dict["last_time"],_dict["max_period"])),
                    "周期":_dict["avg_period"],"历史招标":_dict["json_docid"]}
        aint_docid = json.loads(_dict["json_docid"])
        aobj_should_q_docid = []

        consumed, return_row, next_token = ots_client.get_row("enterprise",[("name",_dict["tenderee"])], ["contacts"], None, 1)
        dict_tmp = getRow_ots_primary(return_row)
        contacts = dict_tmp.get("contacts")
        phone_person,phone_no =  getOneContact(contacts)
        new_dict["招标人联系人"] = phone_person
        new_dict["招标人联系电话"] = phone_no

        for int_docid in aint_docid:
            aobj_should_q_docid.append(TermQuery("docids",int_docid))
        bool_query = BoolQuery(should_queries=aobj_should_q_docid)
        columns = ['win_tenderer','second_tenderer','third_tenderer']
        rows,next_token,total_count,is_all_succeed = ots_client.search("project2","project2_index",
                                                                       SearchQuery(bool_query,limit=100,get_total_count=True),
                                                                       ColumnsToGet(columns,ColumnReturnType.SPECIFIED))
        adict_rows = getRow_ots(rows)
        for dict_row in adict_rows:
            for _k,_company in dict_row.items():
                if _k in columns and _company is not None and _company!="":
                    _succeed = True
                    new_dict1 = {}
                    for k,v in new_dict.items():
                        new_dict1[k] = v
                    new_dict1["潜在客户"] = _company
                    consumed, return_row, next_token = ots_client.get_row("enterprise",[("name",_company)], ["contacts"], None, 1)
                    dict_tmp = getRow_ots_primary(return_row)
                    contacts = dict_tmp.get("contacts")
                    phone_person,phone_no =  getOneContact(contacts)
                    new_dict1["潜在客户联系人"] = phone_person
                    new_dict1["潜在客户联系电话"] = phone_no

                    if _company in sstr_staff:
                        company_info = sstr_staff[_company]
                        new_dict1["付费客户"] = "是"
                        conn = pool_conn.getConnector()
                        try:
                            cursor = conn.cursor()
                            sql = " select name from bxkc.b2c_mall_staff_basic_info where userid='%s'"%(company_info.get("aftermarket",""))
                            cursor.execute(sql)
                            rows = cursor.fetchall()
                            if len(rows)>0:
                                new_dict1["归属客服"] = rows[0][0]
                            else:
                                new_dict1["归属客服"] = ""
                            new_dict1["付费客户联系人"] = company_info.get("contactname","")
                            new_dict1["付费客户电话"] = company_info.get("phone","")
                            sql = " select date_FORMAT(etiem,\'%Y-%m-%d\') from bxkc.bxkc_member_term where userid='"+company_info.get("userid","")+"' and memberlevelid<>81 order by etiem desc limit 1"
                            cursor.execute(sql)
                            rows = cursor.fetchall()
                            if len(rows)>0:
                                etime = rows[0][0]
                                new_dict1["付费客户到期日"] = etime
                                if time.mktime(time.strptime(etime,"%Y-%m-%d"))>time.mktime(time.localtime()):
                                    new_dict1["付费客户到期"] = "否"
                                else:
                                    new_dict1["付费客户到期"] = "是"
                            else:
                                new_dict1["付费客户到期日"] = ""
                                new_dict1["付费客户到期"] = ""

                        except Exception as e:
                            traceback.print_exc()
                            _succeed = False
                        finally:
                            pool_conn.putConnector(conn)

                    else:
                        new_dict1["付费客户"] = "否"
                        new_dict1["归属客服"] = ""
                        new_dict1["付费客户联系人"] = ""
                        new_dict1["付费客户电话"] = ""
                        new_dict1["付费客户到期日"] = ""
                        new_dict1["付费客户到期"] = ""
                    if _succeed:
                        result_queue.put(new_dict1)

    mt = MultiThreadHandler(task_queue,_comsumer,result_queue,ots_client=ots_client,sstr_staff=sstr_staff,pool_conn=pool_conn,thread_count=30)
    mt.run()

    df_data = {}
    set_staff = set()
    while True:
        try:
            _dict = result_queue.get(timeout=1)
            tenderee = _dict.get("招标人","")
            product = _dict.get("产品","")
            staff = _dict.get("潜在客户","")
            _s = "%s-%s-%s"%(tenderee,product,staff)
            if _s in set_staff:
                continue
            set_staff.add(_s)
            for k,v in _dict.items():
                if k not in df_data:
                    df_data[k] = []
                df_data[k].append(v)
        except Exception as e:
            break


    df1 = pd.DataFrame(df_data)
    df1.to_excel("../data/%s_周期项目.xlsx"%(getCurrent_date("%Y-%m-%d_%H%M%S")))


def appendCellphones():

    file = "../data/"

from export.exportUtils import *
import jieba

def export_industry_keywords_by_enterprise(list_enterprise):

    task_queue = Queue()
    result_queue = Queue()

    list_query = []
    for _enterprise in list_enterprise:
        _query = BoolQuery(must_queries=[
            TermQuery("win_tenderer",_enterprise),
            RangeQuery("status",201,301)
        ])
        list_query.append({"query":_query,"limit":1000})

    list_data = getDocument(list_query,columns=["docid","doctitles","project_name","product","win_tenderer"],
                            table_name="project2",
                            table_index="project2_index")
    dict_keywords = {}
    dict_keywords_product = {}
    dict_keywords_product_count = {}
    for _data in list_data:
        doctitles = _data.get("doctitles","")
        project_name = _data.get("project_name","")
        product = _data.get("product","")
        for _keyword in doctitles.split(","):
            for _word in jieba.cut(_keyword):
                if _word in dict_keywords:
                    dict_keywords[_word] += 1
                else:
                    dict_keywords[_word] = 1
        for _keyword in project_name.split(","):
            for _word in jieba.cut(_keyword):
                if _word in dict_keywords:
                    dict_keywords[_word] += 1
                else:
                    dict_keywords[_word] = 1
        for _keyword in product.split(","):
            if _keyword in dict_keywords_product_count:
                dict_keywords_product_count[_keyword] += 1
            else:
                dict_keywords_product_count[_keyword] = 1
            for _word in jieba.cut(_keyword):
                if _word in dict_keywords:
                    dict_keywords[_word] += 1
                else:
                    dict_keywords[_word] = 1

                if _word in dict_keywords_product:
                    dict_keywords_product[_word] += 1
                else:
                    dict_keywords_product[_word] = 1

    list_keywords = []
    for _keyword,count in dict_keywords.items():
        list_keywords.append([_keyword,count])
    list_keywords.sort(key=lambda x:x[1],reverse=True)
    list_keywords.insert(0,["关键词","数量"])
    list_keywords = list_keywords[:10000]

    list_keywords_product = []
    for _keyword,count in dict_keywords_product.items():
        list_keywords_product.append([_keyword,count])
    list_keywords_product.sort(key=lambda x:x[1],reverse=True)
    list_keywords_product.insert(0,["关键词","数量"])
    list_keywords_product = list_keywords_product[:10000]

    list_keywords_product_count = []
    for _keyword,count in dict_keywords_product_count.items():
        list_keywords_product_count.append([_keyword,count])
    list_keywords_product_count.sort(key=lambda x:x[1],reverse=True)
    list_keywords_product_count.insert(0,["关键词","数量"])
    list_keywords_product_count = list_keywords_product_count[:10000]

    filename = "../data/%s_行业关键词.xlsx"%(getCurrent_date("%Y-%m-%d_%H%M%S"))
    with pd.ExcelWriter(filename) as writer:
        df_1 = pd.DataFrame(list_data)
        df_1.to_excel(writer,sheet_name="项目数据")
        df_data = pd.DataFrame(list_keywords)
        df_data.to_excel(writer,sheet_name="标题项目名称产品词频统计")
        df_data = pd.DataFrame(list_keywords_product)
        df_data.to_excel(writer,sheet_name="产品词频统计")
        df_data = pd.DataFrame(list_keywords_product_count)
        df_data.to_excel(writer,sheet_name="产品项目词频统计")


def turn_structure():
    filename = r'G:\新建文件夹\WeChat Files\wxid_kluerlj8cn3b21\FileStorage\File\2025-06\食堂食材行业关键词.xlsx'
    df = pd.read_excel(filename)
    list_product_exclude = df["产品排除词"]
    list_title_exclude = df["标题排除词"]
    list_keywords = df["标题+正文关键词"]
    list_title_exclude = [a for a in list_title_exclude if isinstance(a,str)]
    list_keywords = [a for a in list_keywords if isinstance(a,str)]
    list_product_exclude = [a for a in list_product_exclude if isinstance(a,str)]
    list_data = [["行业","全文关键词","全文排除词","标题排除词","产品排除词"]]
    list_data.append(["食堂食材","、".join(list_keywords),"","、".join(list_title_exclude),"、".join(list_product_exclude)])
    df1 = pd.DataFrame(list_data)
    df1.to_excel("../data/%s_行业关键词.xlsx"%(getCurrent_date("%Y-%m-%d_%H%M%S")),sheet_name="行业关键词")


if __name__=="__main__":
    # exportProject_by_pagetime()
    # exportProjectWithOneDocid()
    # exportCompanyByCycleProduct()
    turn_structure()
#     list_enterprise = splitIntoList('''
#     明喆集团股份有限公司
# 招商积余物业管理有限公司
# 广州粤华物业有限公司
# 广州广电城市服务集团股份有限公司
# 绿城物业服务集团有限公司
# 龙城城市运营服务集团有限公司
# 深业物业运营集团股份有限公司
# 广东宏德科技物业有限公司
# 保利物业服务股份有限公司
# 新大正物业集团股份有限公司
# 山东明德物业管理集团有限公司
# 深圳市金地物业管理有限公司
# 上海复欣物业管理发展有限公司
# 招商局物业管理有限公司
# 东吴服务产业集团（江苏）有限公司
# 碧桂园生活服务集团股份有限公司
# 天津市金玉物业管理有限公司
# 润加物业服务（深圳）有限公司
# 山东宏泰物业发展有限公司
# 爱玛客服务产业（中国）有限公司
# 中海物业管理有限公司
# 浙江亚太酒店物业服务有限公司
# 深圳万物商企物业服务有限公司
# 天津天孚物业管理有限公司
# 上海益中亘泰（集团）股份有限公司
# 上海申勤物业管理服务有限公司
# 广东公诚设备资产服务有限公司
# 上海东湖物业管理有限公司
# 天津市赛驰物业服务有限公司
# 安徽省长城物业管理有限公司
# 深圳市万科物业服务有限公司
# 上海生乐物业管理有限公司
# 金科智慧服务集团股份有限公司
# 山东润华物业管理有限公司
# 国药诺达物业服务有限公司
# 深业置地（深圳）物业管理有限公司
# 广东华信服务集团有限公司
# 天津玉龙源物业管理服务股份有限公司
# 广州珠江城市管理服务集团股份有限公司
# 中航物业管理有限公司
# 深圳市广美隆物业清洁服务有限公司
# 浙江浙大新宇物业集团有限公司
# 金融街物业股份有限公司
# 天津峥嵘物业管理有限公司
# 新疆德泰保安服务有限公司
# 北京住总北宇物业服务有限责任公司
# 广东泰科物业管理有限公司
# 德州市陵城区人才发展集团有限公司
# 乌鲁木齐阳光管道物业服务有限公司
# 深业物业集团有限公司
#     ''',_splitkeys="\n|\s")
#     export_industry_keywords_by_enterprise(list_enterprise)