使用Python统计深圳市公租房申请人省份年龄统计

使用Python，HtmlParser来统计深圳市保障房申请人的原籍省份分布，年龄分布等。从侧面可以反映鹏城人的地域分布。以下python代码增大了每一次获取的记录数，从而少提交几次请求。如果按照WEB主页设定的每一次请求最多50个记录，那就得提交数千次请求，显然费时。另外，也可以使用多线程处理，快速获得数据，解析数据，然后使用pandas，matplotlib等工具进行数据处理和绘制。查询了系统，截止2016年2月，轮候系统的保障房人数大概4万多，公租房轮候人数大概5万，以下数据仅作学习使用，统计结果如下：

毫无疑问，广东本地人申请的占多数。前十名当中，和广东接壤的省份也占了不少比例，特别是两湖，江西，剩下的由人口大省占据。深圳保障房建设速度和规模居全国首位，但是因为人数众多，所以需要排队等候。远离XX的房东，避免年年涨的房租，那就加入排队轮候大军吧。

 # -*- coding:utf-8 -*-
 import time
 import json
 import lxml.html
 from lxml import etree
 from  HTMLParser import HTMLParser #使用beautifulsoup也可以

 #http://www.crummy.com/software/BeautifulSoup/
 #http://blog.csdn.net/my2010sam/article/details/14526223

 try:
     from urllib.request import urlopen,Request
 except:
     from urllib2 import urlopen, Request

 area={"":"北京","":"天津","":"河北","":"山西","":"内蒙古","":"辽宁","":"吉林","":"黑龙江","":"上海",
       "":"江苏","":"浙江","":"安徽","":"福建","":"江西","":"山东","":"河南","":"湖北","":"湖南",
       "":"广东","":"广西","":"海南","":"重庆","":"四川","":"贵州","":"云南","":"西藏","":"陕西",
       "":"甘肃","":"青海","":"宁夏","":"新疆","":"台湾","":"香港","":"澳门","":"国外"}
 ages =[0]*11
 provinceCnt=[0]*91
 RECORD_BY_EACH_PAGE = [10,15,30,50,5000]
 currentYear=time.localtime()[0]#get year
 URL_BY_PAGESIZE='http://bzflh.szjs.gov.cn/TylhW/lhmcAction.do?pageSize=%s&method=queryYgbLhmcInfo&waittype=2'

 #http://XXX.cn?pageSize=XXX&page=XXX,waittype=2 公租房，waittype=1 安居房
 URL_BY_PAGE_PAGESIZE  ='http://bzflh.szjs.gov.cn/TylhW/lhmcAction.do?pageSize=%s&method=queryYgbLhmcInfo&waittype=%s&page=%s'

 #Social_Housing_Items=[URL_BY_PAGE_PAGESIZE_GongZuFang,URL_BY_PAGE_PAGESIZE_AnJuFang]

 def getHomePage(url,pagesize):
     try:
         request = Request(url)
         lines=urlopen(request,timeout=10).read()
         if len(lines)<20:
             return None #no data
     except Exception as e:
             print e
     else:
         if pagesize!=10 and pagesize!=15 and pagesize!=30 and pagesize!=50 and pagesize !=5000:
             pagesize = 15 #default as 15 record each page
         lines=lines.decode('utf-8')
         splitLines=lines.split('\r\n')
         for line in splitLines:
             #if "pageSize" in line:
                 #print line[:50]
             if "pagebanner" in line:
                 totalPage= line[:50].split('>')[1].split(' ')[0]
                 totalPage=totalPage.split(',')
                 if  len(totalPage)>1:
                     pages=(int(totalPage[0])*1000+int(totalPage[1]))/pagesize
         return pages

 def getRawData(url):
     try:
         request = Request(url)
         lines=urlopen(request,timeout=10).read()
         if len(lines)<20:
             return None #no data
     except Exception as e:
             print e
     else:
         return lines.decode('utf-8')

 def getIdentityInfo(code):
     """
     :param code: identity code showing province and date
     :return: province,date
     """
     provinceCode=code[:2]
     cityCode = code[2:6]
     date=code[6:10]
     return provinceCode,date

 class Dataparser(HTMLParser):
     def __init__(self):
         HTMLParser.__init__(self)
         self.tr=False
         self.td =0
         self.data =False
     def handle_starttag(self,tag,attrs):
         """
         参数tag是标签名,比如td,tr',attrs为标签所有属性(name,value)列表,这里是[('class','para')]
         :param tag:
         :param attrs:
         :return:
         """
         if tag=='tr':
             self.tr=True
         if tag =='td'and self.tr==True:
             self.data = True
             for name,value in attrs:
                 print "name and value are",name,value
     def handle_endtag(self,tag):
         if tag=='td':
             self.data = False
             #print "a end tag:",tag,self.getpos()

     def handle_data(self,data):
         if self.data and len(data)==18 and  '\r\n' not in data:
             #print data #ID card NO
             provinceCode,date=getIdentityInfo(data)
             ageRange=currentYear - int(date)
             if ageRange>=100:
                 print 'test',ageRange
             #ages[ageRange/10] +=1
             #temp=area[provinceCode].decode('utf-8')
             PC=int(provinceCode)
             provinceCnt[PC]+=1

 if __name__ =='__main__':
     #计算总共页数，每页可以自己限定
     for type in range(2):
         pages=getHomePage(URL_BY_PAGE_PAGESIZE%(RECORD_BY_EACH_PAGE[0],type+1,1),RECORD_BY_EACH_PAGE[4])
         parse=Dataparser()
         while pages>=1:
             #for page in range(pages):
             lines=getRawData(URL_BY_PAGE_PAGESIZE%(RECORD_BY_EACH_PAGE[4],type+1,pages))
             parse.feed(lines)
             #parse.close()
             pages-=1
         parse.close()
         if type==0:
             print "深圳安居房申请人全国分布情况统计:"
             for i in provinceCnt:
                 if i>0:          #只打印有数据的省份
                     pIndex=str(provinceCnt.index(i))
                     print area[pIndex],i
             provinceCnt =[0]*91
         elif type==1:
             print "深圳公租房申请人全国分布情况统计:"
             for i in provinceCnt:
                 if i>0:          #只打印有数据的省份
                     pIndex=str(provinceCnt.index(i))
                     print area[pIndex],i
             provinceCnt =[0]*91