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house.py
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# coding=utf-8
import time
import re
import urllib2
import json
import csv
from bs4 import BeautifulSoup
from test import csv_name
try:
import cPickle as pickle
except ImportError:
import pickle
from lxml import etree
from selenium import webdriver
import selenium.webdriver.support.ui as ui
import httplib
httplib.HTTPConnection._http_vsn = 10
httplib.HTTPConnection._http_vsn_str = 'HTTP/1.0' #指定HTTP/1.0而不是HTTP/1.1
#先调用无界面浏览器PhantomJS或Firefox
driver = webdriver.Firefox()
wait = ui.WebDriverWait(driver,10)
def GetCitys(mainUrl):
try:
#**********************************************************************
# 获得所有城市的名称和对应楼盘网址
#**********************************************************************
print u'登陆链家网站...'
driver.get(mainUrl)
time.sleep(2) #避免页面还没显示，出现下面的Element is not visible错误
cityButton = driver.find_element_by_xpath("//div[@class='fl']/span")
cityButton.click() #点击登陆
print u'点击成功'
time.sleep(2)
#**********************************************************************
# diriver打开的网页，可以通过driver.find_elements_by_xpath("//div[@class='fc-main clear']//a//@href")
#来获取页面所有符合条件的网址（element类型），但是无法将网址转化成字符串类型，所以只能先读取整个网页html
#然后用lxml来解析html
#注意：diriver中的xpath要匹配多个元素的话，find_element后要加s
#**********************************************************************
html_unicode = driver.page_source #获取网页所有的内容
SaveHtml(html_unicode) #保存网页内容,可以用于测试，省的每次打开浏览器测试
html = etree.HTML(html_unicode) #lxml中etree将读取的unicode类型网页解析成html
city_urls = []
city_names = []
city_urls = html.xpath("//div[@class='fc-main clear']//a/@href") #获取所有a标签中的href值
print city_urls
for city_name in html.xpath("//div[@class='fc-main clear']//a"): #获取所有a标签内容
city_names.append(city_name.text) #获取所有a标签中文字
print str(city_names).replace('u\'','\'').decode("unicode-escape") #打印中文字符真是烦！！！
if u'北京' in city_names:
print u'北京在城市列表中！！'
except Exception,e:
print "Error: ",e
finally:
return city_names,city_urls
def SaveHtml(html):
data = pickle.dumps(html) #转化为字符串，写文件则不会遇到编码问题
with open ("lianjia.html","wb") as fw:
# 写文件用bytes而不是str，所以要转码
fw.write(data)
def ReadHtml():
with open("lianjia.html",'rb') as fr:
htmlFile = fr.read()
data = pickle.loads(htmlFile)
print u'加载文件成功'
html = etree.HTML(data)
return html
#第一次下载失败，还可以根据num_retries重试几次
def download(url, num_retries=3):
"""Download function that also retries 5XX errors"""
print 'Downloading:', url
try:
req = urllib2.Request(url)
response = urllib2.urlopen(req)
html = response.read()
#查看当前跳转后的url是否和开始url所属城市的相同，不同则有问题;
current_url = response.geturl()
if current_url.split('.')[0] != url.split('.')[0] :
print current_url
return None
except urllib2.URLError as e:
print 'Download error:', e.reason
html = None
if num_retries > 0:
# if hasattr(e, 'code') and 500 <= e.code < 600:
# # retry 5XX HTTP errors
print num_retries
html = download(url, num_retries-1)
return html
#获得楼盘页数
def GetPageNum(pageHtml,flag):
if flag == 'hot':
print flag
try:
page_data = pageHtml.xpath("//div[@class='page-box house-lst-page-box']/@page-data")
#将page_data[0]由类对象编码为字符串，并解析出其中的总页数
page_num = int(re.findall('totalPage.:(.*?),', page_data[0].encode('utf-8'))[0])
except Exception,e:
print "Error: ",e
page_data = pageHtml.xpath("//div[@class='pagination']/@data-totalpage")
page_num = int(page_data[0])
else:
print flag
try:
page_data = pageHtml.xpath("//div[@class='page_box']//a[last()-1]")[0].text
page_num = int(page_data)
except Exception,e:
print "Error: ",e
page_num = 1
return page_num
#处理网页text.判断网页中获取的text是否有 ，有的话要干掉，其不能编码为gbk;
def ProcessText(text):
code = 'gbk'
text_utf8 = text.encode('utf-8')
# print text_utf8+'uu' #可以通过打印看到是否含 
if ' ' in text_utf8 : #去除 这个恶心的东西，它不是空格，要打印出来并拷贝才能得到
tag = text_utf8.split(' ')
try:
return tag[0].decode('utf-8').encode(code)
except Exception,e:
print tag[0]
print "该字符串无法编码为GBK"
return 'None'.decode('utf-8').encode(code)
else:
try:
return text.encode(code)
except Exception,e:
print text
print "该字符串无法编码为GBK"
return 'None'.decode('utf-8').encode(code)
#获取楼盘信息
def GetHouses(url,page_num,flag,list):
code = 'gbk'
page_url = url+'pg'+str(page_num)
house_page = download(page_url)
if house_page == None :
print u'页 数'+str(page_num)+u' 无楼盘信息！！'
return
house_html = etree.HTML(house_page) #两种花样解析网页，此为lxml
house_bp = BeautifulSoup(house_page,'lxml') #两种花样解析网页，此为BeautifulSoup
if flag == 'hot':
#楼盘名称
for tag1 in house_html.xpath("//div[@class='col-1']//a[@target='_blank']/text()"):
tag11 = ProcessText(tag1)
list[0].append(tag11)
#楼盘位置和面积
for tag23 in house_bp.find_all(name='div', attrs={'class':re.compile('col-1')}):
tag2 = tag23.find(name='div', attrs={'class':re.compile('where')})
tag22 = tag2.find(name='span', attrs={'class':re.compile('region')})
tag222 = ProcessText(tag22.get_text())
list[1].append(tag222)
tag3 = tag23.find(name='div', attrs={'class':re.compile('area')})
tag33 = tag3.find(name='span')
if len(tag33) > 0 :
tag333 = re.findall('(.*\d).*', tag33.get_text().encode('utf-8'))[0]+'平'
list[2].append(tag333.decode('utf-8').encode(code))
else:
list[2].append(0)
print 0
#楼盘在售状态
for tag4 in house_html.xpath("//div[@class='col-1']/div[@class='type']/span[1]/text()"):
tag44 = ProcessText(tag4)
list[3].append(tag44)
#楼盘住宅类型
for tag5 in house_html.xpath("//div[@class='col-1']/div[@class='type']/span[2]/text()"):
tag55 = ProcessText(tag5)
list[4].append(tag55)
#楼盘均价或总价、价格待定字段
ff = True
for tag6 in house_html.xpath("//div[@class='col-2']//div[@class='average']/text()"):
#通过ff标志，除去单位‘元/平’,只保留 均价 字段
if ff :
tag66 =re.findall(r'.*(均价|总价|价格待定).*',tag6.encode('utf-8'))[0]
list[5].append(tag66)
if tag66 == '价格待定':
continue
else:
ff = False
else:
ff = True
#楼盘价格,注意，如果上面有价格待定的，则无法获得价格，所以要通过整合，让tag6和tag7对应上
for tag7 in house_html.xpath("//div[@class='col-2']//div[@class='average']/span/text()"):
tag77 = ProcessText(tag7)
list[6].append(tag77)
else:
#楼盘名称
for tag1 in house_html.xpath("//div[@class='lp_m']//a[@target='_blank']/text()"):
tag11 = ProcessText(tag1)
list[0].append(tag11)
#楼盘位置和面积
for tag23 in house_bp.find_all(name='div', attrs={'class':re.compile('lp_m')}):
tag2 = tag23.find_all(name='p', attrs={'class':re.compile('dzh')})
tag22 = ProcessText(tag2[0].get_text())
list[1].append(tag22)
if len(tag2) != 1 :
tag3 = re.findall('(.*\d).*', tag2[1].get_text().encode('utf-8'))[0]+'平'
list[2].append(tag3.decode('utf-8').encode(code))
else:
list[2].append(0)
print 0
#楼盘在售状态
for tag4 in house_html.xpath("//div[@class='lp_m']/div[@class='midbot']/a[1]/text()"):
tag44 = ProcessText(tag4)
list[3].append(tag44)
#楼盘住宅类型
for tag5 in house_html.xpath("//div[@class='lp_m']/div[@class='midbot']/a[2]/text()"):
tag55 = ProcessText(tag5)
list[4].append(tag55)
#楼盘均价或总价、价格待定字段
ff = True
for tag6 in house_html.xpath("//div[@class='lp_r']//p[@class='jj']/text()"):
#通过ff标志，除去单位‘元/平’,只保留 均价 字段
if ff :
tag66 =re.findall(r'.*(均价|总价|价格待定).*',tag6.encode('utf-8'))[0]
list[5].append(tag66)
if tag66 == '价格待定':
continue
else:
ff = False
else:
ff = True
#楼盘价格,注意，如果上面有价格待定的，则无法获得价格，所以要通过整合，让tag6和tag7对应上
for tag7 in house_html.xpath("//div[@class='lp_r']//p[@class='jj']/a/text()"):
tag77 = ProcessText(tag7)
list[6].append(tag77)
#上海s和苏州s的专属函数
def GetHouses_ss(url,page_num,list):
code = 'gbk'
page_url = url+'pg'+str(page_num)
house_page = download(page_url)
if house_page == None :
print u'页 数'+str(page_num)+u' 无楼盘信息！！'
return
house_html = etree.HTML(house_page) #两种花样解析网页，此为lxml
house_bp = BeautifulSoup(house_page,'lxml') #两种花样解析网页，此为BeautifulSoup
#楼盘名称
for tag1 in house_html.xpath("//div[@class='col-1']/div[@class='title-box']//a[@target='_blank']/text()"):
tag11 = ProcessText(tag1)
list[0].append(tag11)
#楼盘位置和面积
for tag23 in house_bp.find_all(name='div', attrs={'class':re.compile('col-1')}):
tag2 = tag23.find_all(name='div', attrs={'class':re.compile('row')})
tag22 = tag2[0].find(name='a', attrs={'class':re.compile('region')})
tag222 = re.sub('\s','',tag22.get_text().encode('utf-8'))
tag2222 = ProcessText(tag222.decode('utf8'))
list[1].append(tag2222)
tag33 = tag2[1].find(name='a', attrs={'class':re.compile('area')})
if len(tag33) > 0 :
if ' ' in tag33.get_text().encode('utf-8') : #恶心的 
tag333 = tag33.get_text().encode('utf-8').split(' ')
tag3333 = re.findall('(.+\d)', tag333[1])
if len(tag3333) > 0 :
tag3_3 = tag3333[0]+'平'
list[2].append(tag3_3.decode('utf-8').encode(code))
else: #有面积标签，但户型未知，无面积参数
list[2].append(0)
else: #无面积标签
list[2].append(0)
#楼盘在售状态
for tag4 in house_html.xpath("//div[@class='col-1']/div[@class='title-box']/span[2]/text()"):
tag44 = ProcessText(tag4)
list[3].append(tag44)
#楼盘住宅类型
for tag5 in house_html.xpath("//div[@class='col-1']/div[@class='title-box']/span[1]/text()"):
tag55 = ProcessText(tag5)
list[4].append(tag55)
#楼盘均价或总价、价格待定字段,以及价格字段
for tag67 in house_bp.find_all(name='div', attrs={'class':re.compile('col-2')}):
tag6 = tag67.find(name='div', attrs={'class':re.compile('average')})
tag7 = tag6.find(name='span')
try:
if len(tag7) > 0 : #如果求长度有问题，说明没有面积标签，则价格统一为'价格待定'
tag66 =re.findall(r'.*(均价|总价).*',tag6.get_text().encode('utf-8'))[0]
list[5].append(tag66)
tag77 = ProcessText(tag7.get_text())
list[6].append(tag77)
except Exception,e:
tag6_6 = '价格待定'
list[5].append(tag6_6)
if __name__ == '__main__':
netAddress = 'https://bj.lianjia.com/'
city_names,city_urls = GetCitys(netAddress)
driver.close()
time.sleep(2)
for i in range(0,len(city_names)):
#打开城市的楼盘网页,网址分热门城市和一般城市，两者网页呈现形式不同。东莞和珠海居然还没有新楼盘！！
#"大理"："http://you.lianjia.com/dl1"，"中山": "https://zs.lianjia.com/"
# if u'保亭' == city_names[i] or u'北京' == city_names[i] or u'成都' == city_names[i] or u'澄迈' == city_names[i] or u'苏州' == city_names[i] \
# or u'大连' == city_names[i] or u'长沙' == city_names[i] or u'重庆' == city_names[i] or u'上海' == city_names[i] \
# or u'定安' == city_names[i] or u'大理' == city_names[i] or u'佛山' == city_names[i] or u'广州' == city_names[i] \
# or u'杭州' == city_names[i] or u'惠州' == city_names[i] or u'海口' == city_names[i] or u'合肥' == city_names[i] \
# or u'济南' == city_names[i] or u'昆明' == city_names[i] or u'陵水' == city_names[i] or u'廊坊' == city_names[i] \
# or u'临高' == city_names[i] or u'乐东' == city_names[i] or u'南京' == city_names[i] or u'青岛' == city_names[i] \
# or u'琼海' == city_names[i] or u'琼中' == city_names[i] or u'儋州' == city_names[i] :
# print u"该城市已经爬取过了"
# continue
if u'上海' == city_names[i] or u'苏州' == city_names[i] :
pass
else:
print u"该城市已经爬取过了"
continue
flag = 'hot'
if u'太原' == city_names[i] :
url = city_urls[i]+'loupan/' #太原的链接比较特殊
flag = 'hot' #热门城市
# csv_name = re.findall('.*//(.*?)\.', city_urls[i])[0] #保存文件的名称
elif city_urls[i][-1] == '/' :
urls = city_urls[i].split('.')
url = urls[0]+'.fang.'+urls[1]+'.'+urls[2]+'loupan/' #热门城市
flag = 'hot'
# csv_name = re.findall('.*//(.*?)\.', city_urls[i])[0]
else:
url = city_urls[i]+'/loupan/' #一般城市
flag = 'cold'
# csv_name = city_urls[i].split('/')[-1]
the_page = download(url)
if the_page == None :
print json.dumps(city_names[i],ensure_ascii=False,encoding="UTF-8") +u' 无楼盘！！'
continue #城市无楼盘的话就跳过
pageHtml = etree.HTML(the_page)
page_num = GetPageNum(pageHtml,flag)
print page_num
print u'开始爬取城市楼盘。。'
list = [[],[],[],[],[],[],[]]
#开始获取城市的楼盘信息
while page_num >0 :
if u'上海' == city_names[i] or u'苏州' == city_names[i] :
GetHouses_ss(url,page_num,list) #上海和苏州专属爬取信息的函数
else:
GetHouses(url,page_num,flag,list)
page_num = page_num-1
print len(list[0]),len(list[1]),len(list[2]),len(list[3]),len(list[4]),len(list[5]),len(list[6])
#有些无价格的房子，价格项显示为0
for m in range(0,len(list[5])):
if list[5][m] == '价格待定':
list[6].insert(m,0)
print len(list[0]),len(list[1]),len(list[2]),len(list[3]),len(list[4]),len(list[5]),len(list[6])
csv_name = city_names[i]+'.csv' #保存文件的名称
csvfile = file(csv_name,'ab+')
writer = csv.writer(csvfile)
writer.writerow(['name','address','area','on-sales','house-type','price-type','price'])
for y in range(0,len(list[6])):
writer.writerow([list[0][y],list[1][y],list[2][y],list[3][y],list[4][y]\
,list[5][y].decode('utf-8').encode('gbk'),list[6][y]])
csvfile.close()
print u'完了'