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+# coding=utf-8
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+'''
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+Created on 2017年5月16日
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+@vsersion:python3.6
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+@author: liuyuqi
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+'''
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+# 导入开发模块
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+import requests
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+from bs4 import BeautifulSoup
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+
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+# 定义空列表，用于创建所有的爬虫链接
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+urls = []
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+# 指定爬虫所需的上海各个区域名称
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+citys1 = ['pudongxinqu', 'minhang', 'baoshan', 'xuhui', 'putuo', 'yangpu', 'changning', 'songjiang',
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+ 'jiading', 'huangpu', 'jinan', 'zhabei', 'hongkou', 'qingpu', 'fengxian', 'jinshan', 'chongming']
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+
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+citys = ['pudongxinqu']
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+
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+data = {"user": "user", "password": "pass"}
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+headers = {"Accept": "text/html,application/xhtml+xml,application/xml;",
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+ "Accept-Encoding": "gzip",
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+ "Accept-Language": "zh-CN,zh;q=0.8",
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+ "Referer": "http://www.example.com/",
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+ "User-Agent": "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/42.0.2311.90 Safari/537.36"
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+ }
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+# 基于for循环，构造完整的爬虫链接
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+for i in citys:
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+ url = 'http://sh.lianjia.com/ershoufang/%s/' % i
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+ res = requests.get(url, headers=headers)
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+ res = res.text.encode(res.encoding).decode('utf-8') # 需要转码，否则会有问题
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+ soup = BeautifulSoup(res, 'html.parser') # 使用bs4模块，对响应的链接源代码进行html解析
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+ page = soup.findAll('div', {'class': 'c-pagination'}) # 使用finalAll方法，获取指定标签和属性下的内容
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+ pages = [i.strip() for i in page[0].text.split('\n')] # 抓取出每个区域的二手房链接中所有的页数
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+ # print(pages)
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+ if len(pages) > 3:
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+ total_pages = int(pages[-3])
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+ else:
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+ total_pages = int(pages[-2])
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+
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+ for j in list(range(1, total_pages + 1)): # 拼接所有需要爬虫的链接
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+ urls.append('http://sh.lianjia.com/ershoufang/%s/d%s' % (i, j))
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+ # print(urls)
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+urlss = []
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+for i in range(0, 1):
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+ urlss.append(urls[i])
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+# print(urls)
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+# exit()
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+##############写文件###################
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+# 创建csv文件，用于后面的保存数据
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+file = open('lianjia.csv', 'w', encoding='utf-8')
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+
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+for url in urls: # 基于for循环，抓取出所有满足条件的标签和属性列表，存放在find_all中
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+ res = requests.get(url)
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+ res = res.text.encode(res.encoding).decode('utf-8')
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+ soup = BeautifulSoup(res, 'html.parser')
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+ find_all = soup.find_all(name='div', attrs={'class': 'info-panel'})
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+
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+ for i in list(range(len(find_all))): # 基于for循环，抓取出所需的各个字段信息
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+ title = find_all[i].find('a')['title'] # 每套二手房的标语
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+
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+ res2 = find_all[i]
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+ name = res2.find_all('div', {'class': 'where'})[0].find_all('span')[0].text # 每套二手房的小区名称
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+ room_type = res2.find_all('div', {'class': 'where'})[0].find_all('span')[1].text # 每套二手房的户型
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+ size = res2.find_all('div', {'class': 'where'})[0].find_all('span')[2].text[:-3] # 每套二手房的面积
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+
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+ # 采用列表解析式，删除字符串的首位空格
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+ info = [i.strip() for i in res2.find_all('div', {'class': 'con'})[0].text.split('\n')]
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+ region = info[1] # 每套二手房所属的区域
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+ loucheng = info[2][2:] # 每套二手房所在的楼层
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+ chaoxiang = info[5][2:] # 每套二手房的朝向
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+ builtdate = info[-3][2:] # 每套二手房的建筑时间
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+
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+ # 每套二手房的总价
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+ price = find_all[i].find('div', {'class': 'price'}).text.strip()[:-1]
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+ # 每套二手房的平方米售价
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+ price_union = find_all[i].find('div', {'class': 'price-pre'}).text.strip()[:-3]
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+
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+ # print(name,room_type,size,region,loucheng,chaoxiang,price,price_union,builtdate)
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+ # 将上面的各字段信息值写入并保存到csv文件中
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+ file.write(','.join((name, room_type, size, region, loucheng, chaoxiang, price, price_union, builtdate)) + '\n')
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+
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+# 关闭文件（否则数据不会写入到csv文件中）
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+file.close()
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