利用python爬取贝壳网租房信息
最近准备换房子，在网站上寻找各种房源信息，看得眼花缭乱，于是想着能否将基本信息汇总起来便于查找，便用python将基本信息爬下来放到excel，这样一来就容易搜索了。
网站建设公司,为您提供网站建设,网站制作,网页设计及定制网站建设服务,专注于企业网站制作,高端网页制作,对成都户外休闲椅等多个行业拥有丰富的网站建设经验的网站建设公司。专业网站设计,网站优化推广哪家好,专业成都网站营销优化,H5建站,响应式网站。
1. 利用lxml中的xpath提取信息
xpath是一门在 xml文档中查找信息的语言，xpath可用来在 xml 文档中对元素和属性进行遍历。对比正则表达式 re两者可以完成同样的工作，实现的功能也差不多，但xpath明显比re具有优势。具有如下优点：(1)可在xml中查找信息 ；(2)支持html的查找；(3)通过元素和属性进行导航
2. 利用xlsxwriter模块将信息保存至excel
xlsxwriter是操作excel的库，可以帮助我们高效快速的，大批量的，自动化的操作excel。它可以写数据，画图，完成大部分常用的excel操作。缺点是xlsxwriter 只能创建新文件，不可以修改原有文件，如果创建新文件时与原有文件同名，则会覆盖原有文件。
3. 爬取思路
观察发现贝壳网租房信息总共是100页，我们可以分每页获取到html代码，然后提取需要的信息保存至字典，将所有页面的信息汇总，最后将字典数据写入excel。
4. 爬虫源代码
# @Author: Rainbowhhy
# @Date : 19-6-25 下午6:35
import requests
import time
from lxml import etree
import xlsxwriter
def get_html(page):
"""获取网站html代码"""
url = "https://bj.zu.ke.com/zufang/pg{}/#contentList".format(page)
headers = {
'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.77 Safari/537.36'
}
response = requests.get(url, headers=headers).text
return response
def parse_html(htmlcode, data):
"""解析html代码"""
content = etree.HTML(htmlcode)
results = content.xpath('///div[@class="content__article"]/div[1]/div')
for result in results[:]:
community = result.xpath('./div[1]/p[@class="content__list--item--title twoline"]/a/text()')[0].replace('\n',
'').strip().split()[
0]
address = "-".join(result.xpath('./div/p[@class="content__list--item--des"]/a/text()'))
landlord = result.xpath('./div/p[@class="content__list--item--brand oneline"]/text()')[0].replace('\n',
'').strip() if len(
result.xpath('./div/p[@class="content__list--item--brand oneline"]/text()')) > 0 else ""
postime = result.xpath('./div/p[@class="content__list--item--time oneline"]/text()')[0]
introduction = ",".join(result.xpath('./div/p[@class="content__list--item--bottom oneline"]/i/text()'))
price = result.xpath('./div/span/em/text()')[0]
description = "".join(result.xpath('./div/p[2]/text()')).replace('\n', '').replace('-', '').strip().split()
area = description[0]
count = len(description)
if count == 6:
orientation = description[1] + description[2] + description[3] + description[4]
elif count == 5:
orientation = description[1] + description[2] + description[3]
elif count == 4:
orientation = description[1] + description[2]
elif count == 3:
orientation = description[1]
else:
orientation = ""
pattern = description[-1]
floor = "".join(result.xpath('./div/p[2]/span/text()')[1].replace('\n', '').strip().split()).strip() if len(
result.xpath('./div/p[2]/span/text()')) > 1 else ""
date_time = time.strftime("%Y-%m-%d", time.localtime())
"""数据存入字典"""
data_dict = {
"community": community,
"address": address,
"landlord": landlord,
"postime": postime,
"introduction": introduction,
"price": '￥' + price,
"area": area,
"orientation": orientation,
"pattern": pattern,
"floor": floor,
"date_time": date_time
}
data.append(data_dict)
def excel_storage(response):
"""将字典数据写入excel"""
workbook = xlsxwriter.Workbook('./beikeHouse.xlsx')
worksheet = workbook.add_worksheet()
"""设置标题加粗"""
bold_format = workbook.add_format({'bold': True})
worksheet.write('A1', '小区名称', bold_format)
worksheet.write('B1', '租房地址', bold_format)
worksheet.write('C1', '房屋来源', bold_format)
worksheet.write('D1', '发布时间', bold_format)
worksheet.write('E1', '租房说明', bold_format)
worksheet.write('F1', '房屋价格', bold_format)
worksheet.write('G1', '房屋面积', bold_format)
worksheet.write('H1', '房屋朝向', bold_format)
worksheet.write('I1', '房屋户型', bold_format)
worksheet.write('J1', '房屋楼层', bold_format)
worksheet.write('K1', '查看日期', bold_format)
row = 1
col = 0
for item in response:
worksheet.write_string(row, col + 0, item['community'])
worksheet.write_string(row, col + 1, item['address'])
worksheet.write_string(row, col + 2, item['landlord'])
worksheet.write_string(row, col + 3, item['postime'])
worksheet.write_string(row, col + 4, item['introduction'])
worksheet.write_string(row, col + 5, item['price'])
worksheet.write_string(row, col + 6, item['area'])
worksheet.write_string(row, col + 7, item['orientation'])
worksheet.write_string(row, col + 8, item['pattern'])
worksheet.write_string(row, col + 9, item['floor'])
worksheet.write_string(row, col + 10, item['date_time'])
row += 1
workbook.close()
def main():
all_datas = []
"""网站总共100页，循环100次"""
for page in range(1, 100):
html = get_html(page)
parse_html(html, all_datas)
excel_storage(all_datas)
if __name__ == '__main__':
main()5. 信息截图
网站栏目：利用python爬取贝壳网租房信息
文章URL：http://6mz.cn/article/ipsjjg.html