1.爬取58同城二手房信息
通过xpath解析网页中信息,准确爬取二手房的标题信息。
from lxml import etree
import requests
# 爬取58二手房信息
if __name__ == '__main__':
# 指定URL
url = 'https://xa.58.com/ershoufang/'
# 加入头信息
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36'
}
page_text = requests.get(url=url,headers=headers).text
#使用xpath对爬取数据进行解析
tree = etree.HTML(page_text)
lis = tree.xpath('//section[@class="list"]/div')
# 给定文件,将爬取的数据写入指定文件中
fp = open('58.txt','w',encoding='utf-8')
for di in lis:
tittle = di.xpath('./a/div[2]/div/div/h3/text()')[0]
print(tittle)
fp.write(tittle +'\n')
爬取之后数据如图所示。
2.批量下载网站中的图片
解析网页中的图片数据,将其爬取并下载到本地文件夹,实现数据的批量获取。
from lxml import etree
import requests
import os
# 批量爬取网页中美女图片
if __name__ == '__main__':
url = 'http://pic.netbian.com/4kmeinv/'
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36'
}
response = requests.get(url=url,headers=headers)
# 手动设定响应数据编码格式
#response.encoding='utf-8'
page_text = response.text
tree = etree.HTML(page_text)
li_list = tree.xpath('//div[@class="slist"]/ul/li')
# 创建一个文件夹
if not os.path.exists('./picLibs'):
os.mkdir('./picLibs')
# 将爬取的图片数据写入文件夹中
for li in li_list:
image_src = 'http://pic.netbian.com' + li.xpath('./a/img/@src')[0]
image_name = li.xpath('./a/img/@alt')[0]+'.jpg'
# 通用处理中文乱码方案
image_name = image_name.encode('iso-8859-1').decode('gbk')
#print(image_src)
image_data = requests.get(url=image_src,headers=headers).content
image_path = 'picLibs/'+image_name
with open(image_path,'wb') as fp:
fp.write(image_data)
print(image_name,'下载成功!!!')
爬取之后效果如图所示。
文件夹中的数据信息如图所示。