文章解析：

1.正则表达式解析

2.beautifulsoup，BeautifulSoup是一个复杂的树形结构，她的每一个节点都是一个python对象，获取网页的内容就是一个提取对象内容的过程，它的提取方法可以归类为三种，1）遍历文档树 2）搜索文档树 3）css选择器

# -*- coding: utf-8 -*- # @Time    : 2018/11/28 17:23 # @Author  : Bo # @Email   : mat_wu@163.com # @File    : re_spider.py # @Software: PyCharm import requests import re from bs4 import BeautifulSoup from lxml import etree def get_title_re_spider(): url = "http://www.santostang.com/" headers = { "user-agent":"Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:63.0) Gecko/20100101 Firefox/63.0", } r = requests.get(url,headers= headers,timeout =10) html = r.text title_list = re.findall('
(.*?)
',html) print(title_list) def beautifulsoup_spider(): url = "http://www.santostang.com/" headers = { "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:63.0) Gecko/20100101 Firefox/63.0", } r = requests.get(url, headers=headers, timeout=10) soup = BeautifulSoup(r.text,"html.parser") title_list = soup.find_all("h1",class_="post-title") for i in range(len(title_list)): title = title_list[i].a.text.strip() print("第 %s篇文章的标题是：%s" %(i+1,title)) def beautiful_methods(): url = "http://www.santostang.com/" headers = { "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:63.0) Gecko/20100101 Firefox/63.0", } r = requests.get(url, headers=headers, timeout=10) soup = BeautifulSoup(r.text, "html.parser") # print(soup.prettify()) #soup对代码进行优化 #遍历文档树 one_element = soup.header.h1 #获取具体的标签节点 elements = soup.header.contents #获取header标签的子节点 first_element = soup.header.contents[1] #标签都在奇数项 # print(one_element) # print(elements) # # print(first_element) # #获取子节点(只有下一级) # for child in soup.body.children: # print(child) # #获取所有子子孙孙的节点 # for child in soup.body.descendants: # print(child) # a_tag = soup.header.div.a # a_parent = a_tag.parent # print(a_parent) # #搜索节点 find() 和find_all() #css选择器 print(soup.select("header h1")) print(soup.select("header > h1")) #css也可以实现文档搜索功能 #使用lxml解析网页 def lxml_spider(): url = "http://www.santostang.com/" headers = { "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:63.0) Gecko/20100101 Firefox/63.0", } r = requests.get(url, headers=headers, timeout=10) html = etree.HTML(r.text) title_list = html.xpath("/html/body/div[1]/div/div[1]/article/header/h1/a/text()") print(title_list)

# 项目实践-爬取安居客二手房信息 def second_house_spider():     url = "https://weihai.anjuke.com/sale/gaoqu/?from=SearchBar" headers = { "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:63.0) Gecko/20100101 Firefox/63.0", } r = requests.get(url,headers = headers,timeout = 10) #使用BeautifulSoup解析网页 soup = BeautifulSoup(r.text,'lxml') house_list = soup.find_all("li",class_="list-item") for house in house_list: name = house.find("div",class_="house-title").a.text.strip() price = house.find("span",class_="price-det").text.strip() price_area = house.find("span",class_="unit-price").text.strip() no_room = house.find("div",class_='details-item').span.text.strip() area = house.find("div",class_="details-item").contents[3].text floor = house.find("div",class_="details-item").contents[5].text address = house.find("span",class_="comm-address").text.strip() address = address.replace('\xa0\xa0\n ',' ') tag_list = house.find_all("span",class_="item-tags") tag = [i.text for i in tag_list] with open('b.txt', "a+",encoding="utf-8") as f: f.write(address) print(name) print(price) print(price_area) print(no_room) print(area) print(floor) print(address) print(tag)

if __name__ == "__main__": # get_title_re_spider() # beautifulsoup_spider() # beautiful_methods() lxml_spider() 学习网址：

https://beautifulsoup.readthedocs.io/zh_CN/v4.4.0/#id27