目录

一，Requests库练习

1，用百度 360 搜索关键字

2，图片爬取并保存本地

 二，网络爬虫之信息提取——Beautiful soup库学习

1，安装Beautiful soup

2,运用Beautiful soup获取源代码

3， beautifulsoup使用格式

4,beautiful的基本使用元素

​ beatiful soup库 解析器

 beautiful soup类基本元素

5,基于bs4库的HTML内容遍历方法 

 标签树的下行遍历

​ 标签树的上行遍历​

 标签树的平行遍历

总结

​ 6,基于bs4库的HTML格式输出

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一，Requests库练习

 

• raise_for_status():若在返回的代码是200的情况下，是不会产生异常，否则产生异常
• 每次爬取前检查能否访问

1，用百度 360 搜索关键字

• 百度关键词搜索 http://www.baidu.com/s?wd=keyword
• 360关键字搜索 http://www.so.com/s?q=keyword

import requests
kv={'wd':'Python'}
r=requests.get("http://www.baidu.com/s",params=kv)
r.status_code
>>>200
r.request.url
>>>'http://www.baidu.com/s?wd=Python'
print(r.request.url)
>>>http://www.baidu.com/s?wd=Python
print(r.text[1000:2000])

当链接返回的非常多的时候，r.text可能会导致idle失效,所以尽量约束一个范围空间 

2，图片爬取并保存本地

• 要考虑一切可能会发生的情况 

import requests
import os
root = 'E://pictures//'
url = 'https://cj.jj20.com/2020/down.html?picurl=/up/allimg/tp03/1Z9211U233AA-0.jpg'
path = root+url.split('/')[-1]
try:
    if not os.path.exists(root):
        os.mkdir(root)
    if not os.path.exists(path):
        r = requests.get(url=url)
        with open(path, 'wb') as f:
            f.write(r.content)
            f.close()
            print("该文件保存成功")
    else:
        print('文件已存在')
except:
    print("爬取失败")

 二，网络爬虫之信息提取——Beautiful soup库学习

1，安装Beautiful soup

pip install beautifulsoup4

用来解析html和xml文件的功能库 

2,运用Beautiful soup获取源代码

from bs4 import BeautifulSoup
import requests
r = requests.get("http://python123.io/ws/demo.html")
demo = r.text
soup = BeautifulSoup(demo, 'html.parser')  # html.parser是html解析器，使代码能看懂
print(soup.prettify())#打印源代码

成功，beatifulsoup成功解析demo页面 

3， beautifulsoup使用格式

from bs4 import BeautifulSoup

soup=BeautifulSoup('<p>data<p>','html.parser')

4,beautiful的基本使用元素

 beatiful soup库 解析器

 beautiful soup类基本元素

from bs4 import BeautifulSoup import requests r = requests.get("http://python123.io/ws/demo.html") demo = r.text soup = BeautifulSoup(demo, 'html.parser') soup.title .>>><title>This is a python demo page</title> tag=soup.a  //只会返回第一个 tag >>><a class="py1" href="http://www.icourse163.org/course/BIT-268001" id="link1">Basic Python</a> 

soup.a.parent.name >>>'p' soup.a.name >>>'a'

soup.a.parent.parent.name >>>'body' tag=soup.a tag.attrs >>>{'href': 'http://www.icourse163.org/course/BIT-268001', 'class': ['py1'], 'id': 'link1'} tag.attrs['href'] >>>'http://www.icourse163.org/course/BIT-268001'

5,基于bs4库的HTML内容遍历方法 

 标签树的下行遍历

 soup.head.contents >>>[<title>This is a python demo page</title>] soup.body.contents >>>['n', <p class="title"><b>The demo python introduces several python courses.</b></p>, 'n', <p class="course">Python is a wonderful general-purpose programming language. You can learn Python from novice to professional by tracking the following courses: <a class="py1" href="http://www.icourse163.org/course/BIT-268001" id="link1">Basic Python</a> and <a class="py2" href="http://www.icourse163.org/course/BIT-1001870001" id="link2">Advanced Python</a>.</p>, 'n'] len(soup.body.contents) >>>5 soup.body.contents[1] >>><p class="title"><b>The demo python introduces several python courses.</b></p>

//可用循环进行遍历 for child in soup.body.children:     print(child)

 标签树的上行遍历

 for parent in soup.a.parents:     if parent is None://遍历父辈会遍历soup本身，但是soup父辈是空，所以用判断         print(parent)     else:         print(parent.name)

>>>         p body html [document]

 标签树的平行遍历

•  平行遍历发生在同一个父节点下的各节点间
• 平行遍历获得的下一个节点不一定是标签类型 

soup.a.next_sibling >>>' and ' soup.a.next_sibling.next_sibling >>><a class="py2" href="http://www.icourse163.org/course/BIT-1001870001" id="link2">Advanced Python</a> 

• 遍历前续节点(循环)

for sibling in soup.a.previous_siblings:

        print(sibling)

总结

 6,基于bs4库的HTML格式输出

•  print(soup.prettify())

• print(soup.a.prettify())

  >>> <a class="py1" href="http://www.icourse163.org/course/BIT-268001" id="link1">

   Basic Python

  </a>

• soup.a.prettify() >>>'<a class="py1" href="http://www.icourse163.org/course/BIT-268001" id="link1">n Basic Pythonn</a>n'