在前面的几篇文章中我介绍了如何通过Python分析源代码来爬取博客、维基百科InfoBox和图片，其文章链接如下：
[python学习] 简单爬取维基百科程序语言消息盒
[Python学习] 简单网络爬虫抓取博客文章及思想介绍
[python学习] 简单爬取图片网站图库中图片
其中核心代码如下：
# coding=utf-8
import urllib
import re
#下载静态HTML网页
url='http://www.csdn.net/'
content = urllib.urlopen(url).read()
open('csdn.html','w+').write(content)
#获取标题
title_pat=r'(?<=<title>).*?(?=</title>)'
title_ex=re.compile(title_pat,re.M|re.S)
title_obj=re.search(title_ex, content)
title=title_obj.group()
print title
#获取超链接内容
href = r'<a href=.*?>(.*?)</a>'
m = re.findall(href,content,re.S|re.M)
for text in m:
print unicode(text,'utf-8')
break #只输出一个url>>>
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>>>import os
import urllib
class AppURLopener(urllib.FancyURLopener):
version = "Mozilla/5.0"
urllib._urlopener = AppURLopener()
url = "http://creatim.allyes.com.cn/imedia/csdn/20150228/15_41_49_5B9C9E6A.jpg"
filename = os.path.basename(url)
urllib.urlretrieve(url , filename)
#!/usr/bin/python
# -*- coding: utf-8 -*-
from bs4 import BeautifulSoup
html_doc = """
<html><head><title>The Dormouse's story</title></head>
<body>
<p class="title"><b>The Dormouse's story</b></p>
<p class="story">Once upon a time there were three little sisters; and their names were
<a href="http://example.com/elsie" class="sister" id="link1">Elsie</a>,
<a href="http://example.com/lacie" class="sister" id="link2">Lacie</a> and
<a href="http://example.com/tillie" class="sister" id="link3">Tillie</a>;
and they lived at the bottom of a well.</p>
<p class="story">...</p>
"""
#获取BeautifulSoup对象并按标准缩进格式输出
soup = BeautifulSoup(html_doc)
print(soup.prettify())<html>
<head>
<title>
The Dormouse's story
</title>
</head>
<body>
<p class="title">
<b>
The Dormouse's story
</b>
</p>
<p class="story">
Once upon a time there were three little sisters; and their names were
<a class="sister" href="http://example.com/elsie" id="link1">
Elsie
</a>
,
<a class="sister" href="http://example.com/lacie" id="link2">
Lacie
</a>
and
<a class="sister" href="http://example.com/tillie" id="link3">
Tillie
</a>
;
and they lived at the bottom of a well.
</p>
<p class="story">
...
</p>
</body>
</html>'''获取title值'''
print soup.title
# <title>The Dormouse's story</title>
print soup.title.name
# title
print unicode(soup.title.string)
# The Dormouse's story
'''获取<p>值'''
print soup.p
# <p class="title"><b>The Dormouse's story</b></p>
print soup.a
# <a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>
'''从文档中找到<a>的所有标签链接'''
print soup.find_all('a')
# [<a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>,
# <a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>,
# <a class="sister" href="http://example.com/tillie" id="link3">Tillie</a>]
for link in soup.find_all('a'):
print(link.get('href'))
# http://example.com/elsie
# http://example.com/lacie
# http://example.com/tillie
print soup.find(id='link3')
# <a class="sister" href="http://example.com/tillie" id="link3">Tillie</a>'''从文档中获取所有文字内容'''
print soup.get_text()
# The Dormouse's story
#
# The Dormouse's story
#
# Once upon a time there were three little sisters; and their names were
# Elsie,
# Lacie and
# Tillie;
# and they lived at the bottom of a well.
#
# ...
#!/usr/bin/python
# -*- coding: utf-8 -*-
from bs4 import BeautifulSoup
html = """
<html><head><title>The Dormouse's story</title></head>
<body>
<p class="title" id="start"><b>The Dormouse's story</b></p>
"""
soup = BeautifulSoup(html)
tag = soup.p
print tag
# <p class="title" id="start"><b>The Dormouse's story</b></p>
print type(tag)
# <class 'bs4.element.Tag'>
print tag.name
# p 标签名字
print tag['class']
# [u'title']
print tag.attrs
# {u'class': [u'title'], u'id': u'start'}print unicode(tag.string)
# The Dormouse's story
print type(tag.string)
# <class 'bs4.element.NavigableString'>
tag.string.replace_with("No longer bold")
print tag
# <p class="title" id="start"><b>No longer bold</b></p>markup = "<b><!--Hey, buddy. Want to buy a used parser?--></b>"
soup = BeautifulSoup(markup)
comment = soup.b.string
print type(comment)
# <class 'bs4.element.Comment'>
print unicode(comment)
# Hey, buddy. Want to buy a used parser?soup.head # <head><title>The Dormouse's story</title></head> soup.title # <title>The Dormouse's story</title> soup.body.b # <b>The Dormouse's story</b>注意：通过点取属性的放是只能获得当前名字的第一个Tag，同时可以在文档树的tag中多次调用该方法如soup.body.b获取<body>标签中第一个<b>标签。
soup.find_all('a') # [<a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>, # <a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>, # <a class="sister" href="http://example.com/tillie" id="link3">Tillie</a>]子节点：在分析HTML过程中通常需要分析tag的子节点，而tag的 .contents 属性可以将tag的子节点以列表的方式输出。字符串没有.contents属性，因为字符串没有子节点。
head_tag = soup.head head_tag # <head><title>The Dormouse's story</title></head> head_tag.contents [<title>The Dormouse's story</title>] title_tag = head_tag.contents[0] title_tag # <title>The Dormouse's story</title> title_tag.contents # [u'The Dormouse's story']通过tag的 .children 生成器,可以对tag的子节点进行循环：
for child in title_tag.children: print(child) # The Dormouse's story子孙节点：同样 .descendants 属性可以对所有tag的子孙节点进行递归循环：
for child in head_tag.descendants: print(child) # <title>The Dormouse's story</title> # The Dormouse's story父节点：通过 .parent 属性来获取某个元素的父节点.在例子“爱丽丝”的文档中,<head>标签是<title>标签的父节点，换句话就是增加一层标签。
title_tag = soup.title title_tag # <title>The Dormouse's story</title> title_tag.parent # <head><title>The Dormouse's story</title></head> title_tag.string.parent # <title>The Dormouse's story</title>兄弟节点：因为<b>标签和<c>标签是同一层：他们是同一个元素的子节点，所以<b>和<c>可以被称为兄弟节点。一段文档以标准格式输出时，兄弟节点有相同的缩进级别.在代码中也可以使用这种关系。
sibling_soup = BeautifulSoup("<a><b>text1</b><c>text2</c></b></a>") print(sibling_soup.prettify()) # <html> # <body> # <a> # <b> # text1 # </b> # <c> # text2 # </c> # </a> # </body> # </html>在文档树中,使用 .next_sibling 和 .previous_sibling 属性来查询兄弟节点。<b>标签有.next_sibling 属性，但是没有.previous_sibling 属性，因为<b>标签在同级节点中是第一个。同理<c>标签有.previous_sibling 属性，却没有.next_sibling 属性：
sibling_soup.b.next_sibling # <c>text2</c> sibling_soup.c.previous_sibling # <b>text1</b>介绍到这里基本就可以实现我们的BeautifulSoup库爬取网页内容，而网页修改、删除等内容建议大家阅读文档。下一篇文章就再次爬取维基百科的程序语言的内容吧！希望文章对大家有所帮助，如果有错误或不足之处，还请海涵！建议大家阅读官方文档和《Python基础教程》书。