Python 开发简单爬虫 - 基础框架
Python 开发简单爬虫 - 基础框架
1. 目标:开发轻量级爬虫(不包括需登陆的 和 Javascript异步加载的)
不需要登陆的静态网页抓取
2. 内容:
2.1 爬虫简介
2.2 简单爬虫架构
2.3 URL管理器
2.4 网页下载器(urllib2)
2.5 网页解析器(BeautifulSoup)
2.6 完整实例:爬取百度百科Python词条相关的1000个页面数据
3. 爬虫简介:一段自动抓取互联网信息的程序
爬虫价值:互联网数据,为我所用。
4. 简单爬虫架构:
运行流程:
5. URL管理器:管理待抓取URL集合 和 已抓取URL集合
- 防止重复抓取、防止循环抓取
- 实现方式:
6. 网页下载器:将互联网URL对应的网页下载到本地的工具
- 分类:
- urllib2 下载网页的方法:
1. 最简洁方法: url ===> urllib2.urlopen(url)
1
2
3
4
5
6
7
8
9
10
|
import urllib2
#
直接请求
response = urllib2.urlopen( 'http://www.baidu.com' )
#
获取状态码,如果是200表示获取成功
print response.getcode()
#
读取内容
cont = response.read()
|
2. 添加data、http header: (url,data,header) ===> urllib2.Request ===> urllib2.urlopen(request)
1
2
3
4
5
6
7
8
9
10
11
12
13
|
import urllib2
#
创建Request对象
request = urllib2.Request(url)
#
添加数据
request.add_data( 'a' , '1' )
#
添加http的header
request.add_header( 'User-Agent' , 'Mozilla/5.0' )
#
发送请求获取结果
response = urllib2.urlopen(request)
|
3. 添加特殊情景的处理器:
1
2
3
4
5
6
7
8
9
10
11
12
13
|
import urllib2,
cookielib
#
创建cookie容器
cj = cookielib.CookieJar()
#
创建1个opener
opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(cj))
#
给urllib2安装opener
urllib2.install_opener(opener)
#
使用带有cookie的urllib2访问网页
response = urllib2.urlopen(“http: / / www.baidu.com / ”)
|
7. urllib2 实例代码演示:
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
|
#
-*- coding: utf-8 -*-
"""
Created
on Tue Feb 14 10:31:06 2017
@author:
Wayne
"""
import urllib2,
cookielib
url = "http://www.baidu.com"
print "the
1st method"
response1 = urllib2.urlopen(url)
print response1.getcode()
print len (response1.read())
print "the
2nd method"
request = urllib2.Request(url)
request.add_header( "user-agent" , "Mozilla/5.0" )
response2 = urllib2.urlopen(request)
print response2.getcode()
print len (response2.read())
print "the
3rd method"
cj = cookielib.CookieJar()
opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(cj))
response3 = urllib2.urlopen(url)
print response3.getcode()
print cj
print response3.read()
|
8. 网页解析器:从网页中提取有价值数据的工具
python 的网页解析器:
结构化解析 - DOM ( Document Object Model) 树:
9. 网页解析器 - Beautiful Soup
9.1 Beautiful Soup
- Python 第三方库,用于从HTML或XML中提取数据
- 官网:http://www.crummy.com/software/BeautifulSoup
9.2 安装并测试 beautifulsoup4
- 安装:pip install beautifulsoup4
- 测试:import bs4
9.3 Beautiful Soup语法
9.4 创建 BeautifulSoup 对象
1
2
3
4
5
6
7
|
from bs4 import BeautifulSoup
#
根据 HTML 网页字符串创建 BeautifulSoup 对象
soup = BeautifulSoup(
html_doc, #
HTML文档字符串
'html.parser' #
HTML解析器
from_encoding = 'utf-8' #
HTML文档的编码
)
|
9.5 搜索节点(find_all, find)
1
2
3
4
5
6
7
8
9
10
|
#
方法:find_all(name, attrs, string)
#
查找所有标签为 a 的节点
soup.find_all( 'a' )
#
查找所有标签为 a,链接符合 /view/123.htm 形式的节点
soup.find_all( 'a' ,
href = '/view/123.htm' )
soup.find_all( 'a' ,
href = re.compiler(r '/view/\d+\.htm' ))
#
查找所有标签为div, class为abc,文字为Python的节点
soup.find_all( 'div' , class_ = 'abc' ,
string = 'Python' )
|
9.6 访问节点信息
1
2
3
4
5
6
7
8
9
10
|
#
得到节点: <a href='1.html'>Python</a>
#
获取查找到的节点的标签名称
node.name
#
获取查找到的a节点的href属性
node[ 'href' ]
#
获取查找到的a节点的链接文字
node.get_text()
|
10. BeautifulSoup 实例测试
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
|
#
-*- coding: utf-8 -*-
"""
Created
on Tue Feb 14 11:00:42 2017
@author:
Wayne
"""
from bs4 import BeautifulSoup
import re
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>
"""
soup = BeautifulSoup(html_doc, 'html.parser' ,
from_encoding = 'urf-8' )
print '\n##
Get all the links'
links = soup.find_all( 'a' )
for link in links:
print link.name,
link[ 'href' ],
link.get_text()
print '\n##
Get the links include "lacie"'
link_node = soup.find( 'a' ,
href = 'http://example.com/lacie' )
print link_node.name,
link_node[ 'href' ],
link_node.get_text()
print '\n##
RE matching'
link_node = soup.find( 'a' ,
href = re. compile (r "ill" ))
print link_node.name,
link_node[ 'href' ],
link_node.get_text()
print '\n##
Get "P" Paragraph Text'
p_node = soup.find( 'p' , class_ = 'title' )
print p_node.name,
p_node.get_text()
|