码迷,mamicode.com
首页 > 编程语言 > 详细

python 爬虫基础

时间:2018-07-21 14:53:08      阅读:45      评论:0      收藏:0      [点我收藏+]

标签:rac   dso   data   .text   poi   bottom   http请求   递归   user   

网络爬虫(又被称为网页蜘蛛,网络机器人,在FOAF社区中间,更经常的称为网页追逐者),是一种按照一定的规则,自动地抓取万维网信息的程序或者脚本。另外一些不常使用的名字还有蚂蚁、自动索引、模拟程序或者蠕虫。

Python标准库中提供了:urllib、urllib2、httplib等模块以供Http请求,但是,它的 API 太渣了。它是为另一个时代、另一个互联网所创建的。它需要巨量的工作,甚至包括各种方法覆盖,来完成最简单的任务。

Requests 是使用 Apache2 Licensed 许可证的 基于Python开发的HTTP 库,其在Python内置模块的基础上进行了高度的封装,从而使得Pythoner进行网络请求时,变得美好了许多,使用Requests可以轻而易举的完成浏览器可有的任何操作。

 

1、GET请求

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
# 1、无参数实例
 
import requests
 
ret = requests.get(‘https://github.com/timeline.json‘)
 
print ret.url
print ret.text
 
 
 
# 2、有参数实例
 
import requests
 
payload = {‘key1‘: ‘value1‘, ‘key2‘: ‘value2‘}
ret = requests.get("http://httpbin.org/get", params=payload)
 
print ret.url
print ret.text

向 https://github.com/timeline.json 发送一个GET请求,将请求和响应相关均封装在 ret 对象中。

2、POST请求

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
# 1、基本POST实例
 
import requests
 
payload = {‘key1‘: ‘value1‘, ‘key2‘: ‘value2‘}
ret = requests.post("http://httpbin.org/post", data=payload)
 
print ret.text
 
 
# 2、发送请求头和数据实例
 
import requests
import json
 
url = ‘https://api.github.com/some/endpoint‘
payload = {‘some‘: ‘data‘}
headers = {‘content-type‘: ‘application/json‘}
 
ret = requests.post(url, data=json.dumps(payload), headers=headers)
 
print ret.text
print ret.cookies

向https://api.github.com/some/endpoint发送一个POST请求,将请求和相应相关的内容封装在 ret 对象中。

3、其他请求

1
2
3
4
5
6
7
8
9
10
requests.get(url, params=None, **kwargs)
requests.post(url, data=None, json=None, **kwargs)
requests.put(url, data=None, **kwargs)
requests.head(url, **kwargs)
requests.delete(url, **kwargs)
requests.patch(url, data=None, **kwargs)
requests.options(url, **kwargs)
 
# 以上方法均是在此方法的基础上构建
requests.request(method, url, **kwargs)

requests模块已经将常用的Http请求方法为用户封装完成,用户直接调用其提供的相应方法即可

 

 

官方文档:http://cn.python-requests.org/zh_CN/latest/user/quickstart.html#id4

BeautifulSoup

BeautifulSoup是一个模块,该模块用于接收一个HTML或XML字符串,然后将其进行格式化,之后遍可以使用他提供的方法进行快速查找指定元素,从而使得在HTML或XML中查找指定元素变得简单。

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
from bs4 import BeautifulSoup
 
html_doc = """
<html><head><title>The Dormouse‘s story</title></head>
<body>
asdf
    <div class="title">
        <b>The Dormouse‘s story总共</b>
        <h1>f</h1>
    </div>
<div class="story">Once upon a time there were three little sisters; and their names were
    <a  class="sister0" id="link1">Els<span>f</span>ie</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.</div>
ad<br/>sf
<p class="story">...</p>
</body>
</html>
"""
 
soup = BeautifulSoup(html_doc, features="lxml")
# 找到第一个a标签
tag1 = soup.find(name=‘a‘)
# 找到所有的a标签
tag2 = soup.find_all(name=‘a‘)
# 找到id=link2的标签
tag3 = soup.select(‘#link2‘)

安装:

1
pip3 install beautifulsoup4

使用示例:

1
2
3
4
5
6
7
8
9
10
11
from bs4 import BeautifulSoup
 
html_doc = """
<html><head><title>The Dormouse‘s story</title></head>
<body>
    ...
</body>
</html>
"""
 
soup = BeautifulSoup(html_doc, features="lxml")
 

 

1. name,标签名称

1
2
3
4
5
# tag = soup.find(‘a‘)
# name = tag.name # 获取
# print(name)
# tag.name = ‘span‘ # 设置
# print(soup)

2. attr,标签属性

1
2
3
4
5
6
# tag = soup.find(‘a‘)
# attrs = tag.attrs    # 获取
# print(attrs)
# tag.attrs = {‘ik‘:123} # 设置
# tag.attrs[‘id‘] = ‘iiiii‘ # 设置
# print(soup)

3. children,所有子标签

1
2
# body = soup.find(‘body‘)
# v = body.children

4. children,所有子子孙孙标签

1
2
# body = soup.find(‘body‘)
# v = body.descendants

5. clear,将标签的所有子标签全部清空(保留标签名)

1
2
3
# tag = soup.find(‘body‘)
# tag.clear()
# print(soup)

6. decompose,递归的删除所有的标签

1
2
3
# body = soup.find(‘body‘)
# body.decompose()
# print(soup)

7. extract,递归的删除所有的标签,并获取删除的标签

1
2
3
# body = soup.find(‘body‘)
# v = body.extract()
# print(soup)

8. decode,转换为字符串(含当前标签);decode_contents(不含当前标签)

1
2
3
4
# body = soup.find(‘body‘)
# v = body.decode()
# v = body.decode_contents()
# print(v)

9. encode,转换为字节(含当前标签);encode_contents(不含当前标签)

1
2
3
4
# body = soup.find(‘body‘)
# v = body.encode()
# v = body.encode_contents()
# print(v)

10. find,获取匹配的第一个标签

1
2
3
4
5
# tag = soup.find(‘a‘)
# print(tag)
# tag = soup.find(name=‘a‘, attrs={‘class‘: ‘sister‘}, recursive=True, text=‘Lacie‘)
# tag = soup.find(name=‘a‘, class_=‘sister‘, recursive=True, text=‘Lacie‘)
# print(tag)

11. find_all,获取匹配的所有标签

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
46
47
48
49
50
51
52
53
54
# tags = soup.find_all(‘a‘)
# print(tags)
 
# tags = soup.find_all(‘a‘,limit=1)
# print(tags)
 
# tags = soup.find_all(name=‘a‘, attrs={‘class‘: ‘sister‘}, recursive=True, text=‘Lacie‘)
# # tags = soup.find(name=‘a‘, class_=‘sister‘, recursive=True, text=‘Lacie‘)
# print(tags)
 
 
# ####### 列表 #######
# v = soup.find_all(name=[‘a‘,‘div‘])
# print(v)
 
# v = soup.find_all(class_=[‘sister0‘, ‘sister‘])
# print(v)
 
# v = soup.find_all(text=[‘Tillie‘])
# print(v, type(v[0]))
 
 
# v = soup.find_all(id=[‘link1‘,‘link2‘])
# print(v)
 
# v = soup.find_all(href=[‘link1‘,‘link2‘])
# print(v)
 
# ####### 正则 #######
import re
# rep = re.compile(‘p‘)
# rep = re.compile(‘^p‘)
# v = soup.find_all(name=rep)
# print(v)
 
# rep = re.compile(‘sister.*‘)
# v = soup.find_all(class_=rep)
# print(v)
 
# rep = re.compile(‘http://www.oldboy.com/static/.*‘)
# v = soup.find_all(href=rep)
# print(v)
 
# ####### 方法筛选 #######
# def func(tag):
# return tag.has_attr(‘class‘) and tag.has_attr(‘id‘)
# v = soup.find_all(name=func)
# print(v)
 
 
# ## get,获取标签属性
# tag = soup.find(‘a‘)
# v = tag.get(‘id‘)
# print(v)

12. has_attr,检查标签是否具有该属性

1
2
3
# tag = soup.find(‘a‘)
# v = tag.has_attr(‘id‘)
# print(v)

13. get_text,获取标签内部文本内容

14. index,检查标签在某标签中的索引位置

1
2
3
4
5
6
7
# tag = soup.find(‘body‘)
# v = tag.index(tag.find(‘div‘))
# print(v)
 
# tag = soup.find(‘body‘)
# for i,v in enumerate(tag):
# print(i,v)

15. is_empty_element,是否是空标签(是否可以是空)或者自闭合标签,

     判断是否是如下标签:‘br‘ , ‘hr‘, ‘input‘, ‘img‘, ‘meta‘,‘spacer‘, ‘link‘, ‘frame‘, ‘base‘

1
2
3
# tag = soup.find(‘br‘)
# v = tag.is_empty_element
# print(v)

16. 当前的关联标签

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
# soup.next
# soup.next_element
# soup.next_elements
# soup.next_sibling
# soup.next_siblings
 
#
# tag.previous
# tag.previous_element
# tag.previous_elements
# tag.previous_sibling
# tag.previous_siblings
 
#
# tag.parent
# tag.parents

17. 查找某标签的关联标签

1
2
3
4
5
6
7
8
9
10
11
12
13
14
# tag.find_next(...)
# tag.find_all_next(...)
# tag.find_next_sibling(...)
# tag.find_next_siblings(...)
 
# tag.find_previous(...)
# tag.find_all_previous(...)
# tag.find_previous_sibling(...)
# tag.find_previous_siblings(...)
 
# tag.find_parent(...)
# tag.find_parents(...)
 
# 参数同find_all

18. select,select_one, CSS选择器

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
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
soup.select("title")
 
soup.select("p nth-of-type(3)")
 
soup.select("body a")
 
soup.select("html head title")
 
tag = soup.select("span,a")
 
soup.select("head > title")
 
soup.select("p > a")
 
soup.select("p > a:nth-of-type(2)")
 
soup.select("p > #link1")
 
soup.select("body > a")
 
soup.select("#link1 ~ .sister")
 
soup.select("#link1 + .sister")
 
soup.select(".sister")
 
soup.select("[class~=sister]")
 
soup.select("#link1")
 
soup.select("a#link2")
 
soup.select(‘a[href]‘)
 
soup.select(‘a[href="http://example.com/elsie"]‘)
 
soup.select(‘a[href^="http://example.com/"]‘)
 
soup.select(‘a[href$="tillie"]‘)
 
soup.select(‘a[href*=".com/el"]‘)
 
 
from bs4.element import Tag
 
def default_candidate_generator(tag):
    for child in tag.descendants:
        if not isinstance(child, Tag):
            continue
        if not child.has_attr(‘href‘):
            continue
        yield child
 
tags = soup.find(‘body‘).select("a", _candidate_generator=default_candidate_generator)
print(type(tags), tags)
 
from bs4.element import Tag
def default_candidate_generator(tag):
    for child in tag.descendants:
        if not isinstance(child, Tag):
            continue
        if not child.has_attr(‘href‘):
            continue
        yield child
 
tags = soup.find(‘body‘).select("a", _candidate_generator=default_candidate_generator, limit=1)
print(type(tags), tags)

19. 标签的内容

1
2
3
4
5
6
7
8
9
10
11
12
13
# tag = soup.find(‘span‘)
# print(tag.string)          # 获取
# tag.string = ‘new content‘ # 设置
# print(soup)
 
# tag = soup.find(‘body‘)
# print(tag.string)
# tag.string = ‘xxx‘
# print(soup)
 
# tag = soup.find(‘body‘)
# v = tag.stripped_strings  # 递归内部获取所有标签的文本
# print(v)

20.append在当前标签内部追加一个标签

1
2
3
4
5
6
7
8
9
10
# tag = soup.find(‘body‘)
# tag.append(soup.find(‘a‘))
# print(soup)
#
# from bs4.element import Tag
# obj = Tag(name=‘i‘,attrs={‘id‘: ‘it‘})
# obj.string = ‘我是一个新来的‘
# tag = soup.find(‘body‘)
# tag.append(obj)
# print(soup)

21.insert在当前标签内部指定位置插入一个标签

1
2
3
4
5
6
# from bs4.element import Tag
# obj = Tag(name=‘i‘, attrs={‘id‘: ‘it‘})
# obj.string = ‘我是一个新来的‘
# tag = soup.find(‘body‘)
# tag.insert(2, obj)
# print(soup)

22. insert_after,insert_before 在当前标签后面或前面插入

1
2
3
4
5
6
7
# from bs4.element import Tag
# obj = Tag(name=‘i‘, attrs={‘id‘: ‘it‘})
# obj.string = ‘我是一个新来的‘
# tag = soup.find(‘body‘)
# # tag.insert_before(obj)
# tag.insert_after(obj)
# print(soup)

23. replace_with 在当前标签替换为指定标签

1
2
3
4
5
6
# from bs4.element import Tag
# obj = Tag(name=‘i‘, attrs={‘id‘: ‘it‘})
# obj.string = ‘我是一个新来的‘
# tag = soup.find(‘div‘)
# tag.replace_with(obj)
# print(soup)

24. 创建标签之间的关系

1
2
3
4
# tag = soup.find(‘div‘)
# a = soup.find(‘a‘)
# tag.setup(previous_sibling=a)
# print(tag.previous_sibling)

25. wrap,将指定标签把当前标签包裹起来

1
2
3
4
5
6
7
8
9
10
11
# from bs4.element import Tag
# obj1 = Tag(name=‘div‘, attrs={‘id‘: ‘it‘})
# obj1.string = ‘我是一个新来的‘
#
# tag = soup.find(‘a‘)
# v = tag.wrap(obj1)
# print(soup)
 
# tag = soup.find(‘a‘)
# v = tag.wrap(soup.find(‘p‘))
# print(soup)

26. unwrap,去掉当前标签,将保留其包裹的标签

1
2
3
# tag = soup.find(‘a‘)
# v = tag.unwrap()
# print(soup)

更多参数官方:http://beautifulsoup.readthedocs.io/zh_CN/v4.4.0/

python 爬虫基础

标签:rac   dso   data   .text   poi   bottom   http请求   递归   user   

原文地址:https://www.cnblogs.com/superfangchao/p/9345994.html

(0)
(0)
   
举报
评论 一句话评论(0
0条  
登录后才能评论!
© 2014 mamicode.com 版权所有 京ICP备13008772号-2
迷上了代码!