先说说爬虫,爬虫常被用来抓取特定网站网页的HTML数据,定位在后端数据的获取,而对于网站而言,爬虫给网站带来流量的同时,一些设计不好的爬虫由于爬得太猛,导致给网站来带很大的负担,当然再加上一些网站并不希望被爬取,所以就出现了许许多多的反爬技术。

1. requests

模块安装方法:

  1. pip3 install requests

2、beautisoup模块

软件安装方法:

  1. pip3 install beautifulsoup4 pip3 install bs4

3、lxml模块

  1. #必须先安装whell依赖 (请换成国内pip源进行安装,否则容易报错)

    pip install wheel
  1. #在cmd中,输入python进入python。
  2. 然后输入import pip;print(pip.pep425tags.get_supported()),界面上输出当前python的版本信息,如图。

再跟据上面查到的版本信息,找到下面对应的版本进行安装。

  1. #下载地址:https://pypi.python.org/pypi/lxml/3.7.3 (网站打不开,请FQ,就可以打开)

    #python3.5就选择cp3m版本
  2. lxml-3.7.3-cp35-cp35m-win32.whl

    #安装方法
    pip3 install lxml-3.6.4-cp35-cp35m-win_amd64.whl

进入python3,输入import lxml,未报错,即表示安装成功。

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

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# 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

2、POST请求

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# 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

3、requests属性

  1. response = requests.get(\'URL\')
  2. response.text # 获取文本内容
  3. response.content # 获取文本内容,字节
  4. response.encoding # 设置返回结果的编码
  5. response.aparent_encoding # 获取网站原始的编码
  6. response.status_code # 状态码
  7. response.cookies.get_dict() # cookies

4、关系和方法

  1. - 方法关系
    requests.get(url, params=None**kwargs)
  1.  
    requests.post(url, data=None, json=None**kwargs)
  1.  
    requests.put(url, data=None**kwargs)
  1.  
    requests.head(url, **kwargs)
  1.  
    requests.delete(url, **kwargs)
  1.  
    requests.patch(url, data=None**kwargs)
  1.  
    requests.options(url, **kwargs)
  1.  
 - 在此方法的基础上构建
  1.  
    requests.request(method, url, **kwargs)
  1. - method: 提交方式
  2. - url: 提交地址
  3. - params: URL中传递的参数,GET
  4. requests.request(
  5. method=\'GET\',
  6. url= \'http://www.nulige.com\',
  7. params = {\'k1\':\'v1\',\'k2\':\'v2\'}
  8. )
  9. # http://www.nulige.com?k1=v1&k2=v2
  10. - data: 在请求体里传递的数据
  11. requests.request(
  12. method=\'POST\',
  13. url= \'http://www.nulige.com\',
  14. params = {\'k1\':\'v1\',\'k2\':\'v2\'},
  15. data = {\'use\':\'alex\',\'pwd\': \'123\',\'x\':[11,2,3}
  16. )
  17. 请求头:
  18. content-type: application/url-form-encod.....
  19. 请求体:
  20. use=alex&pwd=123
  21. - json 在请求体里传递的数据
  22. requests.request(
  23. method=\'POST\',
  24. url= \'http://www.oldboyedu.com\',
  25. params = {\'k1\':\'v1\',\'k2\':\'v2\'},
  26. json = {\'use\':\'alex\',\'pwd\': \'123\'}
  27. )
  28. 请求头:
  29. content-type: application/json
  30. 请求体:
  31. "{\'use\':\'alex\',\'pwd\': \'123\'}"
  32. PS: 字典中嵌套字典时
  33. - headers 请求头
  34. requests.request(
  35. method=\'POST\',
  36. url= \'http://www.oldboyedu.com\',
  37. params = {\'k1\':\'v1\',\'k2\':\'v2\'},
  38. json = {\'use\':\'alex\',\'pwd\': \'123\'},
  39. headers={
  40. \'Referer\': \'http://dig.chouti.com/\',
  41. \'User-Agent\': "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/56.0.2924.87 Safari/537.36"
  42. }
  43. )
  1.      - cookies Cookies
  2.     - files 上传文件
  3.      - auth 基本认证(headers中加入加密的用户名和密码)
  4.      - timeout 请求和响应的超时时间
  5.      - allow_redirects 是否允许重定向
  6.      - proxies 代理 nginx反向代理模块)
  7.      - verify 是否忽略证书
  8.      - cert 证书文件
  9.      - stream 流的方式迭代下载
  10.     - session: 用于保存客户端历史访问信息

 参数用法示例:

  1. def param_method_url():
  2. # requests.request(method=\'get\', url=\'http://127.0.0.1:8000/test/\')
  3. # requests.request(method=\'post\', url=\'http://127.0.0.1:8000/test/\')
  4. pass
  5. def param_param():
  6. # - 可以是字典
  7. # - 可以是字符串
  8. # - 可以是字节(ascii编码以内)
  9. # requests.request(method=\'get\',
  10. # url=\'http://127.0.0.1:8000/test/\',
  11. # params={\'k1\': \'v1\', \'k2\': \'水电费\'})
  12. # requests.request(method=\'get\',
  13. # url=\'http://127.0.0.1:8000/test/\',
  14. # params="k1=v1&k2=水电费&k3=v3&k3=vv3")
  15. # requests.request(method=\'get\',
  16. # url=\'http://127.0.0.1:8000/test/\',
  17. # params=bytes("k1=v1&k2=k2&k3=v3&k3=vv3", encoding=\'utf8\'))
  18. # 错误
  19. # requests.request(method=\'get\',
  20. # url=\'http://127.0.0.1:8000/test/\',
  21. # params=bytes("k1=v1&k2=水电费&k3=v3&k3=vv3", encoding=\'utf8\'))
  22. pass
  23. def param_data():
  24. # 可以是字典
  25. # 可以是字符串
  26. # 可以是字节
  27. # 可以是文件对象
  28. # requests.request(method=\'POST\',
  29. # url=\'http://127.0.0.1:8000/test/\',
  30. # data={\'k1\': \'v1\', \'k2\': \'水电费\'})
  31. # requests.request(method=\'POST\',
  32. # url=\'http://127.0.0.1:8000/test/\',
  33. # data="k1=v1; k2=v2; k3=v3; k3=v4"
  34. # )
  35. # requests.request(method=\'POST\',
  36. # url=\'http://127.0.0.1:8000/test/\',
  37. # data="k1=v1;k2=v2;k3=v3;k3=v4",
  38. # headers={\'Content-Type\': \'application/x-www-form-urlencoded\'}
  39. # )
  40. # requests.request(method=\'POST\',
  41. # url=\'http://127.0.0.1:8000/test/\',
  42. # data=open(\'data_file.py\', mode=\'r\', encoding=\'utf-8\'), # 文件内容是:k1=v1;k2=v2;k3=v3;k3=v4
  43. # headers={\'Content-Type\': \'application/x-www-form-urlencoded\'}
  44. # )
  45. pass
  46. def param_json():
  47. # 将json中对应的数据进行序列化成一个字符串,json.dumps(...)
  48. # 然后发送到服务器端的body中,并且Content-Type是 {\'Content-Type\': \'application/json\'}
  49. requests.request(method=\'POST\',
  50. url=\'http://127.0.0.1:8000/test/\',
  51. json={\'k1\': \'v1\', \'k2\': \'水电费\'})
  52. def param_headers():
  53. # 发送请求头到服务器端
  54. requests.request(method=\'POST\',
  55. url=\'http://127.0.0.1:8000/test/\',
  56. json={\'k1\': \'v1\', \'k2\': \'水电费\'},
  57. headers={\'Content-Type\': \'application/x-www-form-urlencoded\'}
  58. )
  59. def param_cookies():
  60. # 发送Cookie到服务器端
  61. requests.request(method=\'POST\',
  62. url=\'http://127.0.0.1:8000/test/\',
  63. data={\'k1\': \'v1\', \'k2\': \'v2\'},
  64. cookies={\'cook1\': \'value1\'},
  65. )
  66. # 也可以使用CookieJar(字典形式就是在此基础上封装)
  67. from http.cookiejar import CookieJar
  68. from http.cookiejar import Cookie
  69. obj = CookieJar()
  70. obj.set_cookie(Cookie(version=0, name=\'c1\', value=\'v1\', port=None, domain=\'\', path=\'/\', secure=False, expires=None,
  71. discard=True, comment=None, comment_url=None, rest={\'HttpOnly\': None}, rfc2109=False,
  72. port_specified=False, domain_specified=False, domain_initial_dot=False, path_specified=False)
  73. )
  74. requests.request(method=\'POST\',
  75. url=\'http://127.0.0.1:8000/test/\',
  76. data={\'k1\': \'v1\', \'k2\': \'v2\'},
  77. cookies=obj)
  78. def param_files():
  79. # 发送文件
  80. # file_dict = {
  81. # \'f1\': open(\'readme\', \'rb\')
  82. # }
  83. # requests.request(method=\'POST\',
  84. # url=\'http://127.0.0.1:8000/test/\',
  85. # files=file_dict)
  86. # 发送文件,定制文件名
  87. # file_dict = {
  88. # \'f1\': (\'test.txt\', open(\'readme\', \'rb\'))
  89. # }
  90. # requests.request(method=\'POST\',
  91. # url=\'http://127.0.0.1:8000/test/\',
  92. # files=file_dict)
  93. # 发送文件,定制文件名
  94. # file_dict = {
  95. # \'f1\': (\'test.txt\', "hahsfaksfa9kasdjflaksdjf")
  96. # }
  97. # requests.request(method=\'POST\',
  98. # url=\'http://127.0.0.1:8000/test/\',
  99. # files=file_dict)
  100. # 发送文件,定制文件名
  101. # file_dict = {
  102. # \'f1\': (\'test.txt\', "hahsfaksfa9kasdjflaksdjf", \'application/text\', {\'k1\': \'0\'})
  103. # }
  104. # requests.request(method=\'POST\',
  105. # url=\'http://127.0.0.1:8000/test/\',
  106. # files=file_dict)
  107. pass
  108. def param_auth():
  109. from requests.auth import HTTPBasicAuth, HTTPDigestAuth
  110. ret = requests.get(\'https://api.github.com/user\', auth=HTTPBasicAuth(\'wupeiqi\', \'sdfasdfasdf\'))
  111. print(ret.text)
  112. # ret = requests.get(\'http://192.168.1.1\',
  113. # auth=HTTPBasicAuth(\'admin\', \'admin\'))
  114. # ret.encoding = \'gbk\'
  115. # print(ret.text)
  116. # ret = requests.get(\'http://httpbin.org/digest-auth/auth/user/pass\', auth=HTTPDigestAuth(\'user\', \'pass\'))
  117. # print(ret)
  118. #
  119. def param_timeout():
  120. # ret = requests.get(\'http://google.com/\', timeout=1)
  121. # print(ret)
  122. # ret = requests.get(\'http://google.com/\', timeout=(5, 1))
  123. # print(ret)
  124. pass
  125. def param_allow_redirects():
  126. ret = requests.get(\'http://127.0.0.1:8000/test/\', allow_redirects=False)
  127. print(ret.text)
  128. def param_proxies():
  129. # proxies = {
  130. # "http": "61.172.249.96:80",
  131. # "https": "http://61.185.219.126:3128",
  132. # }
  133. # proxies = {\'http://10.20.1.128\': \'http://10.10.1.10:5323\'}
  134. # ret = requests.get("http://www.proxy360.cn/Proxy", proxies=proxies)
  135. # print(ret.headers)
  136. # from requests.auth import HTTPProxyAuth
  137. #
  138. # proxyDict = {
  139. # \'http\': \'77.75.105.165\',
  140. # \'https\': \'77.75.105.165\'
  141. # }
  142. # auth = HTTPProxyAuth(\'username\', \'mypassword\')
  143. #
  144. # r = requests.get("http://www.google.com", proxies=proxyDict, auth=auth)
  145. # print(r.text)
  146. pass
  147. def param_stream():
  148. ret = requests.get(\'http://127.0.0.1:8000/test/\', stream=True)
  149. print(ret.content)
  150. ret.close()
  151. # from contextlib import closing
  152. # with closing(requests.get(\'http://httpbin.org/get\', stream=True)) as r:
  153. # # 在此处理响应。
  154. # for i in r.iter_content():
  155. # print(i)
  156. def requests_session():
  157. import requests
  158. session = requests.Session()
  159. ### 1、首先登陆任何页面,获取cookie
  160. i1 = session.get(url="http://dig.chouti.com/help/service")
  161. ### 2、用户登陆,携带上一次的cookie,后台对cookie中的 gpsd 进行授权
  162. i2 = session.post(
  163. url="http://dig.chouti.com/login",
  164. data={
  165. \'phone\': "8615131255089",
  166. \'password\': "xxxxxx",
  167. \'oneMonth\': ""
  168. }
  169. )
  170. i3 = session.post(
  171. url="http://dig.chouti.com/link/vote?linksId=8589623",
  172. )
  173. print(i3.text)

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

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。

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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\')

使用示例:

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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

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# tag = soup.find(\'a\')
# name = tag.name # 获取
# print(name)
# tag.name = \'span\' # 设置
# print(soup)

2. attr,标签属性

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# 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

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# body = soup.find(\'body\')
# v = body.children

4. children,所有子子孙孙标签

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# 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)

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# tag = soup.find(\'body\')
# tag.clear()
# print(soup)

6. decompose,递归的删除所有的标签

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# 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

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# 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)

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# 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)

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# 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

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# 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

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# 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

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# tag = soup.find(\'a\')
# v = tag.has_attr(\'id\')
# print(v)

13. get_text,获取标签内部文本内容

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# tag = soup.find(\'a\')
# v = tag.get_text
# print(v)

14. index,检查标签在某标签中的索引位置

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# 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\’

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# tag = soup.find(\'br\')
# v = tag.is_empty_element
# print(v)

16. 当前的关联标签

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# 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

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# 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

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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

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# 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

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# 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

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# 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

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# 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

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# 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

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# 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

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# 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

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# tag = soup.find(\'a\')
# v = tag.unwrap()
# print(soup)

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

 

把下面代码,加入到代码中,可以下载网站源码到本地分析

  1. with open(\'weixin.html\',\'wb\') as f:
  2. f.write(wx_login_page.content)
  1. #!/usr/bin/env python
  2. # -*- coding:utf-8 -*-
  3. # Author: nulige
  4. import requests
  5. from bs4 import BeautifulSoup
  6. response = requests.get(
  7. url=\'http://www.autohome.com.cn/news/\'
  8. )
  9. #解决爬虫乱码问题
  10. response.encoding = response.apparent_encoding
  11. # 生成Soup对象,
  12. soup = BeautifulSoup(response.text, features=\'html.parser\')
  13. # find查找第一个符合条件的对象
  14. target = soup.find(id=\'auto-channel-lazyload-article\')
  15. #find_all查找所有符合的对象,查找出来的值在列表中
  16. li_list = target.find_all(\'li\')
  17. #循环拿到具体每个对象
  18. for i in li_list:
  19. a = i.find(\'a\')
  20. if a:
  21. print(a.attrs.get(\'href\')) # # .attrs查找到属性
  22. txt = a.find(\'h3\').text # 是对象
  23. img_url = a.find(\'img\').attrs.get(\'src\')
  24. print(img_url)
  25. # 再发一个请求
  26. img_response = requests.get(url=img_url)
  27. import uuid
  28. file_name = str(uuid.uuid4()) + \'.jpg\'
  29. with open(file_name,\'wb\') as f:
  30. f.write(img_response.content)


    备注:
     # 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\')
  1. #!/usr/bin/env python
  2. # -*- coding: utf8 -*-
  3. # __Author: "Skiler Hao"
  4. # date: 2017/5/10 11:06
  5. import requests
  6. from bs4 import BeautifulSoup
  7. # 第一次请求
  8. first_request_response = requests.get(
  9. url = \'http://dig.chouti.com/\',
  10. )
  11. # 获取第一次登录获取的cookie内容
  12. firstget_cookie_dict = first_request_response.cookies.get_dict()
  13. # 登录POST请求
  14. post_dict = {
  15. \'phone\': \'8618811*****\', #86+手机号码
  16. \'password\': \'******\', #密码
  17. \'oneMonth\': 1
  18. }
  19. # 发送请求,携带cookie和数据
  20. login_response = requests.post(
  21. url = \'http://dig.chouti.com/login\',
  22. data = post_dict,
  23. cookies= firstget_cookie_dict
  24. )
  25. # 点赞请求
  26. dianzan_response = requests.post(
  27. url = \'http://dig.chouti.com/link/vote?linksId=11832246\',
  28. cookies= firstget_cookie_dict
  29. )
  30. print(dianzan_response.text)
  31. # 取消点赞
  32. cancel_dianzan_response = requests.post(
  33. url = \'http://dig.chouti.com/vote/cancel/vote.do\',
  34. cookies= firstget_cookie_dict,
  35. data={\'linksId\':11832246}
  36. )
  37. print(cancel_dianzan_response.text)
  38. # 获取个人信息
  39. get_person_info_resonse = requests.get(
  40. url = \'http://dig.chouti.com/profile\',
  41. cookies= firstget_cookie_dict,
  42. )
  43. # 按照某种encoding方式编码
  44. get_person_info_resonse.encoding = get_person_info_resonse.apparent_encoding
  45. # 将其内容放入BS中进行解析
  46. person_info_site = BeautifulSoup(get_person_info_resonse.text,features=\'html.parser\')
  47. # 找到之后可以做任何处理,获取配置中的nickname
  48. nickname_tag = person_info_site.find(id=\'nick\')
  49. nickname = person_info_site.find(id=\'nick\').attrs.get(\'value\')
  50. print(\'昵称:\',nickname)
  51. # 更新自己在抽屉上的个人信息
  52. personal_info = {
  53. \'jid\': \'cdu_49017916793\',
  54. \'nick\': \'努力哥\',
  55. \'imgUrl\': \'http://img2.chouti.com/CHOUTI_90A38B32473A49B7B26A49F46B34268C_W585H359=C60x60.png\',
  56. # http://img2.chouti.com/CHOUTI_BAE7F736FE7B48E49D1CEE459020F3B0_W390H390=48x48.jpg
  57. \'sex\': True,
  58. \'proveName\': \'北京\',
  59. \'cityName\': \'澳门\',
  60. \'sign\': \'hi呃呃哈发到付\'
  61. }
  62. update_person_info_resonse = requests.post(
  63. url = \'http://dig.chouti.com/profile/update\',
  64. cookies= firstget_cookie_dict,
  65. data=personal_info
  66. )
  67. print(update_person_info_resonse.text)
  68. #########################Session方式登录抽屉#########################
  69. session = requests.Session()
  70. # 先登陆一下抽屉网
  71. i1 = session.get(
  72. url=\'http://dig.chouti.com/\'
  73. )
  74. # 模拟抽屉登录
  75. login_post_dict = {
  76. \'phone\': \'86188116*****\', #86+手机号码
  77. \'password\': \'******\', #密码
  78. \'oneMonth\': 1
  79. }
  80. i2 = session.post(
  81. url=\'http://dig.chouti.com/login\',
  82. data=login_post_dict,
  83. )
  1. #!/usr/bin/env python
  2. # -*- coding: utf8 -*-
  3. # date: 2017/5/10 16:32
  4. import requests
  5. from bs4 import BeautifulSoup
  6. # GitHub是基于authenticity_token,具有预防csrf_token的功能
  7. # 首先访问页面,获取页面上的authenticity_token
  8. i1 = requests.get(\'https://github.com/login\')
  9. # print(i1.content)
  10. login_page_res = BeautifulSoup(i1.content,features=\'lxml\')
  11. authenticity_token = login_page_res.find(name=\'input\',attrs={\'name\':\'authenticity_token\'}).attrs.get(\'value\')
  12. cookies1 = i1.cookies.get_dict()
  13. # print(authenticity_token)
  14. form_data = {
  15. \'commit\': \'Sign in\',
  16. \'utf8\': \'\',
  17. \'authenticity_token\': authenticity_token,
  18. \'login\': \'*****\',
  19. \'password\': \'******\',
  20. }
  21. # 将数据封装在post请求中进行登录,而且要加上cookie
  22. login_res = requests.post(
  23. url=\'https://github.com/session\',
  24. data=form_data,
  25. cookies=cookies1
  26. )
  27. # print(login_res.text)
  28. # 拿到页面中的自己的项目列表
  29. login_page_res = BeautifulSoup(login_res.content,features=\'lxml\')
  30. list_info = login_page_res.select("span .repo")
  31. for i in list_info:
  32. print(i.text)
  33. cookies1 = i1.cookies.get_dict()

4、自动登录cnblog

博客园站用了一个rsa算法的加密模块,所以安装加密模块。才能验证登录。

  1. pip3 install rsa

代码:

  1. #!/usr/bin/env python
  2. # -*- coding: utf8 -*-
  3. # date: 2017/5/11 10:51
  4. import re
  5. import json
  6. import base64
  7. import rsa
  8. import requests
  9. from bs4 import BeautifulSoup
  10. # 负责模仿前端js模块对账号和密码加密
  11. def js_enrypt(text):
  12. # 先从博客园拿到public key
  13. public_key = \'MIGfMA0GCSqGSIb3DQEBAQUAA4GNADCBiQKBgQCp0wHYbg/NOPO3nzMD3dndwS0MccuMeXCHgVlGOoYyFwLdS24Im2e7YyhB0wrUsyYf0/nhzCzBK8ZC9eCWqd0aHbdgOQT6CuFQBMjbyGYvlVYU2ZP7kG9Ft6YV6oc9ambuO7nPZh+bvXH0zDKfi02prknrScAKC0XhadTHT3Al0QIDAQAB\'
  14. # 将拿到的一串字符,转换成64进制
  15. der = base64.standard_b64decode(public_key)
  16. # 再将其转换成数字,作为公钥加载
  17. pk = rsa.PublicKey.load_pkcs1_openssl_der(der)
  18. # 运用公钥对传进来的文字进行加密
  19. v1 = rsa.encrypt(bytes(text,\'utf8\'),pk)
  20. # 对加密后的内容进行解码
  21. value = base64.encodebytes(v1).replace(b\'\n\',b\'\')
  22. value = value.decode(\'utf8\')
  23. # 将其返回
  24. return value
  25. session = requests.Session()
  26. # 写个错误的用户名和密码,提交一下。就找到提交数据
  27. post_data = {
  28. \'input1\': js_enrypt(\'******\'),
  29. \'input2\': js_enrypt(\'******\'),
  30. \'remember\': True
  31. }
  32. # 发送一次请求,获取ajax发送post时要发送的VerificationToken,需要将其放在请求头部
  33. login_page = session.get(
  34. url=\'https://passport.cnblogs.com/user/signin\',
  35. )
  36. VerificationToken = re.compile("\'VerificationToken\': \'(.*)\'")
  37. v = re.search(VerificationToken,login_page.text)
  38. VerificationToken = v.group(1)
  39. # 发送请求,注意将数据json序列化,因为Accept:application/json
  40. login_post_res = session.post(
  41. url=\'https://passport.cnblogs.com/user/signin\',
  42. data=json.dumps(post_data),
  43. headers={
  44. \'VerificationToken\': VerificationToken,
  45. \'X-Requested-With\': \'XMLHttpRequest\',
  46. \'Content-Type\': \'application/json; charset=UTF-8\'
  47. }
  48. )
  49. # 登录账号设置页
  50. setting_page = session.get(
  51. url=\'https://home.cnblogs.com/set/account/\',
  52. )
  53. soup = BeautifulSoup(setting_page.content,features=\'lxml\')
  54. name = soup.select_one(\'#loginName_display_block div\').get_text().strip()
  55. print(\'你的账号名为:\',name)

5、自动登录知乎

  1. #!/usr/bin/env python
  2. # -*- coding: utf8 -*-
  3. import requests
  4. from bs4 import BeautifulSoup
  5. session = requests.Session()
  6. # 知乎会查看你的是否有用户客户端信息,没有不会让爬的
  7. signin_page = session.get(
  8. url=\'https://www.zhihu.com/#signin\',
  9. headers={
  10. \'User-Agent\': \'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.98 Safari/537.36\',
  11. }
  12. )
  13. # 拿到页面的_xrf为了防止csrf攻击,post数据的时候需要提供
  14. signin_page_tag = BeautifulSoup(signin_page.content,features=\'lxml\')
  15. xsrf_code = signin_page_tag.find(\'input\',attrs={\'name\':\'_xsrf\'}).attrs.get(\'value\')
  16. # 从知乎服务器获取验证码照片,发送请求POST,发现需要传入以下三个参数
  17. # r:1494416****
  18. # type:login
  19. # lang:cn
  20. import time
  21. current_time = time.time()
  22. yanzhengma = session.get(
  23. url=\'https://www.zhihu.com/captcha.gif\',
  24. params={
  25. \'r\': current_time,
  26. \'type\': \'login\',
  27. # \'lang\': \'en\' # 使用不同的语言,cn最为复杂,不加的话,最容易识别,en为立体的英文也不好识别
  28. },
  29. headers={
  30. \'User-Agent\': \'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.98 Safari/537.36\',
  31. }
  32. )
  33. # 将从服务器收到的验证码写入文件,可以查看啦
  34. with open(\'zhihu.gif\', \'wb\') as f:
  35. f.write(yanzhengma.content)
  36. captcha = input("请打开照片查看验证码:")
  37. form_data = {
  38. \'_xsrf\': xsrf_code,
  39. \'password\': \'********\',
  40. \'captcha\': captcha,
  41. # \'captcha\': \'{"img_size": [200, 44], "input_points": [[40.2, 34.2], [156.2, 28.2], [138.2, 24.2]]}\',
  42. # \'captcha_type\': \'cn\', # 如果为中文的验证码比较复杂
  43. \'phone_num\': \'***********\', #填手机号码登录
  44. # \'email\':"sddasd@123.com" # 邮箱登录的方式
  45. }
  46. login_response = session.post(
  47. url=\'https://www.zhihu.com/login/phone_num\', #前端会根据你的数据类型选择用邮箱或者手机号码登录
  48. # url=\'https://www.zhihu.com/login/phone_num\'
  49. data=form_data,
  50. headers = {
  51. \'User-Agent\': \'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.98 Safari/537.36\',
  52. }
  53. )
  54. index_page = session.get(
  55. url=\'https://www.zhihu.com/\',
  56. headers={
  57. \'User-Agent\': \'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.98 Safari/537.36\',
  58. }
  59. )
  60. index_page_tag = BeautifulSoup(index_page.content,features=\'lxml\')
  61. print(index_page_tag)

运行程序后,输入验证码。登录成功后,搜索用户名称,能找到我多个相同的用户名称,就说明登录成功。

 

 

 

 

 

 

 

 

 

    

 

版权声明:本文为nulige原创文章,遵循 CC 4.0 BY-SA 版权协议,转载请附上原文出处链接和本声明。
本文链接:https://www.cnblogs.com/nulige/p/6834180.html