一、话说爬虫

  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。

二、安装模块

1. requests

模块安装方法:

pip3 install requests

2、beautisoup模块

软件安装方法:

pip3 install beautifulsoup4  或 pip3 install bs4

3、lxml模块

#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
#在cmd中,输入python进入python。
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。

#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 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。

三、requests模块用法

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

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

4、关系和方法

- 方法关系
    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)

 - 在此方法的基础上构建

    requests.request(method, url, **kwargs)
- method:  提交方式
            - url:     提交地址
            - params:  在URL中传递的参数,GET 
                requests.request(
                    method=\'GET\',
                    url= \'http://www.nulige.com\',
                    params = {\'k1\':\'v1\',\'k2\':\'v2\'}
                )
                # http://www.nulige.com?k1=v1&k2=v2
            - data:    在请求体里传递的数据
            
                requests.request(
                    method=\'POST\',
                    url= \'http://www.nulige.com\',
                    params = {\'k1\':\'v1\',\'k2\':\'v2\'},
                    data = {\'use\':\'alex\',\'pwd\': \'123\',\'x\':[11,2,3}
                )
                
                请求头:
                    content-type: application/url-form-encod.....
                    
                请求体:
                    use=alex&pwd=123
                
                
            - json   在请求体里传递的数据
                requests.request(
                    method=\'POST\',
                    url= \'http://www.oldboyedu.com\',
                    params = {\'k1\':\'v1\',\'k2\':\'v2\'},
                    json = {\'use\':\'alex\',\'pwd\': \'123\'}
                )
                请求头:
                    content-type: application/json
                    
                请求体:
                    "{\'use\':\'alex\',\'pwd\': \'123\'}"
                
                PS: 字典中嵌套字典时
                
            - headers   请求头
            
                requests.request(
                    method=\'POST\',
                    url= \'http://www.oldboyedu.com\',
                    params = {\'k1\':\'v1\',\'k2\':\'v2\'},
                    json = {\'use\':\'alex\',\'pwd\': \'123\'},
                    headers={
                        \'Referer\': \'http://dig.chouti.com/\',
                        \'User-Agent\': "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/56.0.2924.87 Safari/537.36"
                    }
                )
                 - cookies  Cookies
             
                 - files    上传文件
             
                 - auth      基本认证(headers中加入加密的用户名和密码)
             
                 - timeout  请求和响应的超时时间
             
                 - allow_redirects  是否允许重定向
             
                 - proxies   代理 (nginx反向代理模块)
             
                 - verify   是否忽略证书
             
                 - cert     证书文件
             
                 - stream   流的方式迭代下载
             
                - session: 用于保存客户端历史访问信息

 参数用法示例:

def param_method_url():
    # requests.request(method=\'get\', url=\'http://127.0.0.1:8000/test/\')
    # requests.request(method=\'post\', url=\'http://127.0.0.1:8000/test/\')
    pass


def param_param():
    # - 可以是字典
    # - 可以是字符串
    # - 可以是字节(ascii编码以内)

    # requests.request(method=\'get\',
    # url=\'http://127.0.0.1:8000/test/\',
    # params={\'k1\': \'v1\', \'k2\': \'水电费\'})

    # requests.request(method=\'get\',
    # url=\'http://127.0.0.1:8000/test/\',
    # params="k1=v1&k2=水电费&k3=v3&k3=vv3")

    # requests.request(method=\'get\',
    # url=\'http://127.0.0.1:8000/test/\',
    # params=bytes("k1=v1&k2=k2&k3=v3&k3=vv3", encoding=\'utf8\'))

    # 错误
    # requests.request(method=\'get\',
    # url=\'http://127.0.0.1:8000/test/\',
    # params=bytes("k1=v1&k2=水电费&k3=v3&k3=vv3", encoding=\'utf8\'))
    pass


def param_data():
    # 可以是字典
    # 可以是字符串
    # 可以是字节
    # 可以是文件对象

    # requests.request(method=\'POST\',
    # url=\'http://127.0.0.1:8000/test/\',
    # data={\'k1\': \'v1\', \'k2\': \'水电费\'})

    # requests.request(method=\'POST\',
    # url=\'http://127.0.0.1:8000/test/\',
    # data="k1=v1; k2=v2; k3=v3; k3=v4"
    # )

    # requests.request(method=\'POST\',
    # url=\'http://127.0.0.1:8000/test/\',
    # data="k1=v1;k2=v2;k3=v3;k3=v4",
    # headers={\'Content-Type\': \'application/x-www-form-urlencoded\'}
    # )

    # requests.request(method=\'POST\',
    # url=\'http://127.0.0.1:8000/test/\',
    # data=open(\'data_file.py\', mode=\'r\', encoding=\'utf-8\'), # 文件内容是:k1=v1;k2=v2;k3=v3;k3=v4
    # headers={\'Content-Type\': \'application/x-www-form-urlencoded\'}
    # )
    pass


def param_json():
    # 将json中对应的数据进行序列化成一个字符串,json.dumps(...)
    # 然后发送到服务器端的body中,并且Content-Type是 {\'Content-Type\': \'application/json\'}
    requests.request(method=\'POST\',
                     url=\'http://127.0.0.1:8000/test/\',
                     json={\'k1\': \'v1\', \'k2\': \'水电费\'})


def param_headers():
    # 发送请求头到服务器端
    requests.request(method=\'POST\',
                     url=\'http://127.0.0.1:8000/test/\',
                     json={\'k1\': \'v1\', \'k2\': \'水电费\'},
                     headers={\'Content-Type\': \'application/x-www-form-urlencoded\'}
                     )


def param_cookies():
    # 发送Cookie到服务器端
    requests.request(method=\'POST\',
                     url=\'http://127.0.0.1:8000/test/\',
                     data={\'k1\': \'v1\', \'k2\': \'v2\'},
                     cookies={\'cook1\': \'value1\'},
                     )
    # 也可以使用CookieJar(字典形式就是在此基础上封装)
    from http.cookiejar import CookieJar
    from http.cookiejar import Cookie

    obj = CookieJar()
    obj.set_cookie(Cookie(version=0, name=\'c1\', value=\'v1\', port=None, domain=\'\', path=\'/\', secure=False, expires=None,
                          discard=True, comment=None, comment_url=None, rest={\'HttpOnly\': None}, rfc2109=False,
                          port_specified=False, domain_specified=False, domain_initial_dot=False, path_specified=False)
                   )
    requests.request(method=\'POST\',
                     url=\'http://127.0.0.1:8000/test/\',
                     data={\'k1\': \'v1\', \'k2\': \'v2\'},
                     cookies=obj)


def param_files():
    # 发送文件
    # file_dict = {
    # \'f1\': open(\'readme\', \'rb\')
    # }
    # requests.request(method=\'POST\',
    # url=\'http://127.0.0.1:8000/test/\',
    # files=file_dict)

    # 发送文件,定制文件名
    # file_dict = {
    # \'f1\': (\'test.txt\', open(\'readme\', \'rb\'))
    # }
    # requests.request(method=\'POST\',
    # url=\'http://127.0.0.1:8000/test/\',
    # files=file_dict)

    # 发送文件,定制文件名
    # file_dict = {
    # \'f1\': (\'test.txt\', "hahsfaksfa9kasdjflaksdjf")
    # }
    # requests.request(method=\'POST\',
    # url=\'http://127.0.0.1:8000/test/\',
    # files=file_dict)

    # 发送文件,定制文件名
    # file_dict = {
    #     \'f1\': (\'test.txt\', "hahsfaksfa9kasdjflaksdjf", \'application/text\', {\'k1\': \'0\'})
    # }
    # requests.request(method=\'POST\',
    #                  url=\'http://127.0.0.1:8000/test/\',
    #                  files=file_dict)

    pass


def param_auth():
    from requests.auth import HTTPBasicAuth, HTTPDigestAuth

    ret = requests.get(\'https://api.github.com/user\', auth=HTTPBasicAuth(\'wupeiqi\', \'sdfasdfasdf\'))
    print(ret.text)

    # ret = requests.get(\'http://192.168.1.1\',
    # auth=HTTPBasicAuth(\'admin\', \'admin\'))
    # ret.encoding = \'gbk\'
    # print(ret.text)

    # ret = requests.get(\'http://httpbin.org/digest-auth/auth/user/pass\', auth=HTTPDigestAuth(\'user\', \'pass\'))
    # print(ret)
    #


def param_timeout():
    # ret = requests.get(\'http://google.com/\', timeout=1)
    # print(ret)

    # ret = requests.get(\'http://google.com/\', timeout=(5, 1))
    # print(ret)
    pass


def param_allow_redirects():
    ret = requests.get(\'http://127.0.0.1:8000/test/\', allow_redirects=False)
    print(ret.text)


def param_proxies():
    # proxies = {
    # "http": "61.172.249.96:80",
    # "https": "http://61.185.219.126:3128",
    # }

    # proxies = {\'http://10.20.1.128\': \'http://10.10.1.10:5323\'}

    # ret = requests.get("http://www.proxy360.cn/Proxy", proxies=proxies)
    # print(ret.headers)


    # from requests.auth import HTTPProxyAuth
    #
    # proxyDict = {
    # \'http\': \'77.75.105.165\',
    # \'https\': \'77.75.105.165\'
    # }
    # auth = HTTPProxyAuth(\'username\', \'mypassword\')
    #
    # r = requests.get("http://www.google.com", proxies=proxyDict, auth=auth)
    # print(r.text)

    pass


def param_stream():
    ret = requests.get(\'http://127.0.0.1:8000/test/\', stream=True)
    print(ret.content)
    ret.close()

    # from contextlib import closing
    # with closing(requests.get(\'http://httpbin.org/get\', stream=True)) as r:
    # # 在此处理响应。
    # for i in r.iter_content():
    # print(i)


def requests_session():
    import requests

    session = requests.Session()

    ### 1、首先登陆任何页面,获取cookie

    i1 = session.get(url="http://dig.chouti.com/help/service")

    ### 2、用户登陆,携带上一次的cookie,后台对cookie中的 gpsd 进行授权
    i2 = session.post(
        url="http://dig.chouti.com/login",
        data={
            \'phone\': "8615131255089",
            \'password\': "xxxxxx",
            \'oneMonth\': ""
        }
    )

    i3 = session.post(
        url="http://dig.chouti.com/link/vote?linksId=8589623",
    )
    print(i3.text)

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

四、BeautifulSoup

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/

 

五、示例

把下面代码,加入到代码中,可以下载网站源码到本地分析

with open(\'weixin.html\',\'wb\') as f:
    f.write(wx_login_page.content)

1、爬取汽车之家新闻频道页面里面的图片

#!/usr/bin/env python
# -*- coding:utf-8 -*- 
# Author: nulige

import requests
from bs4 import BeautifulSoup

response = requests.get(
    url=\'http://www.autohome.com.cn/news/\'
)

#解决爬虫乱码问题
response.encoding = response.apparent_encoding  

# 生成Soup对象,
soup = BeautifulSoup(response.text, features=\'html.parser\')


# find查找第一个符合条件的对象
target = soup.find(id=\'auto-channel-lazyload-article\')

#find_all查找所有符合的对象,查找出来的值在列表中
li_list = target.find_all(\'li\')

#循环拿到具体每个对象
for i in li_list:
    a = i.find(\'a\')

    if a:
        print(a.attrs.get(\'href\'))   #    # .attrs查找到属性
        txt = a.find(\'h3\').text  # 是对象
        img_url = a.find(\'img\').attrs.get(\'src\')
        print(img_url)
        # 再发一个请求
        img_response = requests.get(url=img_url)
        import uuid
        file_name = str(uuid.uuid4()) + \'.jpg\'
        with open(file_name,\'wb\') as f:
            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\')

2、自动登陆抽屉网

#!/usr/bin/env python
# -*- coding: utf8 -*-
# __Author: "Skiler Hao"
# date: 2017/5/10 11:06
import requests
from bs4 import BeautifulSoup

# 第一次请求
first_request_response = requests.get(
    url = \'http://dig.chouti.com/\',
)
# 获取第一次登录获取的cookie内容
firstget_cookie_dict = first_request_response.cookies.get_dict()


# 登录POST请求
post_dict = {
    \'phone\': \'8618811*****\', #86+手机号码
    \'password\': \'******\',    #密码
    \'oneMonth\': 1
}
# 发送请求,携带cookie和数据
login_response = requests.post(
    url = \'http://dig.chouti.com/login\',
    data = post_dict,
    cookies= firstget_cookie_dict
)


# 点赞请求
dianzan_response = requests.post(
    url = \'http://dig.chouti.com/link/vote?linksId=11832246\',
    cookies= firstget_cookie_dict
)
print(dianzan_response.text)


# 取消点赞
cancel_dianzan_response = requests.post(
    url = \'http://dig.chouti.com/vote/cancel/vote.do\',
    cookies= firstget_cookie_dict,
    data={\'linksId\':11832246}
)
print(cancel_dianzan_response.text)


# 获取个人信息
get_person_info_resonse = requests.get(
    url = \'http://dig.chouti.com/profile\',
    cookies= firstget_cookie_dict,
)
# 按照某种encoding方式编码
get_person_info_resonse.encoding = get_person_info_resonse.apparent_encoding
# 将其内容放入BS中进行解析
person_info_site = BeautifulSoup(get_person_info_resonse.text,features=\'html.parser\')
# 找到之后可以做任何处理,获取配置中的nickname
nickname_tag = person_info_site.find(id=\'nick\')
nickname = person_info_site.find(id=\'nick\').attrs.get(\'value\')
print(\'昵称:\',nickname)

# 更新自己在抽屉上的个人信息
personal_info = {
    \'jid\': \'cdu_49017916793\',
    \'nick\': \'努力哥\',
    \'imgUrl\': \'http://img2.chouti.com/CHOUTI_90A38B32473A49B7B26A49F46B34268C_W585H359=C60x60.png\',
# http://img2.chouti.com/CHOUTI_BAE7F736FE7B48E49D1CEE459020F3B0_W390H390=48x48.jpg
    \'sex\': True,
    \'proveName\': \'北京\',
    \'cityName\': \'澳门\',
    \'sign\': \'黑hi呃呃哈发到付\'
}
update_person_info_resonse = requests.post(
    url = \'http://dig.chouti.com/profile/update\',
    cookies= firstget_cookie_dict,
    data=personal_info
)
print(update_person_info_resonse.text)

#########################Session方式登录抽屉#########################

session = requests.Session()
# 先登陆一下抽屉网
i1 = session.get(
    url=\'http://dig.chouti.com/\'
)
# 模拟抽屉登录
login_post_dict = {
    \'phone\': \'86188116*****\', #86+手机号码
    \'password\': \'******\',  #密码
    \'oneMonth\': 1
}
i2 = session.post(
    url=\'http://dig.chouti.com/login\',
    data=login_post_dict,
)

 3、自动登陆GitHub

#!/usr/bin/env python
# -*- coding: utf8 -*-
# date: 2017/5/10 16:32

import requests
from bs4 import BeautifulSoup
# GitHub是基于authenticity_token,具有预防csrf_token的功能

# 首先访问页面,获取页面上的authenticity_token
i1 = requests.get(\'https://github.com/login\')
# print(i1.content)
login_page_res = BeautifulSoup(i1.content,features=\'lxml\')
authenticity_token = login_page_res.find(name=\'input\',attrs={\'name\':\'authenticity_token\'}).attrs.get(\'value\')
cookies1 = i1.cookies.get_dict()

# print(authenticity_token)
form_data = {
    \'commit\': \'Sign in\',
    \'utf8\': \'✓\',
    \'authenticity_token\': authenticity_token,
    \'login\': \'*****\',
    \'password\': \'******\',
}

# 将数据封装在post请求中进行登录,而且要加上cookie
login_res = requests.post(
    url=\'https://github.com/session\',
    data=form_data,
    cookies=cookies1
)
# print(login_res.text)
# 拿到页面中的自己的项目列表
login_page_res = BeautifulSoup(login_res.content,features=\'lxml\')
list_info = login_page_res.select("span .repo")
for i in list_info:
    print(i.text)
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。

pip3 install rsa

代码:

#!/usr/bin/env python
# -*- coding: utf8 -*-
# date: 2017/5/11 10:51
import re
import json
import base64
import rsa
import requests
from bs4 import BeautifulSoup

# 负责模仿前端js模块对账号和密码加密
def js_enrypt(text):
    # 先从博客园拿到public key
    public_key = \'MIGfMA0GCSqGSIb3DQEBAQUAA4GNADCBiQKBgQCp0wHYbg/NOPO3nzMD3dndwS0MccuMeXCHgVlGOoYyFwLdS24Im2e7YyhB0wrUsyYf0/nhzCzBK8ZC9eCWqd0aHbdgOQT6CuFQBMjbyGYvlVYU2ZP7kG9Ft6YV6oc9ambuO7nPZh+bvXH0zDKfi02prknrScAKC0XhadTHT3Al0QIDAQAB\'

    # 将拿到的一串字符,转换成64进制
    der = base64.standard_b64decode(public_key)

    # 再将其转换成数字,作为公钥加载
    pk = rsa.PublicKey.load_pkcs1_openssl_der(der)

    # 运用公钥对传进来的文字进行加密
    v1 = rsa.encrypt(bytes(text,\'utf8\'),pk)

    # 对加密后的内容进行解码
    value = base64.encodebytes(v1).replace(b\'\n\',b\'\')

    value = value.decode(\'utf8\')

    # 将其返回
    return value

session = requests.Session()

# 写个错误的用户名和密码,提交一下。就找到提交数据
post_data = {
    \'input1\': js_enrypt(\'******\'),
    \'input2\': js_enrypt(\'******\'),
    \'remember\': True
}

# 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
login_page = session.get(
    url=\'https://passport.cnblogs.com/user/signin\',
)
VerificationToken = re.compile("\'VerificationToken\': \'(.*)\'")
v = re.search(VerificationToken,login_page.text)
VerificationToken = v.group(1)

# 发送请求,注意将数据json序列化,因为Accept:application/json
login_post_res = session.post(
    url=\'https://passport.cnblogs.com/user/signin\',
    data=json.dumps(post_data),
    headers={
        \'VerificationToken\': VerificationToken,
        \'X-Requested-With\': \'XMLHttpRequest\',
        \'Content-Type\': \'application/json; charset=UTF-8\'
    }
)

# 登录账号设置页
setting_page = session.get(
    url=\'https://home.cnblogs.com/set/account/\',
)

soup = BeautifulSoup(setting_page.content,features=\'lxml\')
name = soup.select_one(\'#loginName_display_block div\').get_text().strip()
print(\'你的账号名为:\',name)

5、自动登录知乎

#!/usr/bin/env python
# -*- coding: utf8 -*-

import requests
from bs4 import BeautifulSoup

session = requests.Session()

# 知乎会查看你的是否有用户客户端信息,没有不会让爬的
signin_page = session.get(
    url=\'https://www.zhihu.com/#signin\',
    headers={
        \'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\',
    }
)

# 拿到页面的_xrf为了防止csrf攻击,post数据的时候需要提供
signin_page_tag = BeautifulSoup(signin_page.content,features=\'lxml\')
xsrf_code = signin_page_tag.find(\'input\',attrs={\'name\':\'_xsrf\'}).attrs.get(\'value\')

# 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
# r:1494416****
# type:login
# lang:cn
import time
current_time = time.time()
yanzhengma = session.get(
    url=\'https://www.zhihu.com/captcha.gif\',
    params={
        \'r\': current_time,
        \'type\': \'login\',
        # \'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
    },
    headers={
        \'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\',
    }
)

# 将从服务器收到的验证码写入文件,可以查看啦
with open(\'zhihu.gif\', \'wb\') as f:
    f.write(yanzhengma.content)

captcha = input("请打开照片查看验证码:")
form_data = {
    \'_xsrf\': xsrf_code,
    \'password\': \'********\',
    \'captcha\': captcha,

    # \'captcha\': \'{"img_size": [200, 44], "input_points": [[40.2, 34.2], [156.2, 28.2], [138.2, 24.2]]}\',
    # \'captcha_type\': \'cn\',  # 如果为中文的验证码比较复杂

    \'phone_num\': \'***********\',  #填手机号码登录
    # \'email\':"sddasd@123.com"  # 邮箱登录的方式
}

login_response = session.post(
    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
    # url=\'https://www.zhihu.com/login/phone_num\'
    data=form_data,
    headers = {
        \'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\',
    }
)
index_page = session.get(
    url=\'https://www.zhihu.com/\',
    headers={
        \'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\',
    }
)
index_page_tag = BeautifulSoup(index_page.content,features=\'lxml\')
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