requests与BeautifulSoup结合爬取网页数据应用

1.1 爬虫相关模块命令回顾

  1、requests模块

                  1、 pip install requests

                  2、 response = requests.get('http://www.baidu.com/ ')            #获取指定url的网页内容

                  3、 response.text                                                                                #获取文本文件

                  4、 response.content                                                                         #获取字节类型

                  5、 response.encoding = ‘utf-8’                                                       #指定获取的网页内容用utf-8编码

                      response.encoding = response.apparent_encoding       #下载的页面是什么编码就用什么编码格式

                  6、 response.cookies                                                                         #拿到cookies

                      response.cookies.get_dict()                               #拿到cookie字典样式

       2、beautisoup模块

                  1、 pip install beautifulsoup4

                  2、 把文本转成对象

        1)html.parser 是python内置模块无需安装

          soup = BeautiSoup(response.text,parser='html.parser')

        2)lxml是第三方库,但是性能好(生产用这个

                                   soup = BeautifulSoup(response.text,features='lxml')

                  3、 .find()用法:返回的是对象

        1)从爬取的内容找到id="auto-channel-lazyload-article" 中div的内容

                                   target = soup.find(id="auto-channel-lazyload-article")

        2) 从爬取的内容中找到一个div,并且这个div有一个属性是id=’i1’

                                   target = soup.find('div',id='i1')

                  4、 .find_all()用法:返回的是对象列表

                          1) 从以后取的target对象中找到所有li标签

                                   li_list = target.find_all('li')

                  5、 从.find()获取的对象中找到想要的属性

        a.attrs.get('href')                                                #获取所有a标签的所有href属性(a标签url路径)

        a.find('h3').text                                                   #找到a标签中的所有h3标签,的内容

        img_url = a.find('img').attrs.get('src')       #从a标签中找到img标签所有src属性(图片url路径)

1.2 爬取需要登录和不需要登录页面内容的方法

import requests
from bs4 import BeautifulSoup
response = requests.get(
   url='http://www.autohome.com.cn/news/'
)

response.encoding = response.apparent_encoding          #下载的页面是什么编码就用什么编码格式

#1 把文本转成对象,
#soup = BeautifulSoup(response.text,features='lxml')        #lxml是第三方库,但是性能好(生产用这个)
soup = BeautifulSoup(response.text,features='html.parser')  # html.parser 是python内置模块无需安装

#2 从爬取的内容找到id="auto-channel-lazyload-article" 中div的内容
target = soup.find(id="auto-channel-lazyload-article")

#3.1 找到所有li标签 .find()是找到第一个
#3.2 也可以这样用: .find('div',id='i1')  可以使用这种组合查找的方法
#3.3 .find()找到的是对象,.find_all() 获取的是列表
li_list = target.find_all('li')

for i in li_list:
   a = i.find('a')
   if a:
      print(a.attrs.get('href'))                   #获取所有a标签的url路径
      # a.find('h3') 获取的是对象, 加上 .text才是获取文本
      txt = a.find('h3').text                      #从a标签中找到所有h3标签的值
      print(txt,type(txt))
      img_url = a.find('img').attrs.get('src')#从a标签中找到img标签所有src属性(图片url路径)
      import uuid
      file_name = str(uuid.uuid4()) + '.jpg'

      if img_url.startswith('//www2'):        #由于获取的图片url做了处理,所以才这样处理
         img_url2 = img_url.replace('//www2','http://www3')
         img_response = requests.get(url=img_url2)
         with open(file_name,'wb') as f:
            f.write(img_response.content)       #把图片写到本地
例1:爬取汽车之家新闻页面(爬取无需登录的网页)
import requests

#1 登录抽屉网站的用户名和密码放到字典里
post_dict = {
   "phone":'86185387525',
   'password':'74810',
   'oneMonth':1
}

#2 将密码字典以post方式提交到抽屉的登录界面
response = requests.post(
   url = 'http://dig.chouti.com/login',
   data=post_dict
)

#3下面就是成功登录抽屉的返回值
print(response.text)
# {"result":{"code":"9999", "message":"", "data":{"complateReg":"0","destJid":"cdu_49844923242"}}}

#4 下面是打印成功登录抽屉后返回的的cookie字典
cookie_dict = response.cookies.get_dict()
print(cookie_dict)
#{'JSESSIONID': 'aaaVizwwcod_L5QcwwR9v', 'puid': 'd332ef55361217e544b91f081090ad5e',
#  'route': '37316285ff8286c7a96cd0b03d38e13b', 'gpsd': 'f8b07e259141ae5a11d930334fbfb609'}

#5 当我们每次需要访问抽屉登录后才能看的信息时,就可以在url中添加登录成返回的cookie字典
response=requests.get(
   url='http://dig.chouti.com/profile',
   cookies = cookie_dict
)
例2:自动登录抽屉并获取用户配置页面的信息(cookie方式)

1.3 使用爬虫登录案例总结 

#!/usr/bin/env python
# -*- coding:utf-8 -*-
import requests

# ## 1、首先登陆任何页面,获取cookie
i1 = requests.get(url="http://dig.chouti.com/")
i1_cookies = i1.cookies.get_dict()

# ## 2、用户登陆,携带上一次的cookie,后台对cookie中的 gpsd 进行授权
i2 = requests.post(
    url="http://dig.chouti.com/login",
    data={
        'phone': "8618538752511",
        'password': "7481079xl",
        'oneMonth': ""
    },
    cookies=i1_cookies
)

# ## 3、点赞(只需要携带已经被授权的gpsd即可)
gpsd = i1_cookies['gpsd']
i3 = requests.post(
    url="http://dig.chouti.com/link/vote?linksId=15074576",
    cookies={'gpsd': gpsd}
)
print(i3.text)
例1:方式一: 使用cookie方式点赞抽屉
import requests

session = requests.Session()
i1 = session.get(url="http://dig.chouti.com/help/service")
i2 = session.post(
    url="http://dig.chouti.com/login",
    data={
        'phone': "8618538752511",
        'password': "7481079xl",
        'oneMonth': ""
    },
)
i3 = session.post(
    url="http://dig.chouti.com/link/vote?linksId=15074576"
)
print(i3.text)
例2:方式二: 使用session方式点赞抽屉
import requests
from bs4 import BeautifulSoup

# 第一步:获取csrf
# 1.1 获取login页面
r1 = requests.get(url='https://github.com/login')
# 1.2 接文本文件解析成对象
b1 = BeautifulSoup(r1.text,'html.parser')
# 1.3 找到csrf_token标签
tag = b1.find(name='input',attrs={'name':'authenticity_token'})
#1.4 获取csrf_token的值
# tag.get('value')等价于 tag.attrs.get('values')
token = tag.get('value')                # 获取csrf_token的值
#1.5 获取第一次发送get请求返回的cookies字典
r1_cookie = r1.cookies.get_dict()       #获取第一次发get请求返回的cookie
print('第一次',r1_cookie)

# 第二步:发送post请求,携带用户名 密码,和第一次get请求返回的cookie,后台进行授权
#2.1 携带:csrf_token,cookies,用户名,密码 发送post请求登录
# requests.post() 等价于  requests.request('post',)
r2 = requests.post(
   url='https://github.com/session',
   data={                        #这里data字典必须和实际登录的格式相同
      'commit':'Sign in',
      'utf8':'',
      'authenticity_token':token,
      'login':'[email protected]',
      'password':'7481079xl',
   },
   cookies = r1_cookie,

)
#2.2 获取第二次返回的cookies字典
r2_cookie = r2.cookies.get_dict()
print('第二次',r2_cookie)
#2.3 将两次获取的cookie字典整合成一个:没有重合就用r1_cookie,有重合的就用r2_cookie更新这个字典
r1_cookie.update(r2_cookie)

# 第三步:访问个人页面,携带cookie
r3 = requests.get(
   url='https://github.com/settings/profile',
   cookies = r1_cookie,                  # 获取数据时携带登录成功的cookie
)
print(r3.text)
例3:使用爬虫登录github并获取用户配置信息
#!/usr/bin/env python
# -*- coding:utf-8 -*-
import time

import requests
from bs4 import BeautifulSoup

session = requests.Session()

i1 = 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',
    }
)

soup1 = BeautifulSoup(i1.text, 'lxml')
xsrf_tag = soup1.find(name='input', attrs={'name': '_xsrf'})
xsrf = xsrf_tag.get('value')

current_time = time.time()
i2 = session.get(
    url='https://www.zhihu.com/captcha.gif',
    params={'r': current_time, 'type': 'login'},
    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',
    })

with open('zhihu.gif', 'wb') as f:
    f.write(i2.content)

captcha = input('请打开zhihu.gif文件,查看并输入验证码:')
form_data = {
    "_xsrf": xsrf,
    'password': 'xxooxxoo',
    "captcha": 'captcha',
    'email': '[email protected]'
}

i3 = session.post(
    url='https://www.zhihu.com/login/email',
    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',
    }
)

i4 = session.get(
    url='https://www.zhihu.com/settings/profile',
    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',
    }
)

soup4 = BeautifulSoup(i4.text, 'lxml')
tag = soup4.find(id='rename-section')
nick_name = tag.find('span',class_='name').string
print(nick_name)
例4:登录知乎
#!/usr/bin/env python
# -*- coding:utf-8 -*-
import re
import json
import base64

import rsa
import requests

def js_encrypt(text):
    b64der = 'MIGfMA0GCSqGSIb3DQEBAQUAA4GNADCBiQKBgQCp0wHYbg/NOPO3nzMD3dndwS0MccuMeXCHgVlGOoYyFwLdS24Im2e7YyhB0wrUsyYf0/nhzCzBK8ZC9eCWqd0aHbdgOQT6CuFQBMjbyGYvlVYU2ZP7kG9Ft6YV6oc9ambuO7nPZh+bvXH0zDKfi02prknrScAKC0XhadTHT3Al0QIDAQAB'
    der = base64.standard_b64decode(b64der)

    pk = rsa.PublicKey.load_pkcs1_openssl_der(der)
    v1 = rsa.encrypt(bytes(text, 'utf8'), pk)
    value = base64.encodebytes(v1).replace(b'\n', b'')
    value = value.decode('utf8')

    return value

session = requests.Session()
i1 = session.get('https://passport.cnblogs.com/user/signin')
rep = re.compile("'VerificationToken': '(.*)'")
v = re.search(rep, i1.text)
verification_token = v.group(1)

form_data = {
    'input1': js_encrypt('wptawy'),
    'input2': js_encrypt('asdfasdf'),
    'remember': False
}
i2 = session.post(url='https://passport.cnblogs.com/user/signin',
                  data=json.dumps(form_data),
                  headers={
                      'Content-Type': 'application/json; charset=UTF-8',
                      'X-Requested-With': 'XMLHttpRequest',
                      'VerificationToken': verification_token}
                  )

i3 = session.get(url='https://i.cnblogs.com/EditDiary.aspx')
print(i3.text)
例5:登录博客园

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转载自www.cnblogs.com/jiaxinzhu/p/12528957.html