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 requestsfrom bs4 import BeautifulSoupresponse = 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
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)
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cookiei1 = 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)
import requestssession = 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)
import requestsfrom 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cookieprint(‘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‘:‘1532363461@qq.com‘, ?????‘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cookier3 = 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)
#!/usr/bin/env python# -*- coding:utf-8 -*-import timeimport requestsfrom bs4 import BeautifulSoupsession = 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‘: ‘424662508@qq.com‘}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‘).stringprint(nick_name)
#!/usr/bin/env python# -*- coding:utf-8 -*-import reimport jsonimport base64import rsaimport requestsdef 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 valuesession = 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)
03:requests与BeautifulSoup结合爬取网页数据应用
原文地址:https://www.cnblogs.com/xiaonq/p/8543618.html