爬虫分类
通用 聚焦 增量式
2.什么事UA检测,如何破解?
服务器通过获取请求,获取请求头中的UA,判断UA的值,请求的载体身份标识 给个伪headers
3.简述https的加密流程
4.什么是动态加载数据？如何爬取动态加载的数据？
有的网站 部分数据使用ajax生成动态数据,所见非所得,使用抓包工具进行分析,获取参数发送请求,得到数据.
5.requests模块中的get和post方法的常用参数及其作用
url data headers proxies(代理)
加密方式
对称加密: 客户端和服务区端交互的时候,客户端制定加密规则,把解密规则和密文给我们服务器端 服务器就可以解密,坏处,一旦被第3放拦截就能破解
非对称机密:服务端创建加密/解密(公钥/私钥)方式,把公钥给客户端 客户端使用公钥加密 把密文发个服务器 效率低
https证书机制:客户端服务器端 找一个信任的3方机构 服务器端想把公钥给客户端,发之前先找第3方认证机构 进行签名,会有一个证书,结合公钥一并发给客户端,客户端会坚持这个公钥是不是3方认证机构签的如果是 就可以拿这个公钥进行加密
requests模块使用流程:
1.指定url
2.发送请求
3.获取相应数据
4.持久化存储
爬取搜狗页面数据
#1指定url url = 'https://www.sogou.com/' #2.发起请求 response = requests.get(url=url) #3获取响应数据 page_text = response.text #text返回的是字符串类型的数据 #持久化存储 with open('./sogou.html','w',encoding='utf-8') as fp: fp.write(page_text) print('over!')
反反扒机制
import requests wd = input('enter a word:') url = 'https://www.sogou.com/web' #参数的封装 param = { 'query':wd } #UA伪装 headers = { 'User-Agent':'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.77 Safari/537.36' } response = requests.get(url=url,params=param,headers=headers) #手动修改响应数据的编码 response.encoding = 'utf-8' page_text = response.text fileName = wd + '.html' with open(fileName,'w',encoding='utf-8') as fp: fp.write(page_text) print(fileName,'爬取成功！！！')
破解百度翻译
import requests wd = input('enter a word:') url = 'https://www.sogou.com/web' #参数的封装 param = { 'query':wd } #UA伪装 headers = { 'User-Agent':'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.77 Safari/537.36' } response = requests.get(url=url,params=param,headers=headers) #手动修改响应数据的编码 response.encoding = 'utf-8' page_text = response.text fileName = wd + '.html' with open(fileName,'w',encoding='utf-8') as fp: fp.write(page_text) print(fileName,'爬取成功！！！')
爬取任意城市对应肯德基的位子
#动态加载的数据 city = input('enter a cityName:') url = 'http://www.kfc.com.cn/kfccda/ashx/GetStoreList.ashx?op=keyword' data = { "cname": "", "pid": "", "keyword": city, "pageIndex": "2", "pageSize": "10", } #UA伪装 headers = { 'User-Agent':'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.77 Safari/537.36' } response = requests.post(url=url,headers=headers,data=data) json_text = response.text print(json_text)
分页肯德基
import json import requests #爬取任意城市对应的肯德基餐厅的位置信息 #动态加载的数据 city = input('enter a cityName:') for i in range(1,9): url = 'http://www.kfc.com.cn/kfccda/ashx/GetStoreList.ashx?op=keyword' data = { "cname": "", "pid": "", "keyword": city, "pageIndex": i, "pageSize": "10", } #UA伪装 headers = { 'User-Agent':'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.77 Safari/537.36' } response = requests.post(url=url,headers=headers,data=data) json_text=response.text # data_dump = json.dumps(json_text) with open('data.json',"a", encoding="UTF-8") as f: f.write(json_text)
抓取国家药品监督管理局 公司
#注意事项 如果是动态数据就需要全局搜索确认找逻辑
import requests headers = { 'User-Agent':'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.77 Safari/537.36' } first_url = 'http://125.35.6.84:81/xk/itownet/portalAction.do?method=getXkzsList' ids = [] for page in range(1,11): data = { "on": "true", "page": str(page), "pageSize": "15", "productName": "", "conditionType": "1", "applyname": "", "applysn": "", } response = requests.post(url=first_url,data=data,headers=headers) #response.headers返回的是响应头信息（字典） if response.headers['Content-Type'] == 'application/json;charset=UTF-8': json_obj = response.json() for dic in json_obj['list']: ids.append(dic['ID']) detail_url = 'http://125.35.6.84:81/xk/itownet/portalAction.do?method=getXkzsById' for _id in ids: data = { 'id':_id } company_text = requests.post(detail_url,data=data,headers=headers).text print(company_text)
爬取图片的2种方法
import requests headers={ "User-Agent":"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/63.0.3239.132 Safari/537.36" } img_url='https://www.baidu.com/img/bd_logo1.png' img_data=requests.get(url=img_url,headers=headers).content with open('./baidu_log.jpg','wb') as f: f.write(img_data) #######方法二 from urllib import request img_url='https://www.baidu.com/img/bd_logo1.png' request.urlretrieve(img_url,'./baidu_log2.jpg')
正则数据解析
解析原理: 标签定位,提取标签中存储的文本数据,或标签属性中的数据
爬取糗事百科正则首页所有图
pip install requests
''' <div class="thumb"> <a href="/article/121859578" target="_blank"> <img src="//pic.qiushibaike.com/system/pictures/12185/121859578/medium/YZQA73IAY8J68GXC.jpg" alt="麻烦p的搞笑一点"> </a> </div> ''' import os import re import requests from urllib import request if not os.path.exists('./qiutu'): os.mkdir('./qiutu') headers={ 'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.77 Safari/537.36' } url='https://www.qiushibaike.com/pic/' page_text=requests.get(url=url,headers=headers).text ex='<div class="thumb">.*?<img src="(.*?)" alt.*?</div>' img_url=re.findall(ex,page_text,re.S)#re.S 去掉空格 for url in img_url: url='https:'+url img_name=url.split('/')[-1] img_path='./qiutu/'+img_name request.urlretrieve(url,img_path) print(img_name,'下载成功')
bs4解析
解析原理:实例化一个Beautifulsoup(谁又福)的对象,将页面源码数据加载到该对象中
使用该对象的相关属性和方法实现标签和数据提取
- pip install bs4
- pip install lxml
- pip install html5lib
2种方式
BeautifulSoup(page_test,'lmxl')#从互联网请求到数据源码加载到对象中 BeautifulSoup(fb,'lmxl')#将本地源码加载在对象中
好处就是 自带标签
from bs4 import BeautifulSoup fp = open('./test.html','r',encoding='utf-8') soup=BeautifulSoup(fp,"lxml") # print(soup.title) # print(soup.div)#默认会找第一个div # print(soup.find('a'))#查询a 默认第一个
# #属性定位 # print(soup.find('div',class_='song')) # print(soup.find_all('div')[2])#查找所有div 并找出第二个div 从0开始的 #select(选择器) # print(soup.select('.song')) # print(soup.select('div'))#变成一个list
#层级 # >表示一个层级 空格表示多个层级 # print(soup.select('.tang > ul > li >a'))#取出所有的a # print(soup.select('.tang a'))#取出所有的a #取出直系文本数据 text获取全部的数据 # print(soup.p.string) # print(soup.find('div',class_='tang').get_text()) # print(soup.find('div',class_='tang').text)
#取属性 # print(soup.a['href']) # print(soup.select('.tang>ul>li>a')[0]['href'])
xpath解析
解析原理:实例一个etree对象,将页面源码加载该对象中,使用etrr中的xpath方法结合xpath表达式进行标签定位和数据提取
2种方式
etree.parse('本地文件路径')
etrss.Html(page_text)#远程文件
from lxml import etree tree=etree.parse('./test.html') #定位title标签 # print(tree.xpath('/html/head/title/text()'))#查找title # print(tree.xpath('/html//title')) # print(tree.xpath('//title/text()')) #定位class print(tree.xpath('//div[@class="song"]/p[1]/text()')[0]) print(tree.xpath('//div[@class="tang"]/ul/li[4]/a/text()')) #定位id print(tree.xpath('//div[@class="id"]/ul/li[4]/a/text()')) #取属性 print(tree.xpath('//a/@title'))#找到所有的title属性 遇到属性取属性 print(tree.xpath('//a/@href'))#找到所有的hraf属性
中文乱码问题
import requests from lxml import etree start_page = int(input('start page num:')) end_page = int(input('end page num:')) if not os.path.exists('./meinvs'): os.mkdir('./meinvs') #通用的url模板(不能修改) url = 'http://pic.netbian.com/4kmeinv/index_%d.html' for page in range(start_page,end_page+1): if page == 1: new_url = 'http://pic.netbian.com/4kmeinv/' else: new_url = format(url%page) response = requests.get(url=new_url,headers=headers) # response.encoding = 'utf-8' page_text = response.text #解析名称和图片的src属性值 tree = etree.HTML(page_text) li_list = tree.xpath('//div[@class="slist"]/ul/li') for li in li_list: img_name = li.xpath('./a/img/@alt')[0] img_name = img_name.encode('iso-8859-1').decode('gbk')+'.jpg' img_src = 'http://pic.netbian.com'+li.xpath('./a/img/@src')[0] img_path = './meinvs/'+img_name request.urlretrieve(img_src,img_path) print(img_name,'下载成功！！！')
xpath 或的使用
#爬取全国城市名称 url = 'https://www.aqistudy.cn/historydata/' page_text = requests.get(url=url,headers=headers).text tree = etree.HTML(page_text) # hot_city = tree.xpath('//div[@class="bottom"]/ul/li/a/text()') # all_city = tree.xpath('//div[@class="bottom"]/ul/div[2]/li/a/text()') # all_city tree.xpath('//div[@class="bottom"]/ul/div[2]/li/a/text() | //div[@class="bottom"]/ul/li/a/text()')
智联职位爬取
import requests from lxml import etree headers = { 'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/63.0.3239.132 Safari/537.36' } url = 'https://www.zhipin.com/job_detail/?query=python%E7%88%AC%E8%99%AB&city=101010100&industry=&position=' page_text = requests.get(url=url, headers=headers).text # 数据解析 tree = etree.HTML(page_text) list = tree.xpath('//div[@class="job-list"]//li') for i in list: position = i.xpath('.//div[@class="job-title"]/text()')[0] salary = i.xpath('.//span[@class="red"]/text()')[0] gongsi = i.xpath('.//div[@class="company-text"]/h3/a/text()')[0] url_tail = i.xpath('.//div[@class="info-primary"]//a/@href')[0] print(url_tail) url_tail = 'https://www.zhipin.com/' + url_tail page_text_tail=requests.get(url=url_tail,headers=headers).text tree2 = etree.HTML(page_text_tail) maiosu_list=tree2.xpath('//div[@class="detail-content"]') for v in maiosu_list: a=v.xpath('.//div[@class="job-sec"]/div[@class="text"]/text()') print(position,salary,gongsi,a)
requests模块高级操作
- 匿名度： - 透明：对方服务器可以知道你使用了代理，并且也知道你的真实IP - 匿名：对方服务器可以知道你使用了代理，但不知道你的真实IP - 高匿：对方服务器不知道你使用了代理，更不知道你的真实IP。
- 类型： - http：该类型的代理ip只可以发起http协议头对应的请求 - https：该类型的代理ip只可以发起https协议头对应的请求
requests的get和post方法常用的参数：
url
headers
data/params post用data
proxies 代理
Connection:close #来一个连接关闭一个
免费获取代理的方法
import os import requests from lxml import etree # start_page=int(input('start page num:')) # end_page=int(input('end page num:')) if not os.path.exists('./daili'): os.mkdir('./daili') headers = { 'User-Agent':'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.77 Safari/537.36' } for i in range(1,3): url = 'https://www.xicidaili.com/nn/{}'.format(i) response=requests.get(url=url,headers=headers).text #实例化 tree=etree.HTML(response) tr_list=tree.xpath('//*[@id="ip_list"]//tr[@class="odd"]') # print(tr_list) for tr in tr_list: one_ip=tr.xpath('.//td[2]/text()')[0] port=tr.xpath('.//td[3]/text()')[0] list_wr=one_ip+':'+port # print(list_wr) with open('./ip.txt','a') as f: f.write(list_wr+' ')
使用代理的方法
import random import requests https=[ {'https':"122.193.244.58:9999"}, ] http = [ {'http':"101.132.131.158:8118"}, {'http':"120.210.219.101:8080"} ] headers = { 'User-Agent':'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.77 Safari/537.36' } url = 'https://www.baidu.com/s?wd=ip' if url.split(':')[0] == 'https': page_text = requests.get(url=url,headers=headers,proxies=random.choice(https)).text print(page_text) else: page_text = requests.get(url=url,headers=headers,proxies=random.choice(http)).text with open('./ip.html','w',encoding='utf-8') as fp: fp.write(page_text)
cookie相关操作
- cookie：可是使得服务器端记录客户端的相关状态
-处理cookie的方式
-手动处理 cookie是有效时常,动态变化的
-自动处理 使用会发机制session
-session用法:
实例化一个会话对象:requests.Session()
可以进行请求发送(post,get)
请求过程如果产生了cookie就会被自动存储到session中
爬取雪球
#需求：爬取雪球网中的新闻标题和对应的内容简介 url = 'https://xueqiu.com/v4/statuses/public_timeline_by_category.json?since_id=-1&max_id=-1&count=10&category=-1' headers = { 'User-Agent':'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.77 Safari/537.36' } json_obj = requests.get(url=url,headers=headers).json() print(json_obj) {'error_description': '遇到错误，请刷新页面或者重新登录帐号后再试', 'error_uri': '/v4/statuses/public_timeline_by_category.json', 'error_code': '400016'}
加session的方法
import requests headers = { 'User-Agent':'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.77 Safari/537.36' } session=requests.Session() #如果这一步产生了cookie,则cookie会被自动存储到session中 session.get(url='https://xueqiu.com/',headers=headers) #想要对如下的url发送请求,且是携带cookie发动请求 url='https://xueqiu.com/v4/statuses/public_timeline_by_category.json?since_id=-1&max_id=-1&count=10&category=-1' #把这里的requests改成session json_obj = session.get(url=url,headers=headers).json() print(json_obj)
云打码使用流程
- http://www.yundama.com/demo.html
- 注册：
- 普通用户
- 开发者用户
- 登录：
- 登录普通用户：
- 查询剩余题分
- 登录开发者用户：
- 创建一个软件：我的软件-》创建一个新软件（软件名称，秘钥不可以修改），使用软件的id和秘钥
- 下载示例代码：开发文档-》点此下载：云打码接口DLL-》PythonHTTP示例下载
- 登录普通用户：
爬取古诗文(自动打码)
import http.client, mimetypes, urllib, json, time, requests ###################################################################### class YDMHttp: apiurl = 'http://api.yundama.com/api.php' username = '' password = '' appid = '' appkey = '' def __init__(self, username, password, appid, appkey): self.username = username self.password = password self.appid = str(appid) self.appkey = appkey def request(self, fields, files=[]): response = self.post_url(self.apiurl, fields, files) response = json.loads(response) return response def balance(self): data = {'method': 'balance', 'username': self.username, 'password': self.password, 'appid': self.appid, 'appkey': self.appkey} response = self.request(data) if (response): if (response['ret'] and response['ret'] < 0): return response['ret'] else: return response['balance'] else: return -9001 def login(self): data = {'method': 'login', 'username': self.username, 'password': self.password, 'appid': self.appid, 'appkey': self.appkey} response = self.request(data) if (response): if (response['ret'] and response['ret'] < 0): return response['ret'] else: return response['uid'] else: return -9001 def upload(self, filename, codetype, timeout): data = {'method': 'upload', 'username': self.username, 'password': self.password, 'appid': self.appid, 'appkey': self.appkey, 'codetype': str(codetype), 'timeout': str(timeout)} file = {'file': filename} response = self.request(data, file) if (response): if (response['ret'] and response['ret'] < 0): return response['ret'] else: return response['cid'] else: return -9001 def result(self, cid): data = {'method': 'result', 'username': self.username, 'password': self.password, 'appid': self.appid, 'appkey': self.appkey, 'cid': str(cid)} response = self.request(data) return response and response['text'] or '' def decode(self, filename, codetype, timeout): cid = self.upload(filename, codetype, timeout) if (cid > 0): for i in range(0, timeout): result = self.result(cid) if (result != ''): return cid, result else: time.sleep(1) return -3003, '' else: return cid, '' def report(self, cid): data = {'method': 'report', 'username': self.username, 'password': self.password, 'appid': self.appid, 'appkey': self.appkey, 'cid': str(cid), 'flag': '0'} response = self.request(data) if (response): return response['ret'] else: return -9001 def post_url(self, url, fields, files=[]): for key in files: files[key] = open(files[key], 'rb'); res = requests.post(url, files=files, data=fields) return res.text ######################开始########################################### # 将示例代码中的可执行程序封装成函数 def transformCodeImg(imgPath, imgType): # 普通用户名 username = 'bobo328410948' # 密码 password = 'bobo328410948' # 软件ＩＤ，开发者分成必要参数。登录开发者后台【我的软件】获得！ appid = 6003 # 软件密钥，开发者分成必要参数。登录开发者后台【我的软件】获得！ appkey = '1f4b564483ae5c907a1d34f8e2f2776c' # 图片文件 filename = imgPath # 验证码类型，# 例：1004表示4位字母数字，不同类型收费不同。请准确填写，否则影响识别率。在此查询所有类型 http://www.yundama.com/price.html codetype = imgType # 超时时间，秒 timeout = 30 result = None # 检查 if (username == 'username'): print('请设置好相关参数再测试') else: # 初始化 yundama = YDMHttp(username, password, appid, appkey) # 登陆云打码 uid = yundama.login(); print('uid: %s' % uid) # 查询余额 balance = yundama.balance(); print('balance: %s' % balance) # 开始识别，图片路径，验证码类型ID，超时时间（秒），识别结果 cid, result = yundama.decode(filename, codetype, timeout); return result import requests from lxml import etree headers = { 'User-Agent':'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.77 Safari/537.36' } #访问的时候带了cookie s=requests.Session() url='https://so.gushiwen.org/user/login.aspx?from=http://so.gushiwen.org/user/collect.aspx' page_text=s.get(url=url,headers=headers).text tree=etree.HTML(page_text) #验证码图片地址 img_src='https://so.gushiwen.org/'+tree.xpath('//*[@id="imgCode"]/@src')[0] #获取到的图片二进制文件写入 img_data=s.get(url=img_src,headers=headers).content##验证码也会产生一个cookie with open('./gushiwen.jpg','wb') as f: f.write(img_data) #验证码图片 类型 result=transformCodeImg('./gushiwen.jpg',1004) print(result,'打印出打码后的验证码') #登陆的时候发送的值 __VIEWSTATE=tree.xpath('//*[@id="__VIEWSTATE"]/@value')[0] __VIEWSTATEGENERATOR=tree.xpath('//*[@id="__VIEWSTATEGENERATOR"]/@value')[0] #模拟登陆 post_url='https://so.gushiwen.org/user/login.aspx?from=' data={ "__VIEWSTATE":__VIEWSTATE, "__VIEWSTATEGENERATOR":__VIEWSTATEGENERATOR, "from":"", "email": "1820405927@qq.com", "pwd": "1213.com", "code": result, "denglu": "登录" } response=s.post(url=post_url,headers=headers,data=data) print(response.status_code)#登陆后的状态 page_text=response.text#得到登陆后的主页写入html文件 with open('./gushiwen.html','w',encoding='utf-8') as f: f.write(page_text)
线程池使用测试方法
from time import sleep import time from multiprocessing.dummy import Pool urls=['www.baidu.com','www.songou.com','www.xinlang.com'] def request(url): print('正在请求:',url) sleep(2) print('下载成功',url) start=time.time() pool=Pool(3) pool.map(request,urls) print(time.time()-start)
线程池爬取梨视频中的短数据
*线程池需要作用到 爬虫为最耗时的操作中
耗时操作:视频下载,视频的保存
# 使用线程池爬取视频中的短视频 from lxml import etree import requests import random headers = { 'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.77 Safari/537.36' } url = 'https://www.pearvideo.com/category_1' page_text = requests.get(url=url, headers=headers).text from multiprocessing.dummy import Pool pool = Pool(4) viseo_urls = [] # 所有视频的url tree = etree.HTML(page_text) # 解析视频详情url li_list = tree.xpath('//*[@id="listvideoListUl"]/li') ''' var contId="1559965",liveStatusUrl="liveStatus.jsp",liveSta="",playSta="1",autoPlay=!1,isLiving=!1,isVrVideo=!1,hdflvUrl="",sdflvUrl="",hdUrl="",sdUrl="",ldUrl="", srcUrl="https://video.pearvideo.com/mp4/adshort/20190528/cont-1559965-13958439_adpkg-ad_hd.mp4",vdoUrl=srcUrl,skinRes="//www.pearvideo.com/domain/skin",videoCDN="//video.pearvideo.com"; ex='srcUrl="(.*?)",vdoUrl' ''' import re def getiVideoData(url): return requests.get(url=url, headers=headers).content #进行随机保存 def saveVido(data): name=str(random.randint(0,9999))+'.mp4' with open(name,'wb') as f: f.write(data) print(name,'下载成功') for li in li_list: detail_url = 'https://www.pearvideo.com/' + li.xpath('./div/a/@href')[0] detail_page_text = requests.get(url=detail_url, headers=headers).text ex = 'srcUrl="(.*?)",vdoUrl' video_src = re.findall(ex, detail_page_text, re.S)[0] # 正则获取视屏url viseo_urls.append(video_src) print(viseo_urls) #使用线程池进行视频数据的异步下载 all_video_data_list=pool.map(getiVideoData, viseo_urls) #保存视频 pool.map(saveVido,all_video_data_list)