#yyds干货盘点#Python爬虫之Urllib用法合集

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#yyds干货盘点#Python爬虫之Urllib用法合集

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@TOC
一、何为爬虫
#yyds干货盘点#Python爬虫之Urllib用法合集

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网络爬虫(又被称为网页蜘蛛,网络机器人,在FOAF社区中间,更经常的称为网页追逐者),是一种按照一定的规则,自动地抓取万维网信息的程序或者脚本。
我们平时的上网就是浏览器提交请求-> 下载网页代码-> 解析/渲染成页面。而我们的爬虫就是模拟浏览器发送请求-> 下载网页代码-> 只提取有用的数据-> 存放于数据库或文件中。所以,我们的爬虫程序只提取网页代码中对我们有用的数据。
如果我们把互联网比作一张大的蜘蛛网,那计算机上的数据便是蜘蛛网上的一个猎物,而`爬虫程序就是一只小蜘蛛,沿着蜘蛛网抓取自己想要的数据。
`
二、爬虫核心三、爬虫的用途1.数据分析 / 人工数据集
2.社交软件冷启动
3.舆情控制
4.竞争对手监控
#yyds干货盘点#Python爬虫之Urllib用法合集

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四、爬虫分类 1.通用爬虫:实例: 百度、360、google、sougou等搜索引擎‐‐‐伯乐在线
功能: 访问网页‐> 抓取数据‐> 数据存储‐> 数据处理‐> 提供检索服务
robots协议一个约定俗成的协议,添加robots.txt文件,来说明本网站哪些内容不可以被抓取,起不到限制作用 自己写的爬虫无需遵守
网站排名(SEO)
  1. 根据pagerank算法值进行排名(参考个网站流量、点击率等指标)
  2. 百度竞价排名
缺点:
1.抓取的数据大多是无用的
2.不能根据用户的需求来精准获取数据
2.聚焦爬虫功能: 根据需求,实现爬虫程序,抓取需要的数据
设计思路:
1.确定要爬取的url 如何获取Url
2.模拟浏览器通过http协议访问url,获取服务器返回的html代码 如何访问
3.解析html字符串(根据一定规则提取需要的数据) 如何解析
五、反爬手段 1.User‐Agent:User Agent中文名为用户代理,简称 UA,它是一个特殊字符串头,使得服务器能够识别客户使用的操作系统及版,urllib库使用 7.请求对象的定制 扩展:编码的由来 User Agent中文名为用户代理,简称 UA,它是一个特殊字符串头,使得服务器能够识别客户使用的操作系统及版 本、CPU 类型、浏览器及版本、浏览器渲染引擎、浏览器语言、浏览器插件等。
2.代理IP西次代理
快代理
什么是高匿名、匿名和透明代理?它们有什么区别?
1.使用透明代理,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。
2.使用匿名代理,对方服务器可以知道你使用了代理,但不知道你的真实IP。
3.使用高匿名代理,对方服务器不知道你使用了代理,更不知道你的真实IP。
3.验证码访问打码平台 :云打码平台
4.动态加载网页网站返回的是js数据 并不是网页的真实数据
selenium驱动真实的浏览器发送请求
5.数据加密分析js代码
六、.urllib库使用 1.爬取网站界面urllib.request.urlopen() 模拟浏览器向服务器发送请求
response 服务器返回的数据 response的数据类型是HttpResponse
# -*-coding:utf-8 -*- # @Author:到点了,心疼徐哥哥 # 奥利给干!!! # # 使用urllib获取百度首页源码 import urllib.request# 1.定义一个url 就是要访问的地址 url = https://www.bilibili.com/# 2.模拟浏览器向服务器发送请求 response响应 response = urllib.request.urlopen(url)# 3.获取响应中的页面中的源码 content内容 # read方法 返回的是字节形式的二进制字 # 将二进制的数据转换为字符串 # 二进制到字符串 解码! decode(编码的格式) content = response.read().decode(utf-8)# 打印数据 print(content)

#yyds干货盘点#Python爬虫之Urllib用法合集

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2.一个类型,六个方法
# -*-coding:utf-8 -*- # @Author:到点了,心疼徐哥哥 # 奥利给干!!! import urllib.requesturl = https://www.bilibili.com/# 模拟浏览器向服务器发送请求 response = urllib.request.urlopen(url)# 一个类型:HTTPResponse # 六个方法:read readline readlines getcode geturl getheader# 返回多少个字节 # content = response.read(5) # print(content)# 读取一行 # content=response.readline() # print(content)# 一行一行的读,直至读完 # content=response.readlines() # print(content)# 返回状态码 如果是200,就证明我们的逻辑没有错误 # print(response.getcode())# 返回url地址 # print(response.geturl())# 获取一个状态信息 print(response.getheaders())

3.下载网页、图片and视频【#yyds干货盘点#Python爬虫之Urllib用法合集】网页:
import urllib.request # 下载网页 # url_page=https://www.bilibili.com/ # # url代表的是下载的路径 filename是文件的名字 # 在python中 可以是变量的名字也可以是直接写值 # urllib.request.urlretrieve(url_page,bilibili.html)# 后缀很重要

#yyds干货盘点#Python爬虫之Urllib用法合集

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图片:
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# urllib.request.urlretrieve(url=url_img,filename=xzq.jpg)

视频:
# 下载视频 url_video=https://vd2.bdstatic.com/mda-mj01i9fur5bzkwj7/sc/cae_h264/1633050469983308417/mda-mj01i9fur5bzkwj7.mp4?v_from_s=hkapp-haokan-hnb& auth_key=1633070432-0-0-e7d194ed5654813f4560e2184fbff9e0& bcevod_channel=searchbox_feed& pd=1& pt=3& abtest= urllib.request.urlretrieve(url_video,阅兵.mp4)

七.请求对象的定制UA介绍:User Agent中文名为用户代理,简称 UA,它是一个特殊字符串头,使得服务器能够识别客户使用的操作系统 及版本、CPU 类型、浏览器及版本。浏览器内核、浏览器渲染引擎、浏览器语言、浏览器插件等
编码的由来:
# -*-coding:utf-8 -*- # @Author:到点了,心疼徐哥哥 # 奥利给干!!! import urllib.request import urllib.parseurl = https://www.baidu.com/s?wd= # 请求对象的定制为了解决反爬的第一种手段 headers = User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.61 Safari/537.36# 将周杰伦三个字变为unicode编码的格式 # 我们需要依赖于urllib.parse name = urllib.parse.quote(薛之谦)url = url + name # print(url)# 请求对象的定制 request = urllib.request.Request(url=url,headers=headers)# 模拟浏览器向服务器发送请求 response = urllib.request.urlopen(request)# 获取响应的内容 content = response.read().decode(utf-8)# 打印数据 print(content)

2.get请求方式:urllib.parse.urlencode()
# -*-coding:utf-8 -*- # @Author:到点了,心疼徐哥哥 # 奥利给干!!! # urlencode 应用场景:多个参数的时候 import urllib.request import urllib.parse base_url=https://www.baidu.com/s?data = https://www.songbingjia.com/android/wd:周杰伦, sex:男 new_data = urllib.parse.urlencode(data)# 请求资源路径 url = base_url +new_data# print(new_data) headers = User-Agent:Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.61 Safari/537.36# 请求对象的定制 request = urllib.request.Request(url=url,headers=headers)# 模拟浏览器向服务器发送请求 response = urllib.request.urlopen(request)# 获取网页源码的数据 content = response.read().decode(utf-8) print(content)

3.post请求方式
# -*-coding:utf-8 -*- # @Author:到点了,心疼徐哥哥 # 奥利给干!!! import urllib.request import urllib.parseurl = https://fanyi.baidu.com/sug headers = User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.61 Safari/537.36data = https://www.songbingjia.com/android/kw:spider# post请求的参数 必须进行编码 data = urllib.parse.urlencode(data).encode(utf8)# post请求的参数,不会拼接在url的后立案,需要放在请求对象定制的参数中 request = urllib.request.Request(url=url,data=data,headers=headers)# 模拟服务器发送求求 response=urllib.request.urlopen(request)# 获取响应的数据 content = response.read().decode(utf8) # print(content)# post请求的参数必须编码:data = urllib.parse.urlencode(data) # 编码之后 必须调用encode方法:data = urllib.parse.urlencode(data).encode(utf8) # 参数是放在请求对象定制的方法中:request = urllib.request.Request(url=url,data=data,headers=headers)# 字符串———》json对象 import jsonobj = json.loads(content) print(obj)

#yyds干货盘点#Python爬虫之Urllib用法合集

文章图片

总结:post和get区别

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