Python爬虫❤️ Urllib用法合集——⚡一键轻松入门爬虫⚡
Posted 是Dream呀
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前言：
接下来一起和大家重温一下爬虫吧~
轻松入门爬虫：
一、何为爬虫
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。
解释1：通过一个程序，根据Url(http://www.taobao.com)进行爬取网页，获取有用信息
解释2：使用程序模拟浏览器，去向服务器发送请求，获取响应信息
`
二、爬虫核心
1.爬取页面：爬取整个页面，包含页面中的所有内容
2.解析数据：将页面中你得到的数据，进行解析
3.难点：爬虫和反爬虫之间的博弈
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
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)
- 根据pagerank算法值进行排名（参考个网站流量、点击率等指标）
- 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)
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.request
url = '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
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
图片：
# 下载图片
# url_img='data:image/jpeg;base64,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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
语法：request = urllib.request.Request()
编码的由来：
由于计算机是美国人发明的，因此，最早只有127个字符被编码到计算机里，也就是大小写英文字母、数字和一些符号，
这个编码表被称为ASCII编码，比如大写字母A的编码是65，小写字母z的编码是122。
但是要处理中文显然一个字节是不够的，至少需要两个字节，而且还不能和ASCII编码冲突， 所以，中国制定了GB2312编码，用来把中文编进去。
你可以想得到的是，全世界有上百种语言，日本把日文编到Shift_JIS里，韩国把韩文编到Euc‐kr里，
各国有各国的标准，就会不可避免地出现冲突，结果就是，在多语言混合的文本中，显示出来会有乱码。
因此，Unicode应运而生。Unicode把所有语言都统一到一套编码里，这样就不会再有乱码问题了。
Unicode标准也在不断发展，但最常用的是用两个字节表示一个字符（如果要用到非常偏僻的字符，就需要4个字节）。
现代操作系统和大多数编程语言都直接支持Unicode。
八、编解码
1.get请求方式：urllib.parse.quote（）
# -*-coding:utf-8 -*-
# @Author:到点了,心疼徐哥哥
# 奥利给干！！！
import urllib.request
import urllib.parse
url = '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 = {
'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.parse
url = '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/537.36'
}
data = {
'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 json
obj = json.loads(content)
print(obj)
总结：post和get区别
1：get请求方式的参数必须编码，参数是拼接到url后面，编码之后不需要调用encode方法
2：post请求方式的参数必须编码，参数是放在请求对象定制的方法中，编码之后需要调用encode方法
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