全网最全python爬虫系统进阶学习(附原代码)学完可就业（爬虫python入门代码）

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第一章 爬虫介绍

1.认识爬虫

第二章：requests实战（基础爬虫）

1.豆瓣电影爬取

2.肯德基餐厅查询

3.破解百度翻译

4.搜狗首页

5.网页采集器

6.药监总局相关数据爬取

第三章：爬虫数据分析（bs4,xpath,正则表达式)

1.bs4解析基础

2.bs4案例

3.xpath解析基础

4.xpath解析案例-4k图片解析爬取

5.xpath解析案例-58二手房

6.xpath解析案例-爬取站长素材中免费简历模板

7.xpath解析案例-全国城市名称爬取

8.正则解析

9.正则解析-分页爬取

10.爬取图片

第四章：自动识别验证码

1.古诗文网验证码识别

fateadm_api.py(识别需要的配置，建议放在同一文件夹下）

调用api接口

第五章：request模块高级（模拟登录）

1.代理操作

2.模拟登陆人人网

3.模拟登陆人人网

第六章：高性能异步爬虫(线程池，协程)

1.aiohttp实现多任务异步爬虫

2.flask服务

3.多任务协程

4.多任务异步爬虫

5.示例

6.同步爬虫

7.线程池基本使用

8.线程池在爬虫案例中的应用

9.协程

第七章：动态加载数据处理(selenium模块应用,模拟登录12306)

1.selenium基础用法

2.selenium其他自动操作

3.12306登录示例代码

4.动作链与iframe的处理

5.谷歌无头浏览器+反检测

6.基于selenium实现1236模拟登录

7.模拟登录qq空间

第八章：scrapy框架

1.各种项目实战，scrapy各种配置修改

2.bossPro示例

3.bossPro示例

4.数据库示例

第一章 爬虫介绍

第0关 认识爬虫

1、初始爬虫

爬虫，从本质上来说，就是利用程序在网上拿到对我们有价值的数据。

2、明晰路径

2-1、浏览器工作原理

（1）解析数据：当服务器把数据响应给浏览器之后，浏览器并不会直接把数据丢给我们。因为这些数据是用计算机的语言写的，浏览器还要把这些数据翻译成我们能看得懂的内容；

（2）提取数据：我们就可以在拿到的数据中，挑选出对我们有用的数据；

（3）存储数据：将挑选出来的有用数据保存在某一文件/数据库中。

2-2、爬虫工作原理

第二章：requests实战（基础爬虫）

1.豆瓣电影爬取

import requests import json headers = { 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/86.0.4240.193 Safari/537.36' } url = "https://movie.douban.com/j/chart/top_list" params = { 'type': '24', 'interval_id': '100:90', 'action': '', 'start': '0',#从第几部电影开始取 'limit': '20'#一次取出的电影的个数 } response = requests.get(url,params = params,headers = headers) list_data = response.json() fp = open('douban.json','w',encoding= 'utf-8') json.dump(list_data,fp = fp,ensure_ascii= False) print('over!!!!')

2.肯德基餐厅查询

import requests headers = { 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/86.0.4240.193 Safari/537.36' } url = 'http://www.kfc.com.cn/kfccda/ashx/GetStoreList.ashx?op=keyword' word = input('请输入一个地址：') params = { 'cname': '', 'pid': '', 'keyword': word, 'pageIndex': '1', 'pageSize': '10' } response = requests.post(url,params = params ,headers = headers) page_text = response.text fileName = word + '.txt' with open(fileName,'w',encoding= 'utf-8') as f: f.write(page_text)

3.破解百度翻译

import requests import json headers = { 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/86.0.4240.193 Safari/537.36' } post_url = 'https://fanyi.baidu.com/sug' word = input('enter a word:') data = { 'kw':word } response = requests.post(url = post_url,data = data,headers = headers) dic_obj = response.json() fileName = word + '.json' fp = open(fileName,'w',encoding= 'utf-8') #ensure_ascii = False,中文不能用ascii代码 json.dump(dic_obj,fp = fp,ensure_ascii = False) print('over!')

4.搜狗首页

import requests url = 'https://www.sogou.com/?pid=sogou-site-d5da28d4865fb927' response = requests.get(url) page_text = response.text print(page_text) with open('./sougou.html','w',encoding= 'utf-8') as fp: fp.write(page_text) print('爬取数据结束!!!')

5.网页采集器

import requests headers = { 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/86.0.4240.193 Safari/537.36' } url = 'https://www.sogou.com/sogou' kw = input('enter a word:') param = { 'query':kw } response = requests.get(url,params = param,headers = headers) page_text = response.text fileName = kw +'.html' with open(fileName,'w',encoding= 'utf-8') as fp: fp.write(page_text) print(fileName,'保存成功!!!')

6.药监总局相关数据爬取

import requests import json url = "http://scxk.nmpa.gov.cn:81/xk/itownet/portalAction.do?method=getXkzsList" headers = { 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/89.0.4385.0 Safari/537.36' } for page in range(1,6): page = str(page) data = { 'on': 'true', 'page': page, 'pageSize': '15', 'productName':'', 'conditionType': '1', 'applyname': '', 'applysn':'' } json_ids = requests.post(url,data = data,headers = headers).json() id_list = [] for dic in json_ids['list']: id_list.append(dic['ID']) #print(id_list) post_url = 'http://scxk.nmpa.gov.cn:81/xk/itownet/portalAction.do?method=getXkzsById' all_data_list = [] for id in id_list: data = { 'id':id } datail_json = requests.post(url = post_url,data = data,headers = headers).json() #print(datail_json,'---------------------over') all_data_list.append(datail_json) fp = open('allData.json','w',encoding='utf-8') json.dump(all_data_list,fp = fp,ensure_ascii= False) print('over!!!')

第三章：爬虫数据分析（bs4,xpath,正则表达式)

1.bs4解析基础

from bs4 import BeautifulSoup fp = open('第三章 数据分析/text.html','r',encoding='utf-8') soup = BeautifulSoup(fp,'lxml') #print(soup) #print(soup.a) #print(soup.div) #print(soup.find('div')) #print(soup.find('div',class_="song")) #print(soup.find_all('a')) #print(soup.select('.tang')) #print(soup.select('.tang > ul > li >a')[0].text) #print(soup.find('div',class_="song").text) #print(soup.find('div',class_="song").string) print(soup.select('.tang > ul > li >a')[0]['href'])

2.bs4案例

from bs4 import BeautifulSoup import requests headers = { 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/86.0.4240.193 Safari/537.36' } url = "http://sanguo.5000yan.com/" page_text = requests.get(url ,headers = headers).content #print(page_text) soup = BeautifulSoup(page_text,'lxml') li_list = soup.select('.list > ul > li') fp = open('./sanguo.txt','w',encoding='utf-8') for li in li_list: title = li.a.string #print(title) detail_url = 'http://sanguo.5000yan.com/'+li.a['href'] print(detail_url) detail_page_text = requests.get(detail_url,headers = headers).content detail_soup = BeautifulSoup(detail_page_text,'lxml') div_tag = detail_soup.find('div',class_="grap") content = div_tag.text fp.write(title+":"+content+'\n') print(title,'爬取成功！！！')

3.xpath解析基础

from lxml import etree tree = etree.parse('第三章 数据分析/text.html') # r = tree.xpath('/html/head/title') # print(r) # r = tree.xpath('/html/body/div') # print(r) # r = tree.xpath('/html//div') # print(r) # r = tree.xpath('//div') # print(r) # r = tree.xpath('//div[@class="song"]') # print(r) # r = tree.xpath('//div[@class="song"]/P[3]') # print(r) # r = tree.xpath('//div[@class="tang"]//li[5]/a/text()') # print(r) # r = tree.xpath('//li[7]/i/text()') # print(r) # r = tree.xpath('//li[7]//text()') # print(r) # r = tree.xpath('//div[@class="tang"]//text()') # print(r) # r = tree.xpath('//div[@class="song"]/img/@src') # print(r)

4.xpath解析案例-4k图片解析爬取

import requests from lxml import etree import os headers = { 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/86.0.4240.193 Safari/537.36' } url = 'http://pic.netbian.com/4kmeinv/' response = requests.get(url,headers = headers) #response.encoding=response.apparent_encoding #response.encoding = 'utf-8' page_text = response.text tree = etree.HTML(page_text) li_list = tree.xpath('//div[@class="slist"]/ul/li') # if not os.path.exists('./picLibs'): # os.mkdir('./picLibs') for li in li_list: img_src = 'http://pic.netbian.com/'+li.xpath('./a/img/@src')[0] img_name = li.xpath('./a/img/@alt')[0]+'.jpg' img_name = img_name.encode('iso-8859-1').decode('gbk') # print(img_name,img_src) # print(type(img_name)) img_data = requests.get(url = img_src,headers = headers).content img_path ='picLibs/'+img_name #print(img_path) with open(img_path,'wb') as fp: fp.write(img_data) print(img_name,"下载成功")

5.xpath解析案例-58二手房

import requests from lxml import etree url = 'https://bj.58.com/ershoufang/p2/' headers = { 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/86.0.4240.193 Safari/537.36' } page_text = requests.get(url=url,headers = headers).text tree = etree.HTML(page_text) li_list = tree.xpath('//section[@class="list-left"]/section[2]/div') fp = open('58.txt','w',encoding='utf-8') for li in li_list: title = li.xpath('./a/div[2]/div/div/h3/text()')[0] print(title) fp.write(title+'\n')

6.xpath解析案例-爬取站长素材中免费简历模板

import requests from lxml import etree import os headers = { 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/86.0.4240.193 Safari/537.36' } url = 'https://www.aqistudy.cn/historydata/' page_text = requests.get(url,headers = headers).text

7.xpath解析案例-全国城市名称爬取

import requests from lxml import etree import os headers = { 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/86.0.4240.193 Safari/537.36' } url = 'https://www.aqistudy.cn/historydata/' page_text = requests.get(url,headers = headers).text tree = etree.HTML(page_text) # holt_li_list = tree.xpath('//div[@class="bottom"]/ul/li') # all_city_name = [] # for li in holt_li_list: # host_city_name = li.xpath('./a/text()')[0] # all_city_name.append(host_city_name) # city_name_list = tree.xpath('//div[@class="bottom"]/ul/div[2]/li') # for li in city_name_list: # city_name = li.xpath('./a/text()')[0] # all_city_name.append(city_name) # print(all_city_name,len(all_city_name)) #holt_li_list = tree.xpath('//div[@class="bottom"]/ul//li') holt_li_list = tree.xpath('//div[@class="bottom"]/ul/li | //div[@class="bottom"]/ul/div[2]/li') all_city_name = [] for li in holt_li_list: host_city_name = li.xpath('./a/text()')[0] all_city_name.append(host_city_name) print(all_city_name,len(all_city_name))

8.正则解析

import requests import re import os if not os.path.exists('./qiutuLibs'): os.mkdir('./qiutuLibs') url = 'https://www.qiushibaike.com/imgrank/' headers = { 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/89.0.4385.0 Safari/537.36' } page_text = requests.get(url,headers = headers).text ex = '

.*?

fateadm_api.py(识别需要的配置，建议放在同一文件夹下）

调用api接口

字数20000字限制，无法上传更多，见谅，公众号上有完整资源。

个人公众号 yk 坤帝

后台回复 scrapy 获取整理资源

Python 爬虫

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