场景
最近在学习爬虫，实践使用的是https://scrape.center/ 网站环境
网站的环境是一个系列的，一个系列中不通关卡考验的是小技巧，目前的环境是第一个环境，结果爬取的是所有的电影地址，标题，主题，分数，剧情简介
技术
主要使用的是request库和BeautifulSoup，最后导出一个csv文档
关卡
第一关 ssr1
电影数据网站，无反爬，数据通过服务端渲染，适合基本爬虫练习。
import pandas as pd
import urllib3
from bs4 import BeautifulSoup
import requests
urllib3.disable_warnings() #去除因为网页没有ssl证书出现的警告
url,title,theme,score,content = [],[],[],[],[]
headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) '
'Chrome/87.0.4280.141 Safari/537.36'}
global url_list,title_list,theme_list,score_list,content_list
for i in range(1,11):
the_url = 'https://ssr1.scrape.center/page/' + str(i)
html = requests.get(the_url,headers=headers,verify=False)
soup = BeautifulSoup(html.content,'lxml')
url_list = soup.find_all(class_='name')
for x in url_list :
url.append('https://ssr1.scrape.center'+x['href'])
for a in url :
html = requests.get(a,headers=headers,verify=False)
soup = BeautifulSoup(html.content, 'lxml')
title_list = soup.find_all(class_='m-b-sm')
theme_list = soup.find_all(class_='categories')
score_list = soup.find_all(class_='score m-t-md m-b-n-sm')
content_list = soup.find_all("div",class_='drama')
for y,z,i,x in zip(title_list,theme_list,score_list,content_list):
title.append(y.text)
theme.append(z.text.replace('\n','').replace('\r',''))
score.append(i.text.strip())
content.append(x.text.replace('剧情简介','').replace('\n','').replace('\r','').strip())
bt = {
'链接':url,
'标题':title,
'主题':theme,
'评分':score,
'剧情简介':content
}
work = pd.DataFrame(bt)
work.to_csv('work.csv')
第二关 ssr2
电影数据网站，无反爬，无 HTTPS 证书，适合用作 HTTPS 证书验证。
上关代码可以继续使用，能够爬取结果
第三关 ssr3
电影数据网站，无反爬，带有 HTTP Basic Authentication，适合用作 HTTP 认证案例，用户名密码均为 admin。
这一关主要考验的是网站初始登录HTTP认证，在代码第一次访问网站中添加认证
auth = HTTPBasicAuth('admin','admin')
html = requests.get(the_url,headers=headers,auth=auth,verify=False)
总代码
import pandas as pd
import urllib3
from bs4 import BeautifulSoup
import requests
from requests.auth import HTTPBasicAuth
urllib3.disable_warnings() #去除因为网页没有ssl证书出现的警告
url,title,theme,score,content = [],[],[],[],[]
headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) '
'Chrome/87.0.4280.141 Safari/537.36'}
global url_list,title_list,theme_list,score_list,content_list
for i in range(1,11):
the_url = 'https://ssr3.scrape.center/page/' + str(i)
auth = HTTPBasicAuth('admin','admin')
html = requests.get(the_url,headers=headers,auth=auth,verify=False)
soup = BeautifulSoup(html.content,'lxml')
url_list = soup.find_all(class_='name')
for x in url_list :
url.append('https://ssr1.scrape.center'+x['href'])
for a in url :
html = requests.get(a,headers=headers,verify=False)
soup = BeautifulSoup(html.content, 'lxml')
title_list = soup.find_all(class_='m-b-sm')
theme_list = soup.find_all(class_='categories')
score_list = soup.find_all(class_='score m-t-md m-b-n-sm')
content_list = soup.find_all("div",class_='drama')
for y,z,i,x in zip(title_list,theme_list,score_list,content_list):
title.append(y.text)
theme.append(z.text.replace('\n','').replace('\r',''))
score.append(i.text.strip())
content.append(x.text.replace('剧情简介','').replace('\n','').replace('\r','').strip())
bt = {
'链接':url,
'标题':title,
'主题':theme,
'评分':score,
'剧情简介':content
}
work = pd.DataFrame(bt)
work.to_csv('work.csv')
第四关 ssr4
电影数据网站，无反爬，每个响应增加了 5 秒延迟，适合测试慢速网站爬取或做爬取速度测试，减少网速干扰。
这关主要是限制了延迟，在网站中添加超时时间，因为他设置的是5秒延迟，但是在实际测试还有其他的延迟，所以需要15秒左右以上的时间进行访问，不然会访问超时
html = requests.get(the_url,headers=headers,verify=False,timeout=15)
在这里因为延迟关系，所以只爬取第一页，并没有所有爬取
总代码
import pandas as pd
import urllib3
from bs4 import BeautifulSoup
import requests
global url_list, title_list, theme_list, score_list, content_list
urllib3.disable_warnings() #去除因为网页没有ssl证书出现的警告
url,title,theme,score,content = [],[],[],[],[]
headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) '
'Chrome/87.0.4280.141 Safari/537.36'}
the_url = 'https://ssr4.scrape.center/page/1'
html = requests.get(the_url,headers=headers,verify=False,timeout=15)
soup = BeautifulSoup(html.content,'lxml')
url_list = soup.find_all(class_='name')
for x in url_list :
url.append('https://ssr1.scrape.center'+x['href'])
for a in url :
html = requests.get(a,headers=headers,verify=False,timeout=15)
soup = BeautifulSoup(html.content, 'lxml')
title_list = soup.find_all(class_='m-b-sm')
theme_list = soup.find_all(class_='categories')
score_list = soup.find_all(class_='score m-t-md m-b-n-sm')
content_list = soup.find_all("div",class_='drama')
for y,z,i,x in zip(title_list,theme_list,score_list,content_list):
title.append(y.text)
theme.append(z.text.replace('\n','').replace('\r',''))
score.append(i.text.strip())
content.append(x.text.replace('剧情简介','').replace('\n','').replace('\r','').strip())
bt = {
'链接':url,
'标题':title,
'主题':theme,
'评分':score,
'剧情简介':content
}
work = pd.DataFrame(bt)
work.to_csv('work.csv')
[复制链接]
发表于 2021-11-2 09:51
|
发表于 2021-11-2 10:48
