找不到使用BeautifulSoup Python的HTML元素

Question

我在https://towardsdatascience.com/网站上找到了一个非常好的网页抓取代码，我正在尝试实现它以供我自己使用

https://ingatlan.com/lista/elado+lakas+ii-ker?page=1这是一个匈牙利房地产网站。首先，我只想获取房地产的价格，但是如果我运行代码，我没有得到任何结果，找到的项目数是0

import urllib.request,sys,time
from bs4 import BeautifulSoup
import requests
import pandas as pd

pagesToGet= 1

upperframe=[]  
for page in range(1,pagesToGet+1):
    print('processing page :', page)
    url = 'https://ingatlan.com/lista/elado+lakas+ii-ker?page='+str(page)
    print(url)
    
    
    try:
        page=requests.get(url)                            
    
    except Exception as e:                                   
        error_type, error_obj, error_info = sys.exc_info()     
        print ('ERROR FOR LINK:',url)                          
        print (error_type, 'Line:', error_info.tb_lineno)     
        continue                                              
    time.sleep(2)   
    soup=BeautifulSoup(page.text,'html.parser')
    frame=[]
    links=soup.find_all('div',attrs={'class':'listing js-listing '})
    print(len(links))
    filename="NEWS.csv"
    f=open(filename,"w", encoding = 'utf-8')
    headers="Price\n"
    f.write(headers)
    
for j in links:
        Price = j.find("div",attrs={'class':'price'})
        frame.append((Price))
        upperframe.extend(frame)
f.close()
data=pd.DataFrame(upperframe, columns=['Price'])
data.head()

我能毁了什么？有一些网站是它的工作场所，比如Myprotein，但也有一些地方不是

Answer 1

这里只有你要求的价格

如果没有用户代理，它将给出403错误禁止

import requests
from bs4 import BeautifulSoup
import pandas as pd

start_url="https://ingatlan.com/lista/elado+lakas+ii-ker?page=1"
page_data=requests.get(start_url, headers={'User-Agent': 'XYZ/3.0'})
soup=BeautifulSoup(page_data.content,"html.parser")

#for i in soup:  #i was first just checking http staus here 
    #print(i)    #without useragent i got 403 as response
    #print()
    
Price=[]

for job_tag in soup.find_all("div",class_="resultspage__content"):
    for job_tag2 in job_tag.find_all("div",class_="listing js-listing"):
        for job_tag3 in job_tag2.find_all("div",class_="price__container js-has-sqm-price-info-tooltip"): 


            price=job_tag3.find("div",class_="price")
            Price.append(price.text.strip())
            #print(Price)

data=pd.DataFrame(Price,columns=["price"])
print(data)

数据帧的输出

         price
0    31.5 M Ft
1    77.9 M Ft
2      62 M Ft
3   129.5 M Ft
4     125 M Ft
5    95.9 M Ft
6    46.9 M Ft
7    45.9 M Ft
8    59.9 M Ft
9     109 M Ft
10     48 M Ft
11     87 M Ft