Webscrap и разбиение полученных данных на разные строки

Question

Я пытаюсь собрать дату, время и место проведения мероприятия. Они вышли успешно, но тогда это не дружелюбный читатель. Как сделать так, чтобы дата, время и место отображались отдельно, например:

- event
  Date:
  Time:
  Venue:

- event
  Date:
  Time:
  Venue:

Я думал о разделении, но у меня было много [], что сделало его еще более уродливым. Я думал о раздевании, но мое регулярное выражение, но, похоже, ничего не делает. Есть предложения?

from urllib.request import urlopen
from bs4 import BeautifulSoup
import re

url_toscrape = "https://www.ntu.edu.sg/events/Pages/default.aspx"
response = urllib.request.urlopen(url_toscrape)
info_type = response.info()
responseData = response.read()
soup = BeautifulSoup(responseData, 'lxml')

events_absFirst = soup.find_all("div",{"class": "ntu_event_summary_title_first"})
date_absAll = tr.find_all("div",{"class": "ntu_event_summary_date"})
events_absAll = tr.find_all("div",{"class": "ntu_event_summary_title"})

for first in events_absFirst:
    print('-',first.text.strip())
    print (' ',date)

for tr in soup.find_all("div",{"class":"ntu_event_detail"}):
    date_absAll = tr.find_all("div",{"class": "ntu_event_summary_date"})
    events_absAll = tr.find_all("div",{"class": "ntu_event_summary_title"})

    for events in events_absAll:
        events = events.text.strip()
    for date in date_absAll:
        date = date.text.strip('^Time.*')
    print ('-',events)
    print (' ',date)

Answer 1

Вы можете выполнить итерацию по div s, содержащему информацию о событии, сохранить результаты и затем распечатать каждое:

import requests, re
from bs4 import BeautifulSoup as soup
d = soup(requests.get('https://www.ntu.edu.sg/events/Pages/default.aspx').text, 'html.parser')
results = [[getattr(i.find('div', {'class':re.compile('ntu_event_summary_title_first|ntu_event_summary_title')}), 'text', 'N/A'), getattr(i.find('div', {'class':'ntu_event_summary_detail'}), 'text', 'N/A')] for i in d.find_all('div', {'class':'ntu_event_articles'})]
new_results = [[a, re.findall('Date : .*?(?=\sTime)|Time : .*?(?=Venue)|Time : .*?(?=$)|Venue: [\w\W]+', b)] for a, b in results]
print('\n\n'.join('-{}\n{}'.format(a, '\n'.join(f'  {h}:{i}' for h, i in zip(['Date', 'Time', 'Venue'], b))) for a, b in new_results))

Вывод:

-​​7th ASEF Rectors' Conference and Students' Forum (ARC7)
 Date:Date : 29 Nov 2018  to 14 May 2019
 Time:Time : 9:00am to 5:00pm

-​Be a Youth Corps Leader
 Date:Date : 1 Dec 2018  to 31 Mar 2019
 Time:Time : 9:00am to 5:00pm

-​NIE Visiting Artist Programme January 2019
 Date:Date : 14 Jan 2019  to 11 Apr 2019
 Time:Time : 9:00am to 8:00pm
 Venue:Venue: NIE Art gallery

-​Exercise Classes for You: Healthy Campus@NTU
 Date:Date : 21 Jan 2019  to 18 Apr 2019
 Time:Time : 6:00pm to 7:00pm
 Venue:Venue: The Wave @ Sports & Recreation Centre

-​[eLearning Course] Information & Media Literacy (From January 2019)
 Date:Date : 23 Jan 2019  to 31 May 2019
 Time:Time : 9:00am to 5:00pm
 Venue:Venue: NTULearn
 ...

Answer 2

Вы можете использовать запросы и проверить длину stripped_strings

import requests
from bs4 import BeautifulSoup
import pandas as pd

url_toscrape = "https://www.ntu.edu.sg/events/Pages/default.aspx"
response = requests.get(url_toscrape)

soup = BeautifulSoup(response.content, 'lxml')

events = [item.text for item in soup.select("[class^='ntu_event_summary_title']")]
data =  soup.select('.ntu_event_summary_date')
dates = []
times = []
venues = []

for item in  data:
        strings = [string for string in item.stripped_strings]
        if len(strings) == 3:
            dates.append(strings[0])
            times.append(strings[1])
            venues.append(strings[2])    
        elif len(strings) == 2:
            dates.append(strings[0])
            times.append(strings[1])
            venues.append('N/A')    
        elif len(strings) == 1:
            dates.append(strings[0])
            times.append('N/A')
            venues.append('N/A')   

results = list(zip(events, dates, times, venues))
df = pd.DataFrame(results)
print(df)