使用pandas和bs4从网页上获取信息并写入.xls文件

Question

我是Python编程的初学者。我正在使用python中的bs4模块练习网络抓取。

我已经从网页中提取了一些字段，但是当我尝试将它们写入.xls文件时，.xls文件除标题外仍然为空。 请告诉我我在哪里做错了，如果可能的话，建议要做什么。

from bs4 import BeautifulSoup as bs
import pandas as pd

res = requests.get('https://rwbj.com.au/find-an-agent.html')
soup = bs(res.content, 'lxml')

data = soup.find_all("div",{"class":"fluidgrid-cell fluidgrid-cell-2"})

records = []
name =[]
phone =[]
email=[]
title=[]
location=[]
for item in data:
    name = item.find('h3',class_='heading').text.strip()
    phone = item.find('a',class_='text text-link text-small').text.strip()
    email = item.find('a',class_='text text-link text-small')['href']
    title = item.find('div',class_='text text-small').text.strip()
    location = item.find('div',class_='text text-small').text.strip()

    records.append({'Names': name, 'Title': title, 'Email': email, 'Phone': phone, 'Location': location})

df = pd.DataFrame(records,columns=['Names','Title','Phone','Email','Location'])
df=df.drop_duplicates()
df.to_excel(r'C:\Users\laptop\Desktop\R&W.xls', sheet_name='MyData2', index = False, header=True)

Answer 1

如果您不想使用硒，则可以制作相同的帖子请求网页。这将给您一个xml响应，您可以使用Beautifulsoup进行解析以获得所需的输出。

我们可以使用检查工具中的“网络”标签来获取正在发出的请求以及该请求的表单数据。

接下来，我们必须使用python-requests发出相同的请求，然后解析输出。

import requests
from bs4 import BeautifulSoup
import pandas as pd
number_of_agents_required=20 # they only have 20 on the site
payload={
'act':'act_fgxml',
'15[offset]':0,
'15[perpage]':number_of_agents_required,
'require':0,
'fgpid':15,
'ajax':1
}
records=[]
r=requests.post('https://www.rwbj.com.au/find-an-agent.html',data=payload)
soup=BeautifulSoup(r.text,'lxml')
for row in soup.find_all('row'):
    name=row.find('name').text
    title=row.position.text.replace('&','&')
    email=row.email.text
    phone=row.phone.text
    location=row.office.text
    records.append([name,title,email,phone,location])
df=pd.DataFrame(records,columns=['Names','Title','Phone','Email','Location'])
df.to_excel('R&W.xls', sheet_name='MyData2', index = False, header=True)

输出：

Answer 2

您可以使用诸如硒之类的方法来实现内容的javascript呈现。然后，您可以获取page_source以继续执行脚本。我特意保留了您的脚本，只添加了新行以等待内容。

您可以无头运行selenium或切换为使用HTMLSession。

from bs4 import BeautifulSoup as bs
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
import pandas as pd

d = webdriver.Chrome()
d.get('https://rwbj.com.au/find-an-agent.html')

WebDriverWait(d,10).until(EC.presence_of_all_elements_located((By.CSS_SELECTOR, "h3")))

soup = bs(d.page_source, 'lxml')
d.quit()
data = soup.find_all("div",{"class":"fluidgrid-cell fluidgrid-cell-2"})

records = []
name =[]
phone =[]
email=[]
title=[]
location=[]
for item in data:
    name = item.find('h3',class_='heading').text.strip()
    phone = item.find('a',class_='text text-link text-small').text.strip()
    email = item.find('a',class_='text text-link text-small')['href']
    title = item.find('div',class_='text text-small').text.strip()
    location = item.find('div',class_='text text-small').text.strip()
    records.append({'Names': name, 'Title': title, 'Email': email, 'Phone': phone, 'Location': location})

df = pd.DataFrame(records,columns=['Names','Title','Phone','Email','Location'])
print(df)

---

我可能会考虑以下问题，具体取决于是否每个人都有所有物品：

from bs4 import BeautifulSoup as bs
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.chrome.options import Options
import pandas as pd

options = Options()
options.headless = True

d = webdriver.Chrome(options = options) 
d.get('https://rwbj.com.au/find-an-agent.html')

WebDriverWait(d,10).until(EC.presence_of_all_elements_located((By.CSS_SELECTOR, "h3")))

soup = bs(d.page_source, 'lxml')
d.quit()
names = [item.text for item in soup.select('h3')]
titles = [item.text for item in soup.select('h3 ~ div:nth-of-type(1)')]
tels = [item.text for item in soup.select('h3 + a')]
emails = [item['href'] for item in soup.select('h3 ~ a:nth-of-type(2)')]
locations = [item.text for item in soup.select('h3 ~ div:nth-of-type(2)')]      
records = list(zip(names, titles, tels, emails, positions))
df = pd.DataFrame(records,columns=['Names','Title','Phone','Email','Location'])
print(df)