Question

我需要从网站中提取电话号码和网站链接以及大学的名称和国家/地区。该网站为https://www.whed.net/results_institutions.php?Chp2=Business%20Administration，问题是每个大学都需要点击一个+标志，然后需要提取数据，它需要关闭并继续进行下一个。

我尝试了多种硒测试方法，如下所示：

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.common.exceptions import TimeoutException
from selenium.webdriver.common.keys import Keys
import time
from bs4 import BeautifulSoup
import pandas as pd

#opening the web browser
browser = webdriver.Chrome('C:\\Users\\albert.malhotra\\Desktop\\Web Scrapings\\Kentucky State\\chromedriver')

#assigning the link to a variable
url = 'https://www.whed.net/results_institutions.php?Chp2=Business%20Administration'

#opening the url in browser while waiting 10 seconds for it to load
browser.get(url)
dfs = []
dfss = []
for n in range(50):
    html = browser.page_source
    soup = BeautifulSoup(html, 'lxml')

    for data in soup.find_all('p' , {'class' : 'country'}):
        item = data.text

        for thead in soup.find_all('div', {'class' : 'details'}):
            #data_2 = thead.find_all('a')
            data_2 = thead.select('h3')


            browser.find_element_by_link_text('More details').click()
            html_2 = browser.page_source
            soup_1 = BeautifulSoup(html_2, 'lxml')
            name = []
            for phone in soup_1.find_all('span' , {'class' : 'contenu'}):
                data_3 = phone.text
                name.append(data_3)
            browser.find_element_by_class_name("fancybox-item fancybox-close").click()
            dfss.append(data_2[0].text)
            dfs.append(item)

Answer 1

如果您仔细观察代码，则+符号会在弹出窗口中打开URL。因此，在这种情况下，无需单击+按钮然后遍历弹出窗口，而是很容易打开弹出窗口的URL然后遍历页面。这是执行此操作的代码。

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.common.action_chains import ActionChains
from selenium.webdriver.common.by import By


siteURL = "https://www.whed.net/results_institutions.php?Chp2=Business%20Administration"
browser = webdriver.Chrome(executable_path='chromedriver.exe')
browser.get((siteURL))

#this will return all the URL's of popups in an array
search = browser.find_elements_by_class_name('fancybox');
#For test purpose I used only first link
print (search[0].get_attribute("href"))
#This opens the page that comes in first pop up. Just parse the source code and get your data.
browser.get(search[0].get_attribute("href"))
#You can run a loop loop to traverse the complete array of URL's.

要获取URL的数量，可以使用array的length属性。

Answer 2

您不一定需要硒。您当然可以将请求用于较大的结果集。该页面通过运行SQL查询的服务器检索数据，该SQL查询具有记录计数参数，您可以根据需要调整结果数量nbr_ref_pge。您可以编写一个POST请求，该请求传递必要的信息，该信息随后将馈送到SQL查询中。现在，您可以计算出批处理的外观，以获取所需的总数，并查看是否存在偏移量。

我对asyncio经验不足，但是怀疑这是一个不错的方法，因为单个网站页面的请求计数很高。我仅尝试使用Session的情况就显示出来了。我从@datashaman

的答案中获得了重试语法

import requests
import pandas as pd
from bs4 import BeautifulSoup as bs
from requests.packages.urllib3.util.retry import Retry
from requests.adapters import HTTPAdapter

baseUrl = 'https://www.whed.net/'
searchTerm = 'Business Administration'
headers = {'Accept': 'application/json'}
params = {'Chp2' : searchTerm}
url = 'https://www.whed.net/results_institutions.php'
data = {
    'where': "(FOS LIKE '%|" + searchTerm + "|%')",
    'requete' : '(Fields of study=' + searchTerm + ')',
    'ret' : 'home.php',
    'afftri' : 'yes',
    'stat' : 'Fields of study',
    'sort' : 'InstNameEnglish,iBranchName',
    'nbr_ref_pge' : '1000'
}

results = []

with requests.Session() as s:
    retries = Retry(total=5,
                backoff_factor=0.1,
                status_forcelist=[ 500, 502, 503, 504 ])

    s.mount('http://', HTTPAdapter(max_retries=retries))
    res = s.post(url, params = params, headers = headers, data = data)
    soup = bs(res.content, 'lxml')
    links = set([baseUrl + item['href'] for item in soup.select("[href*='detail_institution.php?']")])

    for link in links:
        res = s.get(link)  
        soup = bs(res.content, 'lxml')
        items = soup.select('#contenu span')
        name = soup.select_one('#contenu h2').text.strip()
        country = soup.select_one('.country').text.strip()
        i = 0
        for item in items:
            if 'Tel.' in item.text:
                phone = items[i+1].text
            if 'WWW:' in item.text:
                website = items[i+1].text
            i+=1
        results.append([name, country, phone, website])
        name = country = phone = website = ''
df = pd.DataFrame(results)

Answer 3

要从website中提取大学的网站链接，您不需要 BeautifulSoup 和 Selenium 即可按照以下解决方案轻松提取所需的数据：

代码块：

from selenium import webdriver
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.common.by import By
from selenium.webdriver.support import expected_conditions as EC

options = webdriver.ChromeOptions()
options.add_argument('start-maximized')
options.add_argument('disable-infobars')
options.add_argument('--disable-extensions')
driver = webdriver.Chrome(chrome_options=options, executable_path=r'C:\WebDrivers\chromedriver.exe')
driver.get('https://www.whed.net/results_institutions.php?Chp2=Business%20Administration')
elements = WebDriverWait(driver, 30).until(EC.visibility_of_all_elements_located((By.CSS_SELECTOR, "a.detail.fancybox[title='More details']")))
for element in elements:
    WebDriverWait(driver, 30).until(EC.visibility_of(element)).click()
    WebDriverWait(driver, 10).until(EC.frame_to_be_available_and_switch_to_it((By.CSS_SELECTOR,"iframe.fancybox-iframe")))
    print(WebDriverWait(driver, 5).until(EC.visibility_of_element_located((By.CSS_SELECTOR, "a.lien"))).get_attribute("innerHTML"))
    driver.switch_to_default_content()
    driver.find_element_by_css_selector("a.fancybox-item.fancybox-close").click()
driver.quit()

控制台输出：

http://www.uni-ruse.bg
http://www.vspu.hr
http://www.vfu.bg
http://www.uni-svishtov.bg
http://www.universitateagbaritiu.ro
http://www.shu-bg.net
http://universityecotesbenin.com
http://www.vps-libertas.hr
http://www.swu.bg
http://www.zrinski.org/nikola

注意：现在可以轻松提取电话，名称和国家中的其余项目。< / p>

如何按时间顺序单击页面上的多个“ +”按钮并使用python从中提取数据？

3 个答案: