单击使用循环使用同一类名称的多个Divs

Question

我正在尝试单击具有同一类名称的多个DIV。解析HTML页面，提取一些信息并返回同一页面。 在此 page 。

1. 选择项目并提取相关信息
2. 返回 page < /a>
3. 单击下一个项目。

这在for循环之外完美地工作。

WebDriverWait(wd, 20).until(EC.element_to_be_clickable((By.XPATH,'//*[@class="product__wrapper"][1]'))).click()

但是，当我在循环中使用上述命令时。它引发了错误的错误sectectorexception

for i in range(1,len(all_profile_url)):
        
        
        WebDriverWait(wd, 20).until(EC.element_to_be_clickable((By.XPATH,'//*[@class="product__wrapper"][{i}]'))).click()
        time.sleep(10)
        wd.execute_script('window.scrollTo(0,1000)')
        
        page_source = BeautifulSoup(wd.page_source, 'html.parser')

        info_div = page_source.find('div', class_='ProductInfoCard__Breadcrumb-sc-113r60q-4 cfIqZP')

        info_block = info_div.find_all('a')
        try:
            info_category = info_block[1].get_text().strip()
        except IndexError:
            info_category ="Null"
        wd.back()
        time.sleep(5)

，我想使用以下代码从每个页面中提取什么

page_source = BeautifulSoup(wd.page_source, 'html.parser')

info_div = page_source.find('div', class_='ProductInfoCard__Breadcrumb-sc-113r60q-4 cfIqZP')

info_block = info_div.find_all('a')
try:
    info_category = info_block[1].get_text().strip()
except IndexError:
    info_category ="Null"

try:
    info_sub_category = info_block[2].get_text().strip()
except IndexError:
    info_sub_category='Null'

try:
    info_product_name = info_div.find_all('span')[0].get_text().strip()
except IndexError:
    info_product_name='null'


# Extract Brand name
info_div_1 = page_source.find('div', class_='ProductInfoCard__BrandContainer-sc-113r60q-9 exyKqL')
try:
    info_brand = info_div_1.find_all('a')[0].get_text().strip()
except IndexError:
    info_brand='null'


# Extract details for rest of the page
info_div_2 = page_source.find('div', class_='ProductDetails__RemoveMaxHeight-sc-z5f4ag-3 fOPLcr')
info_block_2 = info_div_2.find_all('div', class_='ProductAttribute__ProductAttributesDescription-sc-dyoysr-2 lnLDYa')
try:
    info_shelf_life = info_block_2[0].get_text().strip()
except IndexError:
    info_shelf_life = 'null'

try:
    info_country_of_origin = info_block_2[3].get_text().strip()
except IndexError:
    info_country_of_origin='null'

try:
    info_weight = info_block_2[9].get_text().strip()
except IndexError:
    info_weight ='null'

try:
    info_expiry_date = info_block_2[7].get_text().strip()
except IndexError:
    info_expiry_date='null'
# Extract MRP and price
# Extract MRP and price
info_div_3 = page_source.find('div', class_='ProductVariants__VariantDetailsContainer-sc-1unev4j-7 fvkqJd')
info_block_3 = info_div_3.find_all('div', class_='ProductVariants__PriceContainer-sc-1unev4j-9 jjiIua')
info_price_raw = info_block_3[0].get_text().strip()
info_price = info_block_3[0].get_text().strip()[1:3]
info_MRP = info_price_raw[-2:]

Answer 1

我们不需要使用BeautifulSoup来解析数据。硒的方法对于我们的用例就足够了。

from selenium import webdriver
from selenium.webdriver.chrome.service import Service
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
import pandas as pd
    

chrome_path = r"C:\Users\hpoddar\Desktop\Tools\chromedriver_win32\chromedriver.exe"
s = Service(chrome_path)
url = 'https://blinkit.com/cn/masala-oil-more/whole-spices/cid/1557/930'
driver = webdriver.Chrome(service=s)
driver.get(url)

click_location_tooltip = driver.find_element(by=By.XPATH, value="//button[@data-test-id='address-correct-btn']")
click_location_tooltip.click()

cards_elements_list = driver.find_elements(by=By.XPATH, value="//a[@data-test-id='plp-product']")
card_link_list = [x.get_attribute('href') for x in cards_elements_list]

df = pd.DataFrame(columns=['info_category','info_sub_category','info_product_name','info_brand','info_shelf_life','info_country_of_origin','info_weight','info_expiry_date','price','mrp'])

for url in card_link_list:
  driver.get(url)
  try:
      WebDriverWait(driver, 15).until(EC.presence_of_element_located((By.CLASS_NAME, 'ProductInfoCard__BreadcrumbLink-sc-113r60q-5')))
  except TimeoutException:
      print(url + ' cannot be loaded')
      continue
  bread_crumb_links = driver.find_elements(by=By.XPATH, value="//a[@class='ProductInfoCard__BreadcrumbLink-sc-113r60q-5 hRvdxN']")
  info_category = bread_crumb_links[1].text.strip()
  info_sub_category = bread_crumb_links[2].text.strip()

  product_name = driver.find_element(by=By.XPATH, value="//span[@class='ProductInfoCard__BreadcrumbProductName-sc-113r60q-6 lhxiqc']")
  info_product_name = product_name.text

  brand_name = driver.find_element(by=By.XPATH, value="//div[@class='ProductInfoCard__BrandContainer-sc-113r60q-9 exyKqL']")
  info_brand = brand_name.text

  product_details = driver.find_elements(by=By.XPATH, value="//div[@class='ProductAttribute__ProductAttributesDescription-sc-dyoysr-2 lnLDYa']")
  info_shelf_life = product_details[0].text.strip()
  info_country_of_origin = product_details[1].text.strip()
  info_weight = product_details[7].text.strip()
  info_expiry_date = product_details[5].text.strip()

  div_containing_radio = driver.find_element(by=By.XPATH, value="//div[starts-with(@class, 'ProductVariants__RadioButtonInner')]//ancestor::div[starts-with(@class, 'ProductVariants__VariantCard')]")

  price_mrp_div = div_containing_radio.find_element(by=By.CSS_SELECTOR, value=".ProductVariants__PriceContainer-sc-1unev4j-9.jjiIua")
  mrp_price_list = price_mrp_div.text.split("₹")
  price = mrp_price_list[1]
  mrp = ''
  if(len(mrp_price_list) > 2):
    mrp = mrp_price_list[2]

  data_dict = {'info_category' : info_category, 'info_sub_category' : info_sub_category, 'info_product_name' : info_product_name, 'info_brand' : info_brand, 'info_shelf_life' : info_shelf_life, 'info_country_of_origin': info_country_of_origin, 'info_weight' : info_weight, 'info_expiry_date' : info_expiry_date , 'price' : price, 'mrp' : mrp}
  df_dict = pd.DataFrame([data_dict])
  df = pd.concat([df, df_dict])

输出：

ps：请注意，product_details如果要为所有URL概括，那么我们不完全是一个结构化元素，只是我们需要使用正则元素来解析的文本，因此，您必须在索引列表product_details时进行一些非凡的处理在您的代码中。