enter image description here 这是我第一次使用 selenium，如果有人能帮助解决这个问题，我真的很感激
"NoSuchElementException: 消息：没有这样的元素：无法定位元素：{"method":"css selector","selector":".selected"} （会话信息：chrome=89.0.4389.114）"
基本上，我在 GitHub 上发现了这段代码，上面写着在 10 分钟内抓取 Glassdoor，这对我来说并非如此:) 花了我整整半天时间，仍然无法找出问题所在并获得我想要的 df。如果有人能通过解释帮助我解决这个问题，我将不胜感激。
这是修改后的代码：
from selenium.common.exceptions import NoSuchElementException, ElementClickInterceptedException
from selenium import webdriver
import time
import pandas as pd
def get_jobs(keyword, num_jobs, verbose, path, slp_time):
'''Gathers jobs as a dataframe, scraped from Glassdoor'''
#Initializing the webdriver
options = webdriver.ChromeOptions()
#Uncomment the line below if you'd like to scrape without a new Chrome window every time.
#options.add_argument('headless')
#Change the path to where chromedriver is in your home folder.
driver = webdriver.Chrome(executable_path=path, options=options)
driver.set_window_size(1120, 1000)
url = 'https://www.glassdoor.co.uk/Job/london-data-analyst-in-london-england-jobs-SRCH_IL.0,6_IC2671300_KO7,19_KE20,37.htm'
driver.get(url)
jobs = []
while len(jobs) < num_jobs: #If true, should be still looking for new jobs.
#Let the page load. Change this number based on your internet speed.
#Or, wait until the webpage is loaded, instead of hardcoding it.
time.sleep(slp_time)
#Test for the "Sign Up" prompt and get rid of it.
try:
driver.find_element_by_class_name("selected").click()
except ElementClickInterceptedException:
pass
time.sleep(.1)
try:
driver.find_element_by_class_name('[alt="close"]').click() #clicking to the X.
print(' x out worked')
except NoSuchElementException:
print(' x out failed')
pass
#Going through each job in this page
job_buttons = driver.find_elements_by_class_name("jl") #jl for Job Listing. These are the buttons we're going to click.
for job_button in job_buttons:
print("Progress: {}".format("" + str(len(jobs)) + "/" + str(num_jobs)))
if len(jobs) >= num_jobs:
break
job_button.click() #You might
time.sleep(1)
collected_successfully = False
while not collected_successfully:
try:
company_name = driver.find_element_by_xpath('.//div[@class="employerName"]').text
location = driver.find_element_by_xpath('.//div[@class="location"]').text
job_title = driver.find_element_by_xpath('.//div[contains(@class, "title")]').text
job_description = driver.find_element_by_xpath('.//div[@class="jobDescriptionContent desc"]').text
collected_successfully = True
except:
time.sleep(5)
try:
salary_estimate = driver.find_element_by_xpath('.//span[@class="gray salary"]').text
except NoSuchElementException:
salary_estimate = -1 #You need to set a "not found value. It's important."
try:
rating = driver.find_element_by_xpath('.//span[@class="rating"]').text
except NoSuchElementException:
rating = -1 #You need to set a "not found value. It's important."
#Printing for debugging
if verbose:
print("Job Title: {}".format(job_title))
print("Salary Estimate: {}".format(salary_estimate))
print("Job Description: {}".format(job_description[:500]))
print("Rating: {}".format(rating))
print("Company Name: {}".format(company_name))
print("Location: {}".format(location))
#Going to the Company tab...
#clicking on this:
#<div class="tab" data-tab-type="overview"><span>Company</span></div>
try:
driver.find_element_by_xpath('.//div[@class="tab" and @data-tab-type="overview"]').click()
try:
#<div class="infoEntity">
# <label>Headquarters</label>
# <span class="value">San Francisco, CA</span>
#</div>
headquarters = driver.find_element_by_xpath('.//div[@class="infoEntity"]//label[text()="Headquarters"]//following-sibling::*').text
except NoSuchElementException:
headquarters = -1
try:
size = driver.find_element_by_xpath('.//div[@class="infoEntity"]//label[text()="Size"]//following-sibling::*').text
except NoSuchElementException:
size = -1
try:
founded = driver.find_element_by_xpath('.//div[@class="infoEntity"]//label[text()="Founded"]//following-sibling::*').text
except NoSuchElementException:
founded = -1
try:
type_of_ownership = driver.find_element_by_xpath('.//div[@class="infoEntity"]//label[text()="Type"]//following-sibling::*').text
except NoSuchElementException:
type_of_ownership = -1
try:
industry = driver.find_element_by_xpath('.//div[@class="infoEntity"]//label[text()="Industry"]//following-sibling::*').text
except NoSuchElementException:
industry = -1
try:
sector = driver.find_element_by_xpath('.//div[@class="infoEntity"]//label[text()="Sector"]//following-sibling::*').text
except NoSuchElementException:
sector = -1
try:
revenue = driver.find_element_by_xpath('.//div[@class="infoEntity"]//label[text()="Revenue"]//following-sibling::*').text
except NoSuchElementException:
revenue = -1
try:
competitors = driver.find_element_by_xpath('.//div[@class="infoEntity"]//label[text()="Competitors"]//following-sibling::*').text
except NoSuchElementException:
competitors = -1
except NoSuchElementException: #Rarely, some job postings do not have the "Company" tab.
headquarters = -1
size = -1
founded = -1
type_of_ownership = -1
industry = -1
sector = -1
revenue = -1
competitors = -1
if verbose:
print("Headquarters: {}".format(headquarters))
print("Size: {}".format(size))
print("Founded: {}".format(founded))
print("Type of Ownership: {}".format(type_of_ownership))
print("Industry: {}".format(industry))
print("Sector: {}".format(sector))
print("Revenue: {}".format(revenue))
print("Competitors: {}".format(competitors))
print("@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@")
jobs.append({"Job Title" : job_title,
"Salary Estimate" : salary_estimate,
"Job Description" : job_description,
"Rating" : rating,
"Company Name" : company_name,
"Location" : location,
"Headquarters" : headquarters,
"Size" : size,
"Founded" : founded,
"Type of ownership" : type_of_ownership,
"Industry" : industry,
"Sector" : sector,
"Revenue" : revenue,
"Competitors" : competitors})
#add job to jobs
#Clicking on the "next page" button
try:
driver.find_element_by_xpath('.//li[@class="next"]//a').click()
except NoSuchElementException:
print("Scraping terminated before reaching target number of jobs. Needed {}, got {}.".format(num_jobs, len(jobs)))
break
return pd.DataFrame(jobs) # This line converts the dictionary object into a pandas DataFrame.