text: #### This program scrapes naukri.com's page and gives our result as a 
  #### list of all the job_profiles which are currently present there. 
    
  import requests
  from bs4 import BeautifulSoup
  from selenium import webdriver
  from selenium.webdriver.common.keys import Keys
  import time
    
  #url of the page we want to scrape
  url = 'https://coinmarketcap.com/currencies/bitcoin/news/'
    
  # initiating the webdriver. Parameter includes the path of the webdriver.
  options = webdriver.ChromeOptions()
  options.add_experimental_option('excludeSwitches', ['enable-logging'])
  driver = webdriver.Chrome(executable_path=r'C:\Users\HP\Downloads\chromedriver.exe', options = options) 
  driver.get(url) 
  loadmorebutton = driver.find_element_by_xpath('/html/body/div/div/div/div[2]/div/div[3]/div/div/main/button')
  for i in range(4):
      loadmorebutton.click() 
      time.sleep(5) 
  
    
  html = driver.page_source
    
  # this renders the JS code and stores all
  # of the information in static HTML code.
    
  # Now, we could simply apply bs4 to html variable
  soup = BeautifulSoup(html, "html.parser")
  all_divs = soup.find('div', {'class' : 'wav26n-1 gWmJSZ'})
  job_profiles = all_divs.find_all('a')
  
    
  # printing top ten job profiles
  count = 0
  for job_profile in job_profiles :
      print(job_profile.text)
      print("----------------------------------------------")
      count = count + 1
      if(count == 20) :
          break
  
  
    
  driver.close() # closing the webdriver