text: 
  #import dependencies
  from splinter import Browser
  from bs4 import BeautifulSoup
  import pandas as pd
  import time
  
  def init_browser():
  # path to driver
      executable_path = {'executable_path': 'chromedriver.exe'}
      return Browser('chrome', **executable_path, headless=False)
  
  # scraping function
  
  def scrape():
      
  
      browser = init_browser()
      
      # News; Browser 1
      url = "https://mars.nasa.gov/news/"
      browser.visit(url)
      
      # define object and parse w/ beautiful soup
      html = browser.html
      soup = BeautifulSoup(html, "html.parser")
  
      # Parse through html to find most recent title and paragraph
      title = soup.find_all("div", class_ = "content_title")
      headline = title[1]
      headline = headline.find("a")
      news_title = headline.text
      teaser = soup.find_all("div", class_ = "article_teaser_body")
      teaser1 = teaser[0]
      news_p = teaser1.text
      
      #print title and paragraph
      print(f'Title: {news_title}\nText: {news_p}')
      browser.quit()
  
      # Second Scrape; Visit second site
      browser = init_browser()
      url2 = "https://www.jpl.nasa.gov/spaceimages/?search=&category=Mars"
      browser.visit(url2)
  
      # click through file to find the image
      browser.click_link_by_id('full_image')
      browser.click_link_by_partial_text('more info')
      browser.click_link_by_partial_href('/largesize')
      featured_image_url = browser.url
      print(featured_image_url)
  
  
      # Third Scrape; Visit third site
      browser = init_browser()
      url3 = "https://space-facts.com/mars/"
      browser.visit(url3)
      tables = pd.read_html(url3)
      
      #save table as df
      df = tables[0]
      df.head()
  
      # convert to html and print
      html_table = df.to_html()
      print(html_table)
      browser.quit()
  
      # Fourth Scrape; Visit fourth site
      browser = init_browser()
      url4 = 'https://astrogeology.usgs.gov/search/results?q=hemisphere+enhanced&k1=target&v1=Mars'
      browser.visit(url4)
      html = browser.html
      soup = BeautifulSoup(html, "html.parser")
  
      #set main url and find all image links
      main_url = "https://astrogeology.usgs.gov"
      images_url = soup.find_all("div", class_="item")
  
      # set list
      url_list = []
      
      for image in images_url:
          hem_url = image.find('a')['href']
          url_list.append(hem_url)
  
      print(url_list)
  
  
      # use links to visit and then find the title; Create dictionary
      html = browser.html
      soup = BeautifulSoup(html, "html.parser")
      hemisphere_image_urls = []
      url_site3 = browser.find_by_css("a.product-item h3")
  
      for item in range(len(url_site3)):
  
          browser.find_by_css("a.product-item h3").click()
          elm = browser.find_link_by_text("Sample").first
          img_url = elm['href']
          title = browser.find_by_css("h2.title").text
          hemisphere_image_urls.append({'title':title, 'img_url': img_url})
          
          browser.back()
      next
      print(hemisphere_image_urls)
      browser.quit()
  
      # Create empty dictionary and add all data
  
      mars_info = [{
          "news_title": news_title, 
          "news_paragraph": news_p,
          "featured_image_url": featured_image_url,
          "mars_facts": html_table,
          "hemisphere_image_urls": hemisphere_image_urls
      }]
  
      print('complete :)')
      return mars_info
  
  
  
  
  