text: import pynder
  import os
  import urllib
  
  from nude import *
  from rake import *
  
  
  if __name__ == "__main__":
      facebook_id = ""                # insert fb login id here
      facebook_auth_token = ""        # insert fb authentication token here
      user_limit = input("\nNumber of tests: ")
      image_limit = input("Number of images per test: ")
  
      session = pynder.Session(facebook_id, facebook_auth_token)
      total_users = session.nearby_users()
      if len(total_users) > user_limit:
          users = total_users[:user_limit]
      else: users = total_users
      
      for user in users:
          total_skin_percent = 0.0
          bio_score = 0.0
          final_percent = 0.0
  
  
          # Image analysis
          image_count = 0
          for image in user.get_photos(width='320'):
              if image_count < image_limit:
                  image_count += 1
                  image_name = 'temp'+str(image_count)+'.jpg'
                  photo_url = str(image)        
                  image = urllib.URLopener()
                  image.retrieve(photo_url, image_name)
  
                  skin_percent = 100*contains_nudity(image_name)
                  total_skin_percent += skin_percent
                  os.remove(image_name)
              else: break
              
          total_skin_percent /= image_count
          
  
          # Bio analysis
          text = user.bio.lower().replace('\n','. ')
          rake = Rake("rake_res/SmartStoplist.txt")
          keywords = rake.run(text.lower())        # keywords -> list of tuples. Each element- (word, wordscore)  
          word_list = load_word_list("rake_res/WordList.txt")
          
          for element in keywords: 
              for word in word_list.keys():
                  if (element[0] in word) or (word in element[0]):
                      if 'no' in element[0] or 'not' in element[0]:
                          bio_score += 1.0*word_list[word]*element[1]
                      else: 
                          bio_score -= 1.0*word_list[word]*element[1]  
          if bio_score > 100 : bio_score = 100
  
          
          # Combining Image and Bio scores
          if bio_score != 0:
              final_percent = (total_skin_percent + bio_score)/2
          else:
              final_percent = total_skin_percent
  
          if final_percent >= 25.0 : user.like()
  