old_contents: import pandas as pd
  from subprocess import check_output
  import sys
  
  fish_df = pd.read_csv(sys.argv[1],names=['fish'])
  
  url_dict = {}
  for fish in fish_df.fish:
      output = check_output(['node','scrape_image_urls.js',fish,sys.argv[2]])
      splits = str(output).replace('\\n','').split(' url: ')
      urls = [s.split(',    width')[0][1:-1] for s in splits[1:]]
      url_dict[fish] = urls
  
  url_df = pd.DataFrame(url_dict)
  url_df.to_csv(sys.argv[3], sep='|', index=False)
new_contents: import pandas as pd
  from subprocess import check_output
  import sys
  
  fish_df = pd.read_csv(sys.argv[1],names=['fish'])
  
  dfs = []
  for fish in fish_df.fish:
      output = check_output(['node','scrape_image_urls.js',fish + ' fish',sys.argv[2]])
      splits = str(output).replace('\\n','').split(' url: ')
      urls = [s.split(',    width')[0][1:-1] for s in splits[1:]]
      dfs.append(pd.DataFrame({'fish': fish, 'url': urls}))
  
  out_df = pd.concat(dfs)
  out_df.to_csv(sys.argv[3], sep='|', index=False)
  
subject: Update scrape fish to handle different size url sets and to specify to google that we want fish