Comparing with other available toolkits, Adobe gives the best output in document conversion. Unfortunately, the team decided -for some reasons - to limit the automation capabilities of the software. A piece of advice from a machine learning/Natural Language Processing/Data science perspectives: you can do a lots more if you open on Big Data community. Companies have dumps of millions of PDF and receive a thousand of PDF each day. Unfortunately, they can do nothing with it because open source softwares are terrible ...... Big noisy Data isn't that useful in data science. An automated - highly parallelized - web service for converting PDF isn't a bad idea.

Until now I can't figure out why batch processing stop, the solution is not more complicated than:

error_list = []

for pdffile in todolist:

  try:

      conver_pdf_to_word(pdf_file)



  # if an error occurs

  except:

       error_list.append(pdf_file)

       continue      

print("Dear user those PDF causes some issues:")

for pdffile in errorlist:

 print(pdf_file)

The following link:
https://drive.google.com/open?id=1c_coofphNstN7R5wJfnC__qvV6quuDiH

contains 50 PDFs that bugs and I wonder if you could fix those bugs and make batch processing never stop. In other words, the action wizard should skip all pop-up messages and avoid crashes. In the end, it can report those buggy PDFs that it previously skipped, because it's so annoying when you ran the wizard and came back after 4 hours expecting that it's over but it surprises you with a "click ok to continue"