How to fetch text from pdf to further proceed with question answer based model from the same document?

Question

To illustrate the above title.

Suppose you have a pdf document, which is basically scanned from hardcopy, now there are set of fixed questions to answer from the document itself. 
For an example a document contains a contract of land, now the set of fixed questions be "who is the seller?" "what is price of the asset? ", document has referred to this answers probably 2-3 times, as a human it's a simple task.

How to automate this?

Musakkhir Sayyed · Answer

You can use pypdf2 to extract text from pdf.

import PyPDF2

with open('sample.pdf','rb') as pdf_file, open('sample_output.txt', 'w') as text_file:
    read_pdf = PyPDF2.PdfFileReader(pdf_file)
    number_of_pages = read_pdf.getNumPages()
    for page_number in range(number_of_pages):   # use xrange in Py2
        page = read_pdf.getPage(page_number)
        print('Page No - ' + str(1 + read_pdf.getPageNumber(page)))
        page_content = page.extractText()
        text_file.write(page_content)

How to fetch text from pdf to further proceed with question answer based model from the same document?

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