extracting text from MS word files in python

Question

for working with MS word files in python, there is python win32 extensions, which can be used in windows. How do I do the same in linux? Is there any library?

Solution 1

You could make a subprocess call to antiword. Antiword is a linux commandline utility for dumping text out of a word doc. Works pretty well for simple documents (obviously it loses formatting). It's available through apt, and probably as RPM, or you could compile it yourself.

Solution 2

Use the native Python docx module. Here's how to extract all the text from a doc:

document = docx.Document(filename)
docText = '\n\n'.join(
    paragraph.text for paragraph in document.paragraphs
)
print(docText)

See Python DocX site

Also check out Textract which pulls out tables etc.

Parsing XML with regexs invokes cthulu. Don't do it!

Solution 3

benjamin's answer is a pretty good one. I have just consolidated...

import zipfile, re

docx = zipfile.ZipFile('/path/to/file/mydocument.docx')
content = docx.read('word/document.xml').decode('utf-8')
cleaned = re.sub('<(.|\n)*?>','',content)
print(cleaned)

Solution 4

OpenOffice.org can be scripted with Python: see here.

Since OOo can load most MS Word files flawlessly, I'd say that's your best bet.

Solution 5

I know this is an old question, but I was recently trying to find a way to extract text from MS word files, and the best solution by far I found was with wvLib:

http://wvware.sourceforge.net/

After installing the library, using it in Python is pretty easy:

import commands

exe = 'wvText ' + word_file + ' ' + output_txt_file
out = commands.getoutput(exe)
exe = 'cat ' + output_txt_file
out = commands.getoutput(exe)

And that's it. Pretty much, what we're doing is using the commands.getouput function to run a couple of shell scripts, namely wvText (which extracts text from a Word document, and cat to read the file output). After that, the entire text from the Word document will be in the out variable, ready to use.

Hopefully this will help anyone having similar issues in the future.

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