This module is useful as an example of real world generators. They have been used to some degree of success to help my mother. She's an avid reader and kindle owner. She enjoys that she can up the font on her kindle. She obtained some pdf's that were quite painful to read in dead tree and on the kindle. Being the kind son I am I translated them to the mobi format and emailed them to her kindle.
I've used these generators on about a dozen pdfs. Some tweaking is required because the output of each pdf seems a bit different. YMMV
pdf to mobi
My process went like this:
- use pdf2txt.py to get text of pdf files.
- inspect txt files and tweak to get them to rst if possible
- create a python generator pipeline to clean up text (using ebookgen)
- use rst2epub2 or rst2html to create mobi file
- email mobi file to email@example.com
For normal people
If you don't care about ebooks that much (or making your own), then this library might be interesting as examples of real-world generators. Of particular interest might be the Peeker class which allows looking ahead in iterators. (This comes in often when tweaking text).
There are also a few examples of basic generators and some fancier ones that use Peeker.
These generators aren't necessarily written in a functional style using map, reduce and filter, though they probably could be. Sorry.
Creating a generator chain
My script to clean the pdf2txt.py output looks something like this:
import sys import ebookgen def run(): data = sys.stdin data = ebookgen.remove_leading_space(data) data = ebookgen.remove_dash_page(data) data = ebookgen.remove_carot_l(data) data = ebookgen.remove_two_spaces(data) data = ebookgen.remove_double_returns(data) data = ebookgen.insert_extra_paragraph_line(data) data = ebookgen.insert_rst_sections(data) for line in data: print line, if __name__ == '__main__': run()
Matt Harrison, 2012