Python binding for libpoppler - focused on text extraction from PDF documents.
Intended as an easy to use replacement for pdfminer, which provides much better performance (see below for short comparison) and is Python3 compatible.
See this article for some comparisons with pdfminer and other approaches.
Binding is written in cython.
Requires recent libpoppler >= 0.40 - so I'd recommend to build it from source to get latest library, but it works also with recent libpoppler library present in common linux distributions (then it requires dev package to build). See below for installation instructions.
Available under GPL v3 or any later version license (libpoppler is also GPL).
How to install
Below or some instructions to install this package
Debian like - system wide libpoppler
sudo apt-get update sudo apt-get install -y libpoppler-private-dev libpoppler-cpp-dev pip install cython pip install git+https://github.com/nghiapq77/pdfparser
pip install cython pip install git+https://github.com/nghiapq77/pdfparser
|tiny document (half page)||0.033s||0.121s||3.6 x|
|small document (5 pages)||0.141s||0.810s||5.7 x|
|medium document (55 pages)||1.166s||10.524s||9.0 x|
|large document (436 pages)||10.581s||108.095s||10.2 x|
pdfparser code used in test
import pdfparser.poppler as pdf import sys d=pdf.Document(sys.argv) print('No of pages', d.no_of_pages) for p in d: print('Page', p.page_no, 'size =', p.size) for f in p: print(' '*1,'Flow') for b in f: print(' '*2,'Block', 'bbox=', b.bbox.as_tuple()) for l in b: print(' '*3, l.text.encode('UTF-8'), '(%0.2f, %0.2f, %0.2f, %0.2f)'% l.bbox.as_tuple()) #assert l.char_fonts.comp_ratio < 1.0 for i in range(len(l.text)): print(l.text[i].encode('UTF-8'), '(%0.2f, %0.2f, %0.2f, %0.2f)'% l.char_bboxes[i].as_tuple(),\ l.char_fonts[i].name, l.char_fonts[i].size, l.char_fonts[i].color,) print()
How to modify parsing algorithm?
As you probably know PDF is document format intended for printing, so all logical structure of the text is lost (paragraphs, columns, tables, etc.). libpoppler is trying to reconstruct some of this logical structure of the document back by comparing physical positions of characters on the page and their mutual distances and reconstructing back words, lines, paragraphs, columns.
Component which is responsible for this reconstruction is C++ class
TextOutputDev (in poppler/TextOutputDev.cc).
It's using many constants for this jobs, vast majority of constants in hardcoded into code.
Actually the only parameter that is available to Python code is combination of parameters
fixed_pitch, which influences how text is ordered into columns. If you put
phys_layout to True and
fixed_pitch to value > 0, then
fixed_pitch will be used as maximum distance between words in a line and
minimum distance between columns (in pixels). I think
phys_layout also influences order of boxes
in page iteration. However influence of these parameters is not quite straight forward - so you'll need to
experiment to see how it works in your case.
Another problem I encoutered is vertical spacing between lines in single box (paragraph) - this parameter
is unfortunatelly fixed in libpoppler - it's constant
maxLineSpacingDelta in poppler/TextOutputDev.cc, which
is set to 1.5 (font size). If you need to accept bigger line spacing in paragraph then, you'll have to change it
in C++ code and recompile libpoppler (in this case I recommend to make library local to pdfparser package).
I've tried with value 2.0 and it seems to work fine.