Mmmh. Bearer of bad news (sorry), but my experience with tabula has been so-so. First, installing it is a major PITN. Second, the output is unpredictable. U

Mmmh. Bearer of bad news (sorry), but my experience with tabula has been so-so. First, installing it is a major PITN. Second, the output is unpredictable. Ultimately, I've found that using: pdftotext -layout somePDF.pdf - | python3 myparser.py where myparser.py is a 20 lines python script with a couple of regexes and a simple state machine works absolute wonders and can extract relevant data from PDFs even when the data isn't really organized in a table. Also, pdftotext is open source, written in C++, and doesn't require to install a bottomless pit of dependencies like tabula does. And of course, neither of these things will solve extracting data from PDFs that embed rasterized images or data that is the result of a complex SVG-type rendering. I believe the real solution to that problem will be: render the PDF to an image at hi-rez and pipe it to some ML-powered process that reverse engineers relevant data out of arbitrary images. Startup idea?