Thanks Alvaro! rows looks top-notch, I'll check it out! I too have support for extracting tables from images on my roadmap, will drop by the rows gitter channel to discuss this further! :)

On Sat, Sep 29, 2018 at 1:40 AM Álvaro Justen [Turicas] <> wrote:
Hi, Vinayak! Good work, thanks for sharing. :)

I'm the creator of the rows library[] and
implemented PDF support early this year (with 3 different strategies)
-- it's not released on PyPI yet since I'm fixing some bugs before
releasing the next version, but you can try it out by installing:

    pip install
pdfminer.six cached-property

It's 100% written in Python and also has a command-line interface (so
you can run `rows convert
newfile.(csv|xls|xlsx|html|sqlite)` or even `rows query "SELECT * FROM
table1 WHERE some_condition"

The idea behind the extraction algorithms is to be flexible, so you
can plug your own if you want (depending on how the PDF is created,
the objects will be very different and you cannot use the same
ordering/grouping strategy).

I'm now implementing support to extract tables from images (and also
from PDFs with images), but it's probably not going to the next
version since I need a better OCR tool. What do you think in joining
efforts so we can have better libraries? I'm going to test the PDFs
you've cited with my code so we can compare better. Feel free to
contact me directly or join the chat at

 Álvaro Justen "Turicas" / @turicas (twitter, github, youtube)
   +55 41 999 311 221
On Fri, Sep 28, 2018 at 11:43 AM Vinayak Mehta <> wrote:
> Hello everyone!
> I recently released a Python library which lets users extract data tables out of PDF files, my first open source library! Here's the link:
> I've created a wiki page comparing it to other open source PDF table extraction tools. I'm currently working on porting it to Python3!
> I would be really grateful if you could check it out and see if its useful to you and give me any feedback that may help me improve it, by replying here, opening an issue or a pull request!
> Looking forward to hearing from you all!
> Thanks for your time!
> Vinayak
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