Data extractor for PDF invoices - invoice2data
A Python library to support your accounting process. Tested on Python 2.7, 3.4 and 3.5
- extracts text from PDF files
- searches for regex in the result
- saves results as CSV
- optionally renames PDF files to match the content
With the flexible template system you can:
- precisely match PDF files
- define static fields that are the same for every invoice
- have multiple regex per field (if layout or wording changes)
- define currency
Go from PDF files to this:
{'date': (2014, 5, 7), 'invoice_number': '30064443', 'amount': 34.73, 'desc': 'Invoice 30064443 from QualityHosting', 'lines': [{'price': 42.0, 'desc': u'Small Business StandardExchange 2010\nGrundgeb\xfchr pro Einheit\nDienst: OUDJQ_office\n01.05.14-31.05.14\n', 'pos': u'7', 'qty': 1.0}]}
{'date': (2014, 6, 4), 'invoice_number': 'EUVINS1-OF5-DE-120725895', 'amount': 35.24, 'desc': 'Invoice EUVINS1-OF5-DE-120725895 from Amazon EU'}
{'date': (2014, 8, 3), 'invoice_number': '42183017', 'amount': 4.11, 'desc': 'Invoice 42183017 from Amazon Web Services'}
{'date': (2015, 1, 28), 'invoice_number': '12429647', 'amount': 101.0, 'desc': 'Invoice 12429647 from Envato'}
Installation
- Install pdftotext
If possible get the latest xpdf/poppler-utils version. It's included with OSX Homebrew, Debian Sid and Ubuntu 16.04. Without it, pdftotext
won't parse tables in PDF correctly.
- Install
invoice2data
using pip
pip install invoice2data
Optionally this uses pdfminer
, but pdftotext
works better. You can choose which module to use. No special Python packages are necessary at the moment, except for pdftotext
.
There is also tesseract
integration as a fallback, if no text can be extracted. But it may be more reliable to use
Usage
Basic usage. Process PDF files and write result to CSV.
invoice2data invoice.pdf
invoice2data *.pdf
Specify folder with yml templates. (e.g. your suppliers)
invoice2data --template-folder ACME-templates invoice.pdf
Only use your own templates and exclude built-ins
invoice2data --exclude-built-in-templates --template-folder ACME-templates invoice.pdf
Processes a folder of invoices and copies renamed invoices to new folder.
invoice2data --copy new_folder folder_with_invoices/*.pdf
Processes a single file and dumps whole file for debugging (useful when adding new templates in templates.py)
invoice2data --debug my_invoice.pdf
Recognize test invoices:
invoice2data invoice2data/test/pdfs/* --debug
If you want to use it as a lib just do
from invoice2data import extract_data
result = extract_data('path/to/my/file.pdf')
Template system
See invoice2data/templates
for existing templates. Just extend the list to add your own. If deployed by a bigger organisation, there should be an interface to edit templates for new suppliers. 80-20 rule. For a short tutorial on how to add new templates, see TUTORIAL.md.
Templates are based on Yaml. They define one or more keywords to find the right template and regexp for fields to be extracted. They could also be a static value, like the full company name.
We may extend them to feature options to be used during invoice processing.
Example:
issuer: Amazon Web Services, Inc.
keywords:
- Amazon Web Services
fields:
amount: TOTAL AMOUNT DUE ON.*\$(\d+\.\d+)
amount_untaxed: TOTAL AMOUNT DUE ON.*\$(\d+\.\d+)
date: Invoice Date:\s+([a-zA-Z]+ \d+ , \d+)
invoice_number: Invoice Number:\s+(\d+)
partner_name: (Amazon Web Services, Inc\.)
options:
remove_whitespace: false
currency: HKD
date_formats:
- '%d/%m/%Y'
lines:
start: Detail
end: \* May include estimated US sales tax
first_line: ^ (?P<description>\w+.*)\$(?P<price_unit>\d+\.\d+)
line: (.*)\$(\d+\.\d+)
last_line: VAT \*\*
Roadmap and open tasks
- tutorial and documentation for template options.
- integrate with online OCR?
- try to 'guess' parameters for new invoice formats.
- can apply machine learning to guess new parameters?
Maintainers
- Manuel Riel
- Alexis de Lattre: Add setup.py for Pypi, fix locale bug, add templates for new invoice types.
Other Contributors
- Holger Brunn: Add support for parsing invoice items.