A command line tool and Python library to support your accounting process.
- extracts text from PDF files using different techniques, like
pdftotext
,pdfminer
or OCR --tesseract
,tesseract4
orgvision
(Google Cloud Vision). - searches for regex in the result using a YAML-based template system
- saves results as CSV, JSON or XML or renames PDF files to match the content.
With the flexible template system you can:
- precisely match content PDF files
- plugins available to match line items and tables
- define static fields that are the same for every invoice
- define custom fields needed in your organisation or process
- have multiple regex per field (if layout or wording changes)
- define currency
- extract invoice-items using the
lines
-plugin developed by Holger Brunn
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'}
- Install pdftotext
If possible get the latest
xpdf/poppler-utils version. It's
included with macOS Homebrew, Debian and Ubuntu. Without it, pdftotext
won't parse tables in PDF correctly.
-
Install
invoice2data
using pippip install invoice2data
Basic usage. Process PDF files and write result to CSV.
invoice2data invoice.pdf
invoice2data *.pdf
Choose any of the following input readers:
- text
invoice2data --input-reader text invoice.txt
(null input-reader, just parse the text file. As the input file is already text extraction is not needed) - pdftotext
invoice2data --input-reader pdftotext invoice.pdf
- tesseract
invoice2data --input-reader tesseract invoice.pdf
- pdf miner
invoice2data --input-reader pdfminer invoice.pdf
- tesseract4
invoice2data --input-reader tesseract4 invoice.pdf
- gvision
invoice2data --input-reader gvision invoice.pdf
(needsGOOGLE_APPLICATION_CREDENTIALS
env var)
Choose any of the following output formats:
- csv
invoice2data --output-format csv invoice.pdf
- json
invoice2data --output-format json invoice.pdf
- xml
invoice2data --output-format xml invoice.pdf
Save output file with custom name or a specific folder
invoice2data --output-format csv --output-name myinvoices/invoices.csv invoice.pdf
Note: You must specify the output-format
in order to create
output-name
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
You can easily add invoice2data
to your own Python scripts as library.
from invoice2data import extract_data
result = extract_data('path/to/my/file.pdf')
Using in-house templates
from invoice2data import extract_data
from invoice2data.extract.loader import read_templates
templates = read_templates('/path/to/your/templates/')
result = extract_data(filename, templates=templates)
See invoice2data/extract/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.
Template files are tried in alphabetical order.
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 \*\*
If you are interested in improving this project, have a look at our developer guide to get you started quickly.
- integrate with online OCR?
- try to 'guess' parameters for new invoice formats.
- can apply machine learning to guess new parameters?
- Harshit Joshi: As Google Summer of Code student.
- Holger Brunn: Add support for parsing invoice items.
- OCR-Invoice (FOSS | C#)
- Docparser (Commercial | Web Service)
- A-PDF (Commercial)
- PDFdeconstruct (Commercial)
- CVision (Commercial)