Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/invoice-x/invoice2data
Extract structured data from PDF invoices
https://github.com/invoice-x/invoice2data
data-mining python
Last synced: 1 day ago
JSON representation
Extract structured data from PDF invoices
- Host: GitHub
- URL: https://github.com/invoice-x/invoice2data
- Owner: invoice-x
- License: mit
- Created: 2015-04-09T09:37:41.000Z (almost 10 years ago)
- Default Branch: master
- Last Pushed: 2024-08-08T17:16:39.000Z (6 months ago)
- Last Synced: 2024-10-29T10:54:47.251Z (4 months ago)
- Topics: data-mining, python
- Language: Python
- Size: 1.99 MB
- Stars: 1,826
- Watchers: 66
- Forks: 480
- Open Issues: 60
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
Awesome Lists containing this project
- awesome-hledger - invoice2data - Import transactions from pdf invoices. (Import Transactions)
- awesome-starred - invoice-x/invoice2data - Extract structured data from PDF invoices (python)
README
# Data extractor for PDF invoices - invoice2data
[][read the docs]
[](https://github.com/invoice-x/invoice2data/actions)
[](https://pypi.python.org/pypi/invoice2data)
[](https://pypi.python.org/pypi/invoice2data)
[][license]
[][tests]
[][codecov]
[][pre-commit]
[](https://github.com/astral-sh/ruff)
[pypi status]: https://pypi.org/project/invoice2data/
[read the docs]: https://invoice2data.readthedocs.io/
[tests]: https://github.com/invoice-x/invoice2data/actions?workflow=Tests
[codecov]: https://app.codecov.io/gh/invoice-x/invoice2data
[pre-commit]: https://github.com/pre-commit/pre-commit
[ruff badge]: https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json
[ruff project]: https://github.com/charliermarsh/ruff
A command line tool and Python library that automates the extraction of key information from invoices to support your accounting
process. The library is very flexible and can be used on other types of business documents as well.
In essence, invoice2data simplifies the process of getting data from invoices by:
Automating text extraction: No more manual copying and pasting.
Using templates for structure: Handles different invoice layouts.
Providing structured output: Makes the data ready for analysis or further processing.
This makes it a valuable tool for businesses and developers dealing with a large volume of invoices, saving time and reducing errors associated with manual data entry.
1. extracts text from PDF files using different techniques, like
`pdftotext`, `text`, `ocrmypdf`, `pdfminer`, `pdfplumber` or OCR -- `tesseract`, or
`gvision` (Google Cloud Vision).
2. searches for regex in the result using a YAML or JSON-based template system
3. 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](https://github.com/hbrunn)
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'}
## Usage
Basic usage. Process PDF files and write result to CSV.
Please see the [Command-line Reference] for details.
- `invoice2data invoice.pdf`
- `invoice2data invoice.txt`
- `invoice2data *.pdf`
Choose any of the following input readers:
- pdftotext `invoice2data --input-reader pdftotext invoice.pdf`
- pdftotext `invoice2data --input-reader text invoice.txt`
- tesseract `invoice2data --input-reader tesseract invoice.pdf`
- pdfminer.six `invoice2data --input-reader pdfminer invoice.pdf`
- pdfplumber `invoice2data --input-reader pdfplumber invoice.pdf`
- ocrmypdf `invoice2data --input-reader ocrmypdf invoice.pdf`
- gvision `invoice2data --input-reader gvision invoice.pdf` (needs `GOOGLE_APPLICATION_CREDENTIALS` env var and a Google Cloud Bucket name. The bucket name can be set as an argument to the function ``to_text`` or as an Environment variable named ``GOOGLE_CLOUD_BUCKET_NAME`` )
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`
### Use as Python Library
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)
## Template system
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](../docs/tutorial.md).
Templates are based on Yaml or JSON. They define one or more keywords to find
the right template, one or more exclude_keywords to further narrow it down
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:
````yaml
issuer: Amazon Web Services, Inc.
keywords:
- Amazon Web Services
exclude_keywords:
- San Jose
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\w+.*)\$(?P\d+\.\d+)
line: (.*)\$(\d+\.\d+)
skip_line: Note
last_line: VAT \*\*
````
The lines package has multiple settings:
- start > The pattern where the lines begin. This is typically the header row of the table. This row is not included in the line matching.
- end > The pattern denoting where the lines end. Typically some text at the very end or immediately below the table. Also not included in the line matching.
- first_line > Optional. This is the primary line item for each entry.
- line > If first_line is not provided, this will be used as the primary line pattern. If first_line is provided, this is the pattern for any sub-lines such as line item details.
- skip_line > Optional. If first_line is passed, this pattern indicates which sub-lines will be skipped and their data not recorded. This is useful if tables span multiple pages and you need to skip over page numbers or headers that appear mid-table.
- last_line > Optional. If first_line is passed, this pattern denotes the final line of the sub-lines and is included in the output data.
:warning: Invoice2data uses a yaml templating system. The yaml templates are loaded with [pyyaml](https://github.com/yaml/pyyaml) which is a pure python implementation. (thus rather slow)
As an alternative json templates can be used. Which are natively better supported by python.
The performance with yaml templates can be greatly increased **10x** by using [libyaml](https://github.com/yaml/libyaml)
It can be installed on most distributions by:
`sudo apt-get libyaml-dev`
## Development
If you are interested in improving this project, have a look at our
[developer guide](../docs/contributing.md) to get you started quickly.
## Roadmap and open tasks
- integrate with online OCR?
- try to 'guess' parameters for new invoice formats.
- apply machine learning to guess new parameters / template creation
- Data cleanup per field
- advanced table parsing with [pypdf_table_extraction](https://github.com/py-pdf/pypdf_table_extraction)
## Maintainers
- [Manuel Riel](https://github.com/m3nu)
- [Alexis de Lattre](https://github.com/alexis-via)
- [bosd](https://github.com/bosd)
## Contributors and Credits
- [Harshit Joshi](https://github.com/duskybomb): As Google Summer of
Code student.
- [Holger Brunn](https://github.com/hbrunn): Add support for parsing
invoice items.
[pypi]: https://pypi.org/
[file an issue]: https://github.com/invoice-x/invoice2data/issues
[pip]: https://pip.pypa.io/
Contributions are very welcome.
To learn more, see the [Contributor Guide].
## Used By
- Odoo, OCA module [account_invoice_import_invoice2data](https://github.com/OCA/edi)
## Related Projects
- [OCR-Invoice](https://github.com/robela/OCR-Invoice) (FOSS \| C\#)
- [DeepLogic AI](https://deeplogicai.tech/case_list/automatic-key-information-extraction-business-documents/) (Commercial \| SaaS)
- [Docparser](https://docparser.com/) (Commercial \| Web Service)
- [A-PDF](http://www.a-pdf.com/data-extractor/index.htm) (Commercial)
- [PDFdeconstruct](http://www.glyphandcog.com/PDFdeconstruct.html?g6)
(Commercial)
- [CVision](http://www.cvisiontech.com/library/document-automation/forms-processing/extract-data-from-invoice.html)
(Commercial)
[license]: https://github.com/invoice-x/invoice2data/blob/main/LICENSE
[contributor guide]: https://github.com/invoice-x/invoice2data/blob/main/CONTRIBUTING.md
[command-line reference]: https://invoice2data.readthedocs.io/en/latest/usage.html