# Data extractor for PDF invoices - invoice2data
[](https://circleci.com/gh/m3nu/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'}
{'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
1. Install pdftotext
If possible get the latest [xpdf/poppler-utils](https://poppler.freedesktop.org/) version. It's included with OSX Homebrew, Debian Sid and Ubuntu 16.04. Without it, `pdftotext` won't parse tables in PDF correctly.
2. 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](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'
```
## Roadmap and open tasks
- tutorial and documentation for template options.
- parse invoice items.
- integrate with online OCR?
- try to 'guess' parameters for new invoice formats.
- can apply machine learning to guess new parameters?
## Maintainers
- [Manuel Riel](https://github.com/m3nu)
- [Alexis de Lattre](https://github.com/alexis-via): Add setup.py for Pypi, fix locale bug, add templates for new invoice types.
## Other Contributors
- [Holger Brunn](https://github.com/hbrunn): Add support for parsing invoice items.
[](https://circleci.com/gh/m3nu/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'}
{'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
1. Install pdftotext
If possible get the latest [xpdf/poppler-utils](https://poppler.freedesktop.org/) version. It's included with OSX Homebrew, Debian Sid and Ubuntu 16.04. Without it, `pdftotext` won't parse tables in PDF correctly.
2. 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](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'
```
## Roadmap and open tasks
- tutorial and documentation for template options.
- parse invoice items.
- integrate with online OCR?
- try to 'guess' parameters for new invoice formats.
- can apply machine learning to guess new parameters?
## Maintainers
- [Manuel Riel](https://github.com/m3nu)
- [Alexis de Lattre](https://github.com/alexis-via): Add setup.py for Pypi, fix locale bug, add templates for new invoice types.
## Other Contributors
- [Holger Brunn](https://github.com/hbrunn): Add support for parsing invoice items.
2 maintainers
Metadata
2 maintainers
Release files for invoice2data 0.2.49
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| invoice2data-0.2.49.tar.gz | 364.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| invoice2data-0.2.49-py2.7.egg | Legacy Egg format | - | - | Details |
Total release size: 762.9 kB
Release files / invoice2data-0.2.49.tar.gz
| Download URL | invoice2data-0.2.49.tar.gz |
|---|---|
| Size | 364.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
d66ad70def52476e7428d7c61035f5f13585af79172039d6b1142afa4e9f6aa4
|
|
BLAKE2b-256 checksum How to use checksums |
a0bed525e82b494d625b10b4a986a577e31c0db4487e44070d0d2eef00613e69
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
Release files / invoice2data-0.2.49-py2.7.egg
| Download URL | invoice2data-0.2.49-py2.7.egg |
|---|---|
| Size | 398.7 kB |
| Tags | Egg |
|
SHA-256 checksum How to use checksums |
0d7b09996373adcae3d10630d0090d5a42bf1a96ca0e5531954106d8cdd6436c
|
|
BLAKE2b-256 checksum How to use checksums |
5cddd84964db717ae734da381e2300e07ca0df18d71e0b051cce50875631b5c6
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
