pdf-toolbox 0.1.0

A package to extract and store data from PDFs

PDF TOOLBOX

This package is designed to be used as an extensible library.

PDF TOOLBOX allows extracting, parsing, structuring and storing text from PDFs.

This package emerges as the solution to a challenge in which I had to obtain and store clinical data but can be used for any other purpose.

Package installation

Download and install this package. To install this package you should run:

python3 setup.py install

Extracting PDF Text

PDF TOOLBOX it is designed to read PDFs from multiple sources.

The pdf.readers.filereader module implements the reading of PDFs stored as files. To read PDFs stored in memory, in a rabbitmq or in another data source, it is necessary to create your own implementation that respects the interface defined in pdf.domain.pdfreader.

Example usage

Retrieving text from a PDF file:

from pdf_toolbox.pdf.readers.filereader import FilePDFReader

pdf_reader = FilePDFReader("inputs/report.pdf")

pdf_text = pdf_reader.extract_text()

Parsing PDF Text

PDF text can have as parsers as PDF types are in the world.

The provided parser parses the PDF text of the challenge. The provided parser obtains the text of a specific clinical PDF and returns its information structured in a dictionary.

Example usage:

from pdf_toolbox.text_extraction.report_parsers.challenge_parser import ChallengeParser

challenge_parser = ChallengeParser(pdf_text)
pdf_data = challenge_parser.parse()

You can define your own parser for other PDF types by implementing the ReportParser interface located in text_extraction.domain.report_parser.

Storing PDF parsed data

Creating an identifier for the report

Before saving the report data we should have defined an identifier for it. This package has a shortcut for it.

The method create_id returns a new uuid version 4 identifier.

Example usage

from pdf_toolbox.shared.utils import create_id

report_id = create_id()

Saving report data

The use of a JSON file as a storage backend is implemented in this package.

Example usage

from pdf_toolbox.report_storage.storages.json_storage import JSONStorage

json_storage = JSONStorage("demo.json")
json_storage.save(pdf_data, report_id)

Any type of backend can be implemented without losing compatibility with the rest of the code. Every storage backend must implement the interface report_storage.domain.storage.Storage.

Running tests

To run the tests of this package you must install dev_requirements.txt and run pytest inside pdf_toolbox folder.

pip install -r dev_requirements.txt
cd pdf_toolbox
pytest

LICENSE MIT

Copyright 2022 Samuel López Saura

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.