pdfharvester 0.2.5

A package for extracting tables and images from PDFs

PDFHarvester

PDFHarvester is a Python package for extracting tables, images, and keywords from PDF documents.

Installation

You can install PDFHarvester using pip:

pip install PDFHarvester

Usage

To extract tables, images, and keywords from a PDF document using PDFHarvester, you can use the following functions:

import pdfharvest as ph

tables = ph.extract_table('path/to/pdf')
images = ph.extract_images('path/to/pdf')
keywords = ph.extract_keywords('path/to/pdf')

extract_table returns a list of pandas dataframes, one for each table in the PDF. extract_images returns a list of images as numpy arrays, and extract_keywords returns a list of keywords as strings.

#Contributing Bug reports and pull requests are welcome on GitHub at https://github.com/yourusername/PDFHarvester. This project is intended to be a safe, welcoming space for collaboration, and contributors are expected to adhere to the Contributor Covenant code of conduct.

#License The package is available as open source under the terms of the MIT License, © 2023 Hashim Puthiyakath.

Please let me know if you have any further questions or concerns.