SciPDF Parser

A Python parser for scientific PDF based on GROBID.

Installation

Use pip to install from this Github repository

pip install git+https://github.com/titipata/scipdf_parser

Note

• We also need an en_core_web_sm model for spacy, where you can run python -m spacy download en_core_web_sm to download it
• You can change GROBID version in serve_grobid.sh to test the parser on a new GROBID version

Usage

Run the GROBID using the given bash script before parsing PDF

bash serve_grobid.sh

This script will download GROBID and run the service at default port 8070 (see more here). To parse a PDF provided in example_data folder or direct URL, use the following function:

import scipdf
article_dict = scipdf.parse_pdf_to_dict('example_data/futoma2017improved.pdf') # return dictionary
 
# option to parse directly from URL to PDF, if as_list is set to True, output 'text' of parsed section will be in a list of paragraphs instead
article_dict = scipdf.parse_pdf_to_dict('https://www.biorxiv.org/content/biorxiv/early/2018/11/20/463760.full.pdf', as_list=False)

# output example
>> {
    'title': 'Proceedings of Machine Learning for Healthcare',
    'abstract': '...',
    'sections': [
        {'heading': '...', 'text': '...'},
        {'heading': '...', 'text': '...'},
        ...
    ],
    'references': [
        {'title': '...', 'year': '...', 'journal': '...', 'author': '...'},
        ...
    ],
    'figures': [
        {'figure_label': '...', 'figure_type': '...', 'figure_id': '...', 'figure_caption': '...', 'figure_data': '...'},
        ...
    ],
    'doi': '...'
}

xml = scipdf.parse_pdf('example_data/futoma2017improved.pdf', soup=True) # option to parse full XML from GROBID

To parse figures from PDF using pdffigures2, you can run

scipdf.parse_figures('example_data', output_folder='figures') # folder should contain only PDF files

You can see example output figures in figures folder.