Metadata-Version: 2.1
Name: citextract
Version: 0.0.2
Summary: CiteXtract - Bringing structure to the papers on ArXiv.
Home-page: https://www.citextract.com/
Author: Kevin Jacobs
Author-email: kevin91nl@gmail.com
License: UNKNOWN
Description: # CiteXtract
        
        [![Read the Docs](https://img.shields.io/readthedocs/citextract.svg)](https://citextract.readthedocs.io/en/latest/)
        [![CircleCI](https://img.shields.io/circleci/build/github/kmjjacobs/citextract/master.svg)](https://circleci.com/gh/kmjjacobs/citextract/tree/master)
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        [![PyPI - Python Version](https://img.shields.io/pypi/pyversions/citextract.svg)](https://img.shields.io/pypi/pyversions/citextract.svg)
        
        [CiteXtract](https://www.citextract.com/) - Bringing structure to the papers on ArXiv.
        
        ## Getting started
        
        In order to install CiteXtract, run the following command:
        
        ```bash
        pip install citextract
        ```
        
        ### Extracting references
        
        Then, one can extract references from a text using the RefXtract model:
        
        ```python
        from citextract.models.refxtract import RefXtractor
        
        refxtractor = RefXtractor().load()
        text = """This is a test sentence.\n[1] Jacobs, K. 2019. This is a test title. In Proceedings of Some Journal."""
        refs = refxtractor(text)
        print(refs)
        ```
        
        It gives the following output:
        
        ```python
        ['[1] Jacobs, K. 2019. This is a test title. In Proceedings of Some Journal.']
        ```
        
        Under the hood, a trained neural network extracts reference boundaries and extracts the references by using these boundaries.
        
        ### Extracting titles
        
        Using the found references, titles can be extracted by using the TitleXtract model:
        
        ```python
        from citextract.models.titlextract import TitleXtractor
        
        titlextractor = TitleXtractor().load()
        ref = """[1] Jacobs, K. 2019. This is a test title. In Proceedings of Some Journal."""
        title = titlextractor(ref)
        print(title)
        ```
        
        It gives the following output:
        
        ```python
        'This is a test title.'
        ```
        
        Here, a trained neural network extracts the titles from the given reference.
        
        ### Converting an arXiv PDF to text
        
        There is a utility available which takes an arXiv URL and converts it to text:
        
        ```python
        from citextract.utils.pdf import convert_pdf_url_to_text
        
        pdf_url = 'https://arxiv.org/pdf/some_file.pdf'
        text = convert_pdf_url_to_text(pdf_url)
        print(text)
        ```
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
