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Description:

paperparser 0.2.2

PaperParser
Parses academic paper information from URLs.
This is a project by Winder Research, a Cloud-Native Data Science consultancy.
Installation
pip install paperparser

Usage
CLI
$ paperparser --help
Usage: paperparser [OPTIONS] URL STRATEGY

Parse the bibtex from a URL using the STRATEGY.

Options:
--version Show the version and exit.
--help Show this message and exit.

$ paperparser https://arxiv.org/abs/1812.02900 arxiv
{'title': 'Off-Policy Deep Reinforcement Learning without Exploration', 'journal': 'CoRR', 'volume': 'abs/1812.02900', 'year': '2018', 'url':
'http://arxiv.org/abs/1812.02900', 'archivePrefix': 'arXiv', 'eprint': '1812.02900', 'timestamp': 'Tue, 01 Jan 2019 15:01:25 +0100', 'biburl': 'https://dblp.org/rec/journals/corr/abs-1812-02900.bib', 'bibsource': 'dblp computer science bibliography, https://dblp.org'}

Python
from paperparser import page

p = page.BibTeXPage(url=url, strategy=strategy)
print(p.as_dict())
print(p.abstract())

Strategies
"arxiv"
Parses bibtex from dblp and abstracts directly.
"nips"
Parses bibtex and abstracts directly.
"acm"
Parses bibtex via the doi from https://dx.doi.org/ and abstracts directly.
"ieee"
Parses bibtex via the doi from https://dx.doi.org/ and abstracts directly.
"sciencedirect"
Parses bibtex via the doi from https://dx.doi.org/ and abstracts directly.
"wiley"
Parses bibtex via the doi from https://dx.doi.org/ and abstracts directly.
"semanticscholar"
Prefer other parsers where possible. Semantic scholar tends to index other websites and therefore results are sketchy. Parses bibtex via the DOI if possible, manual creation if not. Abstracts are direct.