Metadata-Version: 2.1
Name: paperparser
Version: 0.2.1
Summary: A tool for parsing academic papers
Home-page: https://gitlab.com/winderresearch/tools/PaperParser
License: MIT
Author: Phil Winder
Author-email: phil@WinderResearch.com
Requires-Python: >=3.7,<4.0
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Dist: click (>=7.0,<8.0)
Requires-Dist: desert (>=2020.1.6,<2021.0.0)
Requires-Dist: importlib-metadata (>=1.5.0,<2.0.0); python_version < "3.8"
Requires-Dist: marshmallow (>=3.3.0,<4.0.0)
Requires-Dist: pybtex (>=0.22.2,<0.23.0)
Requires-Dist: pyquery (>=1.4.1,<2.0.0)
Requires-Dist: requests (>=2.22.0,<3.0.0)
Project-URL: Documentation, https://gitlab.com/winderresearch/tools/PaperParser
Project-URL: Repository, https://gitlab.com/winderresearch/tools/PaperParser
Description-Content-Type: text/markdown

# PaperParser

Parses academic paper information from URLs.

This is a project by [Winder Research](https://WinderResearch.com), a Cloud-Native Data Science consultancy.

## Installation

```python
pip install paperparser
```

## Usage

### CLI

```bash
$ 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

```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](https://dblp.uni-trier.de) and abstracts directly.

### `"nips"`

Parses bibtex and abstracts directly.

### `"acm"`

Parses bibtex via the doi from [scipython](https://scipython.com) and abstracts directly.
