arxivabscraper

Welcome to arxivabscraper

This is an ArXiV scraper to retrieve abstracts from given categories and date range. A python module for scraping arxiv abstracts for NLP testing purpose originally but can be used by researchers wants to keep up with the latest devlopment in their fields.

Installation

Use pip (or pip3 for python3):

$ pip install arxivabscraper

or download the source and use setup.py:

$ python setup.py install

or if you do not want to install the module, copy arxivabscraper.py into your working directory.

To update the module using pip:

pip install arxivabscraper --upgrade

Examples

There is a tutorial on how to use the package directly on google colab here . it provides the basic usage to the package and can be run directly on the notebook

You can directly use arxivabscraper in your scripts. Let’s import arxivabscraper and create a scraper to fetch all preprints in high energy physics theory category from 27 May 2018 until 7 June 2020 (for other categories, see below):

import arxivabscraper
scraper = arxivabscraper.Scraper(category='physics:hep-th', date_from='2010-05-27',date_until='2020-06-07')

Once we built an instance of the scraper, we can start the scraping:

output = scraper.scrape()

While scraper is running, it prints its status:

fetching up to  1000 records...
fetching up to  2000 records...
Got 503. Retrying after 30 seconds.
fetching up to  3000 records...
fetching is complete.

Finally you can save the output in your favorite format or readily convert it into a pandas dataframe:

import pandas as pd
cols = ('categories', 'abstract')
df = pd.DataFrame(output,columns=cols)

Categories

Here is a list of all categories available on ArXiv.

Contributing

Ideas/bugs/comments? Please open an issue or submit a pull request on Github.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

This work is based on the arxivscraper from Mahdi Sadjadi (2017). arxivscraper: Zenodo. http://doi.org/10.5281/zenodo.889853