An ArXiV scraper to retrieve records from given categories and date range.
Use pip
(or pip3
for python3):
$ pip install arxivscraper
or download the source and use setup.py
:
$ python setup.py install
To update the module using pip
:
pip install arxivscraper --upgrade
You can directly use arxivscraper
in your scripts. Let's import arxivscraper
and create a scraper to fetch all preprints in condensed matter physics category
from 27 May 2017 until 7 June 2017 (for other categories, see below):
import arxivscraper
scraper = arxivscraper.Scraper(category='physics:cond-mat', date_from='2017-05-27',date_until='2017-06-07')
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 = ('id', 'title', 'categories', 'abstract', 'doi', 'created', 'updated', 'authors')
df = pd.DataFrame(output,columns=cols)
To have more control over the output, you could supply a dictionary to filter out the results. As an example, let's collect all preprints related to machine learning. This subcategory (stat.ML
) is part of the statistics (stat
) category. In addition, we want those preprints that word learning
appears in their abstract.
import arxivscraper.arxivscraper as ax
scraper = ax.Scraper(category='stat',date_from='2017-08-01',date_until='2017-08-10',t=10, filters={'categories':['stat.ml'],'abstract':['learning']})
output = scraper.scrape()
In addition to
categories
andabstract
, other available keys forfilters
are:author
andtitle
.
Note that filters are based on logical OR and not mutually exclusive. So if the specified word appears in the abstract, the record will be saved even if it doesn't have the specified categories.
Ideas/bugs/comments? Please open an issue or submit a pull request on Github.
If arxivscraper
was useful in your work/research, please consider to cite it as :
Mahdi Sadjadi (2017). arxivscraper: Zenodo. http://doi.org/10.5281/zenodo.889853
or
@misc{msadjadi,
author = {Mahdi Sadjadi},
title = {arxivscraper},
year = 2017,
doi = {10.5281/zenodo.889853},
url = {https://doi.org/10.5281/zenodo.889853}
}
-
Mahdi Sadjadi, 2017.
-
Website: mahdisadjadi.com
-
Twitter: @mahdisadjadi
This project is licensed under the MIT License - see the LICENSE file for details.
Here is a list of all categories available on ArXiv. For a complete list of subcategories, see categories.md.
Category | Code |
---|---|
Computer Science | cs |
Economics | econ |
Electrical Engineering and Systems Science | eess |
Mathematics | math |
Physics | physics |
Astrophysics | physics:astro-ph |
Condensed Matter | physics:cond-mat |
General Relativity and Quantum Cosmology | physics:gr-qc |
High Energy Physics - Experiment | physics:hep-ex |
High Energy Physics - Lattice | physics:hep-lat |
High Energy Physics - Phenomenology | physics:hep-ph |
High Energy Physics - Theory | physics:hep-th |
Mathematical Physics | physics:math-ph |
Nonlinear Sciences | physics:nlin |
Nuclear Experiment | physics:nucl-ex |
Nuclear Theory | physics:nucl-th |
Physics (Other) | physics:physics |
Quantum Physics | physics:quant-ph |
Quantitative Biology | q-bio |
Quantitative Finance | q-fin |
Statistics | stat |