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import arxiv
import pandas as pd
def format_query(author='',title='',cat='',abstract=''):
"""Returns a formatted arxiv query string to handle simple queries of at most one instance each of these fields. To leave a field unspecified,
leave the corresponding argument blank.
e.g. format_query(cat='math.AP') will return the string used to pull all articles with the subject tag 'PDEs'.
Args:
author: string to search for in the author field.
title: string to search for in the title field.
cat: A valid arxiv subject tag. See the full list of these at:
https://arxiv.org/category_taxonomy
abstract: string to search for in the abstract field.
Returns:
properly formatted query string to return all results simultaneously matching all specified fields.
"""
tags = [f'au:{author}', f'ti:{title}', f'cat:{cat}', f'abs:{abstract}']
query = ' AND '.join([tag for tag in tags if not tag.endswith(':')])
return query
def query_to_df(query,max_results):
"""Returns the results of an arxiv API query in a pandas dataframe.
Args:
query: string defining an arxiv query formatted according to
https://info.arxiv.org/help/api/user-manual.html#51-details-of-query-construction
max_results: positive integer specifying the maximum number of results returned.
Returns:
pandas dataframe with one column for indivial piece of metadata of a returned result.
To see a list of these columns and their descriptions, see the documentation for the Results class of the arxiv package here:
http://lukasschwab.me/arxiv.py/index.html#Result
The 'links' column is dropped and the authors column is a list of each author's name as a string.
The categories column is also a list of all tags appearing.
"""
client = arxiv.Client(page_size=100,num_retries=3)
search = arxiv.Search(
query = query,
max_results=max_results,
sort_by=arxiv.SortCriterion.LastUpdatedDate
)
results = client.results(search)
drop_cols = ['authors','links','_raw']
df = pd.DataFrame()
for result in results:
row_dict = {k : v for (k,v) in vars(result).items() if k not in drop_cols}
row_dict['authors'] = [author.name for author in result.authors]
row_dict['links'] = [link.href for link in result.links]
row = pd.Series(row_dict)
df = pd.concat([df , row.to_frame().transpose()], axis = 0)
return df.reset_index(drop=True,inplace=False)
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