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Simple access to Google Scholar authors and citations

Project description


scholarly is a module that allows you to retrieve author and publication information from Google Scholar in a friendly, Pythonic way.


Because scholarly does not use an official API, no key is required. Simply:

import scholarly

print(next(scholarly.search_author('Steven A. Cholewiak')))


  • search_author -- Search for an author by name and return a generator of Author objects.
>>> search_query = scholarly.search_author('Marty Banks, Berkeley')
>>> print(next(search_query))
{'_filled': False,
 'affiliation': 'Professor of Vision Science, UC Berkeley',
 'citedby': 17758,
 'email': '',
 'id': 'Smr99uEAAAAJ',
 'interests': ['vision science', 'psychology', 'human factors', 'neuroscience'],
 'name': 'Martin Banks',
 'url_picture': ''}
  • search_keyword -- Search by keyword and return a generator of Author objects.
>>> search_query = scholarly.search_keyword('Haptics')
>>> print(next(search_query))
{'_filled': False,
 'affiliation': 'Stanford University',
 'citedby': 31731,
 'email': '',
 'id': '4arkOLcAAAAJ',
 'interests': ['Robotics', 'Haptics', 'Human Motion Understanding'],
 'name': 'Oussama Khatib',
 'url_picture': ''}
  • search_pubs_query -- Search for articles/publications and return generator of Publication objects.
>>> search_query = scholarly.search_pubs_query('Perception of physical stability and center of mass of 3D objects')
>>> print(next(search_query))
{'_filled': False,
 'bib': {'abstract': 'Humans can judge from vision alone whether an object is '
                     'physically stable or not. Such judgments allow observers '
                     'to predict the physical behavior of objects, and hence '
                     'to guide their motor actions. We investigated the visual '
                     'estimation of physical stability of 3-D objects (shown '
                     'in stereoscopically viewed rendered scenes) and how it '
                     'relates to visual estimates of their center of mass '
                     '(COM). In Experiment 1, observers viewed an object near '
                     'the edge of a table and adjusted its tilt to the '
                     'perceived critical angle, ie, the tilt angle at which '
                     'the object …',
         'author': 'SA Cholewiak and RW Fleming and M Singh',
         'eprint': '',
         'title': 'Perception of physical stability and center of mass of 3-D '
         'url': ''},
 'citedby': 14,
 'id_scholarcitedby': '15736880631888070187',
 'source': 'scholar',
 'url_scholarbib': ''}


Here's a quick example demonstrating how to retrieve an author's profile then retrieve the titles of the papers that cite his most popular (cited) paper.

# Retrieve the author's data, fill-in, and print
search_query = scholarly.search_author('Steven A Cholewiak')
author = next(search_query).fill()

# Print the titles of the author's publications
print([pub.bib['title'] for pub in author.publications])

# Take a closer look at the first publication
pub = author.publications[0].fill()

# Which papers cited that publication?
print([citation.bib['title'] for citation in pub.get_citedby()])


Use pip to install from pypi:

pip install scholarly

or pip to install from github:

pip install git+

or clone the package using git:

git clone


Requires arrow, Beautiful Soup, bibtexparser, and requests[security].


The original code that this project was forked from was released by Bello Chalmers under a WTFPL license. In keeping with this mentality, all code is released under the Unlicense.

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