Git Product home page Git Product logo

scholarly's Introduction

Python package codecov Documentation Status DOI

scholarly

scholarly is a module that allows you to retrieve author and publication information from Google Scholar in a friendly, Pythonic way without having to solve CAPTCHAs.

Installation

Anaconda-Server Badge PyPI version

scholarly can be installed either with conda or with pip. To install using conda, simply run

conda install -c conda-forge scholarly

Alternatively, use pip to install the latest release from pypi:

pip3 install scholarly

or pip to install from github:

pip3 install -U git+https://github.com/scholarly-python-package/scholarly.git

We are constantly developing new features. Please update your local package regularly. scholarly follows Semantic Versioning. This means your code that uses an earlier version of scholarly is guaranteed to work with newer versions.

Optional dependencies

  • Tor:

    scholarly comes with a handful of APIs to set up proxies to circumvent anti-bot measures. Tor methods are deprecated since v1.5 and are not actively tested or supported. If you wish to use Tor, install scholarly using the tor tag as

    pip3 install scholarly[tor]

    If you use zsh (which is now the default in latest macOS), you should type this as

    pip3 install scholarly'[tor]'

    Note: Tor option is unavailable with conda installation.

Tests

To check if your installation is succesful, run the tests by executing the test_module.py file as:

python3 test_module

or

python3 -m unittest -v test_module.py

Documentation

Check the documentation for a complete API reference and a quickstart guide.

Examples

from scholarly import scholarly

# Retrieve the author's data, fill-in, and print
# Get an iterator for the author results
search_query = scholarly.search_author('Steven A Cholewiak')
# Retrieve the first result from the iterator
first_author_result = next(search_query)
scholarly.pprint(first_author_result)

# Retrieve all the details for the author
author = scholarly.fill(first_author_result )
scholarly.pprint(author)

# Take a closer look at the first publication
first_publication = author['publications'][0]
first_publication_filled = scholarly.fill(first_publication)
scholarly.pprint(first_publication_filled)

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

# Which papers cited that publication?
citations = [citation['bib']['title'] for citation in scholarly.citedby(first_publication_filled)]
print(citations)

IMPORTANT: Making certain types of queries, such as scholarly.citedby or scholarly.search_pubs, will lead to Google Scholar blocking your requests and may eventually block your IP address. You must use proxy services to avoid this situation. See the "Using proxies" section in the documentation for more details. Here's a short example:

from scholarly import ProxyGenerator

# Set up a ProxyGenerator object to use free proxies
# This needs to be done only once per session
pg = ProxyGenerator()
pg.FreeProxies()
scholarly.use_proxy(pg)

# Now search Google Scholar from behind a proxy
search_query = scholarly.search_pubs('Perception of physical stability and center of mass of 3D objects')
scholarly.pprint(next(search_query))

scholarly also has APIs that work with several premium (paid) proxy services. scholarly is smart enough to know which queries need proxies and which do not. It is therefore recommended to always set up a proxy in the beginning of your application.

Disclaimer

The developers use ScraperAPI to run the tests in Github Actions. The developers of scholarly are not affiliated with any of the proxy services and do not profit from them. If your favorite service is not supported, please submit an issue or even better, follow it up with a pull request.

Contributing

We welcome contributions from you. Please create an issue, fork this repository and submit a pull request. Read the contributing document for more information.

Acknowledging scholarly

If you have used this codebase in a scientific publication, please cite this software as following:

@software{cholewiak2021scholarly,
  author  = {Cholewiak, Steven A. and Ipeirotis, Panos and Silva, Victor and Kannawadi, Arun},
  title   = {{SCHOLARLY: Simple access to Google Scholar authors and citation using Python}},
  year    = {2021},
  doi     = {10.5281/zenodo.5764801},
  license = {Unlicense},
  url = {https://github.com/scholarly-python-package/scholarly},
  version = {1.5.1}
}

License

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

scholarly's People

Contributors

arunkannawadi avatar ipeirotis avatar silvavn avatar programize-admin avatar organicirradiation avatar 1ucian0 avatar stefanct avatar bielsnohr avatar waynehuu avatar tombrien avatar franciscoknebel avatar klipitkaspro avatar jonasengelmann avatar firefly-cpp avatar remram44 avatar ltalirz avatar tallalnparis4ev avatar jjshoots avatar nikitabalabin avatar mmontevil avatar cako avatar bryant1410 avatar rnatella avatar papr avatar spferical avatar guicho271828 avatar abspoel avatar marcoscarpetta avatar percolator avatar louiskirsch avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.