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A package based on SciHub and Google Scholar that can download articles given DOI, website address or keywords.

Project description

getarticle Python


getarticle is a package based on SciHub and Google Scholar that can download articles given DOI, website address or keywords.


Using pip to install:

# for latest version (recommended)
pip install git+

# for last release
pip install getarticle


Features & Usage

getarticle can be imported in Python or used as command line.

To use in command line:

usage: getarticle [-h] [-i INPUT] [-o OUTPUT] [-sd SETDOWNLOAD]

getarticle CLI

optional arguments:
  -h, --help            show this help message and exit
  -i INPUT, --input INPUT
                        article DOI or website
  -o OUTPUT, --output OUTPUT
                        download direction
  -sd SETDOWNLOAD, --setdownload SETDOWNLOAD
                        set default download direction


getarticle -i 10.1126/science.abc7424 -o /Users/haotian/Desktop

The download direction is the current direction in terminal by default. To change the default download direction, use -sd option.


getarticle -sd /Users/haotian/Downloads

# will download to /Users/haotian/Downloads folder
getarticle -i 10.1126/science.abc7424

getarticle can also download article of the current webpage (only supported for MacOS Safari).


# current Safari webpage: 

# download article of current webpage to default direction


To use in Python:

  1. Initialization
from getarticle import GetArticle

ga = GetArticle()
  1. Download a single article given DOI or website address.


  • Once downloaded, all stored articles will be cleared;
  • For download function, direction argument is the current direction by default;
  • Downloaded article is named as either "article title.pdf" if successfull or "year-month-day-hour-minute-second.pdf".
  1. Download multiple articles.


  • Repeatedly using article function can save multiple articles.
  • getarticle will not save & download duplicate articles;
  1. Download related articles given keywords. Keywords can be article names, research fields or author names. (This feature is under development.)"Deep Dive into Machine Learning Models for Protein Engineering")"SARS, Computation", num_of_page=2)"Roberta Croce")


  • num_of_page is the corresponding number of page in Google Scholar.
  • num_of_page is 1 by default.
  1. Show currently stored articles / delete article by index.




Project details

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