Sort Google Scholar by the Number of Citations

sortgs is a Python tool for ranking Google Scholar publications by the number of citations. It is useful for finding relevant papers in a specific field. The data acquired from Google Scholar includes Title, Citations, Links, Rank, and a new column with the number of citations per year. In the background, it first try to fetch results using python requests. If it fails, it will use selenium to fetch the results.

🚀 Run it on Google Colab

• No-Code Version (new!): — No coding required! Perfect for a quick start! ⚡
• Code Version: — For developers who want full control of what's behind the scenes! 💻

💡 All you need is a Google Account to get started.
⚠️ Note: Google Scholar may block access after too many repetitive requests due to CAPTCHA checks, so proceed mindfully!

📚 Colab No-Code Instructions

https://github.com/user-attachments/assets/25de7bad-2a5d-4bcf-b486-faa1d7a29eb3

Installation

You can install sortgs directly using pip:

pip install sortgs

This will install the latest version of sortgs and its dependencies.

Usage

Once installed, you can run sortgs directly from the command line:

sortgs "your keyword"

Replace "your keyword" with any keyword you'd like to search for. A CSV file with the name your_keyword.csv will be created in your current directory.

Misc

For a feedback, send me an email: fernando [dot] wittmann [at] gmail [dot] com

Command Line Arguments

usage: sortgs [-h] [--sortby SORTBY] [--nresults NRESULTS] [--csvpath CSVPATH]
              [--notsavecsv] [--plotresults] [--startyear STARTYEAR]
              [--endyear ENDYEAR] [--debug] kw

positional arguments:
  kw                    Keyword to be searched. Use double quote followed by
                        simple quote for an exact keyword. 
                        Example: sortgs "'exact keyword'"

optional arguments:
  -h, --help            show this help message and exit
  --sortby SORTBY       Column to be sorted by. Default is "Citations". To sort
                        by citations per year, use --sortby "cit/year"
  --langfilter LANGFILTER [LANGFILTER ...]
                        Only languages listed are permitted to pass the filter. 
                        List of supported language codes: zh-CN, zh-TW, nl, en, fr,
                        de, it, ja, ko, pl, pt, es, tr
  --nresults NRESULTS   Number of articles to search on Google Scholar. Default
                        is 100. (careful with robot checking if value is high)
  --csvpath CSVPATH     Path to save the exported csv file. Default is the 
                        current folder
  --notsavecsv          By default, results are exported to a csv file. Select
                        this option to just print results but not store them
  --plotresults         Use this flag to plot results with the original rank on
                        the x-axis and the number of citations on the y-axis.
                        Default is False
  --startyear STARTYEAR
                        Start year when searching. Default is None
  --endyear ENDYEAR     End year when searching. Default is current year
  --debug               Debug mode. Used for unit testing. It will get pages
                        stored on web archive

Examples

1. Default Search:

   sortgs "machine learning"
   

   This command searches for the top 100 results related to "machine learning" and saves them as a CSV file.

2. Sort by Citations per Year:

   sortgs "machine learning" --sortby "cit/year"
   

   Search for "machine learning" and sort by the number of citations per year.

3. Specify Date Range:

   sortgs "machine learning" --startyear 2005 --endyear 2015
   

   Search for papers from 2005 to 2015.

4. Search for an Exact Keyword:

   sortgs "'machine learning'"
   

5. Save Results in a Specific Path:

   sortgs 'neural networks' --csvpath './examples/'
   

   This will save the results under a subfolder called 'examples'.

6. Multiple Keywords:

   sortgs '"deep learning" OR "neural networks" OR "machine learning"' --sortby "cit/year"
   

7. Language Filter:

   sortgs "machine learning" --langfilter pt es fr de
   

   This will only include articles in Portuguese, Spanish, French, and German.

Output Example

While running, sortgs will provide updates in the terminal:

❯ sortgs "'machine learning'"
Running with the following parameters:
Keyword: 'machine learning', Number of results: 100, Save database: True, Path: /Users/wittmann/sort-google-scholar, Sort by: Citations, Plot results: False, Start year: None, End year: 2023, Debug: False
Loading next 10 results
Loading next 20 results
...

Step-by-Step Installation

1. Install Python 3.10+ (a published release uses pip install sortgs)
2. From a checkout, use uv:

uv sync --group dev
uv run sortgs "your keyword"

3. A CSV file with the name your_keyword.csv should be created.

If those steps are too complicated for you, send me an email with a list of keyworks that you'd like them ranked to: fernando [dot] wittmann [at] gmail [dot] com

Running Project Using Docker

This guide will walk you through the process of installing Docker, pulling the fernandowittmann/sort-google-scholar Docker image, and running the project.

Step 1: Install Docker

Windows or Mac

1. Download Docker Desktop: Go to the Docker Desktop website and download the appropriate installer for your operating system.
2. Install Docker Desktop: Run the installer and follow the on-screen instructions.
3. Verify Installation: Open a terminal (or command prompt on Windows) and run docker --version to verify that Docker has been installed successfully.

Linux

1. Update Package Index: Run sudo apt-get update to update your package index.
2. Install Docker: Run sudo apt-get install docker-ce docker-ce-cli containerd.io to install Docker.
3. Start Docker: Run sudo systemctl start docker to start the Docker daemon.
4. Verify Installation: Run docker --version to ensure Docker is installed correctly.

Step 2: Pull the Docker Image

1. Pull Image: Run the following command to pull the fernandowittmann/sort-google-scholar image from Docker Hub:

   docker pull fernandowittmann/sort-google-scholar
   

Step 3: Run the Project

1. Run the Docker Container: Use the following command to run the container:

   docker run -v "$PWD/sortgs-results:/app" fernandowittmann/sort-google-scholar "machine learning" 
   

   Replace $PWD with the absolute path to your results directory if you are not in the parent directory of sortgs-results.

Contributing

See CONTRIBUTING.md for uv setup, tests, pull requests, and the main / PyPI release checklist. Short version:

uv sync --group dev
uv run pytest

About Robot Check

Google Scholar may block access after too many repetitive requests due to CAPTCHA checks. The direct path sends a browser User-Agent so a plain requests call is less likely to be rejected as python-requests. If a block page still appears, Selenium is used as a fallback. You might be asked to solve a CAPTCHA manually. If both paths fail, sortgs exits with status 1 and does not write an empty CSV.

Google Colab shared IPs are often blocked, and the hosted runtime does not start the Chrome session this project uses. Prefer a local run, or a VPN, if Colab returns an empty table.

When using Selenium locally, you might need Chrome and a matching chromedriver. See https://developer.chrome.com/docs/chromedriver/downloads.

LICENSE

• MIT

Updates

Main branch has been renamed from master. Update it locally by running:

git branch -m master main
git fetch origin
git branch -u origin/main main
git remote set-head origin -a

💖 Support the Project

If you find this project helpful and would like to support its development, consider making a donation. Your support is greatly appreciated!

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