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A set of utilities to expedite submission of jupyter notebooks to Gradescope

Project description

gsExport is a utility designed to help educators simplify and streamline the process of grading student notebooks. Designed to alleviate the struggles realized in UC Berkeley’s Data 8, the system allows students to easily export Jupyter notebooks as PDFs which are segmented to allow for easy grading through the Gradescope interface.


The system is easy to use, once installed on the client computer.

In order to generate the PDF file for a notebook, students simply run the following commands

import gsExport

The exporting tool does the following:

  • We diff the student’s notebook with the default “beginning” notebook, to see what regions students actually contributed to. By doing so, we eliminate a lot of the text/in-place code which doesn’t need to be graded

  • Using a custom LaTex template, we export to PDF (with pagebreaks as necessary)

Structure Requirements

How to work with gsExport

In your notebook, add the following

  • add the text #newpage in the Markdown cells before which you’d like to pagebreak (for example, the beginning of a question)

  • add ‘#student’ on all cells in which you expect the student to write information

To generate the new notebook, run the following commands in the shell

jupyter nbconvert hw01a.ipynb --NotebookExporter.preprocessors="['gsExport.gsExportPreprocessor']" --to notebook

which will generate a notebook with all the appropriate structure in hw01a.nbconvert.ipynb. The following structure inside the IPython notebook is added

  • The number of ‘#newpages’ in nb[‘metadata’][‘number_of_pages’]

  • All cells with ‘#student’ set cell[‘metadata’][‘#student’] = True, and the line with ‘#student’ is removed

  • We save a list of MD5 checksums of each cell in the notebook metadata: nb[‘metadata][‘checksums’]


pip install gsExport
pip install git+git:// # alternatively


  • - contains the main logic for the exporter

  • - contains utilities for importing and exporting notebooks

  • - contains the OK autograder and export logic

For those interested in bundling files

See for the commands required to install bundled files See for the commands required to fetch the bundled files (this is actually quite jank right now, because of a weird bug with Jupyter nbConvert )

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