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Building Reproducibility and Efficiency into Document Collaboration Workflows from Jupyter Notebooks

Simon Porter

Audience level:

Brief Summary

Ideal for people who create graphs for collaborative typeset reports and documents and are looking for ways to streamline their workflows. Attendees will need to have a basic level of knowledge on Jupyter Notebooks (able to write scripts that push graphs via git bridge) and be familiar with Overleaf (LaTeX).


The session covers how to write a script in Jupyter Notebooks which automatically pushes graphs via the git bridge into an Overleaf document where team members can collaborate on writing. We’ll cover:

Creating a graph in Jupyter Notebooks, Demo of how Jupyter Notebooks and Overleaf sync works, How to write your script in Jupyter Notebooks, Pushing graphs via the git bridge into Overleaf (using both gitPython and gigaleaf), Choosing an Overleaf report template, Adding a script to your Overleaf template to place your Jupyter Notebooks graphs and tables, How to trace the providence of charts and tables in your overleaf document back to the revision of the notebook that created them.

The key takeaways of the session will be how to create automatic, data driven typeset reports using Jupyter Notebooks, Git bridge and Overleaf.

More information on gigaleaf: https://github.com/gigantum/gigaleaf, Blogpost: https://www.overleaf.com/blog/reproducible-research-with-overleaf-and-gigantum

Gigantum repo: https://github.com/gigantum

Digital Science Case Study: https://www.overleaf.com/blog/a-case-study-how-to-create-professional-looking-documents-in-house