Counting 3,663 Big Data & Machine Learning Frameworks, Toolsets, and Examples...
Suggestion? Feedback? Tweet @stkim1

Last Commit
Mar. 21, 2019
Aug. 21, 2017

ipynb-tex.sty Build Status

ipynb-tex is a simple style sheet which allows you to extract tagged cells out of a Jupyter notebook and include them in a TeX document

overview Rather than save output or copies of source code to insert into TeX docs, ipynb-tex always inserts the latest cells from your notebooks directly into TeX files.


In your main document directory, just make a symlink to the ipynb-tex.sty file.

ln -s /path/to/ipynb-tex/ipynb-tex.sty

Include cells in your .tex document

Command Description
\ipynbsource{notebook}[tag] Include the source from all cells sharing the tag "example".
\ipynboutput{notebook}[tag] Include the output from all cells sharing the tag "example".
\ipynb{notebook}[tag] Include the source and output from all cells sharing the tag "example".
\ipynbimage{notebook}[tag] Include an image
\ipynbtex{notebook}[tag] Include raw TeX output

Compile LaTeX

ipynb-tex uses PythonTeX to execute the cell extraction code. So, just as with PythonTeX, you'll need to execute pythontex as part of your document build. Also include --shell-escape to allow external functions to be called correctly.

pdflatex --shell-escape document.tex    #scan the document, figure out what Python needs to be executed
pythontex --rerun=always document       #executes the Python found in the document
pdflatex --shell-escape document.tex    #include any valid TeX printed from the Python execution
pdflatex --shell-escape document.tex    #ensure any included references are correctly handled

Tagging cells in a notebook

Toggle the toolbar UI

toggle toolbar ui

Tag a cell

tag a cell

Modifying this plugin

This repo comes with a ready to go version of ipynb-tex.sty, but if you want to make changes and rebuild it just run ./build, which merges ipynb-tex-template.sty and to create ipynb-tex.sty.

There are no package dependencies required to run this script, but to execute the sample you'll need to include a set of dependencies.

pip install -r requirements.txt

Running Tests

pip install nose


  • Remove the need to "rerun=always", by registering the [filename].ipynb as a dependency while pythontex is running.
  • Export cells only once, by making an in-memory variable which tags a file as already processed, to avoid repeated work.
  • Add a \ipynbdirectory which serves as the base path for all notebooks, so if you're compiling a doc with lots, no need to keep including the path