Jupyter Notebooks are a versatile and popular instance of the literate programming paradigm. Jupyter allows authors to intersperse code chunks with explanation and annotation, providing readers with more information about the intent and function of programming choices.
Code Ocean allows users to run Jupyter notebooks from the top-down, which we call 'reproducibility mode,' or interactively, which will run the more typical Jupyter notebook interface.
Reproducibility Mode (executing and rendering to HTML):
To publish on Code Ocean we ask that notebooks be executed as a whole, serving as a reproducible record of the analysis from start to finish.
To do so, use a shell script to execute
jupyter nbconvert , rendering the final results into
/results , and with the
--execute flag listed.
jupyter nbconvert \
Note on inline results:
Code Ocean currently strips out the inline results from notebooks in the
/code pane. This showcases that all notebooks in the
/results have been successfully rendered in the Code Ocean environment.
- Fractal Generation with L-Systems: Jupyter and JupyterLab
- A Modularized Efficient Framework for Non-Markov Time Series Estimation (this capsule uses a bash script to execute many notebooks in parallel)
On Writing Reproducible and Interactive Papers (this capsule demonstrates how to render a Jupyter notebook to
.texand subsequently to PDF, which requires LaTeX to be installed
- Identifying Gene Expression Programs of Cell-type Identity and Cellular Activity with Single-Cell RNA-Seq
- Rendering Jupyter notebooks to HTML (with more specific notes on the nbconvert command and its flags)
- Interactive Jupyter Sessions
- Installing additional Jupyter kernels
- Converting a Jupyter notebook to the latest version
- nbconvert GitHub repo (external resource)