notebook – Brushing Up Science

Jupyter Notebooks are gone from my scientific workflow

TL;DR: I’ve just learned that the text editor Sublime Text can display images within Markdown files. Gone therefore is my need to use Jupyter Notebooks.

I was never a true convert to Jupyter Notebooks. I used them for several years, and saw their appeal, but they just didn’t quite feel right to me.

Most complaints against Notebooks are technical ones: they’re awkward to version control, they’re hard to debug, and they promote poor programming practices. But these issues are tangential to my complaints against Notebooks, which are are less concrete:

I’m always scrolling. It’s inefficient.
I don’t want to do work in a browser. Maybe it’s a weak reason, but I like keeping my scientific and programming tools separate from the browser.
Editing and navigating Notebooks feels clumsy. Maybe it’s a lack of practice, but I’d rather leverage the time I’ve invested in learning and setting up my text editor than spend time learning a bunch of new shortcuts specific to Notebooks.

Organise scripts and figures easily with Jupyter Notebooks

Keeping track of scripts used to generate figures is difficult. Before realising that Jupyter Notebooks could solve most of my problems, I would have directories with dozens of scripts with filenames of varying levels of ambiguity. Names that probably meant something to me at the time, but are hardly descriptive months or years later. Names like ISW_plume_plots.m, new_ISW_model_plots.m, and plot_model_behaviour.m. A certain PhD comic springs to mind.

Regardless of whether its Python, R, Julia, Matlab, or pretty much any other type of code, Jupyter Notebooks solve the problem. For example, I use a single notebook to archive the code for all figures in a paper and, more importantly, I can associate each set of code with the figure it generates. Rather than trying to remember what file I want, I need only remember which figure I want. (I say archive because I much prefer to do the bulk of my exploratory analysis in an editor. Alternatively, JupyterLab may work better for you.)

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An improved Matlab command line (plus Jupyter Notebooks for Matlab)

The command line is a large part of any Matlab user’s workflow. This vital tool, however, isn’t as user friendly as it should be: it’s cumbersome to recall multi-line commands from the history, there’s no support for Vim key bindings, and there’s no syntax highlighting if using the nodesktop option (on a remote computer, say). Fortunately, there’s an alternative that avoids these problems: IMatlab. This kernel also lets you run Matlab code in Jupyter Notebooks (originally known as IPython Notebooks).

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