It is difficult to build much without needing to deal with json at some point. In the world of F# there are several options. Today I want to lay out some of the popular choices and offer some some compare and contrast. These libraries all have their own strengths and weaknesses, and bringing it all into a single place to highlight these is a useful point of reference for decision making and general understanding.

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Today I want to spend some time with join-semilattices, specifically my F# implementation, LVar. It is a conceptually interesting data structure and approach to managing information, as well as improving program correctness.

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Yaml is a useful format for both configuration and simple data representation that pops up from time to time. As a result, it is helpful to know how to use it and coding in F#. Today I’ll take a quick look into using Yaml and how it can be integrated into an F# project.

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Recently Ted Unangst wrote about his tool, watc, to extract line count and file size statistics to support some of his work. Chris Wellons followed up with his take on watc. Inspired by both posts, I thought it would be an interesting tool to add to my own toolbox. It pairs nicely with some of my current work on extracting useful information from code repositories. This feels like a good way to put together a quick tool using F#. I’ll also use this as an opportunity to show some F# along the way.

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Today’s “data in motion” post is a visualization of earthquakes over time. I’ll use seismic data from the National Science Foundation. Keeping with the theme, I’ll use F# and FFmpeg to convert the raw data into a video of the data over time.

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