Lifting Markup Language Prototype

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Lifting Markup Language Prototype

✓ Published1🌍 Public

Last edited Sep 24, 2020

Created on Sep 23, 2020

This prototype parses plain-text workout notes into structured data, showing parsed exercise, reps, weight, and notes on the right side against the raw input on the left. It uses `d3.text` to load the text file and a custom `parse` function to extract sets and reps from lines containing an `@` symbol, handling multipliers like `3x5`. The parsed rows are displayed via `JSON.stringify` in the right panel, demonstrating a potential pipeline for downstream visualization of workout history.

AI-generated description

A prototype for an idea: parse workout notes to structured data.

Overall idea is, when you do a workout you can use a note taking app to write in text form your exercises, sets and reps. This parser can then ingest that text and output structured data for downstream visualization. This unlocks the ability to produce charts and graphs of your workout history. Visualizations can highlight progression or lack of progression over time along various metrics such as highest weight lifted per exercise, overall volume, and others.

Thanks to Justin Curry for providing sample data and notation ideas!

MIT Licensed

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