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Watch the entire English language blossom from Wiktionary + Google Books N-grams, rendered as a living, breathing prefix galaxy.

• Zero-config takeover –./setup.sh spins up the virtualenv, fetches every dataset, caches the heavy lifts, and ships final MP4/GIF output.
• Radial growth cinematics – the trie erupts from the core alphabet, framing decades of linguistic evolution as a neon fractal.
• Repeatable science – every artifact (lemmata, first-year inference, trie counts, layouts) checkpoints to disk and into a reusable tarball for instant re-renders.
• Battle-tested – streams 26 full 1-gram shards, handles 1.4GB Wiktionary dumps, and renders 220 frames in glorious 1080p.

Share it, remix it, drop it in your next data-viz thread.

cd /Users/grey/Projects/graph-visualizationsbash setup.sh

The script will:

1. Create/upgradevenv/ with Python 3.
2. Download Wiktionary + Google Books 1-gram shards (a–z).
3. Extract English lemmas, infer first-use years, aggregate prefix counts.
4. Render 220 radial frames (outputs/frames/frame-0000.png →frame-0219.png).
5. Encodeoutputs/english_trie_timelapse.mp4 and a share-ready GIF.

Rerun the script anytime—artifact caching means future passes jump straight to rendering.

source venv/bin/activatepython -m src.viz.render_frames artifacts/trie/prefix_counts.jsonl outputs/framespython -m src.viz.encode outputs/frames outputs/english_trie_timelapse.mp4 outputs/english_trie_timelapse.gif

Use flags such as--min-radius,--max-radius,--base-edge-alpha, or--start-progress to tune the vibe.

Loadartifacts/years/first_years.tsv to explore in Neo4j (Community & Enterprise safe):

:parambatch=> $rows;UNWIND $rowsASrowWITHrowWHERErow.wordISNOTNULLANDrow.word<>""MERGE (w:Word{text:row.word})SETw.first_year=CASEWHENrow.first_year=""THENNULLELSEtoInteger(row.first_year)END;

Full documentation is available at theproject documentation site.

To run the documentation site locally:

cd docsbundle install --path vendor/bundlebundleexec jekyll serve --baseurl""

Visithttp://localhost:4000 to view the site locally.

• Drop the GIF in language history threads (#linguistics #dataart).
• Remix the radial layout with alternative color ramps or depth cutoffs.
• Pair the timelapse with poetry readings for maximum feels.

• Wiktionary community & Google Books N-gram team for open data.
• You, for showing the world how beautifully language grows.

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