wasm

Attention over time

7-day rolling share of analyzed posts/comments mentioning this entity · 90 daily points ending 2026-08-28

Final complete day: 2026-08-28. Attention was 0.2% — this entity appeared in 5 of 2,594 analyzed posts/comments in the seven days ending that day (5 mentions).

Each point is a seven-day rolling window of complete UTC days; a point is comparable only when at least 100 analyzed posts or comments fall inside it. A day with no analyzed records counts as zero; missing coverage is marked and never shown as zero. The series ends at the latest complete analyzed day — it never extends into the current incomplete day. How attention is measured.

Recent mentions

1. 2026-08-26 09:23 UTCComment

   Yup, I use a rust loader in bun that compiles imported rs files to wasm and even generates the ts definitions for them after the first compile. It's really fun.

2. 2026-08-25 18:21 UTCComment

   Neat implementation. Bun plugins using the onLoad hook make custom asset compilers (like Elm or WASM loaders) feel completely native in modern toolchains without needing Webpack loader bloat.

3. 2026-08-24 01:04 UTCComment

   Not quite. WASM memory only grows, never shrinks, so the ceiling is whatever the largest page in the doc pushed it to, and it stays there. A 200-page scan just has more chances to hit that page.

4. 2026-08-23 11:16 UTCPost

   Trazor: an image vectorizer that runs fully in your browser - Hi r/webdev! I'm building an open source app that turns images into clean SVG, and it all runs in your browser. Nothing gets uploaded, there is no back end, and there is no account to make. I am trying to get the quality close to paid tools while keeping it easy to use. There are a lot of settings, but an "Auto settings" button picks good ones for you and explains why. It does not use any existing vectorization library. Each step is built from published research papers (there is a list in the repo if you want to read them). There are also some optional machine learning tools that run on your own device. Right now that is just an edge step that helps find outlines more cleanly. The other ML models are not ready yet (my GPU is on fire). The whole process for building the models is written down and scripted in the repo. It is still early, but I would really like to hear how the results compare to other free or paid tools for your own images. For now it is just the web app. Nothing is on npm yet, but the code is already split into clean packages, so I will release the libraries and a command line tool if people want them. One note, since it always comes up: yes, I built this with a lot of help from Claude. But the design is mine, every step comes from published research, and I understand and stand behind all of it. Source code: The app: It works in any modern browser. The optional ML tools use your GPU when it is there and fall back to the CPU/WASM when it is not.

5. 2026-08-22 17:29 UTCComment

   extracting font glyphs and rebuilding the text stream in-browser is brutal. wasm memory spikes usually crash the tab on large docs, curious how u handle worker cleanup when parsing heavy files.