I wrote JustHTML using coding agents

JustHTML https://github.com/EmilStenstrom/justhtml is a neat new Python library - it implements a compliant HTML5 parser in ~3,000 lines of code that passes the full existing 9,200 test HTML5 conformance suite.

Emil Stenström wrote it with a variety of coding agent tools over the course of a couple of months. It's a really interesting case study in using coding agents to take on a very challenging project, taking advantage of their ability to iterate against existing tests.

I wrote a bit more about it here: https://simonwillison.net/2025/Dec/14/justhtml/

Thanks for sharing simon! Writing a parser is a really good job for a coding agent, because there's a clear right/wrong answer. In this case, the path there is the challenging part. The hours I've spent trying to convince agents to implement adoption agency well... :)

while it's mentioned in the post, it seems to me a bit burried:

isn't this more like a port of `html5ever` from rust to python using LLM, as opposed to creating something "new" based on the test suite alone?

if yes, wouldn't be the distinction rather important?

Depending on your perspective, you can take away any of the two points.

The first iteration of the project created a library from scratch, from the tests all the way to 100% test coverage. So even without the second iteration, it's still possible to create something new.

In an attempt to speed it up, I (with coding agent) rewrote it again based on html5ever's code structure. It's far from a clean port, because it's heavily optimized Rust code, that isn't possible to port to Python (Rust marcos). And it still depended on a lot of iteration and rerunning tests to get it anywhere.

I'm not pushing any agenda here, you're free to take what you want from it!

Thank you for the clarification, that was not entirely clear to me from the post.

You also mention that the current "optimised" version is "good enough" for every-day use (I use `bs4` for working with html), was the first iteration also usable in that way? Did you look at `html5ever` because the LLM hit a wall trying to speed it up?

It was usable! Yeah, the handler based architecture that I had built on was very dependent on object lookups and method calls, and my hunch was that I had hit a wall trying to optimize the speed. I was slower than html5lib still, so decided to go with another "code architecture" (html5ever) that was closer to the metal. Worked out in getting me ~60% faster than html5lib.

As for bs4, if you don't change the default, you get the stdlib html.parser, which doesn't implement html5. Only works for valid HTML.

I just had Codex CLI figure out where that first version ended and the new one began.

It looks to me like this is the last commit before the rewrite: https://github.com/EmilStenstrom/justhtml/tree/989b70818874d...

The commit after that is https://github.com/EmilStenstrom/justhtml/commit/7bab3d2 "radical: replace legacy TurboHTML tree/handler stack with new tokenizer + treebuilder scaffold"

It also adds this document called html5ever_port_plan.md: https://github.com/EmilStenstrom/justhtml/blob/7bab3d22c0da0...

Here's the Codex CLI transcript I used to figure this out: https://gistpreview.github.io/?53202706d137c82dce87d729263df...

> 3,000 loc

I cloned the repo and ran `wc -l` on the src directory and got closer to 9,500. Am i missing something?

Edit: maybe you meant just the parser

if it isnt too much to ask, since you are already insanely familiar with the html parser semantics, can you write a postgres extension that can parse html inside postgres? usecase: cleaning rss feed items while storing

Is it really too much to do a little more editing of the LLM output for the blog post? There's 17 numbered and titled section headings, all of which are linkable to with anchors, and which mostly have two sentences each.

RSS on website is erroring. I'd like to follow!

Hi! Yes, the headers were LLM generated and the text were not. I didn't want the blog post to go on for ages, so I just wrote a few lines under each heading. Any ideas how to make it better, while not being too long?

Thanks! Now fixed.

The license is MIT, so feel free to expand this any way you want! No need to write a new parser from scratch.

I'd start by deleting all the numbered section headings, and add either a transition word (then, so) or a transition sentence (why you went from step n to step n+1 or after how much time or whatnot).

New iteration up. I kept the headings because they make the text easier to scan, but made them more descriptive. Added some transition words. Slight improvement I think.