The big unlock here is https://github.com/html5lib/html5lib-tests - a collection of 9,000+ HTML5 parser tests that are their own independent file format, e.g. this one: https://github.com/html5lib/html5lib-tests/blob/master/tree-...
The Servo html5ever Rust codebase uses them. Emil's JustHTML Python library used them too. Now my JavaScript version gets to tap into the same collection.
This meant that I could set a coding agent loose to crunch away on porting that Python code to JavaScript and have it keep going until that enormous existing test suite passed.
Sadly conformance test suites like html5lib-tests aren't that common... but they do exist elsewhere. I think it would be interesting to collect as many of those as possible.
This blog post isn't really about HTML parsers, however. The JustHTML port described in this blog post was a worthwhile exercise as a demonstration on its own.
Even so, I suspect that for this particular application, it would have been more productive/valuable to port the Java codebase to TypeScript rather than using the already vibe coded JustHTML as a starting point. Most of the value of what is demonstrated by JustHTML's existence in either form comes from Stenström's initial work.
I personally think that even before LLMs, the cost of code wasn't necessarily the cost of typing out the characters in the right order, but having a human actually understand it to the extent that changes can be made. This continues to be true for the most part. You can vibe code your way into a lot of working code, but you'll inevitably hit a hairy bug or a real world context dependency that the LLM just cannot solve, and that is when you need a human to actually understand everything inside out and step in to fix the problem.
Verified Compliance: Passes all 9k+ tests in the official html5lib-tests suite (used by browser vendors).
Yes, browsers do you use it. But they handle a lot of stuff differently. selectolax 68% No Very Fast CSS selectors C-based (Lexbor). Very fast but less compliant.
The original author compares selectolax to html5lib-tests, but the reality is that when you compare selectolax to Chrome output, you get 90%+.One of the tests:
INPUT: <svg><foreignObject></foreignObject><title></svg>foo
It fails for selectolax: Expected:
| <html>
| <head>
| <body>
| <svg svg>
| <svg foreignObject>
| <svg title>
| "foo"
Actual:
| <html>
| <head>
| <body>
| <svg>
| <foreignObject>
| <title>
| "foo"
But you get this in Chrome and selectolax: <html><head></head><body><svg><foreignObject></foreignObject><title></title></svg>foo
</body></html>https://martinalderson.com/posts/has-the-cost-of-software-ju...
This last post was largely dismissed in the comments here on HN. Simon's experiment brings new ground for the argument.
> Does this library represent a legal violation of copyright of either the Rust library or the Python one? Even if this is legal, is it ethical to build a library in this way?
Currently, I am experimenting with two projects in Claude Code: a Rust/Python port of a Python repo which necessitates a full rewrite to get the desired performance/feature improvements, and a Rust/Python port of a JavaScript repo mostly because I refuse to install Node (the speed improvement is nice though).
In both of those cases, the source repos are permissively licensed (MIT), which I interpret as the developer intent as to how their code should used. It is in the spirit of open source to produce better code by iterating on existing code, as that's how the software ecosystem grows. That would be the case whether a human wrote the porting code or not. If Claude 4.5 Opus can produce better/faster code which has the same functionality and passes all the tests, that's a win for the ecosystem.
As courtesy and transparency, I will still link and reference the original project in addition to disclosing the Agent use, although those things aren't likely required and others may not do the same. That said, I'm definitely not using an agent to port any GPL-licensed code.
For solo devs this changes the calculus entirely. Supporting multiple languages used to mean maintaining multiple codebases - now you can treat the original as canonical and regenerate ports as needed. The test suite becomes the actual artifact you maintain.
> It took two initial prompts and a few tiny follow-ups. GPT-5.2 running in Codex CLI ran uninterrupted for several hours, burned through 1,464,295 input tokens, 97,122,176 cached input tokens and 625,563 output tokens and ended up producing 9,000 lines of fully tested JavaScript across 43 commits.
Using a random LLM cost calculator, this amounts to $28.31... pretty reasonable for functional output.I am now confident that within 5-10 years (most/all?) junior & mid and many senior dev positions are going to drop out enormously.
Source: https://www.llm-prices.com/#it=1464295&cit=97123000&ot=62556...
This specific case worked well, I suspect, since LLMs have a LOT of previous knowledge with HTML, and saw multiple impl and parsing of HTML in the training.
Thus I suspect that in real world attempts of similar projects and any non well domain will fail miserably.
I'm curious if this will implicitly drive a shift in the usage of packages / libraries broadly, and if others think this is a good or bad thing. Maybe it cuts down the surface of upstream supply-chain attacks?
No, because it's a derivative work of the base library.
It is enormously useful for the author to know that the code works, but my intuition is if you asked an agent to port files slowly, forming its own plan, making commits every feature, it would still get reasonably close, if not there.
Basically, I am guessing that this impressive output could have been achieved based on how good models are these days with large amounts of input tokens, without running the code against tests.
I'm a bit sad about this; I'd rather have "had fun" doing the coding, and get AI to create the test cases, than vice versa.
As is mentioned in the comments, I think the real story here is two fold - one, we're getting longer uninterrupted productive work out of frontier models - yay - and a formal test suite has just gotten vastly more useful in the last few months. I'd love to see more of these made.
i think the fun conclusion would be: ideally no better, and no worse. that is the state you arrive it IFF you have complete tests and specs (including probably for performance). now a human team handcrafting would undoubtedly make important choices not clarified in specs, thereby extending the spec. i would argue that human chain of thought from deep involvement in building and using the thing is basically 100% of the value of human handcrafting, because otherwise yeah go nuts giving it to an agent.
burned through 1,464,295 input tokens, 97,122,176 cached input tokens and 625,563 output tokens
How much did it cost?^Claude still thinks it's 2024. This happens to me consistently.
There are many OSe out there suffering from the same problem. Lack of drivers.
AI can change it.
It's an interesting assumption that an expert team would build a better library. I'd change this question to: would an expert team build this library better?