Research
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Datasette Lite is my version of Datasette that runs entirely in the browser using Pyodide in WebAssembly.
When I first built it four years ago I used Web Workers and code that intercepts navigation operations and fetches the generated HTML by running the Python app.
This worked, but had the disadvantage that any JavaScript in <script> tags would not be executed - breaking some Datasette functionality and a whole lot of Datasette plugins.
This morning I set Claude Opus 4.8 the task (in Claude Code for web) of figuring out how to run Python ASGI apps in Pyodide using Service Workers instead, and it seems to work! Here's a basic ASGI FastCGI demo and here's a demo that runs Datasette 1.0a31.
I'm still getting my head around exactly how it works, but once I've done that I plan to upgrade Datasette Lite itself.
It's been a few months since I last poked at Monty, the sandboxed subset of Python implemented in Rust. I had Claude Code look at the most recent release.
Importantly the max_duration_secs, max_memory, max_allocations, and max_recursion_depth settings all appear to work as advertised.
If it's good enough for antirez to add to Redis I figured Ville Laurikari's TRE regular expression engine was worth exploring in a little more detail.
I had Claude Code build an experimental Python binding (it used ctypes) and try some malicious regular expression attacks against the library. TRE handles those much better than Python's standard library implementation, thanks mainly to the lack of support for backtracking.
Anthropic publish the system prompts for Claude chat and make that page available as Markdown. I had Claude Code turn that page into separate files for each model and model family with fake git commit dates to enable browsing the changes via the GitHub commit view.
I used this to write my own detailed notes on the changes between Opus 4.6 and 4.7.
In Servo is now available on crates.io the Servo team announced the initial release of the servo crate, which packages their browser engine as an embeddable library.
I set Claude Code for web the task of figuring out what it can do, building a CLI tool for taking screenshots using it and working out if it could be compiled to WebAssembly.
The servo-shot Rust tool it built works pretty well:
git clone https://github.com/simonw/research
cd research/servo-crate-exploration/servo-shot
cargo build
./target/debug/servo-shot https://news.ycombinator.com/
Here's the result:

Compiling Servo itself to WebAssembly is not feasible due to its heavy use of threads and dependencies like SpiderMonkey, but Claude did build me this playground page for trying out a WebAssembly build of the html5ever and markup5ever_rcdom crates, providing a tool for turning fragments of HTML into a parse tree.
Inspired by this conversation on Hacker News about whether two SQLite processes in separate Docker containers that share the same volume might run into problems due to WAL shared memory. The answer is that everything works fine - Docker containers on the same host and filesystem share the same shared memory in a way that allows WAL to collaborate as it should.
In trying to build my own version of Claude Artifacts I got curious about options for applying CSP headers to content in sandboxed iframes without using a separate domain to host the files. Turns out you can inject <meta http-equiv="Content-Security-Policy"...> tags at the top of the iframe content and they'll be obeyed even if subsequent untrusted JavaScript tries to manipulate them.
Stuart Breckenridge pointed out that PC Gamer Recommends RSS Readers in a 37MB Article That Just Keeps Downloading, highlighting a truly horrifying example of web bloat that added up to 100s more MBs thanks to auto-playing video ads. I decided to have Claude Code for web use Rodney to investigate the page - prompt here.
Aaron Harper wrote about Node.js worker threads, which inspired me to run a research task to see if they might help with running JavaScript in a sandbox. Claude Code went way beyond my initial question and produced a comparison of isolated-vm, vm2, quickjs-emscripten, QuickJS-NG, ShadowRealm, and Deno Workers.
I had Claude Code run a micro-benchmark comparing different approaches to implementing tagging in SQLite. Traditional many-to-many tables won, but FTS5 came a close second. Full table scans with LIKE queries performed better than I expected, but full table scans with JSON arrays and json_each() were much slower.