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Interesting approach. I would expect an object JSON stream to be more like a SAX parser though. It's familiar, fast and simple. Any thougts on not chosing the SAX approach?
Noteworthy: Contributions by Claude
Then added benchmarks and started doing optimization, getting it ~10x faster than my initial naive implementation. Then I threw agents at it, and between Claude, Gemini, and Codex we were able to make it an additional 2x faster.
Earlier quoted context omitted.
incomplete strings could be fun in certain cases {"cleanup_cmd":"rm -rf /home/foo/.tmp" }
Yeah, another fun one is string enums. Could tread "DeleteIfEmpty" as "Delete".
I’m imagining it in my mental model as being typed “unknown”. Anything that prevents accidental use as if it were a whole string… I imagine a more complex type with an “isComplete” flag of sorts would be more powerful but a bit of a blunderbuss.
It's less about incrementally parsing objects, and more about picking paths and shapes out from a feed. If you're doing something like array/newline delimited json, it's a great tool for reading things out as they arrive. Also great for example for feed parsing.
I wrote it when I was doing prototyping on doing streaming rendering of UIs defined by JSON generated by LLMs. Using constrained generation you can essentially hand the model a JSON serializable type, and it will always give you back a value that obeys that type, but the big models are slow enough that incremental rendering makes a big difference in the UX.
I'm pretty proud of the testing that's gone into this project. It's fairly exhaustively tested. If you can find a value that it parses differently than JSON.parse, or a place where it disobeys the 5+1 invariants documented in the README I'd be impressed (and thankful!).
This API, where you get a series of partial values, is designed to be easy to render with any of the `UI = f(state)` libraries like React or Lit, though you may need to short circuit some memoization or early exiting since whenever possible jsonriver will mutate existing values rather than creating new ones.
Oh fun, I wrote a similar library in 2015 for Haskell. There is an annoying gotcha to deal with: there are sequences of valid characters that can be parsed incorrectly if you’re doing incremental chunks, namely if “0.0” is split across two input chunks you can get a token stream with two valid float literals rather than 1! Namely “0” and “.0”, which is just a really annoying wart of json float syntax.
Oh fun, I wrote a similar library in 2015 for Haskell. There is an annoying gotcha to deal with: there are sequences of valid characters that can be parsed incorrectly if you’re doing incremental chunks, namely if “0.0” is split across two input chunks you can get a token stream with two valid float literals rather than 1! Namely “0” and “.0”, which is just a really annoying wart of json float syntax.
For those wondering about the use case, this is very useful when enabling streaming for structured output in LLM responses, such as JSON responses. For my local Raspberry Pi agent I needed something performant, I've been using streaming-json-js [1], but development appears to have been a bit dormant over the past year. I'll definitely take a look at your jsonriver and see how it compares! [1] https://github.com/karmi…
Oh fun, I wrote a similar library in 2015 for Haskell. There is an annoying gotcha to deal with: there are sequences of valid characters that can be parsed incorrectly if you’re doing incremental chunks, namely if “0.0” is split across two input chunks you can get a token stream with two valid float literals rather than 1! Namely “0” and “.0”, which is just a really annoying wart of json float syntax.