Hacker News with Generative AI: JSON

Fast columnar JSON decoding with arrow-rs (arroyo.dev)
JSON is the most common serialization format used in streaming pipelines, so it pays to be able to deserialize it fast. This post covers in detail how the arrow-json library works to perform very efficient columnar JSON decoding, and the additions we've made for streaming use cases.
Decoding JSON sum types in Go without panicking (nicolashery.com)
The Go programming language doesn't have native support for sum types, but we'll see how we can emulate them, how to decode and encode them into JSON, and how in some cases they can help avoid runtime panic exceptions.
Matching Regexps 200 Times Faster (eregon.me)
You might have seen @byroot’s excellent blog post series on optimizing the json gem. From the first blog post it’s clear most of the time for generating JSON is spent in generate_json_string() and specifically in convert_UTF8_to_JSON(), i.e., in converting Ruby Strings to JSON Strings.
Show HN: I built a JSON and JSON5 parser with MISRA C conformance (railgunlabs.com)
Abusing C to implement JSON parsing with struct methods (xnacly.me)
Build a JSON parser in cInstead of using by itself functions: attach functions to a struct and use these as methodsmake it C issue family free (segfaults, leaks, stack overflows, etc…)provide an ergonomic API
JSON has become today's machine-readable output format on Unix (utoronto.ca)
Recently, I needed to delete about 1,200 email messages to a particular destination from the mail queue on one of our systems.
Parsing JSON in 500 lines of Rust (krish.gg)
Last semester at university, I took a course called "Syntax-Based Tools and Compilers". It focused on building a scanner, parser, compiler, and so on for a language called PL0. We used Python in the course, but I was really interested in learning Rust at the time.
How (not) to sign a JSON object (2019) (latacora.com)
Last year we did a blog post on interservice auth. This post is mostly about authenticating consumers to an API. That’s a related but subtly different problem: you can probably impose more requirements on your internal users than your customers. The idea is the same though: you’re trying to differentiate between a legitimate user and an attacker, usually by getting the legitimate user to prove that they know a credential that the attacker doesn’t.
Optimizing Ruby's JSON, Part 7 (byroot.github.io)
In the previous post, we started covering some parser optimizations. There’s just a handful more to cover until we reached what’s the state of the currently released version of ruby/json.
Show HN: Galaxybrain.com – a JSON-based knowledge system (ycombinator.com)
Hi HN,<p>I’d like to share a project I’ve been working on called GalaxyBrain. It’s a tool for organizing information.
Synthesizing Music from JSON (phoboslab.org)
pl_synth is a tiny music synthesizer for C & JS and an editor (“tracker”) to create instruments and arrangements.
Show HN: SPath is a Rust lib for query JSONPath over any semi-structured data (github.com/cratesland)
SPath: Query expressions for semi-structured data
Optimizing Ruby's JSON, Part 5 (byroot.github.io)
In the previous post, we showed how we eliminated two malloc/free pairs of calls when generating small JSON documents, and how that put us ahead of Oj when reusing the JSON::State object.
Optimizing Ruby's JSON, Part 4 (byroot.github.io)
In the previous post, we established that as long as ruby/json wasn’t competitive on micro-benchmarks, public perception wouldn’t change. Since what made ruby/json appear so bad on micro-benchmarks was its setup cost, we had to find ways to reduce it further.
Optimizing Ruby's JSON, Part 1 (byroot.github.io)
I was recently made maintainer of the json gem, and aside from fixing some old bugs, I focused quite a bit on its performance, so that it is now the fastest JSON parser and generator for Ruby on most benchmarks.
Nobody gets fired for picking JSON, but maybe they should? (mcyoung.xyz)
JSON is extremely popular but deeply flawed. This article discusses the details of JSON’s design, how it’s used (and misused), and how seemingly helpful “human readability” features cause headaches instead. Crucially, you rarely find JSON-based tools (except dedicated tools like jq) that can safely handle arbitrary JSON documents without a schema—common corner cases can lead to data corruption!
Nobody Gets Fired for Picking JSON, but Maybe They Should? (mcyoung.xyz)
JSON is extremely popular but deeply flawed. This article discusses the details of JSON’s design, how it’s used (and misused), and how seemingly helpful “human readability” features cause headaches instead. Crucially, you rarely find JSON-based tools (except dedicated tools like jq) that can safely handle arbitrary JSON documents without a schema—common corner cases can lead to data corruption!
Internet Object – New Age Data Serialization After JSON (internetobject.org)
Revolutionize your data exchange and storage with a format that's built for efficiency, clarity and reliability. A Text Based Data Serialization and Structured Storage Format Beyond JSON!
JSON5 – JSON for Humans (json5.org)
JSON5 is an extension to the popular JSON file format that aims to be easier to write and maintain by hand (e.g. for config files). It is not intended to be used for machine-to-machine communication. (Keep using JSON or other file formats for that. 🙂)
JSON parsers that can accept comments (technomancy.us)
I know what you've been told. Douglas Crockford said that JSON can't have comments. And you accepted that. Understandable mistake; we've all been there.
Tjq: Giving Types to Jq (github.com/alpaylan)
Giving types to jq
Show HN: CSV Table – Proper GUI for View and Edit CSV, JSON (csvtable.com)
A modern, full-privacy and friendly UI to view and manage CSV, JSON files
JSON Formatter (Free, no ads, no signups) (hqjson.com)
Our JSON formatter is a free online tool that helps you format and validate JSON data.
JSON for Classic C++ (github.com/jart)
json.cpp is an anti-modern JSON parsing / serialization library for C++.
How to Flatten nested JSON arrays (datazip.io)
Flattening nested JSON or MongoDB’s BSON or normalizing semi-structured data and writing queries on it for analytics or regular queries, is a common challenge in data processing.
Show HN: Jist searches JSON 3x faster than jq (github.com/adelamodwala)
jist attempts to find the complete JSON value (string, number, bool, or JSON object) for a given search key.
Show HN: JSON-qs – JSON in query strings, human-readable, compact (github.com/alloc)
Show HN: TypeSchema – A JSON specification to describe data models (typeschema.org)
TypeSchema is a JSON specification to describe data models.
Show HN: Hyper Workspace – A no-code framework for JSON (onrender.com)
A new JSON data type for ClickHouse (clickhouse.com)
JSON has become the lingua franca for handling semi-structured and unstructured data in modern data systems. Whether it’s in logging and observability scenarios, real-time data streaming, mobile app storage, or machine learning pipelines, JSON’s flexible structure makes it the go-to format for capturing and transmitting data across distributed systems.