JSON
We track 19 posts about JSON from 9 engineering blogs. Most active: Abhinav Sarkar, jOOQ, SitePoint. Latest post: Oct 24, 2026.
Companies writing about JSON
Recent posts
Quiz: Working With JSON Data in Python (opens on the source site)
In this quiz, you’ll test your understanding of Working with JSON Data in Python. By working through this quiz, you’ll revisit key concepts related to JSON data manipulation and handling in Python. [ Improve Your Python With 🐍 Python Tricks 💌 – Get a short & sweet Python Trick delivered to your inbox every couple of days. >> Click here to learn more and see examples ]
LLM Structured Output with JSON Schema: Typed Responses in TypeScript (opens on the source site)
Get reliable, typed JSON from LLMs using schema-constrained outputs, function calling, and a TypeScript Zod validation layer with bounded retries. Continue reading LLM Structured Output with JSON Schema: Typed Responses in TypeScript on SitePoint.
JSON-LD for Developers: Building Structured Data That Search and AI Systems Can Parse (opens on the source site)
null Continue reading JSON-LD for Developers: Building Structured Data That Search and AI Systems Can Parse on SitePoint.
Architecting Generative UI with Streaming JSON Schemas and React Server Components (opens on the source site)
Build streaming Generative UI: parse incremental JSON streams with Zod and hydrate type-safe React Server Component trees in Next.js. Continue reading Architecting Generative UI with Streaming JSON Schemas and React Server Components on SitePoint.
AI Agent Tool Manifests: Building a Unified TypeScript JSON Schema (opens on the source site)
Create a unified, vendor-agnostic JSON Schema specification for AI agent skills and tools, complete with a TypeScript runtime adapter that compiles declarations for Claude Code, OpenAI function calling, and custom agent loops. Continue reading AI Agent Tool Manifests: Building a Unified TypeScript JSON Schema on SitePoint.
JSON Schema Design for Document AI: How to Structure ML Training Data That Actually Works (opens on the source site)
null Continue reading JSON Schema Design for Document AI: How to Structure ML Training Data That Actually Works on SitePoint.
How to Configure Playwright Test to run smoke tests, headed tests, and debug versions through scripts in package.json (opens on the source site)
Earlier, we went over how we could create scripts in the package.json file of our Playwright framework to add typechecking, linting, and formatting your code with prettier. Want to see the entire bun-create-playwright project? It is on tinyurl.com/bun-create-playwright!With this post, we will explore how the built-in test runner for Playwright Test can run headed tests, debug versions of tests, and smoke tests.... and shortcuts for all of these can be set up in the scripts in your package.json! If you are using "bun" as a package manager, as we are in bun-create-playwright, just type out "bun…
How to Configure Playwright Test to run smoke tests, headed tests, and debug versions through scripts in package.json (opens on the source site)
Earlier, we went over how we could create scripts in the package.json file of our Playwright framework to add typechecking, linting, and formatting your code with prettier. Want to see the entire bun-create-playwright project? It is on tinyurl.com/bun-create-playwright! With this post, we will explore how the built-in test runner for Playwright Test can run headed tests, debug versions of tests, and smoke tests. ... and shortcuts for all of these can be set up in the scripts in your package.json! If you are using "bun" as a package manager, as we are in bun-create-playwright, just type out…
Consider using JSON arrays instead of JSON objects for serialisation (opens on the source site)
jOOQ ·
When implementing the awesome MULTISET operator in jOOQ, its implementation mostly relied on SQL/JSON support of various RDBMS. In short, while standard SQL supports nested collections via ARRAY or MULTISET operators like this: This is poorly supported in most RDBMS, so jOOQ emulates it using SQL/JSON as follows (or similar): Wait a second. A JSON … Continue reading Consider using JSON arrays instead of JSON objects for serialisation →
Progressive JSON (opens on the source site)
Do you know about Progressive JPEGs? Here’s a nice explanation of what a Progressive JPEG is. The idea is that instead of loading the image top to bottom, the image instead is fuzzy at first and then progressively becomes more crisp. What if we apply the same idea to transferring JSON? Suppose you have a JSON tree with some data: { header: 'Welcome to my blog', post: { content: 'This is my article', comments: [ 'First comment', 'Second comment', // ... ] }, footer: 'Hope you like it' } Now imagine you want to transfer it over the wire. Because the format is JSON, you’re not going to have a…
JSON - The Fine Print: Part 3 - Zero vs Missing Values (opens on the source site)
Introduction In part 1 we took a higher level view on serialization in general and JSON in specific. In part 2 we looked at emitting JSON. In part 3, we’ll look at an issue you might encounter when consuming JSON, Zero vs NULL field values. To clarify the definition of NULL, this means the absence of value. So here is the question: Given a field in a Go struct set to its zero value, how do you know that zero value was set by the user or it’s zero because it was never provided?
JSON - The Fine Print: Part 2 - Emitting JSON (opens on the source site)
Introduction In part 1 we took a high-level view on serialization and JSON. In this part, we’ll roll our sleeves and start working with JSON, focused on emitting JSON. You might think this is a basic topic, but there is much more to it than just calling json.Marshal. json.Marshal vs json.Encoder The encoding/json package has two main APIs: Marshal and NewEncoder. The Marshal function returns a []byte while the NewEncoder function will write to an io.Writer. The question is: When should you use one API over the other?
Scalable JSON Streaming with HTTP and Go - Ep.5 (opens on the source site)
Introduction: Welcome to the final episode of the JSON for Engineers series! In this concluding session, we tackle the challenges of working with large JSON datasets, exploring efficient strategies for streaming data while minimizing memory usage. These techniques enable developers to handle massive payloads without overburdening system resources, ensuring scalable and cost-effective applications. JSON Streaming: Using JSON Lines for memory-efficient data transmission. HTTP Chunked Encoding: Leveraging HTTP/1.1 chunked transfer encoding for streaming large datasets. Practical Error Handling:…
Emulating SQL FILTER with Oracle JSON Aggregate Functions (opens on the source site)
jOOQ ·
A cool standard SQL:2003 feature is the aggregate FILTER clause, which is supported natively by at least these RDBMS: The following aggregate function computes the number of rows per group which satifsy the FILTER clause: This is useful for pivot style queries, where multiple aggregate values are computed in one go. For most basic types … Continue reading Emulating SQL FILTER with Oracle JSON Aggregate Functions →
3.18.0 Release with Support for more Diagnostics, SQL/JSON, Oracle Associative Arrays, Multi dimensional Arrays, R2DBC 1.0 (opens on the source site)
jOOQ ·
DiagnosticsListener improvements A lot of additional diagnostics have been added, including the automated detection of pattern replacements, helping you lint your SQL queries irrespective of whether you’re using jOOQ to write your SQL, or if you’re using it as a JDBC / R2DBC proxy for an existing application. A lot of these diagnostics are available … Continue reading 3.18.0 Release with Support for more Diagnostics, SQL/JSON, Oracle Associative Arrays, Multi dimensional Arrays, R2DBC 1.0 →
JSON Parsing from Scratch in Haskell: Error Reporting—Part 2 (opens on the source site)
In the previous post, we set out to rewrite the JSON parser we wrote in Haskell in an earlier post, to add support for error reporting. The parser was written very naively: if it failed, it returned nothing. You couldn’t tell what the failure was or where it happened. That’s OK for a toy parser but error reporting is an absolute must requirement for all good parsers. In the previous post, we finished writing the basic framework for the same. In this post, we’ll finish adding simple but useful error reporting capability to our JSON parser.
JSON Parsing from Scratch in Haskell: Error Reporting—Part 1 (opens on the source site)
In the previous post we wrote a simple but correct JSON parser in Haskell. The parser was written very naively: if it failed, it returned nothing. You couldn’t tell what the failure was or where it happened. That’s OK for a toy parser but error reporting is an absolute must requirement for all good parsers. So in this post and next post, we’ll add simple but useful error reporting capability to our JSON parser.
JSON Parsing from Scratch in Haskell (opens on the source site)
JSON is probably the most used standard file format for storing and transmitting data on the Internet in recent times. Though it was historically derived from JavaScript, it is a programming language independent format and is now supported by almost all languages. JSON has a simple syntax specification with only four scalar data types and two composite data types. So, writing a parser for JSON is a great exercise for learning the basics of parsing. Let’s write one from scratch in Haskell.
How (not) to sign a JSON object (opens on the source site)
Latacora ·
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.
Related topics
This page is generated automatically from the engineering blogs we follow. Every post links to its source, where it was published. See all sources.