Practical articles on JSON, REST APIs, developer tools and common errors — written for developers who want clear, fast answers.
Expo's app.json controls your app's name, icon, splash screen, permissions, and native build settings — all from one JSON file. Every key that matters, and when you need app.config.js instead.
A practical jq reference — filter, map, select, and reshape JSON from the command line. Field access, iteration, select/map, group_by, raw output, CSV, and NDJSON recipes.
ES2025 standardized importing JSON modules with the `with { type: 'json' }` syntax. How it works, why the type attribute is required, dynamic imports, and the security reason behind it.
This JSON.parse error means a raw newline, tab, or control character is sitting inside a string. Why it happens, how to escape it correctly, and how to stop it at the source.
One tiny interface that Zod, Valibot, and ArkType all implement — so libraries can accept any of them without adapters. What Standard Schema is, why it exists, and how to use it.
JSON is rows of text; Arrow is columns of typed memory. Why analytics engines moved to Arrow, what columnar buys you, and how the two formats actually complement each other.
JSON-RPC 2.0 is a tiny, transport-agnostic remote-call protocol — request, response, error, batch, and notifications. Why it powers MCP, Ethereum, and Language Server Protocol.
How data.gov and other open data portals describe datasets with DCAT JSON-LD — Dataset, Distribution, and catalog records — and how to query a portal's catalog API directly.
Where a JSON Schema check stops and statistical data quality validation begins — Great Expectations' expectation suites and validation results, both expressed as JSON.
The mechanism under 'JSON mode': how a JSON Schema becomes a grammar that masks illegal tokens at generation time, why XGrammar beats retries, and where constrained decoding still bites.
dbt compiles your project into manifest.json — a full JSON graph of models, sources, tests, and dependencies — that powers docs sites, lineage tools, and CI checks.
Get type-safe JSON from LLMs with the Vercel AI SDK's generateObject and streamObject — validated against a Zod schema, with automatic retries.
Pass a Pydantic BaseModel as output_type and Pydantic AI returns validated, typed JSON from any LLM — retrying automatically when a field is wrong.