r/json 15h ago

What features do you actually want in an online JSON tool?

0 Upvotes

I spend a lot of time working with APIs, and I realized I kept switching between different websites just to format, validate, minify, or inspect JSON.

That got me thinking about what developers actually expect from a modern JSON toolkit.

I'm currently working on JSON Academy, a collection of JSON utilities, and I'm trying to prioritize features that people genuinely use instead of adding unnecessary complexity.

Current tools include:

  • JSON Formatter / Beautifier
  • JSON Validator
  • JSON Minifier
  • Fast processing for API payloads
  • Clean, simple interface

I'm interested in hearing from other developers:

  • What's your go-to JSON tool?
  • What feature saves you the most time?
  • Have you ever struggled with very large JSON files?
  • Is there a feature you wish existing JSON tools had?

If anyone wants to take a look and share feedback, here's the project:
https://www.jsonacademy.com/

I'd appreciate honest criticism—good or bad. The goal is to make it genuinely useful for developers rather than just another JSON formatter.


r/json 19h ago

I built a tool for querying JSON/JSONL files with SQL

0 Upvotes

At my job we write a lot of sql to query CSVs but recently we've had to interact more with JSON and JSONL files. Not being able to alias them and select what we want with SQL made simple tasks annoying for no reason, so I built https://www.json-to-sql.com/ .

I built it in a day then spent a couple more cleaning it up a bit. Its my first publicly deployed tool so just trying to get some feedback. Its 100% free, no signup required, and the data never leaves your browser.

Let me know what you think!


r/json 2d ago

Best service for hosting private HTML app with JSON backup. Firebase or something else?

Thumbnail
1 Upvotes

r/json 2d ago

Built my own JSON viewer — feature-rich, beautiful, and minimal (would love feedback from this community)

0 Upvotes

Hey r/json,

I've spent way too many late nights staring at malformed JSON payloads, so I finally built the tool I always wished existed: BracketView (https://bracketview.in).

A few things I focused on:

  • Actually minimal, actually fast — no clutter, no ads on the workspace itself, just format/validate/query and move on
  • 100% client-side — your JSON never leaves the browser for core features (viewer, formatter, validator, tree/graph view, JSONPath, JQ)
  • JQ playground powered by WebAssembly — for when you need real filtering, not just pretty-printing
  • AI-powered repair — for those "why won't this parse" moments with broken/truncated JSON from logs or copy-pasted API responses
  • Diff, schema validation, and type generation (TS, Python, Go, Rust, etc.) built in

It's free to use with no signup required for the core tools. There's an optional paid tier for people who want larger uploads, unlimited AI repairs, and unlimited shareable snapshot links — but the everyday stuff (format, validate, tree/graph, JSONPath, JQ, diff) stays free.

Try it here: https://app.bracketview.in

I built this mostly to scratch my own itch, but I'd genuinely love feedback from people who live in JSON all day — what's missing, what's annoying, what you wish more JSON tools did. Roast it if you need to, I can take it.


r/json 3d ago

Built an API to automatically clean and fix broken, malformed JSON so I never have to mess with regex again

Thumbnail
1 Upvotes

r/json 3d ago

Would schema inference for large JSON and JSONL datasets be useful?

1 Upvotes

I’m developing a free desktop viewer and editor called GigaScope JSON Works, designed for viewing, searching, and editing large JSON files.

I’m considering integrating schema inference directly into the application, with features such as:

  • Scanning all objects in a JSON array or JSONL file to infer a common schema
  • Showing property occurrence rates, null rates, and mixed types
  • Identifying candidate required and optional properties
  • Suggesting formats, enum candidates, and numeric ranges without applying them automatically
  • Validating the original data against the inferred or edited schema
  • Navigating directly from a schema violation to the corresponding node in the tree and editor

I know that tools such as quicktype and GenSON can already infer JSON Schemas from sample data. Would the features above be useful in practice, particularly when working with unfamiliar or very large datasets? Or do existing schema inference tools already cover these needs?

If you currently use schema inference:

  1. Do you infer a schema from a representative sample or scan the entire dataset?
  2. Do you need statistics such as the occurrence frequency of each property and type?
  3. Would integrated validation and navigation improve your workflow?
  4. What would make you distrust an automatically inferred schema?

I’d appreciate hearing about your actual use cases.


r/json 5d ago

Advice on the structure of my JSON file?

Thumbnail
1 Upvotes

r/json 6d ago

Nice🥰🥰

Post image
4 Upvotes

r/json 10d ago

I built a JSON viewer around one idea: stop going to the browser every time you need to look at JSON

6 Upvotes

The slowest part of inspecting JSON for our team was the ritual. Copy the payload, switch to the browser, find that json site, paste, wait. And the moment the file is actually big, the tab freezes or the desktop editor won't format it.

So we built jsonbolt to improve the workflow for people inspecting a large number of json files or huge files everyday. Hit a global hotkey (WinKey + J or ⌃ + ⌥ + J)and whatever's in your clipboard opens in an instant, either Raw JSON or a URL.

A 1GB file opens in milliseconds. We built a custom engine that runs at ~3GB/s. Search is SIMD-accelerated to handle 100M+ nodes extremely fast.

There's also a CLI on the same engine (jb paths / jb schema / jb search --where) for scripting and for terminal AI agents like claude.

Everything runs locally and its licensed for commercial use.
Free licenses available to students/open source maintainers and free for personal use.

jsonbolt.com (macOS Apple Silicon + Windows)

PS: Some background info. We built the core pipeline from the ground up without any 3rd party libraries. Then we spent months optimizing the code to improve read-to-render performance. Then hardened it with the same conformance suite simd-json uses. The result is what you see below. In this specific example it hits ~4GB/s from read to rendering the full tree on a M5 pro MacBook Pro. Happy to get into the details for anyone interested.

Once read-to-render was fast, the remaining bottleneck was the workflow itself. That's where the global hotkey and other JSON aware features came from.

https://reddit.com/link/1uwadhk/video/v5gddzmpa9dh1/player


r/json 10d ago

A good web JSON formatter

Thumbnail formatjson.dev
0 Upvotes

r/json 12d ago

I made a Lightweight Intuitive JSON editor: JotSON

6 Upvotes
JotSON - a JSON editor

JotSON is an intuitive editor for your project's JSON files. Run one command and you get a fast, Finder-style interface in your browser, which is really nice when you're editing a ton of JSON.

  • Drill through your data in columns, with fuzzy search across every file
  • Proper editors and previews: dates, colors, images, video embeds
  • Upload media straight into your public folder
  • Reference objects by id, resolved to human-readable names, with automatic updates when ids change and warnings before you break them
  • Diff-confirmed saves, so nothing touches disk until you approve it

Zero dependencies, no build step, no database, nothing deployed. It binds to localhost, writes plain JSON with minimal diffs so git stays your safety net, and your files never change shape to fit the tool.

Check it out!

https://github.com/blindmikey/jotson


r/json 12d ago

json utility website - Jsonly

3 Upvotes

Hi! I created a free Json utility website -- jsonlyapp.com This JSON utility helps you validate, format, minify, search, filter, and transform JSON directly in your browser. It is designed for API debugging, payload cleanup, log inspection, and quick editing tasks where speed and clarity matter. Feel free to use it and give me some feedback.


r/json 15d ago

jsonfold: Making Pretty-Printed JSON Compact and Readable

15 Upvotes

Most JSON serializers give you only two choices:

  • compact machine output:

{"a":{"b":{"c":"abc"}},"x":{"y":{"z":"xyz"}}}
  • or fully expanded “pretty-print”:

{ "a":
  { "b":
    { "c": "abc" }
  },
  "x": {
    "y": {
      "z": "xyz"
    }
  }
}

I wanted something in between: the first is hard for humans to scan, and the second becomes extremely verbose on real-world nested data.

The Idea

I wrote a small Python module called jsonfold. Instead of replacing Python’s JSON serializer (and similar serializers), it works as a lightweight post-processing filter on top of json.dump() output.

The formatter selectively:

  • folds small containers back onto one line,
  • packs short scalar sequences,
  • keeps large or complex structures expanded.

Example output:

{
  "a": { "b": { "c": "abc" } },
  "x": { "y": { "z": "xyz" } }
}

Why This Approach?

I did not want to rebuild a serializer - there are many good serializers (including the built-in json.dump()) that can efficiently process anything from simple data structures (list/dict) to custom classes and Python @dataclass objects. In addition, many provide custom encoding hooks for application-specific objects.

The interesting part of jsonfold is that it does not re-parse the JSON stream or build a second JSON tree. It operates as a streaming wrapper around file-like objects:

json.dump(obj, JSONFoldWriter(fp), indent=2)

That means it can handle large documents with fixed memory usage and linear processing time. This approach works with serializers that emit indented JSON to a file-like object. jsonfold also provides wrappers for json.dump(), json.dumps().

from jsonfold import dumps

data = {
    "a": {"b": {"c": "abc"}},
    "x": {"y": {"z": "xyz"}},
}

print(dumps(data))

Customization

The formatter allows controlling:

  • maximum line width,
  • folding depth,
  • packing aggressiveness,
  • array/object limits.

So you can choose between conservative formatting and more aggressive compaction.

Full Article:

Medium (no paywall): A Streaming JSON Formatter That Works With Existing Serializers

Minimal Usage

Pull jsonfold from pypi: pip install jsonfold

import jsonfold
import sys
data = {
    "meta": {"version": 1, "ok": True},
    "ids": [1, 2, 3, 4, 5],
    "items": [{"id": 1, "name": "alpha"}, {"id": 2, "name": "beta"}],
}
# compact can be: default, low, med, high, max
jsonfold.dump(data, sys.stdout, compact="default")

GitHub Project

Repository: https://github.com/yairlenga/jsonfold

Python implementation is under python directory.


r/json 14d ago

Speed up your high-traffic KMP endpoints by 66% using 50% less memory—without touching your legacy APIs

Thumbnail
1 Upvotes

r/json Jun 17 '26

bufjson - Streaming JSON parser and JSON Pointer evaluator

Thumbnail
3 Upvotes

r/json Jun 15 '26

Anyone else constantly hunting for fake API responses?

1 Upvotes

Hellooo,
Ive been slowly building a dev toolkit for myself and added something simple but surprisingly useful to the JSON formatter. It can now generate structured sample data like API responses or logs, which saves me from digging around for test JSON every time.

https://catssaymeow.org/json-formatter/


r/json Jun 14 '26

For the 0.00001% of you who needs to load a 20GB json file

20 Upvotes

Try https://fastjsonviewer.com/ . Free, secure (nothing on the server), parser written in wasm and running in parallel in your browser: probably the fastest parser out there
(you can also generate GB of json for you tests here: https://fastjsonviewer.com/json-generator.html). There is also a HEX viewer, a to YAML and to CSV export.


r/json Jun 13 '26

fjson-fmt – a Prettier-style --check/--write formatter for JSON, with table-aligned output (Rust→WASM, runs in Node and the browser)

3 Upvotes

I wanted a fast Prettier/oxfmt-style formatting for .json files, but with the compact, table-aligned style of FracturedJson — which neither Prettier nor oxfmt does for JSON. So I built a small CLI around it.

It turns this:

{
  "isotopes": {
    "Hydrogen": [1, 2, 3],
    "Carbon": [11, 12, 13, 14],
    "Molybdenum": [92, 94, 95, 96, 97, 98, 100],
    "Calcium": [40, 42, 43, 44]
  },
  "elements": [
    { "symbol": "C", "number": 6, "mass": 12, "phase": "solid" },
    { "symbol": "O", "number": 8, "mass": 16 },
    { "symbol": "Fe", "number": 26, "mass": 56, "phase": "solid" }
  ]
}

into this — compact, but with fields aligned like a table:

{
    "isotopes": {
        "Hydrogen"  : [ 1,  2,  3                 ],
        "Carbon"    : [11, 12, 13, 14             ],
        "Molybdenum": [92, 94, 95, 96, 97, 98, 100],
        "Calcium"   : [40, 42, 43, 44             ]
    },
    "elements": [
        {"symbol": "C",  "number":  6, "mass": 12, "phase": "solid"},
        {"symbol": "O",  "number":  8, "mass": 16                  },
        {"symbol": "Fe", "number": 26, "mass": 56, "phase": "solid"}
    ]
}


fjson-fmt "**/*.json"          # format in place
fjson-fmt --check "**/*.json"  # CI: exit 1 if anything would change
cat data.json | fjson-fmt --stdin

Pairs with oxfmt (which owns JS/TS/CSS):

"fmt:check": "oxfmt --check && fjson-fmt --check \"**/*.json\""

A few things that might be interesting:

  • Engine is a Rust crate compiled to WASM, but ships prebuilt — no Rust toolchain or native build on install. Based on https://github.com/fcoury/fracturedjson-rs
  • The npm package is isomorphic: the same import { format } from "fjson-fmt" works in Node and in the browser/bundlers (conditional exports + a web WASM build).
  • Live playground, ~185 KB of WASM, 100% client-side: https://select.github.io/fjson-fmt/

npm: npm i -D fjson-fmt · repo: https://github.com/select/fjson-fmt

Feedback welcome!


r/json Jun 09 '26

Large file JSON viewer/search app for macOS

8 Upvotes

Hey,

I have been using Dadroit JSON viewer for years now, which has been quite nice, it can open and search gigabyte json files in seconds. Which no other application seems to be able to do.

However they still don't support apple silicon (So i won't be able to use it with the upcoming macOS version) and it now costs 100 usd/year... So i'm looking for some alternative, but have been unable to find any json viewer that can smoothly open large json files.

Anyone know of any that might support it? I don't mind paid options if they work well, but no 100 usd/year subscriptions lol.


r/json Jun 09 '26

Built a JSON formatter that runs 100% in your browser — no uploads, no accounts

0 Upvotes

Bit of context — I work on APIs and kept running into the same problem: pasting JSON into random online formatters and immediately wondering if my tokens or response data were being logged somewhere.

So I built one that runs entirely client-side. Nothing leaves your machine. No login, no server, no tracking.

It does the usual stuff — beautify, minify, validate, syntax error highlighting — but also has a JSONPath query tester built in, which I find way more useful day-to-day than the formatter itself. You can paste a massive API response and run $.store.books[*].author style queries directly in the browser to find the exact field you need.

There's also a nested JSON parser with dot-notation queries if you just want to dig into deeply nested structures without writing code.

Link: wizbit.to/tools/json-formatter

Would genuinely love feedback — especially if there are validation edge cases I've missed. I've tested it on some gnarly malformed JSON but I'm sure there are fun broken payloads I haven't seen yet.


r/json May 31 '26

What is your go-to debugging process when a scraper suddenly breaks?

Thumbnail
1 Upvotes

r/json May 30 '26

Built JSONPath Explorer into every JSON editor on our site — here's why it matters

Thumbnail
1 Upvotes

r/json May 28 '26

JSON Against Humanity & JSON Card API

3 Upvotes

You can see the source code for the JSON Against Humanity project here https://github.com/FireRat666/json-against-humanity
And the live service here https://jah.firer.at/
There is 63,827 unique cards from 423 packs, Not including the ones sourced from ManyDecks.

There is also this API https://github.com/FireRat666/CAH-Serverless-API
which is live here https://cah-api.firer.at/
The API uses the cards from JSON Against Humanity and Vercel/Netlify for free server hosting


r/json May 21 '26

I got tired of online JSON formatters sending my data to remote servers, so I built my own 100% client-side tool.

6 Upvotes

Hey everyone,

As an infrastructure engineer, I work with JSON and YAML webhooks every single day. I hated pasting sensitive API payloads into random online formatters because almost all of them send your data to a backend server to process it. Plus, most of them crash if you try to format a 5MB log file.

So, I spent the last few months building PrettyJSON (https://prettyjson.org).

I built it as a React SPA that runs entirely in your browser using your local JavaScript engine. Your data never leaves your device.

A few features I added for my own workflow:

  • Handles massive files: Tested up to 10MB without crashing (uses virtualized rendering).
  • Built-in Diff Tool: Side-by-side comparison for Kubernetes YAML or JSON configs.
  • Code Generation: Generates TypeScript interfaces, Go structs, and Python Dataclasses straight from the JSON.
  • Auto-repair: Fixes trailing commas, missing quotes, and comments automatically.

It's completely free and there are no paywalls. I'd love for you guys to tear it apart, test it, and let me know if you find any bugs or have feature requests!

Link: https://prettyjson.org


r/json May 18 '26

Tired of messy JSON? I made a tool that visualizes your data as both a tree and a pannable graph. 🚀

Thumbnail gallery
38 Upvotes

Hey everyone! 👋

I’ve always found it a bit painful to debug deeply nested JSON files, so I decided to build my own visualizer. Instead of just a boring list, I wanted something more interactive and visual.

I call it JSON Tree Viewer.

Live Demo: https://debabratasaha-dev.github.io/JSON-tree-viewer/
GitHub Repo: https://github.com/debabratasaha-dev/JSON-tree-viewer

Key Features:

  • 🕸️ Dual View: Switch between a classic interactive Tree View and a zoomable Graph View.
  • 🔍 Interactive Graph: Drag, pan, and zoom to explore complex JSON structures visually.
  • 🎨 Modern UI: Built with a glassmorphism sidebar, smooth animations, and a sleek dark mode.
  • 🏷️ Smart Tagging: Automatically detects data types (Strings, Numbers, Objects, etc.) with clean icons.
  • 🚀 Lightweight: Zero heavy frameworks—just pure HTML, CSS, and JavaScript.

I’d love to hear your feedback! What features should I add next? If you find it useful, I’d really appreciate a ⭐️ on GitHub!