惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

博客园 - 【当耐特】
N
Netflix TechBlog - Medium
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
雷峰网
雷峰网
MongoDB | Blog
MongoDB | Blog
有赞技术团队
有赞技术团队
Engineering at Meta
Engineering at Meta
M
MIT News - Artificial intelligence
Google DeepMind News
Google DeepMind News
罗磊的独立博客
Hugging Face - Blog
Hugging Face - Blog
WordPress大学
WordPress大学
T
Tailwind CSS Blog
小众软件
小众软件
J
Java Code Geeks
人人都是产品经理
人人都是产品经理
博客园_首页
MyScale Blog
MyScale Blog
博客园 - 聂微东
V
Visual Studio Blog
The Cloudflare Blog
月光博客
月光博客
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
U
Unit 42

DEV Community

Authentication Security Deep Dive: From Brute Force to Salted Hashing (With Java Examples) Why AI Systems Don’t Fail — They Drift Spilling beans for how i learn for exam😁"Reinforcement Learning Cheat Sheet" I Replaced Chrome with Safari for AI Browser Automation. Here's What Broke (and What Finally Worked) How Python Borrows Other People's Work The $40 Architecture: Processing 1 Billion API Requests with 99.99% Uptime Vibe Coding: A Workflow Guide (From Zero to SaaS) Most webhook security guides protect the wrong side. The scary part is delivery. Headless CMS for TanStack Start: Build a Blog with Cosmic EU Age Verification App "Hacked in 2 Minutes" — What Actually Happened Comfy Cloud’s delete function does not actually remove files Running AI Models on GPU Cloud Servers: A Beginner Guide Event-driven media intelligence with AWS Step Functions and Bedrock I scored 500 AI prompts across 8 quality dimensions — here's what broke How to Call Google Gemini API from Next.js (Free Tier, No Backend Needed) The Portal Protocol: Reclaiming Human Connection in the Age of AI How to Fix Your Team's Scattered Knowledge Problem With a Self-Hosted Forum Intro to tc Cloud Functors: A Graph-First Mental Model for the Modern Cloud Designing Multi-Tenant Backends With Both Ownership and Team Access I Built a Neumorphic CSS Library with 77+ Components — Here's What I Learned PostgreSQL Performance Optimization: Why Connection Pooling Is Critical at Scale Cómo construí un SaaS multi-rubro para gestionar expensas en Argentina con FastAPI + Vue 3 🚀 I Built an Ethical Hacking Scanner Tool – Open Source Project I Replaced /usage and /context in Claude Code With a Single Statusline A Pythonic Way to Handle Emails (IMAP/SMTP) with Auto-Discovery and AI-Ready Design I Collected 8.9 Million Polymarket Price Points — Here's What I Found About How Markets Really Move EcoTrack AI — Carbon Footprint Tracker & Dashboard Everyone's Using AI. No One Agrees How. 5 self-hosted ebook managers worth trying in 2026 Building Your First AI Agent with LangChain: From Chatbot to Autonomous Assistant
Making Pretty-Printed JSON Readable Again in Python
Yair Lenga · 2026-05-24 · via DEV Community
Cover image for Making Pretty-Printed JSON Readable Again in Python

Yair Lenga

Most JSON serializers give you only two choices:

  • compact machine output:
{"a":{"b":{"c":"abc"}},"x":{"y":{"z":"xyz"}}}

Enter fullscreen mode Exit fullscreen mode

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

Enter fullscreen mode Exit fullscreen mode

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, 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" } }
}

Enter fullscreen mode Exit fullscreen mode

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, perform transformations and customize the output layout.

The interesting part is that the formatter does not re-parse the JSON stream. It operates as a streaming wrapper around file-like objects:

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

Enter fullscreen mode Exit fullscreen mode

That means that it can handle large documents with fixed memory usage and linear processing time. This approach works with most existing serializers. It also provides wrappers for json.dump(), json.dumps().

from jsonfold import dumps

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

print(dumps(data))

Enter fullscreen mode Exit fullscreen mode

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.py from GitHub project

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")

Enter fullscreen mode Exit fullscreen mode

GitHub Project

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

Python implementation is under python directory.

Future articles will cover other implementations: JavaScript, Java, C, ... - please watch the GitHub project, or follow the articles on Medium.