JavaScript Object Notation (JSON)

JavaScript Object Notation, or JSON for short, is a lightweight, text-based data interchange format that’s easy for humans to read and write, and easy for machines to parse and generate.

Despite its name suggesting a connection to JavaScript, JSON is language-independent and is supported by most modern programming languages, including Python.

JSON Syntax Example

JSON 
{
  "name": "John Doe",
  "age": 30,
  "is_developer": true,
  "skills": ["Python", "JavaScript", "SQL"],
  "address": {
    "street": "123 Main St",
    "city": "Anytown",
    "postal_code": "12345"
  },
  "phone": null
}

Core Concepts

JSON represents data using two structures:

  1. Collections of key-value pairs: Similar to Python dictionaries, objects in other languages, or hash tables
  2. Ordered lists of values: Similar to Python lists, arrays in other languages

Data Types

JSON supports six data types:

  • String - Text enclosed in double quotes: "Hello World"
  • Number - Integer or floating-point numbers: 42, 3.14159
  • Boolean - Boolean values: true or false (lowercase)
  • Null - Null value: null
  • Object - Unordered collection of key-value pairs: {"name": "Python", "version": 3.12}
  • Array - Ordered list of values: [1, 2, 3] or ["apple", "banana", "cherry"]

Syntax Rules

  • Data is represented in key-value pairs
  • Data items are separated by commas
  • Objects are enclosed in curly braces {}
  • Arrays are enclosed in square brackets []
  • Keys must be strings and are always enclosed in double quotes
  • Values can be any valid JSON data type

Python Integration

Python’s built-in json module provides tools to work with JSON data:

  • json.dumps(): Serialize Python objects to JSON strings
  • json.loads(): Deserialize JSON strings to Python objects
  • json.dump(): Write JSON data to a file
  • json.load(): Read JSON data from a file

Key Differences From Python

While JSON syntax resembles Python, there are important differences:

  • JSON uses null instead of Python’s None
  • JSON Booleans are true or false (lowercase) vs Python’s True or False
  • JSON requires double quotes for strings while Python allows single or double
  • JSON doesn’t support comments
  • JSON keys must be strings while Python dictionary's keys can be various types

Common Use Cases

  • Web APIs and RESTful services
  • Configuration files
  • Data storage and exchange between systems
  • Client-server communication
  • NoSQL database storage formats

Best Practices

  • Keep JSON structures simple and flat when possible
  • Use descriptive key names
  • Validate JSON before parsing because malformed JSON will raise exceptions
  • Consider using JSON Schema for validation of complex structures
  • Be mindful of number precision limitations across different systems
Working With JSON Data in Python

Tutorial

Working With JSON Data in Python

In this tutorial, you'll learn how to read and write JSON-encoded data in Python. You'll begin with practical examples that show how to use Python's built-in "json" module and then move on to learn how to serialize and deserialize custom data.

intermediate python

For additional information on related topics, take a look at the following resources:

By Dan Bader • Updated Aug. 4, 2025 • Reviewed by Leodanis Pozo Ramos
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