When working with JSON in Python, you often need to format JSON output with proper indentation to make it human-readable. This is essential for debugging, logging, and inspecting API responses.

Python's built-in json module makes pretty printing easy with the indent parameter. You can also use our JSON Formatter tool for quick formatting.

Quick Answer: Use json.dumps(data, indent=2) to pretty print JSON with 2-space indentation in Python.

The Problem: Compact vs Pretty JSON

By default, json.dumps() creates compact JSON on a single line, which is hard to read:

❌ Compact JSON (Hard to Read)

import json

data = {
    "name": "Alice",
    "age": 30,
    "city": "New York",
    "hobbies": ["reading", "coding", "hiking"]
}

# Without indentation
compact_json = json.dumps(data)
print(compact_json)

# Output (all on one line):
# {"name": "Alice", "age": 30, "city": "New York", "hobbies": ["reading", "coding", "hiking"]}

✅ Pretty Printed JSON (Easy to Read)

import json

data = {
    "name": "Alice",
    "age": 30,
    "city": "New York",
    "hobbies": ["reading", "coding", "hiking"]
}

# With indentation
pretty_json = json.dumps(data, indent=2)
print(pretty_json)

# Output (formatted with 2-space indentation):
# {
#   "name": "Alice",
#   "age": 30,
#   "city": "New York",
#   "hobbies": [
#     "reading",
#     "coding",
#     "hiking"
#   ]
# }

The indent=2 parameter adds 2 spaces per indentation level.

Basic Pretty Printing Methods

Method 1: Using json.dumps() with indent

import json

data = {"name": "Bob", "age": 25, "active": True}

# 2-space indentation (most common)
print(json.dumps(data, indent=2))

# 4-space indentation
print(json.dumps(data, indent=4))

# Tab indentation
print(json.dumps(data, indent='\t'))

You can use any number for indentation or even a tab character.

Method 2: Using pprint module (for Python objects)

from pprint import pprint

data = {"name": "Charlie", "age": 35, "skills": ["Python", "JavaScript"]}

# Pretty print Python object (not JSON string)
pprint(data)

# Output:
# {'age': 35,
#  'name': 'Charlie',
#  'skills': ['Python', 'JavaScript']}

Note: pprint is for Python objects, not JSON strings. Use json.dumps() for JSON.

Pretty Print JSON to Console

Perfect for debugging and development:

Debugging API Responses

import json
import requests

# Fetch data from API
response = requests.get('https://api.example.com/users/1')
data = response.json()

# Pretty print to console for debugging
print(json.dumps(data, indent=2))

# Example output:
# {
#   "id": 1,
#   "name": "John Doe",
#   "email": "[email protected]",
#   "address": {
#     "street": "123 Main St",
#     "city": "Boston"
#   }
# }

Essential for inspecting API responses during development.

Pretty Print JSON to File

Use json.dump() with indent to save formatted JSON files. For a complete guide, see our Python Write JSON to File tutorial.

Saving Formatted JSON

import json

data = {
    "users": [
        {"id": 1, "name": "Alice"},
        {"id": 2, "name": "Bob"}
    ],
    "total": 2
}

# Write pretty formatted JSON to file
with open('users.json', 'w') as file:
    json.dump(data, file, indent=2)

# users.json will contain:
# {
#   "users": [
#     {
#       "id": 1,
#       "name": "Alice"
#     },
#     {
#       "id": 2,
#       "name": "Bob"
#     }
#   ],
#   "total": 2
# }

Creates a readable JSON file perfect for configuration or data storage.

Sorting Keys Alphabetically

Add sort_keys=True to sort keys alphabetically for consistent output:

Before and After Sorting

import json

data = {
    "zebra": 1,
    "apple": 2,
    "mango": 3,
    "banana": 4
}

# Without sorting
print(json.dumps(data, indent=2))
# {
#   "zebra": 1,
#   "apple": 2,
#   "mango": 3,
#   "banana": 4
# }

# With sorting
print(json.dumps(data, indent=2, sort_keys=True))
# {
#   "apple": 2,
#   "banana": 4,
#   "mango": 3,
#   "zebra": 1
# }

Sorted keys make JSON output consistent and easier to compare in version control.

Handling Unicode Characters

By default, json.dumps() escapes non-ASCII characters. Use ensure_ascii=False to keep them readable:

Default (Escaped)

import json

data = {"city": "São Paulo", "country": "日本"}

print(json.dumps(data, indent=2))

# Output:
# {
#   "city": "S\u00e3o Paulo",
#   "country": "\u65e5\u672c"
# }

Readable Unicode

import json

data = {"city": "São Paulo", "country": "日本"}

print(json.dumps(data, indent=2, ensure_ascii=False))

# Output:
# {
#   "city": "São Paulo",
#   "country": "日本"
# }

Perfect for international applications with non-English text.

Advanced: Custom Separators

Control the separators between items and key-value pairs:

Custom Formatting

import json

data = {"name": "Alice", "age": 30, "city": "NYC"}

# Default separators
print(json.dumps(data, indent=2))
# {
#   "name": "Alice",
#   "age": 30,
#   "city": "NYC"
# }

# Custom separators (no space after comma)
print(json.dumps(data, indent=2, separators=(',', ': ')))

# Custom separators with extra spacing
print(json.dumps(data, indent=2, separators=(', ', ' = ')))
# {
#   "name" = "Alice",
#   "age" = 30,
#   "city" = "NYC"
# }

Real-World Examples

Example 1: Debugging Nested JSON

import json

# Complex nested data
response = {
    "status": "success",
    "data": {
        "user": {
            "id": 1,
            "profile": {
                "name": "Alice",
                "settings": {
                    "theme": "dark",
                    "notifications": True
                }
            }
        }
    }
}

# Pretty print for debugging
print(json.dumps(response, indent=2, sort_keys=True))

# Clear, readable output showing structure

Example 2: Logging JSON Data

import json
import logging

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

data = {"event": "user_login", "user_id": 123, "timestamp": "2025-01-16"}

# Log pretty printed JSON
logger.info(f"Event data:\n{json.dumps(data, indent=2)}")

# Output in logs will be formatted and readable

Example 3: Configuration File

import json

config = {
    "database": {
        "host": "localhost",
        "port": 5432,
        "credentials": {
            "username": "admin",
            "password": "secret"
        }
    },
    "api": {
        "rate_limit": 100,
        "timeout": 30
    }
}

# Save readable configuration
with open('config.json', 'w') as f:
    json.dump(config, f, indent=2, sort_keys=True)

print("Config saved in readable format!")

Reusable Pretty Print Function

Create a helper function for consistent pretty printing:

Custom Pretty Print Function

import json

def pretty_print_json(data, indent=2, sort_keys=True):
    """
    Pretty print JSON data to console
    
    Args:
        data: Python dictionary or list to print
        indent: Number of spaces for indentation (default: 2)
        sort_keys: Whether to sort keys alphabetically (default: True)
    """
    print(json.dumps(
        data,
        indent=indent,
        sort_keys=sort_keys,
        ensure_ascii=False
    ))

# Usage
user_data = {"name": "Alice", "age": 30, "city": "São Paulo"}
pretty_print_json(user_data)

# With custom indentation
pretty_print_json(user_data, indent=4)

Best Practices

Use 2 or 4 spaces: Most common indentation sizes for JSON

Sort keys for consistency: Use sort_keys=True for version control

Handle Unicode properly: Set ensure_ascii=False for international text

Development vs Production: Pretty print in dev, compact in production for bandwidth

Use our tools: Try our JSON Formatter for quick formatting

Quick Reference Cheat Sheet

Basic Pretty Print

json.dumps(data, indent=2)

With Sorted Keys

json.dumps(data, indent=2, sort_keys=True)

With Unicode Support

json.dumps(data, indent=2, ensure_ascii=False)

Complete (All Options)

json.dumps(data, indent=2, sort_keys=True, ensure_ascii=False)

To File

json.dump(data, file, indent=2)

Summary

Pretty printing JSON in Python is essential for debugging, logging, and creating readable configuration files. The indent parameter makes it simple.

•Use json.dumps(data, indent=2) for basic pretty printing
•Add sort_keys=True for consistent output
•Use ensure_ascii=False for Unicode characters
•Pretty print in development, compact in production
•Use json.dump() for files with same formatting options

Next Steps: Learn how to parse JSON to Python dictionaries or explore our Python Dict to JSON guide.

Python Pretty Print JSON - Format JSON with Indentation