JSON (JavaScript Object Notation) is the most common format for data exchange on the web. It's lightweight, easy to read, and supported across many platforms. In Python, the json module provides an easy way to encode and decode JSON data.

In this article, you’ll learn:

• What JSON is and how it relates to Python

• How to convert Python objects to JSON (dump, dumps)

• How to convert JSON back to Python objects (load, loads)

• Reading and writing JSON files

• Custom encoding and decoding

• Common use cases and pitfalls

What is JSON?

JSON is a text-based format for representing structured data. It’s widely used for APIs, configuration files, and data storage.

JSON Example:

{
  "name": "Alice",
  "age": 30,
  "is_active": true,
  "skills": ["Python", "Django"]
}

JSON maps naturally to Python data types:

Importing the json Module

import json

Encoding Python Objects to JSON

Use json.dumps() to convert a Python object to a JSON string.

person = {
    "name": "Alice",
    "age": 30,
    "is_active": True
}

json_string = json.dumps(person)
print(json_string)

Output:

{"name": "Alice", "age": 30, "is_active": true}

Pretty-printed JSON:

print(json.dumps(person, indent=4))

Decoding JSON to Python Objects

Use json.loads() to parse a JSON string into a Python object.

data = '{"name": "Alice", "age": 30, "is_active": true}'
python_obj = json.loads(data)
print(python_obj["name"])

Reading & Writing JSON to Files

✅ Writing to a File (json.dump())

person = {"name": "Bob", "age": 25}

with open("data.json", "w") as f:
    json.dump(person, f, indent=2)

✅ Reading from a File (json.load())

with open("data.json", "r") as f:
    person = json.load(f)
    print(person["age"])

Real-World Example: Saving App Settings

settings = {
    "theme": "dark",
    "notifications": True,
    "volume": 75
}

# Save settings to file
with open("settings.json", "w") as f:
    json.dump(settings, f)

# Later, read them back
with open("settings.json", "r") as f:
    loaded = json.load(f)
    print(loaded["theme"])  # Output: dark

Custom Encoding: Non-Serializable Objects

JSON doesn't support all Python types like datetime, set, or custom classes.

Example: Handling datetime objects

import json
from datetime import datetime

def custom_encoder(obj):
    if isinstance(obj, datetime):
        return obj.isoformat()
    raise TypeError("Type not serializable")

data = {"created_at": datetime.now()}

json_string = json.dumps(data, default=custom_encoder)
print(json_string)

Convert Between JSON and Python Types

Common Pitfalls

Tips for Working with JSON

• ✅ Use indent=2 or indent=4 in dump()/dumps() for pretty-printing

• ✅ Always wrap file operations in with blocks

• ✅ Use json.loads() with error handling (try/except) for untrusted data

• ✅ Use default= in json.dumps() to serialize custom objects

• ✅ Prefer json.load()/json.dump() for working directly with files

Summary Table

Conclusion

The json module is essential for anyone working with web APIs, configurations, or data exchange in Python. By mastering its features, you can write cleaner, safer, and more interoperable code.

Whether you're building a web app, saving user settings, or working with APIs, the json module is your go-to solution for data serialization in Python.