JSON Handling

Introduction

JSON (JavaScript Object Notation) is the most common format used to exchange data between programs, APIs, and files. Whenever you call a web API, save application settings, or send data between a Python backend and a JavaScript frontend, JSON is almost always involved.

Python's built-in json module makes it simple to convert between Python objects like dictionaries and lists and their JSON text representation, in either direction.

What is JSON?

JSON is a lightweight, text-based data format that looks a lot like a Python dictionary. It is language-independent, which means a JSON file created by a Python program can be read by JavaScript, Java, or almost any other language.

{
  "name": "Alex",
  "age": 16,
  "is_student": true,
  "courses": ["Python", "JavaScript"]
}

The json Module

Python includes a built-in json module, so there is nothing to install. Import it and you get four main functions to remember.

Converting Python to JSON

json.dumps() ("dump string") takes a Python object — usually a dictionary or list — and returns a JSON-formatted string.

import json

data = {
    "name": "Alex",
    "age": 16,
    "is_student": True,
    "grades": [88, 92, 79]
}

json_string = json.dumps(data)
print(json_string)
print(type(json_string))

{"name": "Alex", "age": 16, "is_student": true, "grades": [88, 92, 79]}
<class 'str'>

Notice that Python's True became JSON's lowercase true. The json module automatically translates Python-specific values into their JSON equivalents.

Converting JSON to Python

json.loads() ("load string") does the opposite — it takes a JSON string and parses it back into native Python objects like dictionaries and lists.

import json

json_string = '{"name": "Maya", "age": 15, "active": true}'

data = json.loads(json_string)
print(data)
print(type(data))
print(data["name"])

{'name': 'Maya', 'age': 15, 'active': True}
<class 'dict'>
Maya

Once parsed, the result behaves exactly like any normal Python dictionary — you can index it, loop over it, or modify it.

Pretty-Printing with indent

By default, json.dumps() produces compact, single-line output. Passing the indent parameter makes the output far easier to read, which is especially useful when saving configuration files or debugging.

import json

data = {"name": "Alex", "hobbies": ["chess", "coding"], "age": 16}

pretty = json.dumps(data, indent=4)
print(pretty)

{
    "name": "Alex",
    "hobbies": [
        "chess",
        "coding"
    ],
    "age": 16
}

Reading & Writing JSON Files

Most real programs do not just convert JSON to strings in memory — they save it to a file so the data persists between runs. json.dump() and json.load() work directly with an open file object.

import json

data = {"username": "coder123", "score": 950, "level": 7}

with open("profile.json", "w") as file:
    json.dump(data, file, indent=4)

print("Saved profile.json")

Saved profile.json

import json

with open("profile.json", "r") as file:
    data = json.load(file)

print(data)
print("Score:", data["score"])

{'username': 'coder123', 'score': 950, 'level': 7}
Score: 950

Nested JSON Structures

JSON objects frequently contain other objects and lists nested inside them. Python's json module handles this automatically — nested JSON objects simply become nested dictionaries and lists.

import json

data = {
    "student": "Riya",
    "address": {
        "city": "Pune",
        "zip": "411001"
    },
    "subjects": [
        {"name": "Math", "score": 91},
        {"name": "Science", "score": 87}
    ]
}

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

parsed = json.loads(json_string)
print(parsed["address"]["city"])
print(parsed["subjects"][0]["name"])

{
  "student": "Riya",
  "address": {
    "city": "Pune",
    "zip": "411001"
  },
  "subjects": [
    {
      "name": "Math",
      "score": 91
    },
    {
      "name": "Science",
      "score": 87
    }
  ]
}
Pune
Math

You can drill down into nested data using regular dictionary and list indexing, chained together one level at a time.

Python-to-JSON Type Conversion

The json module maps Python types to JSON types (and back) using a fixed set of rules. Knowing this table helps you predict exactly what your output will look like.

Common Pitfalls

A few behaviors trip up almost every beginner working with JSON for the first time.

data = {1: "one", 2: "two"}
print(json.dumps(data))
# {"1": "one", "2": "two"}  <- keys became strings!

data = {"middle_name": None}
print(json.dumps(data))
# {"middle_name": null}

bad = "{'name': 'Alex'}"
json.loads(bad)  # raises json.JSONDecodeError

try:
    with open("data.json") as f:
        data = json.load(f)
except (FileNotFoundError, json.JSONDecodeError):
    data = {}

Best Practices

Frequently Asked Questions

Key Takeaways

Summary

The json module is one of the most practical tools in Python's standard library, letting you move data between Python programs, files, and web APIs with just a few function calls.

In this lesson, you learned how to serialize and deserialize JSON with dumps()/loads(), work with JSON files using dump()/load(), pretty-print with indent, and avoid the most common pitfalls involving keys and None.