JSON Handling in Python

JSON (JavaScript Object Notation) is one of the most popular data formats used for data exchange between a server and a client.

Python provides the built-in json module to easily work with JSON data — allowing you to convert between Python objects and JSON strings seamlessly.

What is JSON?

JSON is a lightweight, text-based format for storing and transferring data. It's commonly used in APIs, web applications, and configuration files.

- JSON data is written as key–value pairs.
- It looks similar to Python dictionaries but uses specific syntax rules.

Example of JSON data:

{
  "name": "Alice",
  "age": 25,
  "skills": ["Python", "Django", "Machine Learning"],
  "isStudent": false
}

Importing the JSON Module

To work with JSON in Python, import the json module:

import json

The json module provides the following key methods:

Converting JSON to Python (Deserialization)

Deserialization means converting JSON data into Python objects. Example using json.loads() (string to Python object):

import json

json_data = '{"name": "Alice", "age": 25, "isStudent": false}'
python_obj = json.loads(json_data)

print(python_obj)
print(type(python_obj))

Output:

{'name': 'Alice', 'age': 25, 'isStudent': False}
<class 'dict'>

Reading JSON from a File

If JSON data is stored in a file, use json.load():

import json

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

print(data)

The with statement ensures the file is properly closed after reading.
The function automatically parses the file content into a Python object (like a dict or list).

Converting Python to JSON (Serialization)

Serialization means converting a Python object into JSON data.

Example using json.dumps():

import json

data = {
    "name": "Bob",
    "age": 30,
    "languages": ["Python", "C++"],
    "isStudent": False
}

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

Output:

{"name": "Bob", "age": 30, "languages": ["Python", "C++"], "isStudent": false}

Writing JSON to a File

To write a Python object as JSON to a file, use json.dump():

import json

data = {"course": "Python", "level": "Intermediate", "duration": "30 hours"}

with open("course.json", "w") as file:
    json.dump(data, file)

This creates a file named course.json with properly formatted JSON data.

Pretty Printing JSON

By default, JSON output is compact. You can format it neatly for readability using indent and sort_keys parameters.

import json

data = {"course": "Python", "level": "Intermediate", "duration": "30 hours"}
json_string = json.dumps(data, indent=4, sort_keys=True)
print(json_string)

Output:

{
    "course": "Python",
    "duration": "30 hours",
    "level": "Intermediate"
}

Handling Complex Data Types

The json module supports basic types like dict, list, str, int, float, bool, and None. However, some Python objects (like sets, tuples, or custom classes) need to be converted manually.

Example — handling unsupported types:

import json

data = {"numbers": {1, 2, 3}}

# Convert set to list before dumping
json_string = json.dumps({"numbers": list(data["numbers"])})
print(json_string)

Output:

{"numbers": [1, 2, 3]}

Converting Between JSON and Custom Classes

Sometimes you may want to convert custom class objects into JSON.

import json

class Student:
    def __init__(self, name, age):
        self.name = name
        self.age = age

def encode_student(obj):
    if isinstance(obj, Student):
        return {"name": obj.name, "age": obj.age}
    raise TypeError(f"Object {obj} not serializable")

s1 = Student("Alice", 21)
json_data = json.dumps(s1, default=encode_student)
print(json_data)

Output:

{"name": "Alice", "age": 21}

JSON Error Handling

While parsing, invalid JSON strings can raise exceptions. Always use try-except blocks to handle errors gracefully.

import json

try:
    data = json.loads('{"name": "Alice", "age": 25,}')  # invalid JSON
except json.JSONDecodeError as e:
    print("Error parsing JSON:", e)

Output:

Error parsing JSON: Illegal trailing comma before end of object: line 1 column 28 (char 27)

Summary

JSON handling is an essential skill for any Python developer working with APIs, web applications, or data serialization. By mastering the json module, you can efficiently read, write, and exchange structured data between systems — making your programs both versatile and web-ready.

In the next topic, we'll explore Object-Oriented Programming (OOP) in Python, where you'll learn how to design reusable, scalable, and real-world applications.