Working With JSON

What Is JSON?

JSON stands for JavaScript Object Notation.

Despite its name, JSON is not limited to JavaScript. Almost every modern programming language can work with JSON.

A simple JSON object looks like this:

{
    "name": "John",
    "age": 30,
    "is_student": false
}

Here we have three pieces of information:

• name → text
• age → number
• is_student → true or false

JSON Data Types

JSON supports several basic data types.

String       → "John"
Number       → 30
Boolean      → true / false
Null         → null
Array        → ["Python", "AI"]
Object       → {"name": "John"}

JSON objects use curly braces { }.

JSON arrays use square brackets [ ].

JSON Object

A JSON object contains key-value pairs.

{
    "name": "Alice",
    "age": 25,
    "city": "London"
}

Think of it like a Python dictionary:

person = {
    "name": "Alice",
    "age": 25,
    "city": "London"
}

The structure looks very similar, but JSON and a Python dictionary are not exactly the same thing.

JSON Arrays

JSON arrays are similar to Python lists.

{
    "languages": [
        "Python",
        "JavaScript",
        "Java"
    ]
}

In Python, this becomes a list when JSON is converted into Python data.

data = {
    "languages": [
        "Python",
        "JavaScript",
        "Java"
    ]
}

Python's json Module

Python provides a built-in module called json.

import json

The two most important concepts are:

JSON → Python
json.loads()

Python → JSON
json.dumps()

Remember the difference:

• loads() means load JSON from a string.
• dumps() means convert Python data into a JSON string.

Converting JSON to Python

Suppose an API sends this JSON:

{
    "name": "John",
    "age": 30
}

We can store it as a string and convert it into a Python dictionary.

import json


json_data = '''
{
    "name": "John",
    "age": 30
}
'''


person = json.loads(json_data)


print(person)

{'name': 'John', 'age': 30}

Now person is a normal Python dictionary.

Accessing JSON Data

After converting JSON into a Python dictionary, you can access values using their keys.

import json


json_data = '''
{
    "name": "John",
    "age": 30
}
'''


person = json.loads(json_data)


print(person["name"])
print(person["age"])

John
30

Converting Python to JSON

Sometimes your Python program needs to send data to an API.

In that situation, you may need to convert Python data into JSON.

import json


person = {
    "name": "John",
    "age": 30
}


json_data = json.dumps(person)


print(json_data)

{"name": "John", "age": 30}

The Python dictionary has now been converted into a JSON string.

Pretty Printing JSON

By default, JSON can appear on one line. You can make it easier to read using indent.

import json


person = {
    "name": "John",
    "age": 30,
    "skills": [
        "Python",
        "AI"
    ]
}


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

{
    "name": "John",
    "age": 30,
    "skills": [
        "Python",
        "AI"
    ]
}

Reading a JSON File

JSON is also commonly stored inside a .json file.

Create a file called user.json:

{
    "name": "Alice",
    "age": 25,
    "skills": [
        "Python",
        "AI"
    ]
}

Python can read the file using json.load().

import json


with open(
    "user.json",
    "r",
    encoding="utf-8"
) as file:

    user = json.load(file)


print(user["name"])
print(user["skills"])

Alice
['Python', 'AI']

Notice the difference:

json.loads()
     ↓
JSON string → Python object


json.load()
     ↓
JSON file → Python object

Writing JSON to a File

You can also save Python data into a JSON file.

import json


user = {
    "name": "Alice",
    "age": 25,
    "skills": [
        "Python",
        "AI"
    ]
}


with open(
    "user.json",
    "w",
    encoding="utf-8"
) as file:

    json.dump(
        user,
        file,
        indent=4
    )

The important difference is:

json.dumps()
     ↓
Python → JSON string


json.dump()
     ↓
Python → JSON file

Nested JSON

Real-world JSON is often nested. That means an object can contain other objects or arrays.

{
    "user": {
        "name": "John",
        "address": {
            "city": "London",
            "country": "UK"
        }
    }
}

After loading it into Python, you can access nested values step by step.

import json


data = json.loads('''
{
    "user": {
        "name": "John",
        "address": {
            "city": "London",
            "country": "UK"
        }
    }
}
''')


print(data["user"]["name"])

print(
    data["user"]["address"]["city"]
)

John
London

JSON and APIs

JSON becomes especially important when working with APIs.

For example, an API might return:

{
    "id": 101,
    "name": "Laptop",
    "price": 1200
}

Python can receive this data and work with it.

product = {
    "id": 101,
    "name": "Laptop",
    "price": 1200
}


print(product["name"])
print(product["price"])

Laptop
1200

This is why understanding JSON is essential before working deeply with APIs and AI services.

JSON in AI Applications

AI applications commonly use JSON to send structured requests and receive structured responses.

For example, an AI application might work with data like this:

{
    "question": "What is Python?",
    "language": "English"
}

Your Python application can read the values:

request = {
    "question": "What is Python?",
    "language": "English"
}


question = request["question"]

language = request["language"]


print(question)
print(language)

What is Python?
English

Handling Invalid JSON

JSON received from an external system may be invalid. Attempting to parse invalid JSON can raise JSONDecodeError.

import json


json_data = '''
{
    "name": "John",
    "age":
}
'''


try:

    data = json.loads(json_data)

    print(data)

except json.JSONDecodeError:

    print("Invalid JSON")

Invalid JSON

This is especially useful when processing data received from APIs or external files.

JSON vs Python Dictionary

Beginners often confuse JSON with a Python dictionary. They look similar, but they are different things.

Python Dictionary

{
    "name": "John",
    "age": 30
}


        ↓ json.dumps()


JSON String

'{"name": "John", "age": 30}'

A Python dictionary is a Python object in memory. JSON is a data format used for storing or exchanging structured data.

Mini Project — AI User Data Processor

Let's build a small program that reads user information from a JSON file and prepares the data for an AI application.

Create this structure:

project/
│
├── main.py
│
└── user.json

Put this inside user.json:

{
    "name": "John",
    "age": 30,
    "interests": [
        "Python",
        "AI",
        "Machine Learning"
    ]
}

Now create main.py:

import json


with open(
    "user.json",
    "r",
    encoding="utf-8"
) as file:

    user = json.load(file)


name = user["name"]

age = user["age"]

interests = user["interests"]


print("Name:", name)

print("Age:", age)

print("Interests:", interests)

Name: John
Age: 30
Interests: ['Python', 'AI', 'Machine Learning']

Now the application has structured Python data that can be passed to another part of the application or an AI service.

The Four JSON Functions to Remember

json.loads()
JSON string → Python object


json.dumps()
Python object → JSON string


json.load()
JSON file → Python object


json.dump()
Python object → JSON file

If you remember these four functions, you can handle most basic JSON operations in Python.

What You Learned

• What JSON is
• JSON data types
• JSON objects and arrays
• Using Python's json module
• Converting JSON strings into Python objects
• Converting Python objects into JSON strings
• Reading JSON files
• Writing JSON files
• Working with nested JSON
• Using JSON with APIs
• Using JSON in AI applications
• Handling invalid JSON
• The difference between JSON and dictionaries