Convert a Nested Dictionary to JSON in Python

While working on a project where I had to send structured data from a Python backend to a web application. The data was stored in a nested dictionary, and I needed to convert it into JSON format.

The issue is… while converting a simple dictionary to JSON is easy, many people get confused when the dictionary has multiple nested levels.

In this tutorial, I’ll show you exactly how I handle this in my projects. I’ll cover different methods, share code examples, and explain each step in a simple way. By the end, you’ll be able to confidently convert any nested dictionary into JSON.

Table of Contents

What is JSON and Why Do We Need It?

JSON (JavaScript Object Notation) is a lightweight format for storing and exchanging data. It’s widely used in APIs, web apps, and databases.

In Python, we often use JSON when:

Sending data to web applications
Saving structured data in files
Interacting with REST APIs

A nested dictionary in Python looks very similar to JSON. But before sending or saving it, we must explicitly convert it into JSON format.

Method 1 – Convert Nested Dictionary to JSON Using json.dumps()

The most common way to convert a dictionary (including nested ones) into JSON is by using the json module’s dumps() function in Python.

Here’s how I usually do it:

import json

# Example nested dictionary (using US-based data)
employee_data = {
    "company": "TechCorp USA",
    "employees": {
        "101": {
            "name": "John Smith",
            "department": "Finance",
            "location": "New York"
        },
        "102": {
            "name": "Emily Johnson",
            "department": "Engineering",
            "location": "San Francisco"
        }
    }
}

# Convert dictionary to JSON string
json_data = json.dumps(employee_data, indent=4)

print(json_data)

You can see the output in the screenshot below.

Explanation:

I imported the built-in json module.
Used json.dumps() to convert the dictionary into a JSON string.
Added indent=4 to make the output more readable.

This is the method I use most often when I just need a quick and clean conversion.

Method 2 – Save Nested Dictionary as a JSON File

Sometimes, instead of just printing JSON, I need to save it into a .json file. For example, when storing user data or exporting reports.

Here’s how I do it:

import json

# Nested dictionary with US state data
state_population = {
    "California": {"population": 39538223, "capital": "Sacramento"},
    "Texas": {"population": 29145505, "capital": "Austin"},
    "Florida": {"population": 21538187, "capital": "Tallahassee"}
}

# Save dictionary to a JSON file
with open("state_population.json", "w") as file:
    json.dump(state_population, file, indent=4)

print("JSON file created successfully!")

You can see the output in the screenshot below.

This method is great when I want to keep a permanent record of my nested dictionary in JSON format.

Method 3 – Sort Keys While Converting

In some projects, I need the JSON output to always have keys in alphabetical order. This makes it easier to compare JSON files or debug.

import json

nested_dict = {
    "zebra": {"count": 5, "location": "San Diego Zoo"},
    "lion": {"count": 3, "location": "Bronx Zoo"},
    "elephant": {"count": 2, "location": "Smithsonian Zoo"}
}

# Convert with sorted keys
json_data = json.dumps(nested_dict, indent=4, sort_keys=True)

print(json_data)

You can see the output in the screenshot below.

Notice how the keys (elephant, lion, zebra) are now sorted alphabetically.

Method 4 – Handle Non-Serializable Data

Sometimes, a dictionary contains objects (like datetime) that JSON doesn’t support directly. In those cases, I use a custom function.

import json
from datetime import datetime

# Nested dictionary with datetime
event_data = {
    "event": "Python Conference",
    "details": {
        "location": "Chicago",
        "date": datetime(2025, 5, 20, 10, 0)
    }
}

# Custom serializer
def custom_serializer(obj):
    if isinstance(obj, datetime):
        return obj.isoformat()
    raise TypeError("Type not serializable")

# Convert with custom function
json_data = json.dumps(event_data, indent=4, default=custom_serializer)

print(json_data)

You can see the output in the screenshot below.

This way, I can handle special data types without breaking the JSON conversion.

Method 5 – Convert JSON Back to Dictionary

It’s also common to convert JSON back into a Python dictionary. I use json.loads() for that.

import json

# JSON string
json_string = '{"city": "Boston", "temperature": {"morning": 65, "afternoon": 75}}'

# Convert JSON back to dictionary
dict_data = json.loads(json_string)

print(dict_data["temperature"]["afternoon"])

This is very useful when working with APIs that return JSON responses.

While there’s no shortage of ways to work with JSON in Python, these are the methods I use most often in real-world projects.

json.dumps() for quick conversions
json.dump() for saving to files
sort_keys=True for consistent outputs
Custom serializers for complex objects

Once you understand these techniques, converting nested dictionaries to JSON becomes second nature.

You may also read other Python articles:

Bijay Kumar

I am Bijay Kumar, a Microsoft MVP in SharePoint. Apart from SharePoint, I started working on Python, Machine learning, and artificial intelligence for the last 5 years. During this time I got expertise in various Python libraries also like Tkinter, Pandas, NumPy, Turtle, Django, Matplotlib, Tensorflow, Scipy, Scikit-Learn, etc… for various clients in the United States, Canada, the United Kingdom, Australia, New Zealand, etc. Check out my profile.

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