Adventures in Machine Learning

Unveiling the Power of Pretty Print in JSON with Python

Unlocking the Potential of JSON Files: Understanding, Reading, and Printing

As we continue to plunge deeper into the digital age, data storage and exchange have become paramount to daily activities. JSON file format has become one of the most popular data exchange and storage methods.

If you’re not already familiar with this format, this article will explore and demystify it. You will learn the features of JSON, read and print JSON files using various methods, and explore how to structure and manipulate data using JSON files.

Understanding JSON File Format

JSON is an acronym for Javascript Object Notation, which is an open-source, text-based format used for data transfer and storage. JSON files are structured in a way that makes them easy-to-read and the perfect format to share data between different platforms.

JSON files are often compared to Python Dictionaries because they both have key-value pair structures that can be easily accessed. Some of the features that make the JSON file format stand out include:

– Data Storage: JSON files offer an efficient way for managing and storing large volumes of data.

– Data Exchange: JSON files are perfect for exchanging data between different applications and systems. – Simple Syntax: The syntax used in creating JSON files is simple and easy-to-understand making it easy for developers to work with.

– Open-Source: JSON files are free to use, making it accessible to individuals and businesses of different sizes. – Python Dictionaries: The key-value pair structure of JSON files makes them similar to Python dictionaries, and thus can be easily understood by Python developers.

Example of JSON File Format

JSON files can be structured in a structured or unstructured way and can be easily viewed using tools such as Microsoft Word and Notepad. A JSON file contains keys and values that hold specific data such as names, addresses, and phone numbers, among others.

A structured JSON file will have a specific format with different parts clearly defined. An unstructured JSON file will be free-flowing and will have only portions of the key-value pairs structured with no overall structure.

The following is an example of a simple JSON file that has key value pairs:


“name”: “Alex”,

“age”: 30,

“phone”: “+2348033333333”,

“email”: “[email protected]


Reading and Printing JSON Files

It’s difficult to extract data from a JSON file without first reading it. Reading a JSON file can be easily done using the json.load() method.

The code sample below illustrates the steps involved in reading a JSON file using the json.load() method. with open(‘data.json’, mode=’r’) as file:

data = json.load(file)

The ‘with’ keyword is used here to open the JSON file and the mode parameter is set to ‘r’ for reading.

The json.load() method is then used to read the contents of the file and save it in a Python object file referred to as ‘data.’

Printing JSON files can be done using different methods to achieve different outcomes. The json.dumps() method can be used to obtain pretty output formats with specific indentation levels.

The following code snippet demonstrates how to use the json.dumps() method to obtain a pretty_output:

json_string = json.dumps(data, indent=4)

Here, the json.dumps() method is applied to the Python object file – ‘data’, with an indent value of 4. This will produce easy-to-read output formats.

Another method of printing JSON files is through use of the pprint library. The pprint library is built into python and is very powerful in printing JSON files in a way that makes it easily readable.

Here, we first create a serialized object using json.load() method then we pass the serialized object to pprint() method.

import pprint

with open(‘data.json’, mode=’r’) as file:

serialized_obj = json.load(file)



JSON files have become the go-to data exchange and storage method. They are simple and easy-to-use, making them accessible to a wide range of developers.

By understanding how to read and parse JSON files, you can unlock the potential of your data. This article has given you a clear overview of JSON files, how to read and print JSON files, and how to structure them.

Start leveraging JSON files in your projects today and communicate with different applications seamlessly.

Recap of Pretty print using python and JSON

In our previous discussion, we delved into understanding, reading, and printing JSON files. We explored the features of JSON files, their structure, and the benefits of using them as a data exchange and storage method.

The focus of the article was on how to read and print JSON files using two popular methods. In this article, we will provide an in-depth exploration of pretty print formats using Python and JSON.

Prettier way to print JSON files

One of the most significant advantages of using the JSON file format is how human-readable the files are. However, when working with large or complex JSON files, it can be challenging to parse through the information or spot errors in formatting.

That’s where pretty print comes in. Pretty print provides an aesthetically pleasing format that is easy to read and understand, even for large and complex JSON files.

Python provides built-in modules that can be used to pretty print JSON files. We explored two of these methods, json.dumps() and pprint().

json.dumps() is used to convert a python object into a JSON string, and pprint() prints the object and its child elements with proper indentation and spacing. Let’s explore these two methods in more detail.

json.dumps() Method

The json.dumps() method provides an easy way to pretty print JSON files in Python. The method takes two arguments, the python object to be converted and an indent value.

The indent value specifies the number of spaces used for indentation in the final pretty output. Here is an example of how to use the json.dumps() method:


import json

json_object = {“name”: “John”, “age”: 30, “city”: “New York”}

pretty_json = json.dumps(json_object, indent=4)



In the code above, we create a python object called `json_object` and assign it three key-value pairs. We then define a variable called `pretty_json` and use the json.dumps() method to convert the python object into JSON with an indent value of 4.

Finally, we print the `pretty_json` variable to the console. The output of our code will be:



“name”: “John”,

“age”: 30,

“city”: “New York”



The `pretty_json` variable contains a formatted JSON string that is much easier to read and understand than the original python object.

pprint() Method

The pprint() method is another way to format JSON output in Python. Although it’s not as straightforward as using the json.dumps() method, it provides a more flexible, user-friendly, and customizable approach to formatting JSON files.

Here is an example of how to use the pprint() method:


import json

import pprint

json_object = {“name”: “John”, “age”: 30, “city”: “New York”}

pprint.pprint(json_object, indent=4)


In the code above, we create a python object called `json_object` and assign it three key-value pairs. We then use the `pprint()` method to print the `json_object` with an indent value of 4.

The `pprint()` method formats the output into an easily readable format as shown below:



“name”: “John”,

“age”: 30,

“city”: “New York”



The `pprint()` method is not limited to only JSON output but can also be used to print all kinds of python objects in a pretty print format. It’s essential to note that, by default, the pprint() method doesn’t return a string – it prints the output directly to the console.

Sometimes this can be quite limiting. Luckily, the string formatting feature of Python makes it easy to save the formatted output to a file.

Interesting Topics on Pretty Print using Python and JSON

1. Customizing the Pretty Print output

Both of the methods we discussed provide options for customizing the output and formatting to match individual or business preferences.

For instance, the pprint() method has optional parameters that allow you to customize the output like the width of each line and the separation between each value pair. On the other hand, the json.dumps() method can handle custom object serialization using a feature called the JSONEncoder class.

The JSONEncoder class inherits from the default Python JSON encoder class and can be used to add custom serialization formatting. 2.

Converting JSON to Python Objects

Both the json.dumps() and pprint() methods are powerful tools in adding pretty print formats to JSON files output. However, what if you need to convert a pretty printed JSON file back to a Python object?

Python’s json module provides a method called json.loads() that can be used to converting a pretty printed JSON file back to its raw format. 3.

Dealing with Large JSON Files

Large or nested JSON files can sometimes pose a challenge when it comes to pretty print formatting since the output can be quite long and unwieldy. However, the good news is that Python offers a solution to this problem.

By using the indent value of -1, the JSON output can be compressed, and its length significantly reduced.


In conclusion, pretty print output is an essential feature of the JSON file format in Python. It provides a format that is both aesthetically pleasing, easy-to-read, and user-friendly.

In this article, we have explored two of the most popular methods of pretty print output using Python, json.dumps() and pprint(). We have also explored some of the interesting topics around customizing the output format and reversing JSON to Python objects.

Pretty print output is an essential feature of JSON for file storage, exchange, and data parsing. In this article, we have explored the importance of pretty print output in JSON files using Python.

We discussed the significance of pretty print formats and their role in making complex JSON files more human-readable. We highlighted two of the most popular methods of pretty print output, json.dumps() and pprint(), and provided insights on customizing the output format and reversing JSON to Python objects.

Pretty print output is an essential feature of JSON file format for storage, exchange, and data parsing, and Python offers tools to make it an effortless process.

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