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Python JSON - Parsing, Creating, and Working with JSON Data

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What is Python JSON?

JSON is an acronym for JavaScript Object Notation. Python has a built-in package named ‘json’ to support JSON in Python. JSON is basically used for encoding and decoding data. The process of encoding the JSON data is referred to as serialization as it involves converting data into a series of bytes that can be stored and transmitted between servers and web applications. Since serialization is the encoding the data, we can guess the term used for decoding. Yes, it is deserialization.

In this module, we will learn about JSON in Python and cover the following topics:

So, without further delay, let’s get started.

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How to Parse JSON in Python?

How to read JSON files in Python?

Reading JSON data from a file is very easy.  json.load() method reads the string from a file, parses the JSON data. Then it populates a Python dictionary with the parsed data and returns it back to us.


#import json in Python
import json
with open('Intellipaat.txt') as json_file:

#load json file python
data = json.load(json_file)

for p in data['Course']:

print('Name: ' + p['name'])
print('Website: ' + p['website'])
print('From: ' + p['from'])

How to convert JSON String to Python Object: json.loads()

If we have a JSON string or JSON data, we can easily parse it using the json.loads() method found in the JSON package. To make use of this method, we have to import the JSON package offered by Python. As discussed above, this method is called deserialization, as we are converting the JSON encoded data into Python objects. Deserialization takes place as per the following table.

For example, the JSON data of the object type will be converted into a Python dictionary.

JSON Python
object dict
array list
string str
number (int) int
number (real) float
true true
false false
null none

Example of Parsing Json in Python:

import json
intellipaat = '{"course":"python", "topic":"Python JSON"}'

#parse a JSON string using json.loads()
intellipaat_dict = json.loads(intellipaat)


{'course': 'python', 'topic': 'Python JSON'}
<class 'str'>
<class 'dict'>

In the above example, intellipaat is a JSON string and intellipaat_dict is a Python dictionary.

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How to convert Python Object to JSON String: json.dumps()

json.dumps() function converts a Python object into a json string.
import json
Dictionary ={1:'Intellipaat', 2:'Python',3:'Tutorial'}
json_string = json.dumps(Dictionary)
print('Equivalent json string of input dictionary:',
print("        ")

The output will be
Equivalent json string of input dictionary: {"1": "Intellipaat", "2": "Python", "3": "Tutorial"}        
<class 'str'>

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How to Convert Python Dictionary to JSON?

We can also convert Python data types into JSON format using the json.dumps() method. Let us take a look at the example and understand how to convert Python objects to JSON in Python programming.


import json
intellipaat = {"course":"python", "topic":"Python JSON"}
intellipaat_json = json.dumps(intellipaat)


{"course": "python", "topic": "Python JSON"}<class 'dict'><class 'str'>

While converting Python objects into JSON, these objects get converted into the equivalent JSON type as per the following table:

Python JSON
dict Object
list Array
tuple Array
str String
int Number
float Number
True true
False false
None null

How to Format the Result of JSON in Python?

Even though we have learned how to convert the Python object into JSON data, it can still be very hard to read the converted JSON data, with no indentation and no line breaks. To make it more readable, there are various parameters of the json.dumps() method that we can use.


#using indent parameter to provide indentation
json.dumps(b, indent = 3)
We can also include various separators, such as, comma and colon.


json.dumps(b, indent = 3, separators = (“.”,”=”))

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Ordering the Result of Json in Python

In certain cases where we might want to sort the resultant JSON data after converting it from Python to JSON, we can simply use another parameter of the json.dumps() method, the sort_keys.

With the help of this parameter, we can define if we want the result to be sorted or not, using values such as true and false.


json.dumps(b, indent = 3, sort_keys=True)

With this, we come to the end of this module in python Tutorial. You can also go through this blog on Python Data Science tutorial if you want to know why Python is the most preferred language for data science.

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About the Author

Senior Consultant Analytics & Data Science

Presenting Sahil Mattoo, a Senior Consultant Analytics & Data Science at Eli Lilly and Company is an accomplished professional with 14 years of experience across data science, analytics, and technical leadership domains, demonstrates a remarkable ability to drive business insights. Sahil holds a Post Graduate Program in Business Analytics and Business Intelligence from Great Lakes Institute of Management.