Question

Create a JSON object with five elements. Explain the definitions of object serialization and deserialization. Write and explain the Python code to apply these concepts to the created JSON object.

Demonstrate how to explain these concepts to the created JSON object.

with error handling code

Python.

Answer 1

Python JSON

JSON stands for JavaScript Object Notation, which is a widely used data format for data interchange on the web. JSON is the ideal format for organizing data between a client and a server. Its syntax is similar to the JavaScript programming language. The main objective of JSON is to transmit the data between the client and the web server. It is easy to learn and the most effective way to interchange the data. It can be used with various programming languages such as Python, Perl, Java, etc.

JSON mainly supports 6 types of data type In JavaScript:

• String
• Number
• Boolean
• Null
• Object
• Array

Working with Python JSON

Python provides a module called json. Python supports standard library marshal and pickle module, and JSON API behaves similarly as these library. Python natively supports JSON features.

The encoding of JSON data is called Serialization. Serialization is a technique where data transforms in the series of bytes and transmitted across the network.

The deserialization is the reverse process of decoding the data that is converted into the JSON format.

Serializing JSON

Serialization is the technique to convert the Python objects to JSON. Sometimes, computer need to process lots of information so it is good to store that information into the file. We can store JSON data into file using JSON function. The json module provides the dump() and dumps() method that are used to transform Python object.

Deserializing JSON

Deserialization is the process to decode the JSON data into the Python objects. The json module provides two methods load() and loads(), which are used to convert JSON data in actual Python object form

Consider the following example:

import json
  
person = '{"Name": "Andrew","City":"English", "Number":90014, "Age": 23,"Subject": ["Data Structure","Computer Graphics", "Discrete mathematics"]}'
  
per_dict = json.loads(person)
  
print(json.dumps(per_dict, indent = 5, sort_keys= True))

Output:

{
    "Age": 23,
    "City": "English",
    "Name": "Andrew",
    "Number": 90014,
    "Subject": [
        "Data Structure",
        "Computer Graphics",
        "Discrete mathematics"
    ]
}

In the above code, we have provided the 5 spaces to the indent argument and the keys are sorted in ascending order. The default value of indent is None and the default value of sort_key is False