JSON Encoder and Decoder Package in Python

Introduction:

In this tutorial we are learning the JSON encoder and decoder package in Python. JSON stands for the JavaScript Object Notation. The JSON is a data interchange format that is lightweight. It is similar to the pickle. However, the pickle serialization is specific to Python, while many programming languages use the JSON format. The Json module in Python's standard library implements object serialization similar to the pickle and the marshal modules. Like the pickle model, the json module provides dumps() and loads() functions to serialize Python objects into JSON-encoded strings. The dump() and load() functions serialize Python objects written or read from a file.

How to get started with the JSON encoder and decoder package in Python?

Python provides the built-in json library for handling JSON objects. All you have to do is import the JSON module into your Python program by using the following commands and start using its functions.

Now, the JSON module has many functions, and we will talk about only 2 of them. These are the dumps and loads. The process of converting Python objects to json objects is called JSON serialization or encoding. The reverse process of converting json objects to Python objects is called deserialization or decoding. We will use json.dumps() for encoding and json.loads() for decoding. Obviously, the dumps method will convert Python objects to JSON strings, and the loading process will parse the Python objects from serialized JSON strings.

It is worth noting here that the JSON object created during serialization is just a Python string. So, you will see the terms "JSON object" and "JSON string" used in this tutorial. Therefore, when you use the load method, the Python dictionary is returned by default (unless you change this behavior as described in the Customization section of the tutorial).

Program Code 1:

Here, we give a program code that uses the JSON encoder and decoder package in Python. The code is given below -

Output:

Now we compile the above code and find the result from it. The output is given below -

 {"a": 0, "b": 1, "c": 2, "d": 3} <class 'str'> {'a': 0, 'b': 1, 'c': 2, 'd': 3} <class 'dict'> 

Program Code 2:

Here, we give another program code, which uses the JSON encoder and decoder package in Python. The code is given below -

Output:

Now we compile the above code and find the result from it. The output is given below -

 ["Priyanka", {"marks": [90, 60, 80]}] ['Priyanka', {'marks': [90, 60, 80]}] {"age": 24, "marks": 90, "rank": 2} {'age': 24, 'marks': 90, 'rank': 2} 

Encoding and decoding the custom object in Python:

In this case, we need to put more effort into serialization. Let us see how to do it. Let's say we have a class that uses a student and wants to make it JSON serializable. The easiest way is to define a method in our class that will return the JSON version of our class instance.

Program code 1:

Here we give a program code for encoding and decoding the custom object in Python. The code is given below -

Output:

Now we compile the above code and find the result from it. The output is given below -

 { "name": "Priyanka", "roll_no": 40, "age": 24, "address": { "city": "Bhatpara", "state": "West Bengal", "pin": "743123" } } <class 'str'> {'name': 'Priyanka', 'roll_no': 40, 'age': 24, 'address': {'city': 'Bhatpara', 'state': 'West Bengal', 'pin': '743123'}} <class 'dict'> 

Program code 2:

Here we give another program code for encoding and decoding the custom object in Python. It is a way to achieve this is to create a new class that extends JSONEncoder and then use this class as a parameter to the dumps method. The code is given below -

Output:

Now we compile the above code and find the result from it. The output is given below -

 { "name": "Priyanka", "roll_no": 40, "age": 24, "address": { "city": "Bhatpara", "state": "West Bengal", "pin": "743123" } } <class 'str'> {'name': 'Priyanka', 'roll_no': 40, 'age': 24, 'address': {'city': 'Bhatpara', 'state': 'West Bengal', 'pin': '743123'}} <class 'dict'> 

Custom Decoding in Python:

In Custom Decoding, if we want to convert the JSON to another Python object (not the original or default dictionary, for example), this is a very simple way; it is to use the object_hook parameter of the method loads. All we need to do is define a method that will define how we want to process the data and then pass this method as an object_hook parameter to the load method; see the code provided. Additionally, the returned object will no longer be a Python dictionary. Even if the return type of the method we pass is Object_hook, then it will still be the return type of the load's method.

Program code:

Here we give a program code for custom decoding in Python. The code is given below -

Output:

Now we compile the above code and find the result from it. The output is given below -

 The result is: (1+2j) The type of the result is: <class 'complex'> 

Advantage of using Encoding and decoding the custom object in Python:

The ability to create custom encoders and custom decoders in Python by using the json module has several advantages, which are given below -

1. Custom data management:

Custom encoders and decoders can serialize and deserialize complex Python objects or unformatted data into JSON format (or vice versa).

2. Control and flexibility:

Developers have greater control over how custom data types are entered into JSON and decoded into Python objects, ensuring accuracy and consistency in the data transfer process.

3. Compatibility and interoperability:

By using custom encoders and decoders, developers can ensure seamless compatibility between Python files and other systems that use JSON as the data exchange format.

4. Customize serialization logic:

You can customize serialization and deserialization logic to manage private data or complex objects and simplify data exchange between different systems or data storage.

Conclusion:

So, in this tutorial, we are learning the JSON encoder and decoder package in Python. The json module provides dumps() and loads() functions to serialize Python objects into JSON-encoded strings. As a result, the ability to create custom encoders and decoders in Python's json module allows developers to effectively manage the serialization and deserialization of different datasets, providing control, flexibility, and changes to transform data. These tools ensure consistency and interoperability in Python applications when working with complex files or custom classes.