In Python, class objects are used to organize complex information. To save or share this information, we need to convert it into a format like JSON, which is easy to read and write. Since class objects can't be saved directly as JSON, we first convert them into a dictionary (a data structure with key-value pairs). Once in this format, the object can easily be turned into JSON. Let's explore different methods to achieve this.

Using json.dumps() with __dict__

Every Python object has a __dict__ attribute that stores its attributes in a dictionary form. By accessing this attribute, you can quickly convert the object's data into a dictionary, which can then be serialized into a JSON string using json.dumps(). This method works well for simple objects but doesn’t give you control over how the object is represented in JSON.

import json

class Person:
    def __init__(self, name, age):
        self.name = name
        self.age = age

p1 = Person("Alice", 30)

# Convert object's attributes (__dict__) to JSON
res = json.dumps(p1.__dict__)
print(res)

{"name": "Alice", "age": 30}

Explanation: json.dumps(p1.__dict__) line converts the object's __dict__ attribute, which holds the instance's attributes as a dictionary, into a JSON string.

Using to_dict()

Defining a to_dict() method within the class gives you more control over how the object is serialized. This method can return a custom dictionary representation of the object, allowing you to exclude certain attributes, rename them, or transform the data before serialization.

import json

class Person:
    def __init__(self, name, age):
        self.name = name
        self.age = age

    def to_dict(self):
        return {'name': self.name, 'age': self.age}

p1 = Person("Alice", 30)
res = json.dumps(p1.to_dict())  # Use to_dict() to serialize
print(res)

{"name": "Alice", "age": 30}

Explanation: json.dumps(p1.to_dict()) calls the to_dict() method of the Person class, which returns a dictionary representation of the object's attributes. This dictionary is then serialized into a JSON string using json.dumps().

Using dataclasses with asdict()

Python’s dataclasses module provides a simple way to define classes with minimal boilerplate. The asdict() function converts a dataclass instance into a dictionary, which can then be easily serialized into JSON. This method is ideal for immutable objects and works seamlessly with dataclass fields.

import json
from dataclasses import dataclass, asdict

@dataclass
class Person:
    name: str
    age: int

p1 = Person("Alice", 30)
res = json.dumps(asdict(p1))  # Convert to dictionary and then JSON
print(res)

{"name": "Alice", "age": 30}

Explanation: json.dumps(asdict(p1)) uses the asdict() function from the dataclasses module to convert the Person dataclass instance into a dictionary. This dictionary representation of the object is then serialized into a JSON string using json.dumps().

Using __json__ method

For more complex serialization needs, you can implement a __json__() method in your class. This method returns a custom dictionary representation of the object when called. By passing a lambda function to the default parameter of json.dumps(), you can ensure that the __json__() method is invoked during serialization, allowing full control over the object’s JSON output.

import json

class Person:
    def __init__(self, name, age):
        self.name = name
        self.age = age

    def __json__(self):
        return {'name': self.name, 'age': self.age}

p1 = Person("Alice", 30)
res = json.dumps(p1, default=lambda o: o.__json__() if hasattr(o, '__json__') else None)
print(res)

{"name": "Alice", "age": 30}

Explanation: json.dumps() uses the __json__() method for custom serialization, converting the object to a dictionary if it exist and then serializing it to JSON. The default parameter applies this only to objects with the __json__() method.

Related Articles:

• Pandas DataFrame to_dict() Method
• Understanding Python Dataclasses