Intermediate Python

Data classes

The code for our Dog looked like this using traditional classes:

class Dog:
    def __init__(self, name, colour):
        self.name = name
        self.colour = colour
        self.energy = 1
    
    def describe(self):
        return f"{self.name} is {self.colour}"
    
    def exercise(self):
        print(f"You take {self.name} for a walk")
        self.energy -= 1
            
    def feed(self):
        print(f"{self.name} eats the food")
        self.energy += 1

Python 3.7 (release June 2018) introduced a new feature called data classes since it was recognised that while classes can be used for very complicated things, most classes exist to hold simple data with a few functions to extract or update those data. Writing __init__ functions is boring with a lot of repetition and so data classes were created to automate some of the standard tasks when writing classes.

To turn our Dog class into a data class we first import the feature from the dataclasses module, we then apply it to our class using a decoration, @dataclass. We can then remove our __init__ function and replace it with a listing of attribute names, each tagged with the type of data that they should hold:

from dataclasses import dataclass

@dataclass
class Dog:
    name: str
    colour: str
    energy: int = 1
    
    def describe(self):
        return f"{self.name} is {self.colour}"
    
    def exercise(self):
        print(f"You take {self.name} for a walk")
        self.energy -= 1
            
    def feed(self):
        print(f"{self.name} eats the food")
        self.energy += 1

All the other functions in the class remain as they were.

Using the class works in exactly the same way:

our_dog = Dog("Spot", "brown")

print(our_dog.describe())

Spot is brown

print(our_dog.energy)

1

our_dog.exercise()

You take Spot for a walk