Abstraction

Learn about abstraction in MicroPython and how it simplifies code interaction by hiding complexity.

Abstraction

In OOP, Abstraction means hiding the complexity of a system by exposing only the necessary details.

We achieve this by creating simple interfaces that allow interaction with the code without needing to know its inner workings.

This approach allows us to change how the system works without affecting the code that interacts with it, or the user noticing any change.

How We Use Abstraction in MicroPython

In MicroPython, we use classes to create abstractions. A class is a blueprint for creating objects that represent real-world entities.

In the example below, we model a popular road bike, the Yamaha MT-07, using a class. We provide two public methods ride and get_mileage to interact with the bike object.

The Bike class also has a private property __mileage that stores the mileage of the bike. __mileage can only be accessed by the ride() method to increase the mileage, and get_mileage() method to return the current mileage the bike has traveled.

class Bike:
    def __init__(self, make, model):
        self.make = make
        self.model = model
        self.__mileage = 0

    def ride(self, distance):
        self.__mileage += distance
    
    def get_mileage(self):
        return self.__mileage
    
my_bike = Bike("Yamaha", "MT-07")
my_bike.ride(100)
print(my_bike.get_mileage())

The Bike class is an abstraction of a real-world bike. It hides the complexity of how the bike works and provides a simple interface for interacting with the bike object.

Modularity

MicroPython allows us to create modular code by using classes to create objects that represent real-world entities.

Classes can be composed of other classes, which allows us to create complex objects that are made up of simpler objects.

For example, if we want to create a robot, we could create a class for the robot and then create objects for the sensors, motors, and other components that make up the robot.

class Sensor:
    def __init__(self, type):
        self.type = type

    def read_value(self):
        # Simulate reading a sensor value
        return 42

class Motor:
    def __init__(self, power):
        self.power = power

    def move(self, direction):
        print(f"Moving {direction} with power {self.power}")

class Robot:
    def __init__(self, name):
        self.name = name
        self.sensor = Sensor("Ultrasonic")
        self.motor = Motor(100)

    def move_forward(self):
        self.motor.move("forward")

    def read_sensor(self):
        return self.sensor.read_value()

robot = Robot("Robo")
robot.move_forward()
print(robot.read_sensor())

We cover Modules in a future lesson.

Abstraction vs. Encapsulation

Abstraction is about hiding complexity by exposing only the necessary details, while Encapsulation is about hiding properties and methods using access modifiers. We cover Encapsulation in a future lesson.

Real-World Example

Think of a car. You don’t need to know how the engine works to drive it. You just use the pedals, steering wheel, and gear stick. The engine is abstracted away from you.

Benefits of Abstraction

• Simplicity: Abstraction simplifies complex systems by hiding unnecessary details.
• Flexibility: We can change the system’s implementation without affecting the code that interacts with it.
• Reusability: Abstraction allows us to create interfaces that can be reused in different contexts.

Summary

Abstraction in OOP allows us to hide complexity and create simple interfaces for interacting with systems. It helps simplify, add flexibility, and reuse code in our programs.

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