Encapsulation with Getters/Setters
Use properties to encapsulate attribute access with getter and setter logic.
Python Encapsulation with Getters/Setters Program
This program helps you to learn the fundamental structure and syntax of Python programming.
# Program to demonstrate encapsulation using properties
class Account:
def __init__(self, balance=0):
self._balance = balance
@property
def balance(self):
return self._balance
@balance.setter
def balance(self, amount):
if amount < 0:
raise ValueError("Balance cannot be negative")
self._balance = amount
acc = Account(100)
print(acc.balance)
acc.balance = 150
print(acc.balance)100 150
Understanding Encapsulation with Getters/Setters
The @property decorator allows attribute-style access while still enforcing validation in the setter.
Note: To write and run Python programs, you need to set up the local environment on your computer. Refer to the complete article Setting up Python Development Environment. If you do not want to set up the local environment on your computer, you can also use online IDE to write and run your Python programs.
Practical Learning Notes for Encapsulation with Getters/Setters
This Python program is part of the "Object-Oriented Programs" topic and is designed to help you build real problem-solving confidence, not just memorize syntax. Start by understanding the goal of the program in plain language, then trace the logic line by line with a custom input of your own. Once you can predict the output before running the code, your understanding becomes much stronger.
A reliable practice pattern is to run the original version first, then modify only one condition or variable at a time. Observe how that single change affects control flow and output. This deliberate style helps you understand loops, conditions, and data movement much faster than copying full solutions repeatedly.
For interview preparation, explain this solution in three layers: the high-level approach, the step-by-step execution, and the time-space tradeoff. If you can teach these three layers clearly, you are ready to solve close variations of this problem under time pressure.