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Encapsulation in Python

OOP Design

Encapsulation

Encapsulation isn't about private keywords—it's about clear boundaries. Use naming conventions, properties, and helper classes to build trustable APIs.

Apply naming conventionsUse properties

Naming conventions​

  • _single_leading_underscore signals "internal use."
  • __double_leading triggers name mangling—rarely needed.
  • property allows validation while exposing attribute-like syntax.
class Account:
    def __init__(self):
        self._balance = 0.0

    @property
    def balance(self) -> float:
        return self._balance

    def deposit(self, amount: float) -> None:
        if amount <= 0:
            raise ValueError("Deposit must be positive")
        self._balance += amount

Property setters​

Add a setter to allow controlled writes:

class Account:
    def __init__(self, balance: float = 0.0):
        self._balance = balance

    @property
    def balance(self) -> float:
        return self._balance

    @balance.setter
    def balance(self, value: float) -> None:
        if value < 0:
            raise ValueError("Balance cannot be negative")
        self._balance = value

Use @property without a setter for read-only attributes.

Composition > inheritance​

Encapsulation thrives when responsibilities are split into collaborating objects instead of huge base classes.

Next up in your learning path

Polymorphism

Expose different behavior behind the same interface.

Design

Abstract classes

Formalize contracts for subclasses.

Architecture

Dataclasses

Encapsulate state with modern conveniences.

Modern