Python - Encapsulation & Data Hiding

Overview

Estimated time: 15–25 minutes

Encapsulation protects invariants and exposes a clean API. In Python, naming conventions and properties support encapsulation without strict privacy.

Learning Objectives

• Use naming conventions (_name, __mangled) and modules to limit surface area.
• Apply @property for validation and computed attributes.
• Expose a stable API and hide implementation details.

Examples

class Account:
    def __init__(self, balance: float):
        self._balance = balance  # protected by convention

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

    @balance.setter
    def balance(self, value: float) -> None:
        if value < 0:
            raise ValueError("negative balance")
        self._balance = value

Guidance & Patterns

• Use a leading underscore for non-public members; respect it in consumers.
• Prefer composition over inheritance to narrow exposed surface.

Best Practices

• Document your public API; use __all__ to control from module import *.
• Keep invariants in setters or dedicated methods; validate early.

Exercises

1. Refactor a class to use @property with validation instead of direct attribute writes.
2. Use __all__ in a package to define the public API.