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Aggregation in object-oriented programming is a "has-a" relationship where one object contains another. It allows objects to collaborate while maintaining independence.
Explore Python's class methods: a key OOP feature that enhances code organization. Learn how they differ from instance and static methods to write more flexible and efficient programs.
Object-oriented programming in Python relies on class relationships like association, where classes connect without strong ownership, enabling flexible and maintainable design.
In Python, composition lets you build complex systems by combining objects instead of inheriting. This approach leads to more flexible, maintainable code. Learn when and how to use it effectively.
Inheritance allows a new class to take on attributes and methods from an existing class, while composition builds objects by combining simpler ones.
Python's copy module offers shallow and deep copy methods. Understanding the difference is crucial to avoid unintended side effects in your code.
In Python, copying objects is nuanced; assignment creates references, not copies. Shallow copies share nested objects, while deep copies clone everything, avoiding unintended side effects.
Regular classes require manual boilerplate code; dataclasses reduce redundancy with decorators. Use dataclasses for simple data storage and regular classes for complex behaviors.
The Factory Pattern simplifies object creation, especially when the exact class isn't known until runtime. It enhances flexibility and maintainability in software design.
Encapsulation in Python bundles data and methods, restricting direct access to some components to improve code quality by controlling what is exposed or kept private.