Classes, inheritance, magic methods, dataclasses, and design patterns
03Stage 3 of the roadmap: Objects & ConfidenceLearn Python classes and objects from scratch. Understand __init__, self, instance methods, class attributes, and __str__ with interactive examples and exercises.
Master Python inheritance - create subclasses, override methods, use super(), and understand polymorphism with interactive code examples and exercises.
Learn the difference between @classmethod and @staticmethod in Python. Master factory methods, utility functions, and when to use each decorator with hands-on exercises.
Master Python @property decorator to create getters, setters, deleters, and computed attributes with validation. Learn encapsulation through hands-on exercises.
Master Python magic methods (dunder methods) including __str__, __repr__, __len__, __eq__, __lt__, __getitem__, __contains__, and __call__ with interactive exercises.
Learn Python operator overloading with __add__, __sub__, __mul__, __eq__, __radd__, and __iadd__. Build custom classes that work with arithmetic and comparison operators.
Learn how to use Python's ABC module to create abstract base classes, enforce method contracts with @abstractmethod, and build reliable class hierarchies.
Understand Python multiple inheritance, the diamond problem, Method Resolution Order (MRO), super() in complex hierarchies, and practical mixin patterns.
Master Python dataclasses to eliminate repetitive __init__, __repr__, and __eq__ boilerplate. Learn @dataclass, field(), __post_init__, frozen classes, and comparison.
Learn when to use NamedTuple, TypedDict, or dataclass in Python. Compare structured data containers with interactive examples and exercises.
Learn how __slots__ works in Python to reduce memory usage and speed up attribute access. Interactive examples with memory comparisons.
Master advanced dataclass features including validation with __post_init__, immutability with frozen, complex defaults with field(), and dataclass inheritance patterns.
Learn when to use composition over inheritance in Python. Understand has-a vs is-a relationships, dependency injection, and how to refactor fragile inheritance hierarchies.