Classes, inheritance, magic methods, dataclasses, and design patterns
Learn 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\
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.