Object Oriented Essentials In Python

Explore object oriented programming in Python, covering classes, objects, attributes, and the constructor. Understand inheritance for code reuse with base classes and subclasses, and distinguish instance variables from class variables.

Create additional objects from a class and see how __init__ runs automatically on each creation, initializing attributes with self and optional default values.

Explore public and private attributes in python object-oriented programming, learn how encapsulation uses underscores and getters and setters to protect internal state from outside access.

Explore how Python's double underscore induces name mangling, making attributes and methods class-specific, and why this is not true private encapsulation, plus how single underscores and getters control access.

Compare class variables and instance variables in Python, showing how class variables are shared across all instances while instance variables are unique to each object, with examples.

Explore inheritance in Python by creating derived classes from a base class and reusing attributes and methods, as shown with Animal and Cat, and extend with new methods.

Learn how a subclass can override base class attributes and methods, giving the derived implementation priority. Use the super function to access the base class version when needed.

Explore how Python supports multiple inheritance by defining a subclass from several base classes. See how left-to-right base class order resolves attribute conflicts, illustrated with carnivore, herbivore, and omnivore diets.

Understand how Python handles multiple inheritance using the method resolution order, a depth-first left-to-right rule, across a base and derived class hierarchy like A, B, C, and D.

Explore polymorphism in Python by comparing duck typing and polymorphic functions, and see how same functions adapt to integers, floats, strings, and class hierarchies like animal, dog, and cat.

Explore operator overloading in Python to define how custom classes interact with operators like add and multiply, making objects behave like built-in types and writing clearer, error-reducing code.

Explore abstract classes in Python, including abstract methods and decorators, and see how square and circle derive from a shape to implement area for polymorphism.

Explore how Python's issubclass and isinstance functions determine subclass relationships and instance membership. Learn examples with animal, dog, and cat to test base and derived class relationships and tuple checks.

Design and implement Python software projects with object oriented concepts like inheritance, method resolution order, and polymorphism. Model components as classes and focus on architecture and relationships.

Create and manipulate employee, manager, and company objects to store and display names and salaries, with inheritance and list operations, while solving the hands-on exercise in a Jupyter notebook.

Define employee class with constructor and __str__ to print name and salary, then create a manager subclass with super and department, and a company class to store and list employees.

Design and implement a library catalog using two classes, book and library, where the book stores title, author, year, and the library exposes add, list, and find operations.

Define a book class with title, author, year and a string method. Build a library class to add, list, and find books by author using comprehensions.

Explore advanced topics in Python object oriented programming, including abstract classes, interfaces, decorators, and properties, with practical examples to build more efficient, organized, and scalable code.

Define abstract classes by inheriting from the ABC base class and decorating abstract methods, then implement concrete subclasses that override these methods; compare abstract classes with interfaces in Python.

Explore decorators in Python, learning how a function can be extended without changing its code, how to define and apply decorators, and how to stack multiple decorators for enhanced behavior.

Explore common decorator use cases, focusing on caching function results with lru_cache to speed up expensive recursive calls like fibonacci. See how memory limits govern cached values.

Explore how decorators enforce access control in Python by defining a require login wrapper that raises a permission error for unauthenticated users and accepts arbitrary arguments.

learn how properties in python enable getter, setter, and deleter behavior to control access to private attributes, with validation and type checks demonstrated on a point class.

Define properties in Python with the built-in property function, using getters, setters, and deleters inside the class, and learn when to use properties for validation.

Learn that class methods and static methods bind to the class, with class methods taking the class as the first argument (cls) via @classmethod, and from_string as an example.

Discover static methods within a class, how to define them with the staticmethod decorator, and compare static, class, and regular methods to decide when to use each.

Learn how Python uses exceptions to signal runtime errors and control flow with try, except, and finally blocks, including handling division by zero and ensuring code executes after errors.

Raise exceptions to signal errors, jump to the nearest except block, and demonstrate with value error messages like 'invalid value' and zero division errors.

Define custom Python exceptions by deriving from the base exception, raise them with informative messages, and use try-except-else for robust error handling.