Mc25104 - data structures and algorithms using PYTHON OOP_Python_Lecture_Notes.pptx

Mc25104 - data structures and algorithms using PYTHON OOP_Python_Lecture_Notes.pptx

• 1.
  Object-Oriented Programming in Python LectureNotes
• 2.
  1. Object-Oriented Programming (OOP) •Focuses on objects (data + behavior) • Models real-world entities • Benefits: Modular, reusable, secure, maintainable
• 3.
  2. Abstract DataTypes (ADT) • Defines operations, not implementation • Examples: Stack, Queue, Linked List • Python Example: Stack with push, pop, peek
• 4.
  3. Classes andObjects • Class = Blueprint • Object = Instance of a class • Example: Student(name, roll).display()
• 5.
  4. Encapsulation andAbstraction • Encapsulation: Data + methods bundled in class • Abstraction: Hides details, shows essentials • Example: BankAccount with deposit, withdraw, balance
• 6.
  5. Inheritance • Reusecode from parent class • Types: Single, Multiple, Multilevel, Hierarchical • Example: Student inherits from Person
• 7.
  6. Namespace • Mappingof names to objects • Types: Built-in, Global, Local • Example: x = Global vs. Local inside function
• 8.
  7. Object Orientation(Integration) • Encapsulation → Security • Abstraction → Simplicity • Inheritance → Reusability • Polymorphism → Flexibility • Namespace → Organization
• 9.
  Summary • OOP helpswrite cleaner, modular, reusable code • ADT: Defines what, not how • Classes & Objects = Foundation • Encapsulation & Abstraction = Hide details • Inheritance = Reuse • Namespace = Scope management • Polymorphism = Same method, different behavior