مقدمة في البرمجة الكائنية بـ Python

Introduction to Object-Oriented Programming (OOP) in Python

• Object-oriented programming (OOP) is a programming paradigm built on the concept of "objects," containing both data (attributes) and code (methods) to manipulate that data.
• Python supports OOP through classes and objects, enabling modular, reusable code.

Defining Classes

• A class acts as a blueprint for creating objects, defining attributes and methods objects will possess.
• Classes are defined using the class keyword, followed by the class name (usually capitalized).
• Example:

class Dog:
    def __init__(self, name, breed):  # Constructor
        self.name = name
        self.breed = breed

    def bark(self):   # Method
        print("Woof!")

Creating Objects

• An object is an instance of a class. Creating an object involves calling the class name as a function.
• Example:

my_dog = Dog("Buddy", "Golden Retriever")

• This creates my_dog, an object of the Dog class.

Attributes and Methods

• Attributes store data associated with an object.
• Methods define actions an object can perform.
• Accessing attributes:

print(my_dog.name)  # Output: Buddy

• Calling methods:

my_dog.bark()    # Output: Woof!

Constructors (__init__)

• The __init__ method, a special constructor, is automatically called when creating a new object; it initializes object attributes.

Inheritance

• Inheritance allows creating new classes (derived) from existing ones (base).
• A derived class inherits attributes and methods from its base class.
• It can also add its own specific attributes and methods.
• Example:

class GoldenRetriever(Dog):
    def __init__(self, name):
        super().__init__(name, "Golden Retriever")  # Call base class constructor

my_golden = GoldenRetriever("Max")  # Output: No error, inherits everything

Polymorphism

• Polymorphism enables objects from different classes to be treated as objects of a common type.
• Methods sharing the same name can have different implementations in each class.
• Example:

class Cat:
    def bark(self):
        print("Meow!")

my_cat = Cat()
my_cat.bark() # Output: Meow

Encapsulation

• Encapsulation bundles data (attributes) and methods operating on that data within a class.
• Access to data is controlled via methods within the class, effectively hiding internal implementation details.

Getting and Setting Attributes

• Methods are used to control attribute access and validation.

Abstraction

• Abstraction simplifies complex systems by hiding internal details and presenting essential information to the user.
• Classes and objects facilitate this abstraction layer.

Python's built-in data structures and OOP

• Python's built-in structures (lists, dictionaries, tuples) are classes.
• Their methods and attributes can be leveraged.
• OOP enhances using and creating custom classes based on data structures.

Advantages of OOP in Python

• Modularity: Code organized into classes and objects promotes reusability.
• Reusability: Classes are reused within a program or across projects.
• Maintainability: Changes in one part seldom affect other parts.
• Readability: Well-structured code is more easily understood.
• Scalability: Handling complex projects is often made easier through OOP.

Access Modifiers (Optional Advanced Topic)

• Python lacks strict access modifiers (like public, private, protected).
• Conventions are used:
  • Attributes and methods with a double underscore prefix (__) are considered “private”.
  • Attributes with a single leading underscore (_) are often treated as subject to change; a clue they're not part of the public interface.
• These are primarily conventions rather than strict language rules.

Exception Handling (in OOP context)

• Exception handling within OOP allows managing errors specifically within class methods or functions.
• This approach helps handle potential issues within objects' operations.

Iterators and Generators (optional, more advanced)

• Iterators and generators, while not strictly OOP constructs, can be utilized within OOP.
• OOP principles can be applied for designing classes that manage iterations.

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