Encapsulation involves bundling data members and functions inside a class to help with data hiding and ensure objects work independently. It wraps both data and methods into a single unit so end-users only need to provide inputs and receive outputs. Encapsulation provides well-defined, readable code; prevents accidental modification; and provides security. Python supports public, private, and protected access modifiers to restrict access to variables and functions within and outside classes.
Encapsulation in Python - What encapsulation actually means | .pdfChinnichinni92
Encapsulation in python:
In this presentation, we are going to explore encapsulation. So that you can know what encapsulation actually is.
It was presented theoretically.
Understanding Data Abstraction and Encapsulation in PythonJulie Bowie
Discover the key concepts of data abstraction and encapsulation in Python. Learn how to effectively apply these principles to enhance your programming skills and build robust, maintainable code.
The document discusses key concepts of object-oriented programming such as classes, objects, encapsulation, inheritance, and polymorphism. It provides examples of defining a Point class in Python with methods like translate() and distance() as well as using concepts like constructors, private and protected members, and naming conventions using underscores. The document serves as an introduction to object-oriented programming principles and their implementation in Python.
The document discusses object-oriented programming concepts like classes, objects, methods, encapsulation, abstraction, and inheritance. It provides examples of defining classes with attributes and methods, creating objects, and accessing object properties and methods. Constructors (__init__()) are discussed as special methods that initialize objects. Encapsulation, information hiding, and abstraction are presented as key concepts for modeling real-world objects in code with public and private interfaces.
Python uses access modifiers like public, protected, and private to control access to class variables and methods. Public members are accessible anywhere, protected members are accessible within the class and subclasses, and private members are only accessible within the class. The document then provides examples of each access modifier type by defining classes with members of each access level and demonstrating how they can be accessed.
This document discusses object-oriented programming concepts in Python like classes, objects, encapsulation, inheritance and polymorphism. It explains that classes are user-defined blueprints that contain data fields and methods, and objects are instances of classes. The key concepts of OOP like data encapsulation, abstraction, inheritance and polymorphism are explained with examples in Python. Various special methods like __init__(), __str__(), __repr__() and their usage with classes are also covered.
The document discusses object-oriented programming concepts in Python including classes, objects, methods, encapsulation, inheritance, and polymorphism. It provides examples of defining a class with attributes and methods, instantiating objects from a class, and accessing object attributes and methods. It also covers the differences between procedure-oriented and object-oriented programming, and fundamental OOP concepts like encapsulation, inheritance, and polymorphism in Python.
1) In Python, all member variables and methods are public by default. To make a member protected, prefix its name with a single underscore. To make a member private, prefix its name with two underscores and suffix it with at most one underscore, which uses name mangling.
2) The document discusses access modifiers in Python including public, protected, and private access. It provides examples of declaring public members without modification, protected members by prepending a single underscore, and private members by prepending two underscores and optional postpending single underscore, which utilizes name mangling.
3) Name mangling is used to prevent private member clashes in subclasses by transforming the name to include the class name.
The document discusses access control in Python object-oriented programming. It explains that in most languages, attributes and methods can be public, protected, or private, but in Python there is no built-in access control. By convention, prefixing with a single underscore _ indicates internal use only, while double underscore __ makes Python attempt to make it private. The document provides an example SecretString class to demonstrate how attributes prefixed with __ cannot be directly accessed but can still be retrieved by external objects in more complex ways.
This document discusses object-oriented programming concepts in Python including:
- Classes define templates for objects with attributes and methods. Objects are instances of classes.
- The __init__ method initializes attributes when an object is constructed.
- Classes can make attributes private using double underscores. Encapsulation hides implementation details.
- Objects can be mutable, allowing state changes, or immutable like strings which cannot change.
- Inheritance allows subclasses to extend and modify parent class behavior through polymorphism.
OOP in Python, a beginners guide..........FerryKemperman
The hair stylist
would cut the hair
Cook: The cook would cut
the vegetables
So the same word 'Cut' has different meaning depending on the context
This is an example of polymorphism. The same method name can behave
differently for different types of objects.
In OOP, polymorphism allows us to define methods in the child class that
have the same name as the methods in the parent class, but different
implementation.
This allows the child class to inherit the parent's interface while
modifying or extending the parent's functionality.
7/26/2014 VYBHAVA TECHNOLOGIES 27
Operator Overloading
Operator
Basics of Object Oriented Programming in PythonSujith Kumar
The document discusses key concepts of object-oriented programming (OOP) including classes, objects, methods, encapsulation, inheritance, and polymorphism. It provides examples of classes in Python and explains OOP principles like defining classes with the class keyword, using self to reference object attributes and methods, and inheriting from base classes. The document also describes operator overloading in Python to allow operators to have different meanings based on the object types.
Encapsulation C++ Piller of OOP it is the important pilleran7539661
Encapsulation in object-oriented programming involves wrapping data and functions that work on that data within a single unit called a class. This bundling of data and functions protects the data from outside modification and exposes a controlled interface. Encapsulation provides data hiding by restricting direct access to data members and requiring use of accessor functions, allowing control over modification and maintaining integrity. It improves maintainability, readability and security of code by combining related data and functions.
OOPS stands for Object-Oriented Programming System or Object-Oriented Programming Structure. It's a programming paradigm that organizes code into objects that contain data and behavior.
I’m thrilled to share my latest presentation on Object-Oriented Programming (OOP) in Python! This presentation delves into essential concepts that enhance code structure, promote reusability, and ensure maintainability. Whether you’re an experienced developer or new to the programming landscape, mastering OOP principles is key to writing efficient and effective code.
Key Highlights:
Core Principles of OOP: Get insights into encapsulation, abstraction, inheritance, and polymorphism.
Classes and Objects: Understand the blueprint for creating objects and their attributes.
Methodologies: Explore various types of inheritance, polymorphism, encapsulation, and abstraction.
Best Practices: Discover strategies to write cleaner and more maintainable code.
📊 Explore the presentation to see how OOP can elevate your programming skills and streamline your projects! Let’s embrace the future of software development with structured, reusable, and adaptable code.
I’d love to hear your thoughts, feedback, or any questions you may have! Happy coding! 💻✨
#Python #ObjectOrientedProgramming #OOP #SoftwareDevelopment #Coding #Programming #LearnToCode #TechTalks
The document discusses object-oriented programming concepts in Python including classes, objects, methods, encapsulation, inheritance, and polymorphism. It provides examples of defining a class with attributes and methods, instantiating objects from a class, and accessing object attributes and methods. It also covers the differences between procedure-oriented and object-oriented programming, and fundamental OOP concepts like encapsulation, inheritance, and polymorphism in Python.
1) In Python, all member variables and methods are public by default. To make a member protected, prefix its name with a single underscore. To make a member private, prefix its name with two underscores and suffix it with at most one underscore, which uses name mangling.
2) The document discusses access modifiers in Python including public, protected, and private access. It provides examples of declaring public members without modification, protected members by prepending a single underscore, and private members by prepending two underscores and optional postpending single underscore, which utilizes name mangling.
3) Name mangling is used to prevent private member clashes in subclasses by transforming the name to include the class name.
The document discusses access control in Python object-oriented programming. It explains that in most languages, attributes and methods can be public, protected, or private, but in Python there is no built-in access control. By convention, prefixing with a single underscore _ indicates internal use only, while double underscore __ makes Python attempt to make it private. The document provides an example SecretString class to demonstrate how attributes prefixed with __ cannot be directly accessed but can still be retrieved by external objects in more complex ways.
This document discusses object-oriented programming concepts in Python including:
- Classes define templates for objects with attributes and methods. Objects are instances of classes.
- The __init__ method initializes attributes when an object is constructed.
- Classes can make attributes private using double underscores. Encapsulation hides implementation details.
- Objects can be mutable, allowing state changes, or immutable like strings which cannot change.
- Inheritance allows subclasses to extend and modify parent class behavior through polymorphism.
OOP in Python, a beginners guide..........FerryKemperman
The hair stylist
would cut the hair
Cook: The cook would cut
the vegetables
So the same word 'Cut' has different meaning depending on the context
This is an example of polymorphism. The same method name can behave
differently for different types of objects.
In OOP, polymorphism allows us to define methods in the child class that
have the same name as the methods in the parent class, but different
implementation.
This allows the child class to inherit the parent's interface while
modifying or extending the parent's functionality.
7/26/2014 VYBHAVA TECHNOLOGIES 27
Operator Overloading
Operator
Basics of Object Oriented Programming in PythonSujith Kumar
The document discusses key concepts of object-oriented programming (OOP) including classes, objects, methods, encapsulation, inheritance, and polymorphism. It provides examples of classes in Python and explains OOP principles like defining classes with the class keyword, using self to reference object attributes and methods, and inheriting from base classes. The document also describes operator overloading in Python to allow operators to have different meanings based on the object types.
Encapsulation C++ Piller of OOP it is the important pilleran7539661
Encapsulation in object-oriented programming involves wrapping data and functions that work on that data within a single unit called a class. This bundling of data and functions protects the data from outside modification and exposes a controlled interface. Encapsulation provides data hiding by restricting direct access to data members and requiring use of accessor functions, allowing control over modification and maintaining integrity. It improves maintainability, readability and security of code by combining related data and functions.
OOPS stands for Object-Oriented Programming System or Object-Oriented Programming Structure. It's a programming paradigm that organizes code into objects that contain data and behavior.
I’m thrilled to share my latest presentation on Object-Oriented Programming (OOP) in Python! This presentation delves into essential concepts that enhance code structure, promote reusability, and ensure maintainability. Whether you’re an experienced developer or new to the programming landscape, mastering OOP principles is key to writing efficient and effective code.
Key Highlights:
Core Principles of OOP: Get insights into encapsulation, abstraction, inheritance, and polymorphism.
Classes and Objects: Understand the blueprint for creating objects and their attributes.
Methodologies: Explore various types of inheritance, polymorphism, encapsulation, and abstraction.
Best Practices: Discover strategies to write cleaner and more maintainable code.
📊 Explore the presentation to see how OOP can elevate your programming skills and streamline your projects! Let’s embrace the future of software development with structured, reusable, and adaptable code.
I’d love to hear your thoughts, feedback, or any questions you may have! Happy coding! 💻✨
#Python #ObjectOrientedProgramming #OOP #SoftwareDevelopment #Coding #Programming #LearnToCode #TechTalks
SVM introduction for machine learning engineersabigailjudith8
In essence, the AWS Machine Learning Foundations program serves as a starting point for those looking to build a solid understanding of machine learning principles and gain practical experience using AWS’s powerful machine learning services. It emphasizes scalable model development, deployment, and management within the cloud infrastructure provided by AWS.
Best Ticket Resale Verification System.pptxcounterten
CounterTEN offers advanced solutions for sports events through its trusted Ticket Resale Verification System, ensuring every ticket resold is authentic and secure. This innovative platform prevents fraud and protects fans by verifying ticket legitimacy before finalizing any resale transaction. Whether you're buying or selling, CounterTEN’s technology guarantees transparency and peace of mind. Our Ticket Resale Verification System streamlines the resale process for organizers and attendees alike, helping maintain fair access to top sports events while enhancing trust in the secondary ticket market.
Chess Mastery: The Path to Excellence (presentation)Brian Shechtman
Becoming highly skilled at the game of chess takes effort and dedication. History shows that reaching the top requires extensive training and preparation. While some believe anyone can become a master, not everyone meets the necessary criteria or puts in the required work.
NCAA Football Betting System That Will Change Your Gambling LifeJoe Duffy
Discover one of the longest-running and most profitable college football betting strategies that still holds up in 2025! This SlideShare breaks down the time-tested system of betting on unranked favorites against ranked teams, especially when the spread is -2.5 or more and the ranked opponent is #17 or higher.
📊 System record: 160-125-5 (56.1% win rate)
This isn’t a fluke — it’s a powerful example of how to use oddsmakers’ knowledge against them. When oddsmakers favor an unranked team over a ranked one, they’re making a bold statement — and the sharper bettors are listening.
Learn:
Why the spread matters more than the rankings
How to read the message behind the odds
Real-world examples of this system at work
Why “the stronger the statement, the stronger the bet”
✅ For more winning systems, visit: OffshoreInsiders.com
#CollegeFootball #SportsBetting #BettingSystems #CFB #OddsmakersEdge #SmartBets #SportsInvesting #VegasKnows #RankedVsUnranked #SlideShare #BettingTips #SharpMoney #OffshoreInsiders
Best Ticket Resale Verification System.pdfcounterten
CounterTEN offers advanced solutions for sports events through its trusted Ticket Resale Verification System, ensuring every ticket resold is authentic and secure. This innovative platform prevents fraud and protects fans by verifying ticket legitimacy before finalizing any resale transaction. Whether you're buying or selling, CounterTEN’s technology guarantees transparency and peace of mind. Our Ticket Resale Verification System streamlines the resale process for organizers and attendees alike, helping maintain fair access to top sports events while enhancing trust in the secondary ticket market.
2. What is Encapsulation?
• Encapsulation in Python is an object-oriented programming (OOP)
concept that refers to the bundling of data (attributes) and
methods (functions) that operate on the data into a single unit, or
class.
• Encapsulation is one of the key concepts of Object-Oriented
Programming (OOP). It restricts direct access to some of an object's
components, which prevents accidental modification of data.
• Encapsulation helps in:
• - Data hiding
• - Restricting access to internal object details
• - Controlling modifications to attributes
3. Public Attributes
• Public attributes are accessible from anywhere inside or
outside the class.
Example:
class Car:
def __init__(self, brand):
self.brand = brand # Public attribute
car1 = Car('Toyota')
print(car1.brand) # Output: Toyota
4. Protected Attributes
• Protected attributes are prefixed with a single underscore (_), indicating
that they should not be accessed directly outside the class but can still
be accessed.
Example:
class Car:
def __init__(self, brand):
self._brand = brand # Protected attribute
car1 = Car('Toyota')
print(car1._brand) # Output: Toyota (not recommended to access directly)
5. Private Attributes
Private attributes are prefixed with double underscores (__),
making them inaccessible directly outside the class.
Example:
class Car:
def __init__(self, brand):
self.__brand = brand # Private attribute
car1 = Car('Toyota')
print(car1.__brand) # Error: AttributeError
6. Accessing Private Attributes
• Private attributes can be accessed using getter methods.
Example:
class Car:
def __init__(self, brand):
self.__brand = brand
def get_brand(self):
return self.__brand
car1 = Car('Toyota')
print(car1.get_brand()) # Output: Toyota
7. Modifying Private Attributes
• Private attributes can be modified using setter methods.
Setter Method (set_brand): This new method provides a controlled way to modify
the __brand attribute.
class Car:
def __init__(self, brand):
self.__brand = brand # Private attribute initialized in the constructor
def get_brand(self):
return self.__brand # Getter method to access the private attribute
def set_brand(self, brand):
self.__brand = brand
car1 = Car('Toyota')
print(car1.get_brand()) # Output: Toyota
car1.set_brand('Honda')
print(car1.get_brand()) # Output: Honda
8. Summary
- Public attributes can be accessed from anywhere.
- Protected attributes are meant to be accessed
only within subclasses.
- Private attributes cannot be accessed directly but
can be accessed via methods.
• Encapsulation helps in maintaining security and
integrity of data in Python classes.
9. Protected Attributes
• Protected attributes are prefixed with a single underscore (_), indicating
that they should not be accessed directly outside the class but can still
be accessed.
Example:
class Car:
def __init__(self, brand):
self._brand = brand # Protected attribute
car1 = Car('Toyota')
print(car1._brand) # Output: Toyota (not recommended to access directly)
10. Protected Attributes
• Protected attributes are prefixed with a single underscore (_), indicating
that they should not be accessed directly outside the class but can still
be accessed.
Example:
class Car:
def __init__(self, brand):
self._brand = brand # Protected attribute
car1 = Car('Toyota')
print(car1._brand) # Output: Toyota (not recommended to access directly)
11. Protected Attributes
# Base class
class Animal:
def __init__(self, age):
self._age = age # Protected attribute
# Derived class
class Dog(Animal):
def __init__(self, age):
super().__init__(age)
def print_age(self):
# Accessing the protected attribute within a subclass
print(f"The dog's age is: {self._age}")
# Creating an instance of Dog
my_dog = Dog(5)
my_dog.print_age() # This will output: The dog's age is: 5
# Direct access from outside the class (not recommended, but possible)
print(my_dog._age) # Outputs 5, demonstrating that 'protected' is a convention
12. Summary
Protected: Accessible within the class and its
subclasses. It’s a guideline (or enforced by the
language) for controlled access.
Private: Strictly hidden inside the class, ensuring
that no external code or subclasses directly
modify sensitive data.