Object-Oriented Programming (OOP) is a programming worldview that coordinates programming configuration around items and information, as opposed to capabilities and rationale. Python, one of the most well known programming dialects, completely upholds OOP and gives useful assets to assist engineers with organizing their code effectively. In this article, we’ll give a complete Python OOP cheat sheet that covers the center standards, linguistic structure, and best acts of Item Situated Programming, alongside viable models.
Toward the finish of this article, you’ll have a strong comprehension of how to execute OOP in Python and be prepared to compose spotless, viable, and particular code.
Introduction to Object-Oriented Programming
Table of Contents
Prior to plunging into the linguistic structure and highlights of Python OOP, understanding the essential standards of OOP is significant. There are four essential ideas that characterize Item Situated Programming:
Core Principles of OOP:
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Encapsulation:
This is the packaging of information (traits) and strategies (works) that work on the information into a solitary unit called a class. It additionally includes limiting admittance to specific subtleties of an article’s inward functions.
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Abstraction:
This includes concealing the perplexing execution subtleties of an article and furnishing a less difficult connection point to collaborate with it.
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Inheritance:
This permits one class to acquire the characteristics and techniques for another class, advancing code reuse and the making of various leveled connections.
-
Polymorphism:
This alludes to the capacity to utilize a solitary technique, administrator, or class in various ways. The most well-known illustration of polymorphism in Python is technique abrogating.
Since we have a general comprehension of OOP, we should continue on toward how Python executes these ideas.
Classes and Objects in Python
In Python, everything is an item. A class is an outline for making objects (examples). It characterizes credits (factors) and techniques (works) that articles made from the class will have.
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Defining a Class
class Car:
# Constructor method (initializer)
def __init__(self, make, model, year):
self.make = make
self.model = model
self.year = year
# Method to display car details
def display_info(self):
print(f”{self.year} {self.make} {self.model}”)
Making Items:
To make an item (occurrence) of a class, you call the class like a capability.
Explanation:
- __init__ technique: This is the constructor strategy in Python, called when another article is made. It states the properties of the article.
- self: This alludes to the ongoing example of the class. Getting to factors and techniques inside the class is utilized.
Attributes and Methods
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Instance Variables
These are variables that belong to a specific instance of a class.
class Dog:
def __init__(self, name, breed):
self.name = name # Instance variable
self.breed = breed
dog1 = Dog(“Buddy”, “Golden Retriever”)
print(dog1.name) # Output: Buddy
Class Variables
Class variables are shared by all instances of a class.
class Dog:
species = “Canis familiaris” # Class variable
def __init__(self, name, breed):
self.name = name
self.breed = breed
dog1 = Dog(“Buddy”, “Golden Retriever”)
dog2 = Dog(“Max”, “Bulldog”)
print(dog1.species) # Output: Canis familiaris
Methods
Techniques are capabilities characterized inside a class that portray the ways of behaving of an item. They can adjust the item’s state or perform activities.
class Dog:
def __init__(self, name, breed):
self.name = name
self.breed = breed
def bark(self):
print(f”{self.name} says woof!”)
dog1 = Dog(“Buddy”, “Golden Retriever”)
dog1.bark() # Output: Buddy says woof!
Inheritance in Python
Legacy permits a class to acquire traits and strategies from another class, which can assist with keeping away from overt repetitiveness and cultivate code reuse.
Syntax for Inheritance
class Animal:
def __init__(self, name):
self.name = name
def speak(self):
print(f”{self.name} makes a sound”)
# Dog class inherits from Animal
class Dog(Animal):
def speak(self):
print(f”{self.name} barks”)
dog = Dog(“Buddy”)
dog.speak() # Output: Buddy barks
Explanation:
-
Base class (Parent class):
Animal is the parent class.
-
Derived class (Child class):
Dog is the subclass that inherits from Animal.
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Method Overriding:
In this example, the speak() method is overridden in the Dog class to provide specific behavior.
Polymorphism in Python
Polymorphism permits you to utilize a solitary strategy, administrator, or class in various ways. In Python, polymorphism is often accomplished through strategy superseding and administrator over-burdening.
Example of Method Overriding
class Animal:
def speak(self):
print(“Animal makes a sound”)
class Dog(Animal):
def speak(self):
print(“Dog barks”)
class Cat(Animal):
def speak(self):
print(“Cat meows”)
animals = [Dog(), Cat()]
for animal in animals:
animal.speak() # Output: Dog barks
# Cat meows
Explanation:
The talk() strategy is superseded in both the Canine and Feline classes, permitting polymorphic ways of behaving.
Encapsulation and Abstraction in Python OOP Cheat Sheet
Encapsulation
Epitome includes limiting admittance to an article’s inside state and just permitting alteration through distinct strategies. In Python, this is regularly finished by utilizing private factors (meant by a main highlight _).
Example of Encapsulation
class BankAccount:
def __init__(self, balance):
self._balance = balance # Private variable
def deposit(self, amount):
self._balance += amount
def withdraw(self, amount):
if amount <= self._balance:
self._balance -= amount
else:
print(“Insufficient funds”)
def get_balance(self):
return self._balance
account = BankAccount(1000)
account.deposit(500)
account.withdraw(200)
print(account.get_balance()) # Output: 1300
Abstraction
Reflection permits you to conceal complex subtleties and just uncover the fundamental usefulness. In Python, deliberation can be carried out utilizing unique classes and strategies, ordinarily with the assistance of the abc module.
Example of Abstraction
from abc import ABC, abstractmethod
class Animal(ABC):
@abstractmethod
def speak(self):
pass
class Dog(Animal):
def speak(self):
print(“Dog barks”)
dog = Dog()
dog.speak() # Output: Dog barks
Explanation:
-
Abstract Base Class (ABC):
The Creature class is dynamic, meaning it can’t be started up straightforwardly. It contains a theoretical technique talk(), which should be carried out by any subclass.
Magic Methods in Python
Enchantment strategies (or dunder techniques) are extraordinary techniques that permit you to characterize how objects of a class act when utilized with specific tasks.
Common Magic Methods:
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__init__: Constructor
-
__str__: String representation of an object
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__repr__: Official string representation
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__add__: Addition operator
-
__len__: Length of an object
Example of Magic Methods
class Point:
def __init__(self, x, y):
self.x = x
self.y = y
def __str__(self):
return f”Point({self.x}, {self.y})”
def __add__(self, other):
return Point(self.x + other.x, self.and + other.y)
point1 = Point(1, 2)
point2 = Point(3, 4)
print(point1) # Output: Point(1, 2)
point3 = point1 + point2
print(point3) # Output: Point(4, 6)
Explanation:
-
The __str__ strategy is utilized to characterize a comprehensible string portrayal of an item.
-
The __add__ strategy permits you to characterize how the + administrator acts for objects of the Point class.
Best Practices in Python OOP
To guarantee your Python OOP code is spotless, effective, and viable, follow these prescribed procedures:
-
Use Meaningful Names:
Pick distinct names for classes, techniques, and factors.
-
Keep Methods Small and Focused:
Every strategy ought to play out a solitary undertaking or activity.
-
Encapsulation:
Utilize private factors and give getter and setter strategies to get to them.
-
Favor Composition Over Inheritance:
Rather than profoundly settling subclasses, favor joining various classes to make complex usefulness.
Final Thoughts:
Python’s Object -Oriented Programming (OOP) highlights give a strong method for putting together and structure your code. By getting it and carrying out the standards of epitome, deliberation, legacy, and polymorphism, you can make exceptionally particular, reusable, and viable applications. With the cheatsheet above, you currently have major areas of strength for a to start integrating OOP standards into your Python ventures and composing productive, clean code. Whether you’re building straightforward applications or huge scope programming, Python’s OOP elements will help you scale and keep up with your code really.
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FAQ’S:
Qno1: Qno1: What Is the Distinction Between a Class and An Item in Python OOP?
Ans: A class is an outline or layout for making objects (occurrences). It characterizes credits (information) and strategies (works) that the articles made from the class will have. An item, then again, is a case of a class, addressing a particular element that can hold values for the traits and execute the strategies characterized in the class.
Qno2: How Does Legacy Work in Python OOP?
Ans: Legacy permits one class (the kid class) to acquire characteristics and strategies from another class (the parent class). This empowers code reuse and the production of additional particular classes that broaden or adjust the way of behaving of the parent class. The kid class can likewise abrogate strategies from the parent class to give a particular way of behaving.
