Skip to main content

Magic/Dunder Methods in Python

 


Learning Sections          show

Magic/Dunder Methods in Python

Magic methods, also known as dunder (double underscore) methods, in Python are special methods that begin and end with double underscores. They allow the customization of the behavior of built-in Python operations for user-defined classes.

Common Magic Methods

1. __init__

Initializes a new instance of a class.


class Person:
    def __init__(self, name, age):
        self.name = name
        self.age = age

person = Person("Alice", 30)
print(person.name)  # Output: Alice
print(person.age)   # Output: 30

2. __str__

Returns a string representation of the object.


class Person:
    def __init__(self, name, age):
        self.name = name
        self.age = age

    def __str__(self):
        return f"Person(name={self.name}, age={self.age})"

person = Person("Alice", 30)
print(person)  # Output: Person(name=Alice, age=30)

3. __repr__

Returns an unambiguous string representation of the object, often one that could be used to recreate the object.


class Person:
    def __init__(self, name, age):
        self.name = name
        self.age = age

    def __repr__(self):
        return f"Person(name='{self.name}', age={self.age})"

person = Person("Alice", 30)
print(repr(person))  # Output: Person(name='Alice', age=30)

4. __add__

Defines the behavior of the addition operator + for the objects of the class.


class Vector:
    def __init__(self, x, y):
        self.x = x
        self.y = y

    def __add__(self, other):
        return Vector(self.x + other.x, self.y + other.y)

v1 = Vector(2, 3)
v2 = Vector(4, 5)
result = v1 + v2
print(result.x, result.y)  # Output: 6 8

5. __len__

Defines the behavior of the len() function for the objects of the class.


class MyList:
    def __init__(self, items):
        self.items = items

    def __len__(self):
        return len(self.items)

my_list = MyList([1, 2, 3])
print(len(my_list))  # Output: 3

Other Dunder Methods

  • __getitem__, __setitem__, __delitem__: Indexing operations
  • __iter__, __next__: Iterator protocol
  • __call__: Callable objects
  • __eq__Defines the functionality of the equality operator
Labels:

Popular posts from this blog

Inheritance in Python

  Learning Sections          show Inheritance in Python Inheritance is a fundamental concept in object-oriented programming (OOP) that allows a class to inherit attributes and methods from another class. The class that inherits is called the child class or subclass, and the class being inherited from is called the parent class or superclass. Basic Inheritance In Python, a child class inherits from a parent class by specifying the parent class in parentheses after the child class name. Example: class Animal : def __init__ ( self , name ): self . name = name def speak ( self ): raise NotImplementedError ( "Subclass must implement this method" ) class Dog ( Animal ): def speak ( self ): return "Woof!" class Cat ( Animal ): def speak ( self ): return "Meow!" # Create instances of Dog and Cat dog = Dog ( "Buddy" ) cat = Cat ( "Whiskers" ...
Read more

Introduction to OOPs in Python

  Learning Sections          show Introduction to Object-Oriented Programming (OOP) Object-Oriented Programming (OOP) is a programming paradigm that organizes software design around objects rather than actions and data rather than logic. It revolves around the concept of "objects", which are instances of classes. These objects encapsulate data, in the form of attributes or properties, and behaviors, in the form of methods or functions. OOP promotes modularity, reusability, and extensibility in software development. Key Concepts of OOP: Class: A class is a blueprint or template for creating objects. It defines the attributes (data) and methods (functions) that will characterize any object instantiated from that class. Object: An object is an instance of a class. It is a concrete realization of the class blueprint, containing actual values instead of placeholders for attributes. Encapsulation: Encapsulation is ...
Read more

Generators in Python

  Learning Sections          show Generators in Python Generators are a special type of iterator in Python that allow you to iterate over a sequence of items without storing them all in memory at once. They are useful for generating large sequences of data on-the-fly, or for processing data in a memory-efficient manner. Creating Generators In Python, generators are created using generator functions or generator expressions: # Generator function def my_generator ( n ): for i in range ( n ): yield i # Generator expression my_generator = ( i for i in range ( 10 )) A generator function uses the yield keyword to yield values one at a time, while a generator expression creates an anonymous generator. Iterating Over Generators You can iterate over the values produced by a generator using a for loop: for value in my_generator ( 5 ): print ( value ) This w...
Read more