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HomeBackend DevelopmentPython TutorialLearn Python Magic Methods: A Simple Explanation

Learn Python Magic Methods: A Simple Explanation

Understanding Magic Methods in Python

Magic methods in Python, also known as dunder methods (because they have double underscores at the beginning and end of their names), allow us to define the behavior of our objects for various operations. They enable custom behavior and can make our classes act like built-in types. In this blog, we will explore different categories of magic methods, provide detailed explanations, and give practical examples and use cases.

1. Attribute Access Methods

These magic methods control how attributes of your objects are accessed, modified, or deleted.

__getattr__ and __getattribute__

  • __getattr__: Called when an attribute is not found in an object.

  • __getattribute__: Called unconditionally to access any attribute.

Example: Custom Attribute Access with Logging

class LoggedAttributes:
    def __init__(self, name):
        self.name = name

    def __getattr__(self, item):
        print(f"Accessing non-existent attribute: {item}")
        return None

    def __getattribute__(self, item):
        print(f"Getting attribute: {item}")
        return super().__getattribute__(item)

# Usage
obj = LoggedAttributes("Alice")
print(obj.name)  # Output: Getting attribute: name\nAlice
print(obj.age)   # Output: Accessing non-existent attribute: age\nNone

Practical Use Case: Logging attribute access in a debugging scenario to trace when and how attributes are accessed or modified.

__setattr__ and __delattr__

  • __setattr__: Called when an attribute assignment is attempted.

  • __delattr__: Called when an attribute deletion is attempted.

Example: Custom Attribute Modification with Validation

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

    def __setattr__(self, key, value):
        if key == "age" and value 



<p><strong>Practical Use Case:</strong> Enforcing validation rules or restrictions when setting or deleting attributes.</p>

<h3>
  
  
  2. <strong>Container Methods</strong>
</h3>

<p>These magic methods allow your objects to behave like containers (lists, dictionaries, etc.).</p>

<h4>
  
  
  __len__, __getitem__, __setitem__, __delitem__, and __iter__
</h4>

  • __len__: Returns the length of the container.

  • __getitem__: Retrieves an item at a given index or key.

  • __setitem__: Sets an item at a given index or key.

  • __delitem__: Deletes an item at a given index or key.

  • __iter__: Returns an iterator object.

Example: Custom List-like Object

class CustomList:
    def __init__(self):
        self._items = []

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

    def __getitem__(self, index):
        return self._items[index]

    def __setitem__(self, index, value):
        self._items[index] = value

    def __delitem__(self, index):
        del self._items[index]

    def __iter__(self):
        return iter(self._items)

    def append(self, item):
        self._items.append(item)

# Usage
cl = CustomList()
cl.append(1)
cl.append(2)
cl.append(3)
print(len(cl))  # Output: 3
print(cl[1])    # Output: 2
for item in cl:
    print(item)  # Output: 1 2 3

Practical Use Case: Creating a custom collection class that needs specialized behavior or additional methods while still supporting standard list operations.

3. Numeric and Comparison Methods

These methods define how objects of your class interact with numeric operations and comparisons.

Numeric Methods

  • __add__, __sub__, __mul__, __truediv__, __floordiv__, __mod__, __pow__: Define arithmetic operations.

Example: Custom Complex Number Class

class Complex:
    def __init__(self, real, imag):
        self.real = real
        self.imag = imag

    def __add__(self, other):
        return Complex(self.real + other.real, self.imag + other.imag)

    def __sub__(self, other):
        return Complex(self.real - other.real, self.imag - other.imag)

    def __repr__(self):
        return f"({self.real} + {self.imag}i)"

# Usage
c1 = Complex(1, 2)
c2 = Complex(3, 4)
print(c1 + c2)  # Output: (4 + 6i)
print(c1 - c2)  # Output: (-2 + -2i)

Practical Use Case: Implementing custom numeric types like complex numbers, vectors, or matrices.

Comparison Methods

  • __eq__, __ne__, __lt__, __le__, __gt__, __ge__: Define comparison operations.

Example: Implementing Total Ordering for a Custom Class

from functools import total_ordering

@total_ordering
class Book:
    def __init__(self, title, author):
        self.title = title
        self.author = author

    def __eq__(self, other):
        return (self.title, self.author) == (other.title, other.author)

    def __lt__(self, other):
        return (self.title, self.author) 



<p><strong>Practical Use Case:</strong> Enabling custom objects to be sorted or compared, useful in data structures like heaps, binary search trees, or simply when sorting lists of custom objects.</p>

<h3>
  
  
  4. <strong>Container Methods: Practical Use Case</strong>
</h3>

<h4>
  
  
  <strong>Custom Dictionary with Case-Insensitive Keys</strong>
</h4>

<p>Creating a dictionary-like object that treats keys as case-insensitive.</p>

<p><strong>Example: Case-Insensitive Dictionary</strong><br>
</p>

<pre class="brush:php;toolbar:false">class CaseInsensitiveDict:
    def __init__(self):
        self._data = {}

    def __getitem__(self, key):
        return self._data[key.lower()]

    def __setitem__(self, key, value):
        self._data[key.lower()] = value

    def __delitem__(self, key):
        del self._data[key.lower()]

    def __contains__(self, key):
        return key.lower() in self._data

    def keys(self):
        return self._data.keys()

    def items(self):
        return self._data.items()

    def values(self):
        return self._data.values()

# Usage
cid = CaseInsensitiveDict()
cid["Name"] = "Alice"
print(cid["name"])  # Output: Alice
print("NAME" in cid)  # Output: True

Practical Use Case: Creating dictionaries where keys should be treated as case-insensitive, useful for handling user inputs, configuration settings, etc.

Conclusion

Magic methods provide a powerful way to customize the behavior of your objects in Python. Understanding and effectively using these methods can make your classes more intuitive and integrate seamlessly with Python's built-in functions and operators. Whether you're implementing custom numeric types, containers, or attribute access patterns, magic methods can greatly enhance the flexibility and functionality of your code

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