Decorators are a powerful feature in Python that allow you to modify or extend the behavior of a function or method without changing its actual code.<\/p>\n\n\n\n
In simple words:
A decorator adds extra functionality to an existing function.<\/p>\n\n\n\n
In Python, functions are first-class objects.
This means:<\/p>\n\n\n\n
Decorators use this concept.<\/p>\n\n\n\n
def greet():
print(\"Hello\")def decorator_function(func):
def wrapper():
print(\"Before function call\")
func()
print(\"After function call\")
return wrappergreet = decorator_function(greet)
greet()<\/pre>\n\n\n\nOutput:<\/p>\n\n\n\n
Before function call
Hello
After function call<\/pre>\n\n\n\nThe decorator added extra behavior before and after the function.<\/p>\n\n\n\n
Using @ Decorator Syntax<\/strong><\/h2>\n\n\n\n
Python provides a cleaner way using
@<\/code>.<\/p>\n\n\n\ndef decorator_function(func):
def wrapper():
print(\"Before function call\")
func()
print(\"After function call\")
return wrapper@decorator_function
def greet():
print(\"Hello\")greet()<\/pre>\n\n\n\nThis is the same as:<\/p>\n\n\n\n
greet = decorator_function(greet)<\/pre>\n\n\n\nDecorator with Arguments<\/strong><\/h2>\n\n\n\n
If the original function has parameters:<\/p>\n\n\n\n
def decorator_function(func):
def wrapper(name):
print(\"Before function call\")
func(name)
print(\"After function call\")
return wrapper@decorator_function
def greet(name):
print(\"Hello\", name)greet(\"Hira\")<\/pre>\n\n\n\n**Using *args and kwargs (Best Practice)<\/strong><\/h2>\n\n\n\n
To handle any number of arguments:<\/p>\n\n\n\n
def decorator_function(func):
def wrapper(*args, **kwargs):
print(\"Before function call\")
result = func(*args, **kwargs)
print(\"After function call\")
return result
return wrapper<\/pre>\n\n\n\nThis makes the decorator flexible.<\/p>\n\n\n\n
Built-in Decorators in Python<\/strong><\/h2>\n\n\n\n
@staticmethod<\/code>@classmethod<\/code>@property<\/code><\/p>\n\n\n\nExample:<\/p>\n\n\n\n
class Student:
def __init__(self, marks):
self._marks = marks @property
def marks(self):
return self._marks<\/pre>\n\n\n\nNow
marks<\/code> can be accessed like a variable, not a method.<\/p>\n\n\n\nKey Points<\/strong><\/h2>\n\n\n\n
\n
- Decorators take a function as input<\/li>\n\n\n\n
- They return a new function<\/li>\n\n\n\n
- Use
@<\/code> syntax for cleaner code<\/li>\n\n\n\n- Useful for logging, timing, authentication, validation<\/li>\n<\/ul>\n\n\n\n
Key Takeaway<\/strong><\/h2>\n\n\n\n
Decorators allow you to add extra functionality to functions or methods without modifying their original code.<\/p>\n\n\n\n
They make programs cleaner, reusable, and more powerful in Python.<\/p>\n\n\n