Decorators in Python 

Python is powerful not just because it is simple, but because it provides advanced features like Decorators and Generators.

If you want to become a strong Python developer, especially for interviews and real-world projects, you must understand these concepts clearly.

In this blog, you will learn:

• What are Decorators?

• How Decorators work

• What are Generators?

• How Generators improve performance

• Real-world examples

• Interview tips

What Are Decorators in Python?

A Decorator is a function that modifies the behavior of another function without changing its actual code.

In simple words:

A decorator adds extra functionality to an existing function.

Why Use Decorators?

Decorators are used for:

• Logging

• Authentication

• Authorization

• Measuring execution time

• Input validation

• Caching

They are widely used in frameworks like:

• Django

• Flask

Basic Example of a Decorator

def my_decorator(func):
    def wrapper():
        print("Something before the function runs")
        func()
        print("Something after the function runs")
    return wrapper

@my_decorator
def say_hello():
    print("Hello!")

say_hello()

Output:

Something before the function runs
Hello!
Something after the function runs

How It Works:
@my_decorator modifies say_hello
The original function is wrapped inside another function

Decorator with Arguments
def decorator(func):
    def wrapper(name):
        print("Welcome!")
        func(name)
        print("Goodbye!")
    return wrapper

@decorator
def greet(name):
    print(f"Hello {name}")

greet("Bency")

Real-World Example: Execution Time Calculator
import time
def calculate_time(func):
    def wrapper(*args, **kwargs):
        start = time.time()
        func(*args, **kwargs)
        end = time.time()
        print("Execution time:", end - start)
    return wrapper
@calculate_time
def slow_function():
    time.sleep(2)
    print("Function completed")

slow_function()
This is very useful in real projects.