Decorators in Python

Decorators in Python are a powerful feature that allows you to modify or extend the behavior of functions or methods without changing their actual code.

Decorators are widely used in logging, authentication, validation, performance monitoring, and automation frameworks.

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Functions are First-Class Objects

In Python, functions can be:

• Assigned to variables
• Passed as arguments
• Returned from other functions

def greet():
    print("Hello")

say_hello = greet
say_hello()

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Function Inside Another Function

def outer():
    print("Outer function")

    def inner():
        print("Inner function")

    inner()

outer()

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Function Returning Another Function

def outer():
    def inner():
        print("Hello from inner")
    return inner

func = outer()
func()

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What is a Decorator?

A decorator is a function that takes another function as an argument and returns a new function with enhanced behavior.

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Simple Decorator Example

def my_decorator(func):
    def wrapper():
        print("Before function execution")
        func()
        print("After function execution")
    return wrapper

def say_hi():
    print("Hi!")

say_hi = my_decorator(say_hi)
say_hi()

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Using @ Decorator Syntax

Python provides the @ symbol to apply decorators easily.

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

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Decorator with Arguments

def my_decorator(func):
    def wrapper(*args, **kwargs):
        print("Arguments:", args)
        return func(*args, **kwargs)
    return wrapper

@my_decorator
def add(a, b):
    return a + b

print(add(5, 3))

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Multiple Decorators

def decorator1(func):
    def wrapper():
        print("Decorator 1")
        func()
    return wrapper

def decorator2(func):
    def wrapper():
        print("Decorator 2")
        func()
    return wrapper

@decorator1
@decorator2
def show():
    print("Hello World")

show()

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Built-in Decorators in Python

• @staticmethod
• @classmethod
• @property

@staticmethod Example

class MathUtils:
    @staticmethod
    def add(a, b):
        return a + b

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Decorator with Timing Example

import time

def calculate_time(func):
    def wrapper():
        start = time.time()
        func()
        end = time.time()
        print("Execution time:", end - start)
    return wrapper

@calculate_time
def test_function():
    for i in range(1000000):
        pass

test_function()

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Decorators in Automation Testing

def retry(func):
    def wrapper():
        for i in range(3):
            try:
                func()
                break
            except:
                print("Retrying...")
    return wrapper

@retry
def click_button():
    print("Clicking button")

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Best Practices

• Use functools.wraps to preserve metadata
• Keep decorators simple and readable
• Avoid deeply nested decorators

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Common Interview Questions

• What is a decorator?
• Why use decorators?
• Difference between function and decorator?
• What are built-in decorators?

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Conclusion

Decorators in Python help extend functionality without modifying existing code. They are a powerful feature used heavily in frameworks, automation testing, and real-world applications.

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