Python Decorators

1. What is a Decorator

A decorator is a function that modifies the behavior of another function without changing its source code.

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

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

say_hello()

Decorators wrap additional logic around an existing function.

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2. Decorator Without @ Syntax

def greet():
    print("Welcome")

greet = my_decorator(greet)
greet()

This demonstrates manual application of a decorator.

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3. Decorator with Arguments

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

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

print(add(5, 3))

Handles flexible function signatures.

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4. Chaining Multiple Decorators

def bold(func):
    def wrapper():
        print("<b>")
        func()
        print("</b>")
    return wrapper

def italic(func):
    def wrapper():
        print("<i>")
        func()
        print("</i>")
    return wrapper

@bold
@italic
def display():
    print("Text")

display()

Decorators execute from bottom to top order.

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5. Decorator with Return Value

def uppercase(func):
    def wrapper():
        result = func()
        return result.upper()
    return wrapper

@uppercase
def message():
    return "hello world"

print(message())

Wraps and transforms return values.

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6. Decorator Preserving Function Metadata

from functools import wraps

def my_decorator(func):
    @wraps(func)
    def wrapper(*args, **kwargs):
        return func(*args, **kwargs)
    return wrapper

@wraps preserves function name, docstring, and metadata.

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7. Decorator for Timing Execution

import time
from functools import wraps

def timer(func):
    @wraps(func)
    def wrapper(*args, **kwargs):
        start = time.time()
        result = func(*args, **kwargs)
        print("Execution Time:", time.time() - start)
        return result
    return wrapper

@timer
def process():
    for _ in range(1000000):
        pass

process()

Used for performance profiling.

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8. Decorator with Parameters

def repeat(n):
    def decorator(func):
        def wrapper(*args, **kwargs):
            for _ in range(n):
                func(*args, **kwargs)
        return wrapper
    return decorator

@repeat(3)
def greet():
    print("Hello")

greet()

Supports configurable decorator logic.

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9. Class-Based Decorator

class Logger:
    def __init__(self, func):
        self.func = func

    def __call__(self, *args, **kwargs):
        print("Calling function...")
        return self.func(*args, **kwargs)

@Logger
def show():
    print("Processing data")

show()

Implements decorators using classes.

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10. Real-World Decorator Example (Authentication)

def require_login(func):
    def wrapper(user):
        if not user.get("authenticated"):
            return "Access Denied"
        return func(user)
    return wrapper

@require_login
def view_profile(user):
    return f"Welcome {user['name']}"

user = {"name": "Alice", "authenticated": True}
print(view_profile(user))

Encapsulates cross-cutting concerns like security and validation.

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