Python function decorator

Mariah 21 Published: 02/04/2025

Python function decorator

I'm happy to oblige! Here's a detailed explanation of Python function decorators:

What is a Decorator?

In Python, a decorator is a small piece of code that modifies or extends the behavior of another function without affecting its original functionality. Think of it as an "aspect-oriented programming" (AOP) concept, where you can add additional logic before or after the execution of the decorated function.

The Syntax

To create a decorator, you need to define a function that takes another function as an argument and returns a new function that "wraps" around the original one. The syntax is straightforward:

@decorator_name

def target_function():

original code here

In this example, decorator_name is the decorator function, and target_function is the function being decorated.

A Simple Example

Let's create a simple decorator that logs the execution time of a function:

import time

def timer_decorator(func):

def wrapper(*args, **kwargs):

start_time = time.time()

result = func(*args, **kwargs)

end_time = time.time()

print(f"{func.name} took {end_time - start_time:.2f} seconds")

return result

return wrapper

@timer_decorator

def my_function(x, y):

return x + y

print(my_function(2, 3)) # Output: my_function took 0.00 seconds

In this example, the timer_decorator function takes a function as an argument and returns a new function (wrapper) that wraps around it. The wrapper function logs the execution time before and after calling the original function.

More Complex Examples

Here are some more advanced examples of decorators:

Caching: You can create a decorator that caches the results of expensive functions to avoid recalculating them multiple times.
def cache_decorator(func):

cache = {}

def wrapper(*args, **kwargs):

key = str(args) + str(kwargs)

if key in cache:

return cache[key]

result = func(*args, **kwargs)

cache[key] = result

return result

return wrapper

@cache_decorator

def fibonacci(n):

if n <= 1:

return n

return fibonacci(n-1) + fibonacci(n-2)

print(fibonacci(5)) # Output: 5

Authentication: You can create a decorator that checks if the user is authenticated before allowing them to access certain functions.
def auth_decorator(func):

def wrapper(*args, **kwargs):

if not authenticated:

raise Exception("Not authenticated")

return func(*args, **kwargs)

return wrapper

@auth_decorator

def restricted_function():

this function can only be accessed by authenticated users

print("Hello, authenticated user!")

Conclusion

In conclusion, Python function decorators are a powerful tool for modifying or extending the behavior of functions without affecting their original functionality. They allow you to add additional logic before or after the execution of the decorated function, making them a versatile and flexible feature in your programming arsenal.

I hope this explanation was helpful! Let me know if you have any questions or need further clarification on decorators.

Python function built-in attributes

Python is a high-level programming language that provides a variety of built-in attributes and functions to help developers write efficient and readable code. Here are some essential built-in attributes and functions in Python:

Built-in Functions: abs(): Returns the absolute value of a number. all(): Returns True if all elements of an iterable (like list or tuple) are true. Otherwise, it returns False. any(): Returns True if at least one element in an iterable is true. Otherwise, it returns False. ascii(): Converts a string to ASCII format. bin(), oct(), and hex(): Convert an integer to binary, octal, or hexadecimal representation respectively. bool(): Converts a value to boolean (True or False). bytearray() and bytes(): Create byte arrays (for non-string data) or convert strings to bytes. chr(): Returns the Unicode character for an integer. complex(): Creates complex numbers. dir(): Returns a list of attributes for an object. divmod(): Returns the quotient and remainder when dividing two numbers. enumerate(), iter(), and reversed(): Help iterate over sequences (like lists or tuples). float() and int(): Convert a string to floating-point number or integer respectively. format(): Formats strings using placeholders. hash(): Returns the hash value of an object. id(): Returns the memory address of an object. input(): Waits for user input and returns it as a string. len(): Returns the length (number of items) in a sequence (like list or tuple). list(), set(), and tuple(): Create lists, sets, or tuples respectively. max() and min(): Return the maximum or minimum value in an iterable. next(): Advances an iterator to the next element and returns it. open(): Opens a file for reading (default) or writing. pow(), round(), and sum(): Perform mathematical operations on numbers. sorted() and reversed(): Sort sequences in ascending or descending order respectively. str(): Converts an object to string format. super(): Returns a proxy object that delegates method calls to the parent class (in a subclass). type(): Returns the type of an object. Built-in Attributes: __doc__, __name__, and __package__: These are special attributes provided by Python. __class__ and __mro__: Get the class of an object or the method resolution order (MRO). __dict__ and __slots__: Access a dictionary-like view of an object's attributes or specify the allowed attribute names for an object.

These are just a few examples of the many built-in attributes and functions available in Python. Understanding these can help you write more efficient, readable, and Pythonic code.