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Decorator
Decorators in Python are a powerful way to modify or extend the behavior of functions or methods without changing their code. Decorators are often used for tasks like logging, authentication, and adding additional functionality to functions. They are denoted by the “@” symbol and are applied above the function they decorate.
def say_hello():
print("World")
say_hello()
How do we change the output without changing the say hello() function?
wrapper() is not reserved word. It can be anyting.
Use Decorators
# Define a decorator function
def hello_decorator(func):
def wrapper():
print("Hello,")
func() # Call the original function
return wrapper
# Use the decorator to modify the behavior of say_hello
@hello_decorator
def say_hello():
print("World")
# Call the decorated function
say_hello()
If you want to replace the new line character and the end of the print statement, use end=''
# Define a decorator function
def hello_decorator(func):
def wrapper():
print("Hello, ", end='')
func() # Call the original function
return wrapper
# Use the decorator to modify the behavior of say_hello
@hello_decorator
def say_hello():
print("World")
# Call the decorated function
say_hello()
Multiple functions inside the Decorator
def hello_decorator(func):
def first_wrapper():
print("First wrapper, doing something before the second wrapper.")
#func()
def second_wrapper():
print("Second wrapper, doing something before the actual function.")
#func()
def main_wrapper():
first_wrapper() # Call the first wrapper
second_wrapper() # Then call the second wrapper, which calls the actual function
func()
return main_wrapper
@hello_decorator
def say_hello():
print("World")
say_hello()
Args & Kwargs
*args: This is used to represent positional arguments. It collects all the positional arguments passed to the decorated function as a tuple.**kwargs: This is used to represent keyword arguments. It collects all the keyword arguments (arguments passed with names) as a dictionary.
from functools import wraps
def my_decorator(func):
@wraps(func)
def wrapper(*args, **kwargs):
print("Positional Arguments (*args):", args)
print("Keyword Arguments (**kwargs):", kwargs)
result = func(*args, **kwargs)
return result
return wrapper
@my_decorator
def example_function(a, b, c=0, d=0):
print("Function Body:", a, b, c, d)
# Calling the decorated function with different arguments
example_function(1, 2)
example_function(3, 4, c=5)
Popular Example
Without Wraps
import time
import random
from functools import wraps
def timer(func):
def wrapper(*args, **kwargs):
name = wrapper.__name__
start = time.perf_counter()
result = func(*args, **kwargs)
end = time.perf_counter()
print(f"{name} took {end - start:.6f} seconds")
return result
return wrapper
@timer
def built_in_sort(data):
return sorted(data)
@timer
def bubble_sort(data):
arr = data.copy()
n = len(arr)
for i in range(n):
for j in range(0, n - i - 1):
if arr[j] > arr[j + 1]:
arr[j], arr[j + 1] = arr[j + 1], arr[j]
return arr
data = [random.randint(1, 100000) for _ in range(5000)]
built_in_sort(data)
bubble_sort(data)
Using Wraps
import time
import random
from functools import wraps
def timer(label=None):
def decorator(func):
@wraps(func)
def wrapper(*args, **kwargs):
name = label or wrapper.__name__
start = time.perf_counter()
result = func(*args, **kwargs)
end = time.perf_counter()
print(f"{name} took {end - start:.6f} seconds")
return result
return wrapper
return decorator
@timer()
def built_in_sort(data):
return sorted(data)
@timer("Custom Bubble Sort")
def bubble_sort(data):
arr = data.copy()
n = len(arr)
for i in range(n):
for j in range(0, n - i - 1):
if arr[j] > arr[j + 1]:
arr[j], arr[j + 1] = arr[j + 1], arr[j]
return arr
data = [random.randint(1, 100000) for _ in range(5000)]
built_in_sort(data)
bubble_sort(data)
The purpose of @wraps is to preserve the metadata of the original function being decorated.