Python decorators are a powerful feature that allows programmers to modify the behavior of a function or a class. Decorators are functions that take another function as input, modify it, and return it. In this document, we will explain a real-world example of a Python decorator.
One of the most common uses of decorators is to measure the execution time of a function. This can be useful when optimizing code or identifying bottlenecks. Here is an example of a Python decorator that measures the execution time of a function:
import time
def measure_time(func):
def wrapper(*args, **kwargs):
start_time = time.time()
result = func(*args, **kwargs)
end_time = time.time()
print("Execution time: ", end_time - start_time, " seconds")
return result
return wrapper
@measure_time
def my_function():
time.sleep(2)
print("Function executed")
my_function()
In this example, we define a decorator function called measure_time that takes a function as input. The decorator function defines a new function called wrapper that measures the execution time of the input function.
The wrapper function calls the input function using the func(*args, **kwargs) syntax, which allows us to pass any number of arguments to the input function. The wrapper function also prints the execution time of the input function using print("Execution time: ", end_time - start_time, " seconds").
Finally, we use the @measure_time syntax to apply the measure_time decorator to the my_function function. When we call my_function(), the decorator measures the execution time of the function and prints it to the console.
Python decorators are a powerful tool that can be used to modify the behavior of functions and classes. In this document, we showed a real-world example of a Python decorator that measures the execution time of a function. This is just one example of the many ways that decorators can be used in Python programming.