Decorators allow you to modify or enhance functions or methods without changing their code. They can be used for logging, access control, and performance measurement.

Python decorators are a powerful tool that allows you to modify or enhance the behavior of functions or methods without altering their core implementation. They are implemented as higher-order functions that take another function as an argument and return a new function with added functionality. This can be particularly useful for aspects like logging, access control, and performance measurement. For example, a simple logging decorator could log the execution time of a function:

def log_execution_time(func):
    def wrapper(*args, **kwargs):
        start_time = time.time()
        result = func(*args, **kwargs)
        end_time = time.time()
        print(f'Executed {func.__name__} in {end_time - start_time} seconds')
        return result
    return wrapper

Using decorators promotes cleaner code by separating concerns, allowing you to keep your business logic focused while managing cross-cutting concerns like logging or validation elsewhere. Additionally, decorators can be stacked, meaning you can apply multiple decorators to a single function, further enhancing its behavior. By leveraging decorators effectively, you can improve code organization and maintainability.