The Power of Doing Less: Decorators and the Art of Lazy Evaluation in Python

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Python’s decorators are a powerful tool that can help you write more efficient and expressive code. But did you know they can also be used to implement lazy evaluation?

In this article, we’ll explore how decorators can make your Python programs more lazy and efficient.

Lazy evaluation is a programming technique where the evaluation of an expression is delayed until its value is needed. This can be especially useful when working with large or infinite data sets, as it can help reduce memory usage and improve performance.

One way to implement lazy evaluation in Python is by using decorators. Decorators are a way to wrap a function with additional functionality, without modifying the function’s source code.

Here’s a simple example of a decorator that can make a function lazy:

def lazy(func):
    def wrapper(*args, **kwargs):
        return lambda: func(*args, **kwargs)
    return wrapper

@lazy
def square(x):
    return x * x

# Now, calling square(4) doesn't actually compute the result
# until we access it
lazy_square = square(4)
print(lazy_square()) # Output: 16

In this example, the lazy decorator wraps the square function with a new function that returns a lambda. This means that the…