Question 1

Basic wrapper pattern

Accepted Answer

A decorator is just a function that takes another function and returns a replacement for it. Here we manually do what @ does for us: greet = shout(greet) replaces greet with wrapper. When we call greet('alice'), we're really calling wrapper('alice'), which calls the original greet and uppercases the result. Every decorator you write follows this same shape - outer function receives the original, inner wrapper does the actual work.

Question 2

@ is syntactic sugar

Accepted Answer

The @ syntax is exactly equivalent to writing add = double_result(add) right after the function definition. Python substitutes add with the wrapper, so calling add(3, 4) runs wrapper(3, 4), which computes 3+4=7 and doubles it to 14. The original add function still exists inside the closure - the wrapper just calls it and transforms the return value. Think of @ as a shorthand that makes the intent visually obvious at the definition site.

Question 3

Logging decorator output

Accepted Answer

The wrapper prints 'calling square' before it calls the original function. After the original runs and returns 25, wrapper returns that value, which gets stored in result. Then print(result) prints 25. The two print statements fire in order: the log line first, then the result. Logging decorators are one of the most common real-world uses - they let you add observability to any function without touching its body.

Question 4

Decorator that prints after the call

Accepted Answer

The wrapper calls the original function first, saves the result, then prints the log message. So 'done: cube' appears before the final print(val) outputs 27. Notice the difference from a pre-call logging decorator: here the log line comes after the function body runs but before the caller sees the return value. This post-call pattern is useful for timing decorators where you want to log after the work finishes, not before it starts.