Let's practice benchmarking by comparing two approaches to squaring the elements of a NumPy array. The first approach, the slower one, uses a for loop to square each element individually, while the second approach leverages vectorization. Don't worry if this concept sounds unfamiliar—we'll discuss it later in the course.

Your task for now is the following:

1. Define two functions:
   • The first, named square_array_slow, should take a single parameter array;
   • The second, named square_array_fast, should also take the same parameter.
2. Decorate both functions with the timeit_decorator and set number to 100.