# First puzzle

In this puzzle, we need to find the person (called Aunt Sue) who send a package. From a package that person sent before, we can infer the following six characteristics: children, cats, goldfish, trees, cars, perfumes, Samoyeds, Pomeranians, Akitas and Vizslas. Those characteristics are represented as integers. The puzzle input is a set of 500 people and some characteristics of each of them. For example, the first person we know: children:2 but for the second person, we know only: cats:0 and goldfish:2. The puzzle solution is to find the index of the person who sends the previous package.

As usual, we need to do some input parsing:

This problem looks simple, we create a distance from the inferred characteristics to the actual people data and find the minimum! Not so easy, I tried it, and it didn’t work even when just ignore the characteristics I didn’t know about to calculate the distance on just the data I have. It was time to look for help. Google had the answer; the trick is that only one person has all the known characteristics equal to the inferred one. That was a real simplification:

# Second puzzle

For the second puzzle, the some characteristics matching is not equal but greater than or fewer than:

- cats and trees => greater than.
- Pomeranians and goldfish => fewer than.

To accommodate the change, we need to change our “distance” function from a forAll to a by-characteristic mapping. The solution of the puzzle continue to be the person index, but using this characteristic-specific matching:

You can find this code along with my input and puzzle answers at here.