Source: Rucksack Reorganization
Part 1
Take a list of characters. For each line, split the line exactly in half and find the one character that’s in both halves. Assign a-z to values 1-26 and A-Z to 27-52. Sum these values.
This one abstracted… oddly.
#[derive(Debug)]
struct Rucksack {
all: HashSet<char>,
left: HashSet<char>,
right: HashSet<char>,
}
impl Rucksack {
fn new(items: String) -> Rucksack {
let all = items.chars().collect();
let half = items.len() / 2;
let left = items.chars().take(half).collect();
let right = items.chars().skip(half).collect();
Rucksack { all, left, right }
}
}
fn rucksack_priority(c: &char) -> u32 {
match c {
'a'..='z' => (*c as u32) - ('a' as u32) + 1,
'A'..='Z' => (*c as u32) - ('A' as u32) + 27,
_ => panic!("unknown rucksack character: {:?}", c)
}
}
It makes enough sense to make the Rucksack
out of two sets since we don’t care if values are unique in either half, just if they’re unique within the entire rucksack.
The real mess of the function comes with applying a bunch of filters and set operations in sequence in Rust:
fn part1(filename: &Path) -> String {
let lines: Vec<String> = read_lines(filename);
let rucksacks: Vec<Rucksack> = lines.into_iter().map(Rucksack::new).collect();
let uniques: Vec<Vec<&char>> = rucksacks
.iter()
.map(|r| r.left.intersection(&r.right).collect())
.collect();
let priorities: Vec<Vec<u32>> = uniques
.into_iter()
.map(|ls| ls.into_iter().map(rucksack_priority).collect())
.collect();
priorities
.into_iter()
.map(|ls| ls.iter().sum::<u32>())
.sum::<u32>()
.to_string()
}
I’m not sure what to think about that. The code is clean enough I suppose, but having to specify all of the types I feel is somewhat counterintuitive.
It does work well enough though.
$ ./target/release/03-rucksackinator 1 data/03.txt
7845
took 2.813541ms
Part 2
Instead, group each set of 3 inputs. Find the one character that occurs in each of the three lines of each group. Score as before.
This isn’t actually that much different:
fn part2(filename: &Path) -> String {
let lines: Vec<String> = read_lines(filename);
let rucksacks: Vec<Rucksack> = lines.into_iter().map(Rucksack::new).collect();
let groups: Vec<&[Rucksack]> = rucksacks.chunks(3).collect();
let uniques: Vec<HashSet<char>> = groups
.into_iter()
.map(|g| {
g[0].all
.intersection(&g[1].all)
.copied()
.collect::<HashSet<char>>()
.intersection(&g[2].all)
.copied()
.collect()
})
.collect();
let priorities: Vec<Vec<u32>> = uniques
.into_iter()
.map(|ls| ls.iter().map(rucksack_priority).collect())
.collect();
priorities
.into_iter()
.map(|ls| ls.iter().sum::<u32>())
.sum::<u32>()
.to_string()
}
Mostly, instead of going through each, we have to get chunks
first, then intersect the 3 .all
sets from each chunk. I’m not a fan of that chaining. Is there a better way to do it?
Still fast though:
$ ./target/release/03-rucksackinator 2 data/03.txt
2790
took 2.230958ms