Day 5: Print Queue
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View all comments 3 points
Rust
While part 1 was pretty quick, part 2 took me a while to figure something out. I figured that the relation would probably be a total ordering, and obtained the actual order using topological sorting. But it turns out the relation has cycles, so the topological sort must be limited to the elements that actually occur in the lists.
Solution
use std::collections::{HashSet, HashMap, VecDeque};
fn parse_lists(input: &str) -> Vec<Vec<u32>> {
input.lines()
.map(|l| l.split(',').map(|e| e.parse().unwrap()).collect())
.collect()
}
fn parse_relation(input: String) -> (HashSet<(u32, u32)>, Vec<Vec<u32>>) {
let (ordering, lists) = input.split_once("\n\n").unwrap();
let relation = ordering.lines()
.map(|l| {
let (a, b) = l.split_once('|').unwrap();
(a.parse().unwrap(), b.parse().unwrap())
})
.collect();
(relation, parse_lists(lists))
}
fn parse_graph(input: String) -> (Vec<Vec<u32>>, Vec<Vec<u32>>) {
let (ordering, lists) = input.split_once("\n\n").unwrap();
let mut graph = Vec::new();
for l in ordering.lines() {
let (a, b) = l.split_once('|').unwrap();
let v: u32 = a.parse().unwrap();
let w: u32 = b.parse().unwrap();
let new_len = v.max(w) as usize + 1;
if new_len > graph.len() {
graph.resize(new_len, Vec::new())
}
graph[v as usize].push(w);
}
(graph, parse_lists(lists))
}
fn part1(input: String) {
let (relation, lists) = parse_relation(input);
let mut sum = 0;
for l in lists {
let mut valid = true;
for i in 0..l.len() {
for j in 0..i {
if relation.contains(&(l[i], l[j])) {
valid = false;
break
}
}
if !valid { break }
}
if valid {
sum += l[l.len() / 2];
}
}
println!("{sum}");
}
// Topological order of graph, but limited to nodes in the set `subgraph`.
// Otherwise the graph is not acyclic.
fn topological_sort(graph: &[Vec<u32>], subgraph: &HashSet<u32>) -> Vec<u32> {
let mut order = VecDeque::with_capacity(subgraph.len());
let mut marked = vec![false; graph.len()];
for &v in subgraph {
if !marked[v as usize] {
dfs(graph, subgraph, v as usize, &mut marked, &mut order)
}
}
order.into()
}
fn dfs(graph: &[Vec<u32>], subgraph: &HashSet<u32>, v: usize, marked: &mut [bool], order: &mut VecDeque<u32>) {
marked[v] = true;
for &w in graph[v].iter().filter(|v| subgraph.contains(v)) {
if !marked[w as usize] {
dfs(graph, subgraph, w as usize, marked, order);
}
}
order.push_front(v as u32);
}
fn rank(order: &[u32]) -> HashMap<u32, u32> {
order.iter().enumerate().map(|(i, x)| (*x, i as u32)).collect()
}
// Part 1 with topological sorting, which is slower
fn _part1(input: String) {
let (graph, lists) = parse_graph(input);
let mut sum = 0;
for l in lists {
let subgraph = HashSet::from_iter(l.iter().copied());
let rank = rank(&topological_sort(&graph, &subgraph));
if l.is_sorted_by_key(|x| rank[x]) {
sum += l[l.len() / 2];
}
}
println!("{sum}");
}
fn part2(input: String) {
let (graph, lists) = parse_graph(input);
let mut sum = 0;
for mut l in lists {
let subgraph = HashSet::from_iter(l.iter().copied());
let rank = rank(&topological_sort(&graph, &subgraph));
if !l.is_sorted_by_key(|x| rank[x]) {
l.sort_unstable_by_key(|x| rank[x]);
sum += l[l.len() / 2];
}
}
println!("{sum}");
}
util::aoc_main!();
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