Day 5: Print Queue
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FAQ
- What is this?: Here is a post with a large amount of details: https://programming.dev/post/6637268
- Where do I participate?: https://adventofcode.com/
- Is there a leaderboard for the community?: We have a programming.dev leaderboard with the info on how to join in this post: https://programming.dev/post/6631465
Smalltalk
parsing logic is duplicated between the two, and I probably could use part2’s logic for part 1, but yeah
part 1
day5p1: in | rules pages i j input | input := in lines. i := input indexOf: ''. rules := ((input copyFrom: 1 to: i-1) collect: [:l | (l splitOn: '|') collect: #asInteger]). pages := (input copyFrom: i+1 to: input size) collect: [:l | (l splitOn: ',') collect: #asInteger]. ^ pages sum: [ :p | (rules allSatisfy: [ :rule | i := p indexOf: (rule at: 1). j := p indexOf: (rule at: 2). (i ~= 0 & (j ~= 0)) ifTrue: [ i < j ] ifFalse: [ true ] ]) ifTrue: [p at: ((p size / 2) round: 0) ] ifFalse: [0]. ]
part 2
day5p2: in | rules pages i pnew input | input := in lines. i := input indexOf: ''. rules := ((input copyFrom: 1 to: i-1) collect: [:l | (l splitOn: '|') collect: #asInteger]). pages := (input copyFrom: i+1 to: input size) collect: [:l | (l splitOn: ',') collect: #asInteger]. ^ pages sum: [ :p | pnew := p sorted: [ :x :y | rules anySatisfy: [ :r | (r at: 1) = x and: [ (r at: 2) = y]] ]. pnew ~= p ifTrue: [ pnew at: ((pnew size / 2) round: 0) ] ifFalse: [0]. ]
Nim
Solution: sort numbers using custom rules and compare if sorted == original. Part 2 is trivial.
Runtime for both parts: 1.05 msproc parseRules(input: string): Table[int, seq[int]] = for line in input.splitLines(): let pair = line.split('|') let (a, b) = (pair[0].parseInt, pair[1].parseInt) discard result.hasKeyOrPut(a, newSeq[int]()) result[a].add b proc solve(input: string): AOCSolution[int, int] = let chunks = input.split("\n\n") let later = parseRules(chunks[0]) for line in chunks[1].splitLines(): let numbers = line.split(',').map(parseInt) let sorted = numbers.sorted(cmp = proc(a,b: int): int = if a in later and b in later[a]: -1 elif b in later and a in later[b]: 1 else: 0 ) if numbers == sorted: result.part1 += numbers[numbers.len div 2] else: result.part2 += sorted[sorted.len div 2]
Nice, compact and easy to follow. The implicit
result
object reminds me of Visual Basic.
C#
using QuickGraph; using QuickGraph.Algorithms.TopologicalSort; public class Day05 : Solver { private List<int[]> updates; private List<int[]> updates_ordered; public void Presolve(string input) { var blocks = input.Trim().Split("\n\n"); List<(int, int)> rules = new(); foreach (var line in blocks[0].Split("\n")) { var pair = line.Split('|'); rules.Add((int.Parse(pair[0]), int.Parse(pair[1]))); } updates = new(); updates_ordered = new(); foreach (var line in input.Trim().Split("\n\n")[1].Split("\n")) { var update = line.Split(',').Select(int.Parse).ToArray(); updates.Add(update); var graph = new AdjacencyGraph<int, Edge<int>>(); graph.AddVertexRange(update); graph.AddEdgeRange(rules .Where(rule => update.Contains(rule.Item1) && update.Contains(rule.Item2)) .Select(rule => new Edge<int>(rule.Item1, rule.Item2))); List<int> ordered_update = []; new TopologicalSortAlgorithm<int, Edge<int>>(graph).Compute(ordered_update); updates_ordered.Add(ordered_update.ToArray()); } } public string SolveFirst() => updates.Zip(updates_ordered) .Where(unordered_ordered => unordered_ordered.First.SequenceEqual(unordered_ordered.Second)) .Select(unordered_ordered => unordered_ordered.First) .Select(update => update[update.Length / 2]) .Sum().ToString(); public string SolveSecond() => updates.Zip(updates_ordered) .Where(unordered_ordered => !unordered_ordered.First.SequenceEqual(unordered_ordered.Second)) .Select(unordered_ordered => unordered_ordered.Second) .Select(update => update[update.Length / 2]) .Sum().ToString(); }
Oh! Sort first and then check for equality. Clever!
You’ll need to sort them anyway :)
(my first version of the first part only checked the order, without sorting).
Kotlin
Took me a while to figure out how to sort according to the rules. 🤯
fun part1(input: String): Int { val (rules, listOfNumbers) = parse(input) return listOfNumbers .filter { numbers -> numbers == sort(numbers, rules) } .sumOf { numbers -> numbers[numbers.size / 2] } } fun part2(input: String): Int { val (rules, listOfNumbers) = parse(input) return listOfNumbers .filterNot { numbers -> numbers == sort(numbers, rules) } .map { numbers -> sort(numbers, rules) } .sumOf { numbers -> numbers[numbers.size / 2] } } private fun sort(numbers: List<Int>, rules: List<Pair<Int, Int>>): List<Int> { return numbers.sortedWith { a, b -> if (rules.contains(a to b)) -1 else 1 } } private fun parse(input: String): Pair<List<Pair<Int, Int>>, List<List<Int>>> { val (rulesSection, numbersSection) = input.split("\n\n") val rules = rulesSection.lines() .mapNotNull { line -> """(\d{2})\|(\d{2})""".toRegex().matchEntire(line) } .map { match -> match.groups[1]?.value?.toInt()!! to match.groups[2]?.value?.toInt()!! } val numbers = numbersSection.lines().map { line -> line.split(',').map { it.toInt() } } return rules to numbers }
I like how clean this is
I guess adding type aliases and removing the regex from parser makes it a bit more readable.
typealias Rule = Pair<Int, Int> typealias PageNumbers = List<Int> fun part1(input: String): Int { val (rules, listOfNumbers) = parse(input) return listOfNumbers .filter { numbers -> numbers == sort(numbers, rules) } .sumOf { numbers -> numbers[numbers.size / 2] } } fun part2(input: String): Int { val (rules, listOfNumbers) = parse(input) return listOfNumbers .filterNot { numbers -> numbers == sort(numbers, rules) } .map { numbers -> sort(numbers, rules) } .sumOf { numbers -> numbers[numbers.size / 2] } } private fun sort(numbers: PageNumbers, rules: List<Rule>): PageNumbers { return numbers.sortedWith { a, b -> if (rules.contains(a to b)) -1 else 1 } } private fun parse(input: String): Pair<List<Rule>, List<PageNumbers>> { val (rulesSection, numbersSection) = input.split("\n\n") val rules = rulesSection.lines() .mapNotNull { line -> val parts = line.split('|').map { it.toInt() } if (parts.size >= 2) parts[0] to parts[1] else null } val numbers = numbersSection.lines() .map { line -> line.split(',').map { it.toInt() } } return rules to numbers }
I wasn’t being sarcastic, but yeah even better
Factor
: get-input ( -- rules updates ) "vocab:aoc-2024/05/input.txt" utf8 file-lines { "" } split1 "|" "," [ '[ [ _ split ] map ] ] bi@ bi* ; : relevant-rules ( rules update -- rules' ) '[ [ _ in? ] all? ] filter ; : compliant? ( rules update -- ? ) [ relevant-rules ] keep-under [ [ index* ] with map first2 < ] with all? ; : middle-number ( update -- n ) dup length 2 /i nth-of string>number ; : part1 ( -- n ) get-input [ compliant? ] with [ middle-number ] filter-map sum ; : compare-pages ( rules page1 page2 -- <=> ) [ 2array relevant-rules ] keep-under [ drop +eq+ ] [ first index zero? +gt+ +lt+ ? ] if-empty ; : correct-update ( rules update -- update' ) [ swapd compare-pages ] with sort-with ; : part2 ( -- n ) get-input dupd [ compliant? ] with reject [ correct-update middle-number ] with map-sum ;
Haskell
Part two was actually much easier than I thought it was!
import Control.Arrow import Data.Bool import Data.List import Data.List.Split import Data.Maybe readInput :: String -> ([(Int, Int)], [[Int]]) readInput = (readRules *** readUpdates . tail) . break null . lines where readRules = map $ (read *** read . tail) . break (== '|') readUpdates = map $ map read . splitOn "," mid = (!!) <*> ((`div` 2) . length) isSortedBy rules = (`all` rules) . match where match ps (x, y) = fromMaybe True $ (<) <$> elemIndex x ps <*> elemIndex y ps pageOrder rules = curry $ bool GT LT . (`elem` rules) main = do (rules, updates) <- readInput <$> readFile "input05" let (part1, part2) = partition (isSortedBy rules) updates mapM_ (print . sum . map mid) [part1, sortBy (pageOrder rules) <$> part2]
Dart
A bit easier than I first thought it was going to be.
I had a look at the Uiua discussion, and this one looks to be beyond my pay grade, so this will be it for today.
import 'package:collection/collection.dart'; import 'package:more/more.dart'; (int, int) solve(List<String> lines) { var parts = lines.splitAfter((e) => e == ''); var pred = SetMultimap.fromEntries(parts.first.skipLast(1).map((e) { var ps = e.split('|').map(int.parse); return MapEntry(ps.last, ps.first); })); ordering(a, b) => pred[a].contains(b) ? 1 : 0; var pageSets = parts.last.map((e) => e.split(',').map(int.parse).toList()); var partn = pageSets.partition((ps) => ps.isSorted(ordering)); return ( partn.truthy.map((e) => e[e.length ~/ 2]).sum, partn.falsey.map((e) => (e..sort(ordering))[e.length ~/ 2]).sum ); } part1(List<String> lines) => solve(lines).$1; part2(List<String> lines) => solve(lines).$2;
Uiua
Well it’s still today here, and this is how I spent my evening. It’s not pretty or maybe even good, but it works on the test data…
spoiler
Uses Kahn’s algorithm with simplifying assumptions based on the helpful nature of the data.
Data ← ⊜(□)⊸≠@\n "47|53\n97|13\n97|61\n97|47\n75|29\n61|13\n75|53\n29|13\n97|29\n53|29\n61|53\n97|53\n61|29\n47|13\n75|47\n97|75\n47|61\n75|61\n47|29\n75|13\n53|13\n\n75,47,61,53,29\n97,61,53,29,13\n75,29,13\n75,97,47,61,53\n61,13,29\n97,13,75,29,47" Rs ← ≡◇(⊜⋕⊸≠@|)▽⊸≡◇(⧻⊚⌕@|)Data Ps ← ≡⍚(⊜⋕⊸≠@,)▽⊸≡◇(¬⧻⊚⌕@|)Data NoPred ← ⊢▽:⟜(≡(=0/+⌕)⊙¤)◴♭⟜≡⊣ # Find entry without predecessors. GetLead ← ⊸(▽:⟜(≡(¬/+=))⊙¤)⟜NoPred # Remove that leading entry. Rules ← ⇌⊂⊃(⇌⊢°□⊢|≡°□↘1)[□⍢(GetLead|≠1⧻)] Rs # Repeatedly find rule without predecessors (Kaaaaaahn!). Sorted ← ⊏⍏⊗,Rules IsSorted ← /×>0≡/-◫2⊗°□: Rules MidVal ← ⊡:⟜(⌊÷ 2⧻) ⇌⊕□⊸≡IsSorted Ps # Group by whether the pages are in sort order. ≡◇(/+≡◇(MidVal Sorted)) # Find midpoints and sum.
Does this language ever look pretty? Great for signaling UFOs though :D
Ah, but the terseness of the code allows the beauty of the underlying algorithm to shine through :-)
Those unicode code points won’t use themselves.
Oh my. I just watched yernab’s video, and this becomes so much easier:
# Order is totally specified, so sort by number of predecessors, # check to see which were already sorted, then group and sum each group. Data ← ⊜(□⊜□⊸≠@\n)⊸(¬⦷"\n\n")"47|53\n97|13\n97|61\n97|47\n75|29\n61|13\n75|53\n29|13\n97|29\n53|29\n61|53\n97|53\n61|29\n47|13\n75|47\n97|75\n47|61\n75|61\n47|29\n75|13\n53|13\n\n75,47,61,53,29\n97,61,53,29,13\n75,29,13\n75,97,47,61,53\n61,13,29\n97,13,75,29,47" Rs ← ≡◇(⊜⋕⊸≠@|)°□⊢Data Ps ← ≡⍚(⊜⋕⊸≠@,)°□⊣Data ⊕(/+≡◇(⊡⌊÷2⧻.))¬≡≍⟜:≡⍚(⊏⍏/+⊞(∈Rs⊟)..).Ps
J
This is a problem where J’s biases lead one to a very different solution from most of the others. The natural representation of a directed graph in J is an adjacency matrix, and sorting is specified in terms of a permutation to apply rather than in terms of a comparator:
x /: y
(respectivelyx \: y
) determines the permutation that would puty
in ascending (descending) order, then applies that permutation tox
.data_file_name =: '5.data' lines =: cutopen fread data_file_name NB. manuals start with the first line where the index of a comma is < 5 start_of_manuals =: 1 i.~ 5 > ',' i.~"1 > lines NB. ". can't parse the | so replace it with a space edges =: ". (' ' & (2}))"1 > start_of_manuals {. lines NB. don't unbox and parse yet because they aren't all the same length manuals =: start_of_manuals }. lines max_page =: >./ , edges NB. adjacency matrix of the page partial ordering; e.i. makes identity matrix adjacency =: 1 (< edges)} e. i. >: max_page NB. ordered line is true if line is ordered according to the adjacency matrix ordered =: monad define pages =. ". > y NB. index pairs 0 <: i < j < n; box and raze to avoid array fill page_pairs =. ; (< @: (,~"0 i.)"0) i. # pages */ adjacency {~ <"1 pages {~ page_pairs ) midpoint =: ({~ (<. @: -: @: #)) @: ". @: > result1 =: +/ (ordered"0 * midpoint"0) manuals NB. toposort line yields the pages of line topologically sorted by adjacency NB. this is *not* a general topological sort but works for our restricted case: NB. we know that each individual manual will be totally ordered toposort =: monad define pages =. ". > y NB. for each page, count the pages which come after it, then sort descending pages \: +/"1 adjacency {~ <"1 pages ,"0/ pages ) NB. midpoint2 doesn't parse, but does remove trailing zeroes midpoint2 =: ({~ (<. @: -: @: #)) @: ({.~ (i. & 0)) result2 =: +/ (1 - ordered"0 manuals) * midpoint2"1 toposort"0 manuals
Rust
Real thinker. Messed around with a couple solutions before this one. The gist is to take all the pairwise comparisons given and record them for easy access in a ranking matrix.
For the sample input, this grid would look like this (I left out all the non-present integers, but it would be a 98 x 98 grid where all the empty spaces are filled with
Ordering::Equal
):13 29 47 53 61 75 97 13 = > > > > > > 29 < = > > > > > 47 < < = < < > > 53 < < > = > > > 61 < < > < = > > 75 < < < < < = > 97 < < < < < < =
I discovered this can’t be used for a total order on the actual puzzle input because there were cycles in the pairs given (see how rust changed sort implementations as of 1.81). I used
usize
for convenience (I did it withu8
for all the pair values originally, but kept having to cast over and overas usize
). Didn’t notice a performance difference, but I’m sure uses a bit more memory.Also I Liked the
simple_grid
crate a little better than thegrid
one. Will have to refactor that out at some point.solution
use std::{cmp::Ordering, fs::read_to_string}; use simple_grid::Grid; type Idx = (usize, usize); type Matrix = Grid<Ordering>; type Page = Vec<usize>; fn parse_input(input: &str) -> (Vec<Idx>, Vec<Page>) { let split: Vec<&str> = input.split("\n\n").collect(); let (pair_str, page_str) = (split[0], split[1]); let pairs = parse_pairs(pair_str); let pages = parse_pages(page_str); (pairs, pages) } fn parse_pairs(input: &str) -> Vec<Idx> { input .lines() .map(|l| { let (a, b) = l.split_once('|').unwrap(); (a.parse().unwrap(), b.parse().unwrap()) }) .collect() } fn parse_pages(input: &str) -> Vec<Page> { input .lines() .map(|l| -> Page { l.split(",") .map(|d| d.parse::<usize>().expect("invalid digit")) .collect() }) .collect() } fn create_matrix(pairs: &[Idx]) -> Matrix { let max = *pairs .iter() .flat_map(|(a, b)| [a, b]) .max() .expect("iterator is non-empty") + 1; let mut matrix = Grid::new(max, max, vec![Ordering::Equal; max * max]); for (a, b) in pairs { matrix.replace_cell((*a, *b), Ordering::Less); matrix.replace_cell((*b, *a), Ordering::Greater); } matrix } fn valid_pages(pages: &[Page], matrix: &Matrix) -> usize { pages .iter() .filter_map(|p| { if check_order(p, matrix) { Some(p[p.len() / 2]) } else { None } }) .sum() } fn fix_invalid_pages(pages: &mut [Page], matrix: &Matrix) -> usize { pages .iter_mut() .filter(|p| !check_order(p, matrix)) .map(|v| { v.sort_by(|a, b| *matrix.get((*a, *b)).unwrap()); v[v.len() / 2] }) .sum() } fn check_order(page: &[usize], matrix: &Matrix) -> bool { page.is_sorted_by(|a, b| *matrix.get((*a, *b)).unwrap() == Ordering::Less) } pub fn solve() { let input = read_to_string("inputs/day05.txt").expect("read file"); let (pairs, mut pages) = parse_input(&input); let matrix = create_matrix(&pairs); println!("Part 1: {}", valid_pages(&pages, &matrix)); println!("Part 2: {}", fix_invalid_pages(&mut pages, &matrix)); }
On github
*Edit: I did try switching to just using
std::collections::HashMap
, but it was 0.1 ms slower on average than using thesimple_grid::Grid
…Vec[idx]
access is faster maybe?I think you may have over thought it, I just applied the rules by swapping unordered pairs until it was ordered :D cool solution though
Good old bubble sort
Its called AdventOfCode, not AdventOfEfficientCode :D
Very cool approach. I didn’t think that far. I just wrote a compare function and hoped for the best.
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!();
also on github
C
I got the question so wrong - I thought a|b and b|c would imply a|c so I went and used dynamic programming to propagate indirect relations through a table.
It worked beautifully but not for the input, which doesn’t describe an absolute global ordering at all. It may well give a|c and b|c AND c|a. Nothing can be deduced then, and nothing needs to, because all required relations are directly specified.
The table works great though, the sort comparator is a simple 2D array index, so O(1).
Code
#include "common.h" #define TSZ 100 #define ASZ 32 /* tab[a][b] is -1 if a<b and 1 if a>b */ static int8_t tab[TSZ][TSZ]; static int cmp(const void *a, const void *b) { return tab[*(const int *)a][*(const int *)b]; } int main(int argc, char **argv) { char buf[128], *rest, *tok; int p1=0,p2=0, arr[ASZ],srt[ASZ], n,i, a,b; if (argc > 1) DISCARD(freopen(argv[1], "r", stdin)); while (fgets(buf, sizeof(buf), stdin)) { if (sscanf(buf, "%d|%d", &a, &b) != 2) break; assert(a>=0); assert(a<TSZ); assert(b>=0); assert(b<TSZ); tab[a][b] = -(tab[b][a] = 1); } while ((rest = fgets(buf, sizeof(buf), stdin))) { for (n=0; (tok = strsep(&rest, ",")); n++) { assert(n < (int)LEN(arr)); sscanf(tok, "%d", &arr[n]); } memcpy(srt, arr, n*sizeof(*srt)); qsort(srt, n, sizeof(*srt), cmp); *(memcmp(srt, arr, n*sizeof(*srt)) ? &p1 : &p2) += srt[n/2]; } printf("05: %d %d\n", p1, p2); return 0; }
Same, I initially also thought a|b and a|c implies a|c. However when I drew the graph of the example on paper, I suspected that all relations will be given, and coded it with that assumption, that turned out to be correct
Well, this one ended up with a surprisingly easy part 2 with how I wrote it.
Not the most computationally optimal code, but since they’re still cheap enough to run in milliseconds I’m not overly bothered.C#
class OrderComparer : IComparer<int> { Dictionary<int, List<int>> ordering; public OrderComparer(Dictionary<int, List<int>> ordering) { this.ordering = ordering; } public int Compare(int x, int y) { if (ordering.ContainsKey(x) && ordering[x].Contains(y)) return -1; return 1; } } Dictionary<int, List<int>> ordering = new Dictionary<int, List<int>>(); int[][] updates = new int[0][]; public void Input(IEnumerable<string> lines) { foreach (var pair in lines.TakeWhile(l => l.Contains('|')).Select(l => l.Split('|').Select(w => int.Parse(w)))) { if (!ordering.ContainsKey(pair.First())) ordering[pair.First()] = new List<int>(); ordering[pair.First()].Add(pair.Last()); } updates = lines.SkipWhile(s => s.Contains('|') || string.IsNullOrWhiteSpace(s)).Select(l => l.Split(',').Select(w => int.Parse(w)).ToArray()).ToArray(); } public void Part1() { int correct = 0; var comparer = new OrderComparer(ordering); foreach (var update in updates) { var ordered = update.Order(comparer); if (update.SequenceEqual(ordered)) correct += ordered.Skip(ordered.Count() / 2).First(); } Console.WriteLine($"Sum: {correct}"); } public void Part2() { int incorrect = 0; var comparer = new OrderComparer(ordering); foreach (var update in updates) { var ordered = update.Order(comparer); if (!update.SequenceEqual(ordered)) incorrect += ordered.Skip(ordered.Count() / 2).First(); } Console.WriteLine($"Sum: {incorrect}"); }
Haskell
I should probably have used
sortBy
instead of this ad-hoc selection sort.import Control.Arrow import Control.Monad import Data.Char import Data.List qualified as L import Data.Map import Data.Set import Data.Set qualified as S import Text.ParserCombinators.ReadP parse = (,) <$> (fromListWith S.union <$> parseOrder) <*> (eol *> parseUpdate) parseOrder = endBy (flip (,) <$> (S.singleton <$> parseInt <* char '|') <*> parseInt) eol parseUpdate = endBy (sepBy parseInt (char ',')) eol parseInt = read <$> munch1 isDigit eol = char '\n' verify :: Map Int (Set Int) -> [Int] -> Bool verify m = and . (zipWith fn <*> scanl (flip S.insert) S.empty) where fn a = flip S.isSubsetOf (findWithDefault S.empty a m) getMiddle = ap (!!) ((`div` 2) . length) part1 m = sum . fmap getMiddle getOrigin :: Map Int (Set Int) -> Set Int -> Int getOrigin m l = head $ L.filter (S.disjoint l . preds) (S.toList l) where preds = flip (findWithDefault S.empty) m order :: Map Int (Set Int) -> Set Int -> [Int] order m s | S.null s = [] | otherwise = h : order m (S.delete h s) where h = getOrigin m s part2 m = sum . fmap (getMiddle . order m . S.fromList) main = getContents >>= print . uncurry runParts . fst . last . readP_to_S parse runParts m = L.partition (verify m) >>> (part1 m *** part2 m)