Haskell

It’s more complicated than it needs to be, could’ve done the first part just like the second.
Also it takes one second (!) to run it .-.

import Data.Maybe as Maybe
import Data.List as List
import Control.Arrow hiding (first, second)

parseRule :: String -> (Int, Int)
parseRule s = (read . take 2 &&& read . drop 3) s

replace t r c = if t == c then r else c

parse :: String -> ([(Int, Int)], [[Int]])
parse s = (map parseRule rules, map (map read . words) updates)
        where
                rules = takeWhile (/= "") . lines $ s
                updates = init . map (map (replace ',' ' ')) . drop 1 . dropWhile (/= "") . lines $ s

validRule (pairLeft, pairRight) (ruleLeft, ruleRight)
        | pairLeft == ruleRight && pairRight == ruleLeft = False
        | otherwise = True

validatePair rs p = all (validRule p) rs

validateUpdate rs u = all (validatePair rs) pairs
        where 
                pairs = List.concatMap (\ t -> map (head t, ) (tail t)) . filter (length >>> (> 1)) . tails $ u

middleElement :: [a] -> a
middleElement us = (us !!) $ (length us `div` 2)

part1 (rs, us) = sum . map (middleElement) . filter (validateUpdate rs) $ us

insertOrderly rs i is = insertOrderly' frontRules i is
        where
                frontRules = filter (((== i) . fst)) rs

insertOrderly' _  i [] = [i]
insertOrderly' rs i (i':is)
        | any (snd >>> (== i')) rs = i : i' : is
        | otherwise = i' : insertOrderly' rs i is

part2 (rs, us) = sum . map middleElement . Maybe.mapMaybe ((orderUpdate &&& id) >>> \ p -> if (fst p /= snd p) then Just $ fst p else Nothing) $ us
        where
                orderUpdate = foldr (insertOrderly rs) []

main = getContents >>= print . (part1 &&& part2) . parse

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();
}

Nim

Solution: sort numbers using custom rules and compare if sorted == original. Part 2 is trivial.
Runtime for both parts: 1.05 ms

proc 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]

Codeberg repo

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
}

Dart

A bit easier than I first thought it was going to be. I might try it in Uiua later now I’ve got my head around it.

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 ret1 = 0, ret2 = 0;
  for (var pages in pageSets) {
    if (pages.isSorted(ordering)) {
      ret1 += pages[pages.length ~/ 2];
    } else {
      pages.sort(ordering);
      ret2 += pages[pages.length ~/ 2];
    }
  }
  return (ret1, ret2);
}

part1(List<String> lines) => solve(lines).$1;
part2(List<String> lines) => solve(lines).$2;

Python

sort using a compare function

from math import floor
from pathlib import Path
from functools import cmp_to_key
cwd = Path(__file__).parent

def parse_protocol(path):

  with path.open("r") as fp:
    data = fp.read().splitlines()

  rules = data[:data.index('')]
  page_to_rule = {r.split('|')[0]:[] for r in rules}
  [page_to_rule[r.split('|')[0]].append(r.split('|')[1]) for r in rules]

  updates = list(map(lambda x: x.split(','), data[data.index('')+1:]))

  return page_to_rule, updates

def sort_pages(pages, page_to_rule):

  compare_pages = lambda page1, page2:\
    0 if page1 not in page_to_rule or page2 not in page_to_rule[page1] else -1

  return sorted(pages, key = cmp_to_key(compare_pages))

def solve_problem(file_name, fix):

  page_to_rule, updates = parse_protocol(Path(cwd, file_name))

  to_print = [temp_p[int(floor(len(pages)/2))] for pages in updates
              if (not fix and (temp_p:=pages) == sort_pages(pages, page_to_rule))
              or (fix and (temp_p:=sort_pages(pages, page_to_rule)) != pages)]

  return sum(map(int,to_print))

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).

#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;
}

https://github.com/sjmulder/aoc/blob/master/2024/c/day05.c

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 (respectively x \: y) determines the permutation that would put y in ascending (descending) order, then applies that permutation to x.

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

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 ;

on GitHub

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 with u8 for all the pair values originally, but kept having to cast over and over as 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 the grid one. Will have to refactor that out at some point.

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 the simple_grid::Grid… Vec[idx] access is faster maybe?

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.

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

Python

Also took advantage of cmp_to_key.

from functools import cmp_to_key
from pathlib import Path


def parse_input(input: str) -> tuple[dict[int, list[int]], list[list[int]]]:
    rules, updates = tuple(input.strip().split("\n\n")[:2])
    order = {}
    for entry in rules.splitlines():
        values = entry.split("|")
        order.setdefault(int(values[0]), []).append(int(values[1]))
    updates = [[int(v) for v in u.split(",")] for u in updates.splitlines()]
    return (order, updates)


def is_ordered(update: list[int], order: dict[int, list[int]]) -> bool:
    return update == sorted(
        update, key=cmp_to_key(lambda a, b: 1 if a in order.setdefault(b, []) else -1)
    )


def part_one(input: str) -> int:
    order, updates = parse_input(input)
    return sum([u[len(u) // 2] for u in (u for u in updates if is_ordered(u, order))])


def part_two(input: str) -> int:
    order, updates = parse_input(input)
    return sum(
        [
            sorted(u, key=cmp_to_key(lambda a, b: 1 if a in order[b] else -1))[
                len(u) // 2
            ]
            for u in (u for u in updates if not is_ordered(u, order))
        ]
    )


if __name__ == "__main__":
    input = Path("input").read_text("utf-8")
    print(part_one(input))
    print(part_two(input))

Go

Using a map to store u|v relations. Part 2 sorting with a custom compare function worked very nicely

func main() {
	file, _ := os.Open("input.txt")
	defer file.Close()
	scanner := bufio.NewScanner(file)

	mapPages := make(map[string][]string)
	rulesSection := true
	middleSumOk := 0
	middleSumNotOk := 0

	for scanner.Scan() {
		line := scanner.Text()
		if line == "" {
			rulesSection = false
			continue
		}

		if rulesSection {
			parts := strings.Split(line, "|")
			u, v := parts[0], parts[1]
			mapPages[u] = append(mapPages[u], v)
		} else {
			update := strings.Split(line, ",")
			isOk := true

			for i := 1; i < len(update); i++ {
				u, v := update[i-1], update[i]
				if !slices.Contains(mapPages[u], v) {
					isOk = false
					break
				}
			}

			middlePos := len(update) / 2
			if isOk {
				middlePage, _ := strconv.Atoi(update[middlePos])
				middleSumOk += middlePage
			} else {
				slices.SortFunc(update, func(u, v string) int {
					if slices.Contains(mapPages[u], v) {
						return -1
					} else if slices.Contains(mapPages[v], u) {
						return 1
					}
					return 0
				})
				middlePage, _ := strconv.Atoi(update[middlePos])
				middleSumNotOk += middlePage
			}
		}
	}

	fmt.Println("Part 1:", middleSumOk)
	fmt.Println("Part 2:", middleSumNotOk)
}

I was very much unhappy because my previous implementation took 1 second to execute and trashed through 2GB RAM in the process of doing so, I sat down again with some inspiration about the sorting approach.
I am very much happy now, the profiler tells me that most of time is spend in the parsing functions now.

I am also grateful for everyone else doing haskell, this way I learned about Arrays, Bifunctors and Arrows which (I think) improved my code a lot.

Haskell

import Control.Arrow hiding (first, second)

import Data.Map (Map)
import Data.Set (Set)
import Data.Bifunctor

import qualified Data.Maybe as Maybe
import qualified Data.List as List
import qualified Data.Map as Map
import qualified Data.Set as Set
import qualified Data.Ord as Ord


parseRule :: String -> (Int, Int)
parseRule s = (read . take 2 &&& read . drop 3) s

replace t r c = if t == c then r else c

parse :: String -> (Map Int (Set Int), [[Int]])
parse s = (map parseRule >>> buildRuleMap $ rules, map (map read . words) updates)
        where
                rules = takeWhile (/= "") . lines $ s
                updates = init . map (map (replace ',' ' ')) . drop 1 . dropWhile (/= "") . lines $ s

middleElement :: [a] -> a
middleElement us = (us !!) $ (length us `div` 2)

ruleGroup :: Eq a => (a, b) -> (a, b') -> Bool
ruleGroup = curry (uncurry (==) <<< fst *** fst)

buildRuleMap :: [(Int, Int)] -> Map Int (Set Int)
buildRuleMap rs = List.sortOn fst
        >>> List.groupBy ruleGroup 
        >>> map ((fst . head) &&& map snd) 
        >>> map (second Set.fromList) 
        >>> Map.fromList 
        $ rs

elementSort :: Map Int (Set Int) -> Int -> Int -> Ordering 
elementSort rs a b
        | Maybe.maybe False (Set.member b) (rs Map.!? a) = LT
        | Maybe.maybe False (Set.member a) (rs Map.!? b) = GT
        | otherwise = EQ

isOrdered rs u = (List.sortBy (elementSort rs) u) == u

part1 (rs, us) = filter (isOrdered rs)
        >>> map middleElement
        >>> sum
        $ us
part2 (rs, us) = filter (isOrdered rs >>> not)
        >>> map (List.sortBy (elementSort rs))
        >>> map middleElement
        >>> sum
        $ us

main = getContents >>= print . (part1 &&& part2) . parse

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)