Rust

Ooof. Part 1 was easy enough, but for part two I initially went with the naive solution of trying every single seed which took more than a minute (I never really measured). Although that got me the right answer, to me that was just unacceptable.

I proceeded to try and combine all mappings into one but gave up after spending way too much time on it.

Then I had the idea that the lowest number in the end must lie at the beginning of a range somewhere. Either the start of a seed range in the beginning or the start of a range in one of the mappings. Any in-between numbers must end up with a higher result. So I considered the start points of all ranges, went through the mappings in reverse to find out if that point is actually within a seed range, and only tested those starting points.

Finally I had only 183 points to test which ran much faster (0.9ms).

[JavaScript] Well that was by far the hardest out of all of the days, part 1 was relatively fine but part 2 took me awhile of trying different things

Ended up solving it by working backwards by trying different location values and seeing if that can become a valid seed. Takes around 3 secs to compute the answer.

Link to code

// Part 1
// ======

function part1(input) {
  const split = input.split("\r\n\r\n");

  let pastValues = split[0].match(/\d+/g).map((x) => parseInt(x));
  let currentValues = [];

  for (const section of split.slice(1)) {
    for (const line of section.split("\r\n")) {
      const values = line.match(/\d+/g)?.map((x) => parseInt(x));

      if (!values) {
        continue;
      }

      const sourceStart = values[1];
      const destinationStart = values[0];
      const length = values[2];

      for (let i = 0; i < pastValues.length; i++) {
        if (
          pastValues[i] >= sourceStart &&
          pastValues[i] < sourceStart + length
        ) {
          currentValues.push(destinationStart + pastValues[i] - sourceStart);
          pastValues.splice(i, 1);
          i--;
        }
      }
    }

    for (let i = 0; i < pastValues.length; i++) {
      currentValues.push(pastValues[i]);
    }

    pastValues = [...currentValues];
    currentValues = [];
  }

  return Math.min(...pastValues);
}

// Part 2
// ======

function part2(input) {
  const split = input.split("\r\n\r\n");

  let seeds = split[0].match(/\d+/g).map((x) => parseInt(x));
  seeds = seeds
    .filter((x, i) => i % 2 == 0)
    .map((x, i) => [x, seeds[i * 2 + 1]]);

  const maps = split
    .slice(1)
    .map((x) => {
      const lines = x.split("\r\n");
      return lines
        .map((x) => x.match(/\d+/g)?.map((x) => parseInt(x)))
        .filter((x) => x);
    })
    .reverse();

  for (let i = 0; true; i++) {
    let curValue = i;

    for (const map of maps) {
      for (const line of map) {
        const sourceStart = line[1];
        const destinationStart = line[0];
        const length = line[2];

        if (
          curValue >= destinationStart &&
          curValue < destinationStart + length
        ) {
          curValue = sourceStart + curValue - destinationStart;
          break;
        }
      }
    }

    for (const [seedRangeStart, seedRangeLength] of seeds) {
      if (
        curValue >= seedRangeStart &&
        curValue < seedRangeStart + seedRangeLength
      ) {
        return i;
      }
    }
  }
}

Haskell

Not hugely proud of this one; part one would have been easier if I’d spend more time reading the question and not started on an overly-general solution, and I lost a lot of time on part two to a missing a +. More haste, less speed, eh?

import Data.List
import Data.List.Split

readInput :: String -> ([Int], [(String, [(Int, Int, Int)])])
readInput s =
  let (seedsChunk : mapChunks) = splitOn [""] $ lines s
      seeds = map read $ tail $ words $ head seedsChunk
      maps = map readMapChunk mapChunks
   in (seeds, maps)
  where
    readMapChunk (title : rows) =
      let name = head $ words title
          entries = map ((\[a, b, c] -> (a, b, c)) . map read . words) rows
       in (name, entries)

part1 (seeds, maps) =
  let f = foldl1' (flip (.)) $ map (ref . snd) maps
   in minimum $ map f seeds
  where
    ref [] x = x
    ref ((a, b, c) : rest) x =
      let i = x - b
       in if i >= 0 && i < c
            then a + i
            else ref rest x

mapRange :: [(Int, Int, Int)] -> (Int, Int) -> [(Int, Int)]
mapRange entries (start, end) =
  go start $ sortOn (\(_, b, _) -> b) entries
  where
    go i [] = [(i, end)]
    go i es@((a, b, c) : rest)
      | i > end = []
      | b > end = go i []
      | b + c <= i = go i rest
      | i < b = (i, b - 1) : go b es
      | otherwise =
          let d = min (b + c - 1) end
           in (a + i - b, a + d - b) : go (d + 1) rest

part2 (seeds, maps) =
  let seedRanges = map (\[a, b] -> (a, a + b - 1)) $ chunksOf 2 seeds
   in minimum $ map fst $ foldl' (flip mapRanges) seedRanges $ map snd maps
  where
    mapRanges m = concatMap (mapRange m)

main = do
  input <- readInput <$> readFile "input05"
  print $ part1 input
  print $ part2 input

Finally. :cries:

Part 1 was fine, I was figuring I might be able to practice classes.

Part 2 told me that nope, memory management required for you. In the end instead of calculating seeds, I resolved the whole thing down to a single mapping of seeds to locations. Then I could just sort by location ranges and try to see if they were a seed. Code is full of old parts from failed solutions but I’ve had enough of day 5, so I no longer care to clean it up.

Odin

When I read the problem description I expected the input to also be 2 digit numbers. When I looked at it I just had to say “huh.”

Second part I think you definitely have to do in reverse (edit: if you are doing a linear search for the answer), as that allows you to nope out as soon as you find a match, whereas with doing it forward you have to keep checking just in case.

Formatted code

package day5

import "core:fmt"
import "core:strings"
import "core:slice"
import "core:strconv"

Range :: struct {
    dest: int,
    src: int,
    range: int,
}

Mapper :: struct {
    ranges: []Range,
}

parse_range :: proc(s: string) -> (ret: Range) {
    rest := s

    parseLen := -1

    destOk: bool
    ret.dest, destOk = strconv.parse_int(rest, 10, &parseLen)
    rest = strings.trim_left_space(rest[parseLen:])

    srcOk: bool
    ret.src, srcOk = strconv.parse_int(rest, 10, &parseLen)
    rest = strings.trim_left_space(rest[parseLen:])

    rangeOk: bool
    ret.range, rangeOk = strconv.parse_int(rest, 10, &parseLen)

    return
}

parse_mapper :: proc(ss: []string) -> (ret: Mapper) {
    ret.ranges = make([]Range, len(ss)-1)
    for s, i in ss[1:] {
        ret.ranges[i] = parse_range(s)
    }

    return
}

parse_mappers :: proc(ss: []string) -> []Mapper {
    mapsStr := make([dynamic][]string)
    defer delete(mapsStr)

    restOfLines := ss
    isLineEmpty :: proc(s: string)->bool {return len(s)==0}

    for i, found := slice.linear_search_proc(restOfLines, isLineEmpty); 
        found; 
        i, found  = slice.linear_search_proc(restOfLines, isLineEmpty) {
        
        append(&mapsStr, restOfLines[:i])
        restOfLines = restOfLines[i+1:]
    }
    append(&mapsStr, restOfLines[:])

    return slice.mapper(mapsStr[1:], parse_mapper)
}

apply_mapper :: proc(mapper: Mapper, num: int) -> int {
    for r in mapper.ranges {
        if num >= r.src && num - r.src < r.range do return num - r.src + r.dest
    }

    return num
}

p1 :: proc(input: []string) {
    maps := parse_mappers(input)
    defer {
        for m in maps do delete(m.ranges)
        delete(maps)
    }

    restSeeds := input[0][len("seeds: "):]
    min := 0x7fffffff

    for len(restSeeds) > 0 {
        seedLen := -1
        seed, seedOk := strconv.parse_int(restSeeds, 10, &seedLen)
        restSeeds = strings.trim_left_space(restSeeds[seedLen:])

        fmt.print(seed)
        for m in maps {
            seed = apply_mapper(m, seed)
            fmt.print(" ->", seed)
        }
        fmt.println()

        if seed < min do min = seed
    }

    fmt.println(min)
}

apply_mapper_reverse :: proc(mapper: Mapper, num: int) -> int {
    for r in mapper.ranges {
        if num >= r.dest && num - r.dest < r.range do return num - r.dest + r.src
    }

    return num
}

p2 :: proc(input: []string) {
    SeedRange :: struct {
        start: int,
        len: int,
    }

    seeds := make([dynamic]SeedRange)
    restSeeds := input[0][len("seeds: "):]

    for len(restSeeds) > 0 {
        seedLen := -1
        seedS, seedSOk := strconv.parse_int(restSeeds, 10, &seedLen)
        restSeeds = strings.trim_left_space(restSeeds[seedLen:])

        seedL, seedLOk := strconv.parse_int(restSeeds, 10, &seedLen)
        restSeeds = strings.trim_left_space(restSeeds[seedLen:])

        append(&seeds, SeedRange{seedS, seedL})
    }

    maps := parse_mappers(input)
    defer {
        for m in maps do delete(m.ranges)
        delete(maps)
    }

    for i := 0; true; i += 1 {
        rseed := i
        #reverse for m in maps {
            rseed = apply_mapper_reverse(m, rseed)
        }

        found := false
        for sr in seeds {
            if rseed >= sr.start && rseed < sr.start + sr.len {
                found = true
                break
            }
        }
        if found {
            fmt.println(i)
            break
        }
    }
}

Like many others, I really didn’t enjoy this one. I particularly struggled with part 02, which ended up with me just brute forcing it and checking each seed. On my system it took over 15 minutes to run, which is truly awful. I’m open to pointers on how I could better have solved part two.

Solution in Rust 🦀

Formatted Solution on GitLab

use std::{
    env, fs,
    io::{self, BufReader, Read},
};

fn main() -> io::Result<()> {
    let args: Vec = env::args().collect();
    let filename = &args[1];
    let file1 = fs::File::open(filename)?;
    let file2 = fs::File::open(filename)?;
    let mut reader1 = BufReader::new(file1);
    let mut reader2 = BufReader::new(file2);

    println!("Part one: {}", process_part_one(&mut reader1));
    println!("Part two: {}", process_part_two(&mut reader2));
    Ok(())
}

#[derive(Debug)]
struct Map {
    lines: Vec,
}

impl Map {
    fn map_to_lines(&self, key: u32) -> u32 {
        for line in &self.lines {
            if line.in_range(key) {
                return line.map(key);
            }
        }
        key
    }
}

#[derive(Debug)]
struct MapLine {
    dest_range: u32,
    source_range: u32,
    range_length: u32,
}

impl MapLine {
    fn map(&self, key: u32) -> u32 {
        let diff = key - self.source_range;
        if self.dest_range as i64 + diff as i64 > 0 {
            return (self.dest_range as i64 + diff as i64) as u32;
        }
        key
    }

    fn in_range(&self, key: u32) -> bool {
        self.source_range <= key
            && (key as i64) < self.source_range as i64 + self.range_length as i64
    }
}

fn parse_input(reader: &amp;mut BufReader) -> (Vec, Vec<map>) {
    let mut almanac = String::new();
    reader
        .read_to_string(&amp;mut almanac)
        .expect("read successful");
    let parts: Vec&lt;&amp;str> = almanac.split("\n\n").collect();
    let (seeds, others) = parts.split_first().expect("at least one part");
    let seeds: Vec&lt;_> = seeds
        .split(": ")
        .last()
        .expect("at least one")
        .split_whitespace()
        .map(|s| s.to_string())
        .collect();
    let maps: Vec&lt;_> = others
        .iter()
        .map(|item| {
            let lines_iter = item
                .split(':')
                .last()
                .expect("exists")
                .trim()
                .split('\n')
                .map(|nums| {
                    let nums_split = nums.split_whitespace().collect::>();
                    MapLine {
                        dest_range: nums_split[0].parse().expect("is digit"),
                        source_range: nums_split[1].parse().expect("is digit"),
                        range_length: nums_split[2].parse().expect("is digit"),
                    }
                });
            Map {
                lines: lines_iter.collect(),
            }
        })
        .collect();
    (seeds, maps)
}

fn process_part_one(reader: &amp;mut BufReader) -> u32 {
    let (seeds, maps) = parse_input(reader);
    let mut res = u32::MAX;
    for seed in &amp;seeds {
        let mut val = seed.parse::().expect("is digits");
        for map in &amp;maps {
            val = map.map_to_lines(val);
        }
        res = u32::min(res, val);
    }
    res
}

fn process_part_two(reader: &amp;mut BufReader) -> u32 {
    let (seeds, maps) = parse_input(reader);
    let seed_chunks: Vec&lt;_> = seeds.chunks(2).collect();
    let mut res = u32::MAX;
    for chunk in seed_chunks {
        let range_start: u32 = chunk[0].parse().expect("is digits");
        let range_length: u32 = chunk[1].parse().expect("is digits");
        let range_end: u32 = range_start + range_length;
        for seed in range_start..range_end {
            let mut val = seed;
            for map in &amp;maps {
                val = map.map_to_lines(val);
            }
            res = u32::min(res, val);
        }
    }
    res
}

#[cfg(test)]
mod tests {
    use super::*;

    const INPUT: &amp;str = "seeds: 79 14 55 13

seed-to-soil map:
50 98 2
52 50 48

soil-to-fertilizer map:
0 15 37
37 52 2
39 0 15

fertilizer-to-water map:
49 53 8
0 11 42
42 0 7
57 7 4

water-to-light map:
88 18 7
18 25 70

light-to-temperature map:
45 77 23
81 45 19
68 64 13

temperature-to-humidity map:
0 69 1
1 0 69

humidity-to-location map:
60 56 37
56 93 4";

    #[test]
    fn test_process_part_one() {
        let input_bytes = INPUT.as_bytes();
        assert_eq!(35, process_part_one(&amp;mut BufReader::new(input_bytes)));
    }

    #[test]
    fn test_process_part_two() {
        let input_bytes = INPUT.as_bytes();
        assert_eq!(46, process_part_two(&amp;mut BufReader::new(input_bytes)));
    }
}

Nim

Woof. Part 1 was simple enough. I thought I could adapt my solution to part 2 pretty easily, just add all the values in the ranges to the starting set. Worked fine for the example, but the ranges for the actual input are too large. Ended up taking 16gb of RAM and crunching forever.

I finally abandoned my quick and dirty approach when rewriting part 2, and made some proper types and functions. Treated each range as an object, and used set operations on them. The difference operation tends to fragment the range that it’s used on, so I meant to write some code to defragment the ranges after each round of mappings. Forgot to do so, but the code ran quick enough this time anyway.

• Day 5, part 1
• Day 5, part 2 first attempt
• Day 5, part 2 rewrite

Scala3

kind of convoluted, but purely functional

import scala.collection.immutable.NumericRange.Exclusive
import math.max
import math.min

extension [A] (l: List[A])
  def chunk(pred: A => Boolean): List[List[A]] =
    def go(l: List[A], partial_acc: List[A], acc: List[List[A]]): List[List[A]] =
      l match
        case (h :: t) if pred(h) => go(t, List(), partial_acc.reverse :: acc)
        case (h :: t) => go(t, h :: partial_acc, acc)
        case _ => partial_acc.reverse :: acc
    
    go(l, List(), List()).reverse

type R = Exclusive[Long]

def intersectTranslate(r: R, c: R, t: Long): R =
    (t + max(r.start, c.start) - c.start) until (t + min(r.end, c.end) - c.start)

case class MappingEntry(from: R, to: Long)
case class Mapping(entries: List[MappingEntry], produces: String):
    def resolveRange(in: R): List[R] =
        entries.map(e => intersectTranslate(in, e.from, e.to)).filter(!_.isEmpty)

def completeEntries(a: List[MappingEntry]): List[MappingEntry] = 
    a ++ ((0L until 0L) +: a.map(_.from).sorted :+ (Long.MaxValue until Long.MaxValue)).sliding(2).flatMap{ case List(a, b) => Some(MappingEntry(a.end until b.start, a.end)); case _ => None}.toList

def parse(a: List[String], init: List[Long] => List[R]): (List[R], Map[String, Mapping]) =
    def parseEntry(s: String): MappingEntry =
        s match
            case s"$end $start $range" => MappingEntry(start.toLong until start.toLong + range.toLong, end.toLong)

    a.chunk(_ == "") match
        case List(s"seeds: $seeds") :: maps => 
            init(seeds.split(raw"\s+").map(_.toLong).toList) -> (maps.flatMap{ case s"$from-to-$to map:" :: entries => Some(from -> Mapping(completeEntries(entries.map(parseEntry)), to)); case _ => None }).toMap
        case _ => (List(), Map()).ensuring(false)

def singletons(a: List[Long]): List[R] = a.map(s => s until s + 1)
def paired(a: List[Long]): List[R] = a.grouped(2).flatMap{ case List(x, y) => Some(x until x+y); case _ => None }.toList

def chase(d: (List[R], Map[String, Mapping]), initial: String, target: String) =
    val (init, m) = d
    def go(a: List[R], s: String): List[R] =
        if trace(s) == target then a else
            val x = m(s)
            go(a.flatMap(x.resolveRange), x.produces)
    go(trace(init), initial)

def task1(a: List[String]): Long = 
    chase(parse(a, singletons), "seed", "location").min.start

def task2(a: List[String]): Long =
    chase(parse(a, paired), "seed", "location").min.start

This was interesting! So iterating through the solution space would be infeasible here and it seems we need to look for boundaries between regions and follow them to find places where a solution could occur.

Python: https://pastebin.com/8Ckx36fu

• Make a list of places where location mappings are discontinuous (0, the end of each mapping, and the number before)
• Repeat this for discontinuities in each intermediate layer
• Trace each such location to its seed, and filter by seed ranges
• Run the very minimal set of interesting seed numbers (around 2000 seeds) through the existing part1 algorithm

[Language: Lean4]

I’ll only post the actual parsing and solution. I have written some helpers (in this case particularly relevant: Quicksort) which are in other files, as is the main function. For the full code, please see my github repo.

This one also ended up quite long, because I couldn’t resist to use different types for the different things, and to have the type checker confirm that I’m combining the maps between them in the correct order.

Also, I am not 100% certain that part 2 doesn’t have any off-by-one errors. I didn’t write any unit tests for it… The answer is correct though, so I probably didn’t mess it up too horribly. Also, it is pretty fast. Part 2 takes about 1.2 milliseconds on my machine, and this is including the file parsing (but not the loading of the file).

It seems my solution is too long for a single post though, so I’ll split off part 2 and post it separately.

Edit: There was a bug in the function that checks overlaps between ranges while parsing.

structure Seed where
  id : Nat
  deriving BEq, Ord, Repr

structure Soil where
  id : Nat
  deriving BEq, Ord, Repr

structure Fertilizer where
  id : Nat
  deriving BEq, Ord, Repr

structure Water where
  id : Nat
  deriving BEq, Ord, Repr

structure Light where
  id : Nat
  deriving BEq, Ord, Repr

structure Temperature where
  id : Nat
  deriving BEq, Ord, Repr

structure Humidity where
  id : Nat
  deriving BEq, Ord, Repr

structure Location where
  id : Nat
  deriving BEq, Ord, Repr

private class NatId (α : Type) where
  fromNat : Nat → α
  toNat : α → Nat

private instance : NatId Seed where
  fromNat := Seed.mk
  toNat := Seed.id

private instance : NatId Soil where
  fromNat := Soil.mk
  toNat := Soil.id

private instance : NatId Fertilizer where
  fromNat := Fertilizer.mk
  toNat := Fertilizer.id

private instance : NatId Water where
  fromNat := Water.mk
  toNat := Water.id

private instance : NatId Light where
  fromNat := Light.mk
  toNat := Light.id

private instance : NatId Temperature where
  fromNat := Temperature.mk
  toNat := Temperature.id

private instance : NatId Humidity where
  fromNat := Humidity.mk
  toNat := Humidity.id

private instance : NatId Location where
  fromNat := Location.mk
  toNat := Location.id

private instance : Min Location where
  min a b := if Ord.compare a b == Ordering.lt then a else b

structure Mapping (α β : Type) where
  inputStart : α
  outputStart : β
  length : Nat
  deriving Repr

structure Mappings (α β : Type) where
  mappings : List $ Mapping α β
  deriving Repr

private def Mapping.apply? {α β : Type} [NatId α] [NatId β] (mapping : Mapping α β) (input : α) : Option β :=
  let input := NatId.toNat input
  let fromStart := NatId.toNat mapping.inputStart
  let toStart := NatId.toNat mapping.outputStart
  if input ≥ fromStart ∧ input < fromStart + mapping.length then
    some $ NatId.fromNat $ toStart + input - fromStart
  else
    none

private def Mappings.apply {α β : Type} [NatId α] [NatId β] (mappings : Mappings α β) (input : α) : β :=
  let applied := mappings.mappings.findSome? $ flip Mapping.apply? input
  applied.getD $ NatId.fromNat $ NatId.toNat input

structure Almanach where
  seedsToSoil : Mappings Seed Soil
  soilToFertilizer : Mappings Soil Fertilizer
  fertilizerToWater : Mappings Fertilizer Water
  waterToLight : Mappings Water Light
  lightToTemperature : Mappings Light Temperature
  temperatureToHumidity : Mappings Temperature Humidity
  humidityToLocation : Mappings Humidity Location
  deriving Repr

private def parseSeeds (input : String) : Option (List Seed) :=
  if input.startsWith "seeds: " then
    let input := input.drop 7
    let input := String.trim <$> input.split Char.isWhitespace
    let numbers := input.mapM String.toNat?
    List.map NatId.fromNat <$> numbers
  else
    none

private def parseMapping {α β : Type} [NatId α] [NatId β] (input : String) : Option $ Mapping α β := do
  let input := String.trim <$> input.split Char.isWhitespace
  let nums ← input.mapM String.toNat?
  match nums with
  | [a,b,c] => some $ {inputStart := NatId.fromNat b, outputStart := NatId.fromNat a, length := c}
  | _ => none

private def Mapping.overlap {α β : Type} [NatId α] [NatId β] (a : Mapping α β) (b : Mapping α β) : Bool :=
  let aStart := NatId.toNat $ a.inputStart
  let aEnd := aStart + a.length
  let bStart := NatId.toNat $ b.inputStart
  let bEnd := bStart + b.length
  (bStart ≥ aStart && bStart < aEnd)
   || (bEnd > aStart && bEnd ≤ aEnd)
   || (aStart ≥ bStart && aStart < bEnd)
   || (aEnd > bStart && aEnd ≤ bEnd)

private def parseMappings (α β : Type) [NatId α] [NatId β] (input : String) (header : String) : Option $ Mappings α β :=
  if input.startsWith header then
    let lines := String.trim <$> input.splitOn "\n" |> List.drop 1 |> List.filter (not ∘ String.isEmpty)
    let mappings := lines.mapM parseMapping
    let rec overlapHelper := λ (a : List $ Mapping α β) ↦ match a with
      | [] => false
      | a :: as => as.any (λ b ↦ a.overlap b) || overlapHelper as
    let mappings := mappings.filter $ not ∘ overlapHelper --make sure no ranges overlap. That would be faulty
    Mappings.mk <$> mappings
  else
   none

def parse (input : String) : Option ((List Seed) × Almanach) := do
  let blocks := input.splitOn "\n\n" |> List.filter (not ∘ String.isEmpty)
  let blocks := String.trim <$> blocks
  if let [seeds, seedToSoil, soilToFertilizer, fertilizerToWater, waterToLight, lightToTemperature, temperatureToHumidity, humidityToLocation] := blocks then
    let seeds ← parseSeeds seeds
    let seedToSoil ← parseMappings Seed Soil seedToSoil "seed-to-soil map:"
    let soilToFertilizer ← parseMappings Soil Fertilizer soilToFertilizer "soil-to-fertilizer map:"
    let fertilizerToWater ← parseMappings Fertilizer Water fertilizerToWater "fertilizer-to-water map:"
    let waterToLight ← parseMappings Water Light waterToLight "water-to-light map:"
    let lightToTemperature ← parseMappings Light Temperature lightToTemperature "light-to-temperature map:"
    let temperatureToHumidity ← parseMappings Temperature Humidity temperatureToHumidity "temperature-to-humidity map:"
    let humidityToLocation ← parseMappings Humidity Location humidityToLocation "humidity-to-location map:"
    (seeds, {
      seedsToSoil := seedToSoil
      soilToFertilizer := soilToFertilizer
      fertilizerToWater := fertilizerToWater
      waterToLight := waterToLight
      lightToTemperature := lightToTemperature
      temperatureToHumidity := temperatureToHumidity
      humidityToLocation := humidityToLocation
    : Almanach})
  else
    none

def part1 (input : ((List Seed) × Almanach)) : Option Nat :=
  let a := input.snd
  let seedToLocation  := a.humidityToLocation.apply
                      ∘ a.temperatureToHumidity.apply
                      ∘ a.lightToTemperature.apply
                      ∘ a.waterToLight.apply
                      ∘ a.fertilizerToWater.apply
                      ∘ a.soilToFertilizer.apply
                      ∘ a.seedsToSoil.apply
  let locations := input.fst.map seedToLocation
  NatId.toNat <$> locations.minimum?

Well, I can’t say much about this one. The code is ugly, horribly inefficient, and part two takes a solid half hour to run. It got the right answer though, so that’s something I suppose. I think something like nom to parse the input would be much cleaner, and there’s got to be a better way of going about part two than just brute forcing through every possible seed, but hey, it works so that’s good enough for now.

https://github.com/capitalpb/advent_of_code_2023/blob/main/src/solvers/day05.rs

#[derive(Clone, Debug)]
struct AlmanacMapEntry {
    destination_range: RangeInclusive,
    source_range: RangeInclusive,
}

#[derive(Clone, Debug)]
struct AlmanacMap {
    entries: Vec,
}

impl AlmanacMap {
    fn from(input: &str) -> AlmanacMap {
        let entries = input
            .lines()
            .skip(1)
            .map(|line| {
                let numbers = line
                    .split(' ')
                    .filter_map(|number| number.parse::().ok())
                    .collect::>();
                AlmanacMapEntry {
                    destination_range: numbers[0]..=(numbers[0] + numbers[2]),
                    source_range: numbers[1]..=(numbers[1] + numbers[2]),
                }
            })
            .collect();
        AlmanacMap { entries }
    }

    fn convert(&self, source: &u64) -> u64 {
        let entry = self
            .entries
            .iter()
            .find(|entry| entry.source_range.contains(&source));

        if let Some(entry) = entry {
            entry.destination_range.start() + (source - entry.source_range.start())
        } else {
            source.clone()
        }
    }
}

#[derive(Debug)]
struct Almanac {
    seeds: Vec,
    seed_to_soil: AlmanacMap,
    soil_to_fertilizer: AlmanacMap,
    fertilizer_to_water: AlmanacMap,
    water_to_light: AlmanacMap,
    light_to_temperature: AlmanacMap,
    temperature_to_humidity: AlmanacMap,
    humidity_to_location: AlmanacMap,
}

impl Almanac {
    fn star_one_from(input: &str) -> Almanac {
        let mut input_sections = input
            .split("\n\n")
            .map(|section| section.split_once(':').unwrap().1);

        let seeds = input_sections
            .next()
            .unwrap()
            .split_whitespace()
            .filter_map(|seed| seed.parse::().ok())
            .collect();

        let almanac_maps = input_sections.map(AlmanacMap::from).collect::>();

        Almanac {
            seeds,
            seed_to_soil: almanac_maps[0].clone(),
            soil_to_fertilizer: almanac_maps[1].clone(),
            fertilizer_to_water: almanac_maps[2].clone(),
            water_to_light: almanac_maps[3].clone(),
            light_to_temperature: almanac_maps[4].clone(),
            temperature_to_humidity: almanac_maps[5].clone(),
            humidity_to_location: almanac_maps[6].clone(),
        }
    }

    fn star_two_from(input: &str) -> Almanac {
        let mut input_sections = input
            .split("\n\n")
            .map(|section| section.split_once(':').unwrap().1);

        let seeds = input_sections
            .next()
            .unwrap()
            .split_whitespace()
            .filter_map(|seed| seed.parse::().ok())
            .collect::>()
            .chunks(2)
            .map(|chunk| (chunk[0]..(chunk[0] + chunk[1])).collect::>())
            .flatten()
            .collect::>();

        let almanac_maps = input_sections.map(AlmanacMap::from).collect::>();

        Almanac {
            seeds,
            seed_to_soil: almanac_maps[0].clone(),
            soil_to_fertilizer: almanac_maps[1].clone(),
            fertilizer_to_water: almanac_maps[2].clone(),
            water_to_light: almanac_maps[3].clone(),
            light_to_temperature: almanac_maps[4].clone(),
            temperature_to_humidity: almanac_maps[5].clone(),
            humidity_to_location: almanac_maps[6].clone(),
        }
    }
}

pub struct Day05;

impl Solver for Day05 {
    fn star_one(&self, input: &str) -> String {
        let almanac = Almanac::star_one_from(input);

        almanac
            .seeds
            .iter()
            .map(|seed| almanac.seed_to_soil.convert(seed))
            .map(|soil| almanac.soil_to_fertilizer.convert(&soil))
            .map(|fertilizer| almanac.fertilizer_to_water.convert(&fertilizer))
            .map(|water| almanac.water_to_light.convert(&water))
            .map(|light| almanac.light_to_temperature.convert(&light))
            .map(|temperature| almanac.temperature_to_humidity.convert(&temperature))
            .map(|humidity| almanac.humidity_to_location.convert(&humidity))
            .min()
            .unwrap()
            .to_string()
    }

    fn star_two(&self, input: &str) -> String {
        let almanac = Almanac::star_two_from(input);

        almanac
            .seeds
            .iter()
            .map(|seed| almanac.seed_to_soil.convert(seed))
            .map(|soil| almanac.soil_to_fertilizer.convert(&soil))
            .map(|fertilizer| almanac.fertilizer_to_water.convert(&fertilizer))
            .map(|water| almanac.water_to_light.convert(&water))
            .map(|light| almanac.light_to_temperature.convert(&light))
            .map(|temperature| almanac.temperature_to_humidity.convert(&temperature))
            .map(|humidity| almanac.humidity_to_location.convert(&humidity))
            .min()
            .unwrap()
            .to_string()
    }
}

[C]

My first approach to part 2 was to take the list of ranges, map it to a new list of (possibly split up) ranges, etc, but I realized that would take more memory and bookkeeping than I’d like. Scrapped it and rewrote it with recursion. Much cleaner and the benchmarks are still looking good! (But for how much longer?)

$ bmake bench
day01  0:00.00  1380 Kb  0+78 faults
day02  0:00.00  1660 Kb  0+82 faults
day03  0:00.00  1540 Kb  0+107 faults
day04  0:00.00  1536 Kb  0+80 faults
day05  0:00.00  1668 Kb  0+83 faults

https://github.com/sjmulder/aoc/blob/master/2023/c/day05.c

Edit: I see some people went for looping from 0 to try possible answers. Clever and short but I wanted to go for a more efficient approach.

Nim

Part 1 was really easy.
Part 2, I struggled to solve efficiently, so I just ran naive bruteforce for 5 minutes until I got the answer.
Later, I’ve rewritten my solution for Part 2. The idea is to handle ranges as ranges, check seed ranges against map ranges, transform overlaps, but keep not-overlapping parts.

Total runtime after rewrite: ~ 0.4 ms.
Today’s puzzle was nice - 8.5/10.

Code: day_05/solution.nim

Honestly this one was quite easy for me. Not so much for my computer though…

https://git.sr.ht/~aidenisik/aoc23/tree/master/item/day5

C solutions. Disclaimer, part 2 has not finished running. But it’s mostly the same code as part 1 and it works on the small sample data so it’ll be fine.

Language: Python

Github

Catching up missed days.