advent-of-code VS advent-of-code

I just did simple BFS on the lava cubes for part 1. For part 2, I just did a BFS on the bounding cube. Total runtime - 500 micro seconds for both parts on my 8 years old laptop: https://github.com/SvetlinZarev/advent-of-code/blob/main/2022/aoc-day-18/src/lib.rs

My solution is pretty simple - top down DP. On each step we can do only one of two things: * open a valve and stay in current position * do not open a vale, but move to a different positions

🦀🦀🦀 RUST 🦀🦀🦀

You can see it in action here: https://github.com/SvetlinZarev/advent-of-code/blob/main/2022/aoc-day-04/src/lib.rs

Rust

Here are the results of my benchmarks, which you can also run

You can calculate the distances between the points found by each scanner. If two scanners report points with the same distance between them, then most probably they are adjacent. Runs in 4ms on my machine: https://github.com/SvetlinZarev/advent-of-code/tree/main/2021/aoc-day-19

You can copy the release profile from here https://github.com/SvetlinZarev/advent-of-code/blob/main/2021/aoc-day-25/Cargo.toml#L8 and copy that directory to enable compilation for the machine's cpu https://github.com/SvetlinZarev/advent-of-code/tree/main/2021/aoc-day-25/.cargo

I want to share my repo for whoever is interested. It contains Rust solutions for:

Mine (rust)runs for 50ms for both parts. I've used just a regular bruteforce approach, so nothing fancy. There are several things I did that reduced the execution time:

Scala using µJson. Really happy with how concise this is. I was able to parse everything into a Packet class that extends Ordered, which gives us the compare function. So once that was implemented recursively according to the rules we were given, I was able to jsut call .sorted for part 2.

Scala using jgrapht. I thought part 2 would require a different graph (similar to 2018 day 22) since the story said "to avoid needing to get out your climbing gear..." Glad that wasn't the case!

Scala. Pretty happy with how I parsed these into anonymous instances of my Monkey trait. For me part 2 wasn't hard because of the modulo trick, but because I was using mutable queues. So I had to add a reset() method to get things back the way they were before running part 2

Scala using tail recursion. Not the prettiest, but it works

Scala. Not too bad with my Point helper class. After part 1 I refactored the movements into a move helper that just takes 2 arbitrary points; the current point and the one we are moving towards. Then it was easy enough to just apply that in order each iteration for part 2.

Scala. It's ugly, but it works ¯\_(ツ)_/¯

Scala. Parsing wasn't as hard as I thought it would be using transpose and then just filtering non-alphanumeric characters. I initially parsed to a Map[Int, mutable.Stack[Char]] but then that bit me in part 2 when I would have to "reset" it (dang mutability!). So instead I parse to Map[Int, String] and just build the mutable stacks twice.

Updated version using sets instead of ranges

Scala. A little more verbose than I would like, but it works ¯\_(ツ)_/¯

Scala