AdventOfCode VS AdventOfCodeCSharp

Here's an example implementation in Rust, using rayon's parallel iterators to automatically distribute the computation of a range of hashes over all available cores. It solves both parts together in around 3 seconds on my M2 MacBook Pro. Single-threaded, it takes around 25s in Rust and 35s in Python.

Here are mine: https://github.com/benediktwerner/AdventOfCode

I love doing optimizations like this but I don't really have enough time anymore to really do it. In 2020 I spent a fair amount of time writing super optimized solutions for the first 10 or so days (repo solving all those days together in 150us i.e. <1ms) but even back then, I eventually stopped since I had other things to do and it took more and more time as the days went on.

Python 3 116/125

Wow, my final solution looks almost exactly the same. Though I calculated my initial answers by hand.

That's certainly not necessary though and really not what makes most of the speed, especially for problems like today's. I don't really look at other leaderboard competitor's solutions much but at least my solutions (ranked ~20 today) are almost always completely vanilla Python (the only exception is networkx for the occasional graph problem but even that isn't really that much of a speedup if you know the common graph algorithms) and always self-contained.

Interesting approach. I guess mine could be considered a bit nicer, doing it recursively and returning the number to add to the left or right.

My priority Q/heap Dijkstra in Python runs just fine. I don't remember and can't check rn if it was instant or took a second but it definitely wasn't longer than that.

Code Here: https://github.com/Bpendragon/AdventOfCodeCSharp/blob/332e303/AdventOfCode/Solutions/Year2022/Day18-Solution.cs

C#/Csharp: Code here

rewrote it as a pair of linq oneliners (sort of, if you ignore parsing, like that's the one thing I wish C# could do better: read ints from files) https://github.com/Bpendragon/AdventOfCodeCSharp/blob/0800b/AdventOfCode/Solutions/Year2022/Day04-Solution.cs