I'm doing this one in Python to get a better grasp of the language basics.
Simple as this one was, thus did I find out that Python defaults to floating point division, even when dividing integers.
Fantasy computers! Always fun. I couldn't think of a way to solve this without brute-forcing the second half, though.
This one was pretty straight-forward. I was impressed by the ability to logical and two Sets to get an intersection.
This code was really hacky, but that's what you get when you tell me I get to constrain the length of my search as well as only worry about positive integer numbers.
More fantasy computer. This was just elaborating the computer and wasn't too tricky.
Tree traversal. Building the tree is so amazingly concise in Python. I thought I might need to build a spanning tree for the second part until I realized I could find the closest overlapping node between two trees from the origin.
More fantasy computer. Adding pipes was a neat concept.
Displaying this as black on white (and illegible to me) instead of white on black slowed me down way more than it ought to.
Yet more fantasy computer. I got it into my head that input and output address modes could / should be handled by the same function and this was wrong.
This one threw me for a while. I was on the right track using division to find out if two points shared a slope relative to another point, and therefore a line. What I was not so lucky about was that if the denominator of a fraction is negative, Python turns the numerator negative instead.
More and more fantasy computer! This one was neat, but I got hung up far too long on the second part for not realizing that I was specifying the starting square in two separate spots.
Revenge of basic algebra. Harder than I wish it were :(
OK THIS ONE JUST AWESOME
This was really fiddly for me and went very poorly :(
That intcode computer is still going strong. This time I had to write an exploration algorithm, which ended up just brute-forcing a route to the nearest unknown. Not A*, but A* wasn't needed.
This solution only works for very particular constraints and isn't a general problem solver. It makes it orders of magnitude more efficient, though.