Day 6: Guard Gallivant
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Python
Part 1: Simulate the guard’s walk, keeping track of visited positions
Part 2: Semi brute-force. Try to place an obstacle at every valid position in the guard’s original path and see if it leads to a loop.
import os from collections import defaultdict # paths here = os.path.dirname(os.path.abspath(__file__)) filepath = os.path.join(here, 'input.txt') # read input with open(filepath, mode='r', encoding='utf8') as f: data = f.read() rows = data.splitlines() # bounds m = len(rows) n = len(rows[0]) # directions following 90 degree clockwise turns # up, right, down, left DIRECTIONS = [(-1, 0), (0, 1), (1, 0), (0, -1)] # find position of guard guard_i, guard_j = -1, -1 for i in range(m): for j in range(n): if rows[i][j] == '^': guard_i, guard_j = i, j break if guard_i != -1: break def part1(guard_i, guard_j): # keep track of visited positions visited = set() visited.add((guard_i, guard_j)) dir_idx = 0 # current direction index # loop while guard is in map while True: delta_i, delta_j = DIRECTIONS[dir_idx] next_gi, next_gj = guard_i + delta_i, guard_j + delta_j # next pos # if out of bounds, we are done if not (0 <= next_gi < m) or not (0 <= next_gj < n): break # change direction when obstacle encountered if rows[next_gi][next_gj] == "#": dir_idx = (dir_idx + 1) % 4 continue # update position and visited guard_i, guard_j = next_gi, next_gj visited.add((guard_i, guard_j)) print(f"{len(visited)=}") def part2(guard_i, guard_j): # keep track of visited positions visited = set() visited.add((guard_i, guard_j)) dir_idx = 0 # current direction index loops = 0 # loops encountered # walk through the path while True: delta_i, delta_j = DIRECTIONS[dir_idx] next_gi, next_gj = guard_i + delta_i, guard_j + delta_j # next pos # if out of bounds, we are done if not (0 <= next_gi < m) or not (0 <= next_gj < n): break # change direction when obstacle encountered if rows[next_gi][next_gj] == "#": dir_idx = (dir_idx + 1) % 4 continue # if a position is not already in path, # put a obstacle there and see if guard will loop if (next_gi, next_gj) not in visited and willLoop(guard_i, guard_j, dir_idx): loops += 1 # update position and visited guard_i, guard_j = next_gi, next_gj visited.add((guard_i, guard_j)) print(f"{loops=}") # used in part 2 # returns whether placing an obstacle on next pos causes a loop or not def willLoop(guard_i, guard_j, dir_idx) -> bool: # obstacle pos obs_i, obs_j = guard_i + DIRECTIONS[dir_idx][0], guard_j + DIRECTIONS[dir_idx][1] # keep track of visited pos and the direction of travel visited: defaultdict[tuple[int, int], list[int]] = defaultdict(list) visited[(guard_i, guard_j)].append(dir_idx) # walk until guard exits map or loops while True: delta_i, delta_j = DIRECTIONS[dir_idx] next_gi, next_gj = guard_i + delta_i, guard_j + delta_j # next pos # if out of bounds, no loop if not (0 <= next_gi < m) or not (0 <= next_gj < n): return False # change direction when obstacle encountered if rows[next_gi][next_gj] == "#" or (next_gi == obs_i and next_gj == obs_j): dir_idx = (dir_idx + 1) % 4 continue # we are looping if we encounter a visited pos in a visited direction if (next_gi, next_gj) in visited and dir_idx in visited[(next_gi, next_gj)]: return True # update position and visited guard_i, guard_j = next_gi, next_gj visited[(guard_i, guard_j)].append(dir_idx) part1(guard_i, guard_j) part2(guard_i, guard_j)
How long did brute force take? Mine was 9s on an m1 with rust.
My rust code ran in 6s on my phone (Samsung A35 running under Termux). When I’m back at a computer it’d be interesting to compare times properly.
About 15-20 seconds, not too bad.
I got mine down to 3s, but it wasn’t a very smart loop detection. All I did was count steps and stop after 10000. The 9 second run was 100000 steps, which is obviously a bit excessive.
Does save iterating over the list of past visits, so probably a good shortcut.
I did a similar approach (place obstacles on guards path). Takes about
80s10-15s in 11th Gen Intel® Core™ i7-11800H. Motivated by the code above, I also restricted the search to start right before the obstacle rather than the whole path which took it down from 80s to 10-15sThat’s about how long it takes for my python solution to complete.
How did you detect loops? I just ran for 100000 steps to see if I escaped, got my time down to 3s by doing only 10000 steps.
I added each visited position/direction to a set, and when a ‘state’ is reached again you have entered a loop:
v = set() while t[g.r][g.c] != 'X': state = (g.r, g.c, g.d) if state in v: acc += 1 break v.add(state) g.move(t)
You can view my full solution here.
Not who you asked but: I save coordinates and direction into a vector each time the guard faces a #. Also every time the guard faces a #, I check if the position exists in the vector, if true, it’s an infinite loop. 78ms rust aolution.
That’s probably quite optimal, compared with checking every state in the path, or running off a fixed number of steps