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import heapq
grid = [[int(x) for x in l] for l in open("./input").read().strip().split("\n")]
def in_bounds(c):
x, y = c
return x >= 0 and y >= 0 and y < len(grid) and x < len(grid[y])
def next_steps(path):
sx, sy = path[0]
for c in [(sx + 1, sy), (sx - 1, sy), (sx, sy + 1), (sx, sy - 1)]:
if c not in path and in_bounds(c):
yield c
def step_path(path):
for c in next_steps(path):
yield [c] + path
def total_risk(path):
acc = 0
for x, y in path:
if (x, y) == (0, 0):
continue
risk = grid[y][x]
acc += risk
return acc
def manhattan(a, b):
dx = abs(a[0] - b[0])
dy = abs(a[1] - b[1])
return dx + dy
def heuristic(path):
return total_risk(path) - manhattan(path[0], (len(grid), len(grid[0])))
class HeapItem:
def __init__(self, path):
self.heur = heuristic(path)
self.path = path
def __lt__(self, other):
return self.heur < other.heur
def find_path(start):
q = []
visited = set()
heapq.heappush(q, HeapItem([start]))
while True:
path = heapq.heappop(q).path
if path[0] == (len(grid) - 1, len(grid[0]) - 1):
return path
if path[0] in visited:
continue
visited.add(path[0])
for new in step_path(path):
heapq.heappush(q, HeapItem(new))
path = find_path((0, 0))
print(path)
print(total_risk(path))
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