Minimum cost to buy apples

We will use Dijkstra's algorithm to find the shortest path from the source to the target. The cost of each edge is the number of apples in that node.

class Solution:
    def minCost(self, n: int, roads: List[List[int]], appleCost: List[int], k: int) -> List[int]:
        graph = collections.defaultdict(list)
        for start, end, cost in roads:
            graph[start].append((cost, end))
            graph[end].append((cost, start))

        def dijkstra(start_city: int) -> int:
            queue = [(0, start_city)]
            visited = set()
            res = math.inf
            while queue:
                acc_cost, city = heapq.heappop(queue)
                visited.add(city)
                res = min(res, acc_cost*(k+1) + appleCost[city-1])
                for cost, next_city in graph[city]:
                    if next_city not in visited:
                        heapq.heappush(queue, (acc_cost+cost, next_city))
            return res

        return [dijkstra(city) for city in range(1, n+1)]

Time complexity: O(nlog(n))
Space complexity: O(n)