Minimum cost to reach city with discounts

We will use Dijkstra's algorithm to solve this problem. We will create a graph with the cities as the nodes and the edges as the roads. We will then use Dijkstra's algorithm to find the shortest path from the source city to the destination city. We will return the cost of the shortest path.

class Solution:
    def minimumCost(self, n: int, highways: List[List[int]], discounts: int) -> int:
        graph = collections.defaultdict(list)
        for s, d, w in highways:
            graph[s].append((d, w))
            graph[d].append((s, w))

        visited = {}
        heap = [(0, 0, discounts)]
        while heap:
            cur_cost, cur, cur_discount = heapq.heappop(heap)

            if cur in visited and visited[cur] >= cur_discount:
                continue

            if cur == n-1:
                return cur_cost

            visited[cur] = cur_discount
            for neighbor, cost in graph[cur]:
                if neighbor in visited:
                    continue

                if cur_discount > 0:    # apply discount
                    heapq.heappush(heap, (cur_cost+cost//2, neighbor, cur_discount-1))

                heapq.heappush(heap, (cur_cost + cost, neighbor, cur_discount))

        return -1  

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