<p>You are given an integer <code>n</code> and a 2D integer array <code>queries</code>.</p>

<p>There are <code>n</code> cities numbered from <code>0</code> to <code>n - 1</code>. Initially, there is a <strong>unidirectional</strong> road from city <code>i</code> to city <code>i + 1</code> for all <code>0 &lt;= i &lt; n - 1</code>.</p>

<p><code>queries[i] = [u<sub>i</sub>, v<sub>i</sub>]</code> represents the addition of a new <strong>unidirectional</strong> road from city <code>u<sub>i</sub></code> to city <code>v<sub>i</sub></code>. After each query, you need to find the <strong>length</strong> of the <strong>shortest path</strong> from city <code>0</code> to city <code>n - 1</code>.</p>

<p>Return an array <code>answer</code> where for each <code>i</code> in the range <code>[0, queries.length - 1]</code>, <code>answer[i]</code> is the <em>length of the shortest path</em> from city <code>0</code> to city <code>n - 1</code> after processing the <strong>first </strong><code>i + 1</code> queries.</p>

<p>&nbsp;</p>
<p><strong class="example">Example 1:</strong></p>

<div class="example-block">
<p><strong>Input:</strong> <span class="example-io">n = 5, queries = [[2,4],[0,2],[0,4]]</span></p>

<p><strong>Output:</strong> <span class="example-io">[3,2,1]</span></p>

<p><strong>Explanation: </strong></p>

<p><img alt="" src="https://assets.leetcode.com/uploads/2024/06/28/image8.jpg" style="width: 350px; height: 60px;" /></p>

<p>After the addition of the road from 2 to 4, the length of the shortest path from 0 to 4 is 3.</p>

<p><img alt="" src="https://assets.leetcode.com/uploads/2024/06/28/image9.jpg" style="width: 350px; height: 60px;" /></p>

<p>After the addition of the road from 0 to 2, the length of the shortest path from 0 to 4 is 2.</p>

<p><img alt="" src="https://assets.leetcode.com/uploads/2024/06/28/image10.jpg" style="width: 350px; height: 96px;" /></p>

<p>After the addition of the road from 0 to 4, the length of the shortest path from 0 to 4 is 1.</p>
</div>

<p><strong class="example">Example 2:</strong></p>

<div class="example-block">
<p><strong>Input:</strong> <span class="example-io">n = 4, queries = [[0,3],[0,2]]</span></p>

<p><strong>Output:</strong> <span class="example-io">[1,1]</span></p>

<p><strong>Explanation:</strong></p>

<p><img alt="" src="https://assets.leetcode.com/uploads/2024/06/28/image11.jpg" style="width: 300px; height: 70px;" /></p>

<p>After the addition of the road from 0 to 3, the length of the shortest path from 0 to 3 is 1.</p>

<p><img alt="" src="https://assets.leetcode.com/uploads/2024/06/28/image12.jpg" style="width: 300px; height: 70px;" /></p>

<p>After the addition of the road from 0 to 2, the length of the shortest path remains 1.</p>
</div>

<p>&nbsp;</p>
<p><strong>Constraints:</strong></p>

<ul>
	<li><code>3 &lt;= n &lt;= 500</code></li>
	<li><code>1 &lt;= queries.length &lt;= 500</code></li>
	<li><code>queries[i].length == 2</code></li>
	<li><code>0 &lt;= queries[i][0] &lt; queries[i][1] &lt; n</code></li>
	<li><code>1 &lt; queries[i][1] - queries[i][0]</code></li>
	<li>There are no repeated roads among the queries.</li>
</ul>

from collections import defaultdict

class Solution:
    def __init__(self):
        self.adj_list = defaultdict(list)

    def shortestDistanceAfterQueries(self, n: int, queries: List[List[int]]) -> List[int]:
        self.edge_list_to_adj_list(queries, n)
        # print(self.adj_list)
        result = []
        for edge in queries:
            u = edge[0]
            v = edge[1]
            self.adj_list[u].append(v)
            # print(self.adj_list)
            shortest_paths = self.dijkstra(self.adj_list, 0, n)
            # print(shortest_paths)
            result.append(shortest_paths[n-1])
        # print(result)
        return result

    def edge_list_to_adj_list(self, edge_list, n):
        for i in range(n - 1):
            self.adj_list[i].append(i + 1)

    def dijkstra(self, graph, start, n):
        priority_queue = []
        shortest_paths = {node: float('inf') for node in graph}
        shortest_paths[n-1] = float('inf')
        # print(shortest_paths)
        shortest_paths[start] = 0
        priority_queue = [(0, start)]
        while priority_queue:
            current_distance, current_node = heapq.heappop(priority_queue)
            # print(current_distance, current_node)
            if current_distance > shortest_paths[current_node]:
                continue
            for neighbor in graph[current_node]:
                # print("neighbor", neighbor)
                distance = current_distance + 1
                # print(current_node, neighbor, "distance", distance)
                if distance < shortest_paths[neighbor]:
                    shortest_paths[neighbor] = distance
                    heapq.heappush(priority_queue, (distance, neighbor))
        return shortest_paths

2432