DEV Community

Abhishek Chaudhary
Abhishek Chaudhary

Posted on

Network Delay Time

You are given a network of n nodes, labeled from 1 to n. You are also given times, a list of travel times as directed edges times[i] = (ui, vi, wi), where ui is the source node, vi is the target node, and wi is the time it takes for a signal to travel from source to target.

We will send a signal from a given node k. Return the minimum time it takes for all the n nodes to receive the signal. If it is impossible for all the n nodes to receive the signal, return -1.

Example 1:

Input: times = [[2,1,1],[2,3,1],[3,4,1]], n = 4, k = 2
Output: 2

Example 2:

Input: times = [[1,2,1]], n = 2, k = 1
Output: 1

Example 3:

Input: times = [[1,2,1]], n = 2, k = 2
Output: -1

Constraints:

  • 1 <= k <= n <= 100
  • 1 <= times.length <= 6000
  • times[i].length == 3
  • 1 <= ui, vi <= n
  • ui != vi
  • 0 <= wi <= 100
  • All the pairs (ui, vi) are unique. (i.e., no multiple edges.)

SOLUTION:

class Solution:
    def networkDelayTime(self, times: List[List[int]], n: int, k: int) -> int:
        dist = [float('inf')] * n
        dist[k - 1] = 0
        for i in range(n - 1):
            for a, b, d in times:
                if dist[b - 1] > dist[a - 1] + d:
                    dist[b - 1] = dist[a - 1] + d
        delay = max(dist)
        if delay == float('inf'):
            return -1
        return delay
Enter fullscreen mode Exit fullscreen mode

AWS GenAI LIVE image

Real challenges. Real solutions. Real talk.

From technical discussions to philosophical debates, AWS and AWS Partners examine the impact and evolution of gen AI.

Learn more

Top comments (0)

AWS GenAI LIVE image

How is generative AI increasing efficiency?

Join AWS GenAI LIVE! to find out how gen AI is reshaping productivity, streamlining processes, and driving innovation.

Learn more

👋 Kindness is contagious

Please leave a ❤️ or a friendly comment on this post if you found it helpful!

Okay