Minimum project duration
You are given a DAG of n tasks (0..n-1) as edges [u, v] meaning task u must complete before task v starts, plus a duration[i] for each task. A task can start only after all its prerequisites finish, and independent tasks run in parallel. Return the minimum total time to finish all tasks (the length of the longest weighted path through the DAG, where a node's weight is its duration). The input is guaranteed acyclic.
Implement
min_project_time(n: int, edges: list[list[int]], duration: list[int]) → intExamples
in
[3,[[0,2],[1,2]],[3,2,5]]out8What a strong answer looks like
State your approach and its time/space complexity out loud before you optimize. Handle the edge cases (empty input, duplicates, overflow), and say why you chose this over the brute force. Green tests are the floor, not the grade.
0:00 of about 35 min
solution.py
InputExpectedGot
[3,[[0,2],[1,2]],[3,2,5]]8not run yetsample