Leetcode #636: Exclusive Time of Functions
In this guide, we solve Leetcode #636 Exclusive Time of Functions in Python and focus on the core idea that makes the solution efficient.
You will see the intuition, the step-by-step method, and a clean Python implementation you can use in interviews.
Problem Statement
On a single-threaded CPU, we execute a program containing n functions. Each function has a unique ID between 0 and n-1.
Quick Facts
- Difficulty: Medium
- Premium: No
- Tags: Stack, Array
Intuition
The problem has a natural nested or last-in-first-out structure.
A stack lets us resolve matches in the correct order as we scan.
Approach
Push items as they appear and pop when you can finalize a decision.
The stack captures the unresolved part of the input.
Steps:
- Push elements as you scan.
- Pop when a rule or match is satisfied.
- Use the stack to compute results.
Example
Input: n = 2, logs = ["0:start:0","1:start:2","1:end:5","0:end:6"]
Output: [3,4]
Explanation:
Function 0 starts at the beginning of time 0, then it executes 2 for units of time and reaches the end of time 1.
Function 1 starts at the beginning of time 2, executes for 4 units of time, and ends at the end of time 5.
Function 0 resumes execution at the beginning of time 6 and executes for 1 unit of time.
So function 0 spends 2 + 1 = 3 units of total time executing, and function 1 spends 4 units of total time executing.
Python Solution
class Solution:
def exclusiveTime(self, n: int, logs: List[str]) -> List[int]:
stk = []
ans = [0] * n
pre = 0
for log in logs:
i, op, t = log.split(":")
i, cur = int(i), int(t)
if op[0] == "s":
if stk:
ans[stk[-1]] += cur - pre
stk.append(i)
pre = cur
else:
ans[stk.pop()] += cur - pre + 1
pre = cur + 1
return ans
Complexity
The time complexity is , and the space complexity is . The space complexity is .
Edge Cases and Pitfalls
Watch for boundary values, empty inputs, and duplicate values where applicable. If the problem involves ordering or constraints, confirm the invariant is preserved at every step.
Summary
This Python solution focuses on the essential structure of the problem and keeps the implementation interview-friendly while meeting the constraints.