Leetcode #2637: Promise Time Limit
In this guide, we solve Leetcode #2637 Promise Time Limit 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
Given an asynchronous function fn and a time t in milliseconds, return a new time limited version of the input function. fn takes arguments provided to the time limited function.
Quick Facts
- Difficulty: Medium
- Premium: No
- Tags: JavaScript
Intuition
The constraints allow a direct scan that keeps only the essential state.
By translating the requirements into a clean loop, the logic stays easy to reason about.
Approach
Iterate through the data once, updating the state needed to compute the answer.
Return the final state after the traversal is complete.
Steps:
- Parse the input.
- Iterate and update state.
- Return the computed answer.
Example
Input:
fn = async (n) => {
await new Promise(res => setTimeout(res, 100));
return n * n;
}
inputs = [5]
t = 50
Output: {"rejected":"Time Limit Exceeded","time":50}
Explanation:
const limited = timeLimit(fn, t)
const start = performance.now()
let result;
try {
const res = await limited(...inputs)
result = {"resolved": res, "time": Math.floor(performance.now() - start)};
} catch (err) {
result = {"rejected": err, "time": Math.floor(performance.now() - start)};
}
console.log(result) // Output
The provided function is set to resolve after 100ms. However, the time limit is set to 50ms. It rejects at t=50ms because the time limit was reached.
Python Solution
# TODO: add Python solution
Complexity
The time complexity is O(n). The space complexity is O(1) to O(n).
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.