Leetcode #2869: Minimum Operations to Collect Elements
In this guide, we solve Leetcode #2869 Minimum Operations to Collect Elements 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
You are given an array nums of positive integers and an integer k. In one operation, you can remove the last element of the array and add it to your collection.
Quick Facts
- Difficulty: Easy
- Premium: No
- Tags: Bit Manipulation, Array, Hash Table
Intuition
Fast membership checks and value lookups are the heart of this problem, which makes a hash map the natural choice.
By storing what we have already seen (or counts/indexes), we can answer the question in one pass without backtracking.
Approach
Scan the input once, using the map to detect when the condition is satisfied and to update state as you go.
This keeps the solution linear while remaining easy to explain in an interview setting.
Steps:
- Initialize a hash map for seen items or counts.
- Iterate through the input, querying/updating the map.
- Return the first valid result or the final computed value.
Example
Input: nums = [3,1,5,4,2], k = 2
Output: 4
Explanation: After 4 operations, we collect elements 2, 4, 5, and 1, in this order. Our collection contains elements 1 and 2. Hence, the answer is 4.
Python Solution
class Solution:
def minOperations(self, nums: List[int], k: int) -> int:
is_added = [False] * k
count = 0
n = len(nums)
for i in range(n - 1, -1, -1):
if nums[i] > k or is_added[nums[i] - 1]:
continue
is_added[nums[i] - 1] = True
count += 1
if count == k:
return n - i
Complexity
The time complexity is , where is the length of the array . 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.