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Tested Python solution for LeetCode 347 with 13 pytest cases. Generate a practice environment with lcpy.
lcpy gen -n 347 # by problem number
lcpy gen -s top_k_frequent_elements # by problem name
nums and an integer k, return the k most frequent elements. You may return the answer in any order.
Input: nums = [1,1,1,2,2,3], k = 2
Output: [1,2]
Input: nums = [1], k = 1
Output: [1]
Input: nums = [1,2,1,2,1,2,3,1,3,2], k = 2
Output: [1,2]
O(n log n), where n is the array’s size.
import heapq
from collections import Counter
class Solution:
def top_k_frequent(self, nums: list[int], k: int) -> list[int]:
"""
Optimized version using heap for O(n log k) time complexity.
Time: O(n log k) - heap operations
Space: O(n) - for counter and heap
"""
counter = Counter(nums)
# Use min heap of size k - keep the k most frequent elements
heap: list[tuple[int, int]] = []
for num, count in counter.items():
if len(heap) < k:
heapq.heappush(heap, (count, num))
elif count > heap[0][0]:
heapq.heapreplace(heap, (count, num))
# Extract numbers from heap (order doesn't matter for this problem)
return [num for _, num in heap]
| Time | Space |
|---|---|
| - | - |