Algorithm Notes
Summary: Top K Frequent Words — notes not yet curated.
Time: Estimate via loops/recurrences; common classes: O(1), O(log n), O(n), O(n log n), O(n^2)
Space: Count auxiliary structures and recursion depth.
Tip: See the Big-O Guide for how to derive bounds and compare trade-offs.
Big-O Guide
Source
"""
Top K Frequent Words
TODO: Add problem description
"""
import heapq
import random
from collections import Counter
from src.interview_workbook.leetcode._registry import register_problem
from src.interview_workbook.leetcode._types import Category, Difficulty
class Solution:
def top_k_frequent(self, words: list[str], k: int) -> list[str]:
"""
Return the k most frequent words sorted by frequency and lexicographic order.
"""
counts = Counter(words)
# min-heap with custom ordering
heap = [(-freq, word) for word, freq in counts.items()]
heapq.heapify(heap)
result = []
for _ in range(k):
if heap:
freq, word = heapq.heappop(heap)
result.append(word)
return result
def demo() -> str:
"""Demonstration of Top K Frequent Words with deterministic seeding."""
random.seed(0)
words = ["i", "love", "leetcode", "i", "love", "coding"]
k = 2
sol = Solution()
result = sol.top_k_frequent(words, k)
return f"Words: {words}, K: {k}, Top K Frequent: {result}"
register_problem(
id=692,
slug="top_k_frequent_words",
title="Top K Frequent Words",
category=Category.HEAP,
difficulty=Difficulty.MEDIUM,
tags=["string", "hashmap", "heap", "sorting"],
url="https://leetcode.com/problems/top-k-frequent-words/",
notes="",
)