Top K Frequent Elements
Given an integer array and a number k, return the k most frequent elements using a heap-based approach.
Kth Largest Element in an Array (Heap Edition)
Implement a function that returns the kth largest element in an unsorted integer array using a heap.
Top K Frequent Elements
Given a list of integers and a number k, return the k most frequent elements in descending order of frequency, with ties broken by larger value.
Task Scheduler Heap
Given a list of tasks and a cooldown, find the minimum number of CPU intervals needed to schedule all tasks without violating the cooldown.
Find K pairs with smallest sums
Given two sorted arrays and an integer k, return the k smallest pairs (u, v) with the smallest sums, sorted by sum.
Meeting Rooms II with Heaps
Given a list of meeting intervals, compute the minimum number of rooms required using a heap-based approach.
Sliding Window Maximum using Heap
Given an array of integers and a window size k, return an array of maximums for each contiguous subarray of length k.
Maximum Average Pass Ratio
Given class pass/total counts and extra students, maximize the average pass ratio by assigning extra students optimally.
Minimum Cost to Connect Sticks
Compute the minimum total cost to connect all sticks into one stick by repeatedly combining two sticks with the smallest lengths.
Showing 1–9 of 9 challenges · medium · Heaps & Priority Queues
Heaps & Priority Queues — Python coding challenges
What you will find here
This page lists heaps & priority queues challenges — real Python problems you solve in the browser IDE with instant test feedback. Each challenge includes a clear brief, starter code, and automated checks.
Challenges vs tutorials and quizzes
Challenges test what you can build under constraints. For guided teaching, use our Python tutorials. For quick checks, try quizzes or copy snippets from code samples.