Binary search
Return the index of target in a sorted list, or -1 if not present.
Quicksort
Implement quicksort and return a sorted list.
BFS level-order traversal
Return the level-order traversal of a binary tree as a list of lists.
Count inversions lite
Implement a function that counts inversions in a list of numbers efficiently.
Count pairs with given difference
Count how many unordered pairs in a list have a given absolute difference using an efficient approach.
Longest Consecutive Sequence
Given an unsorted list of integers, find the length of the longest consecutive elements sequence in O(n) time.
Pascal Triangle Row
Given a non-negative integer n, return the nth row of Pascal's triangle as a list of integers.
Bubble Sort
Implement bubble sort that sorts a list of numbers in ascending order.
Selection Sort Implementation
Implement selection sort to sort a list of numbers in ascending order.
Merge Sort
Implement merge_sort(numbers) that returns a sorted copy of the input list using the merge sort algorithm.
Heap Sort Implementation
Implement the heap sort algorithm to sort a list of comparable elements in non-decreasing order.
Radix Sort
Implement LSD radix sort to sort a list of non-negative integers in ascending order.
Bucket Sort
Implement bucket sort to sort a list of floating-point numbers in the range [0,1).
Exponential Search
Implement exponential search to find any valid index of a target in a sorted list.
Redundant Connection
Given a list of edges forming a tree plus one extra edge, return the edge that appears last in the input and creates a cycle.
Reconstruct Itinerary
Given a list of airline tickets, reconstruct the itinerary in order using each ticket exactly once, choosing the lexicographically smallest path when multiple options exist.
Showing 16 challenges · Data Structures & Algorithms
Data Structures & Algorithms — Python coding challenges
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This page lists data structures & algorithms 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.
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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.