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.
Graph DFS
Return all nodes reachable from a start node via DFS.
Find Peak Element
Implement a function that returns the index of any peak element in an integer array.
Merge Sort
Implement merge_sort(numbers) that returns a sorted copy of the input list using the merge sort algorithm.
Path Sum II All Paths
Return all root-to-leaf paths where the sum of node values equals a target.
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.
K Closest Elements
Implement a function to return the k closest elements to a target in a sorted array.
Online Stock Span
Implement StockSpanner.next(price) that returns the maximum number of consecutive days (including today) with price <= current price.
AST Visitor Lite
Implement a depth-first traversal of a simplified AST and return identifier names in order.
Merge time intervals
Given a list of time intervals, merge all overlapping intervals and return the merged intervals.
Top N per group
Implement top_n_per_group that returns the top N scores for each group from a list of (group, score) pairs.
Level Order Traversal
Implement a function that performs a level order traversal of a binary tree and returns node values as a list of lists.
Delete duplicates sorted II
Given a sorted list, remove duplicates in place so each element appears at most twice, returning the new length.
Accounts Merge
Given a list of accounts, merge those that share any email and return sorted accounts.
Strobogrammatic number II
Given a positive integer n, return all strobogrammatic numbers of length n in ascending order.
Showing 1–16 of 16 challenges · medium · 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.