Practice Arena

Python Coding Challenges

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467 challenges 330 easy 120 medium 17 hard
Dynamic Programming medium

Kadane Variant: Maximum Product Subarray

Implement max_product_subarray(nums) that returns the maximum product of any contiguous subarray.

kadane subarray product
+30 pts 25m
Dynamic Programming medium

Max Profit from Selling Twice

Compute the maximum profit that can be achieved by completing at most two buy-sell transactions on a given price array.

dynamic programming arrays stock
+28 pts 30m
Dynamic Programming medium

House Robber Circular

Solve the House Robber problem with houses arranged in a circle.

dynamic-programming arrays circular
+25 pts 30m
Dynamic Programming medium

Maximal square

Given a 2D binary matrix of 0s and 1s, compute the area of the largest square containing only 1s.

dynamic-programming matrix maximal-square
+30 pts 30m
Dynamic Programming medium

0/1 Knapsack

Implement the classic 0/1 Knapsack dynamic programming solution to maximize value under a weight capacity.

dynamic-programming knapsack optimization
+30 pts 25m
Dynamic Programming medium

Unbounded Knapsack

Given item weights and values with unlimited copies, find the maximum total value that fits in a knapsack capacity.

dynamic-programming knapsack optimization
+30 pts 25m
Dynamic Programming medium

Integer Break Product

Given a positive integer n, break it into at least two positive integers that sum to n and maximize their product.

integer-break dynamic-programming max-product
+25 pts 30m
Dynamic Programming medium

Buy Sell Stock with Cooldown (DP)

Given daily stock prices, compute the maximum profit you can achieve if you must wait one day after selling before buying again.

dynamic-programming state-machine stocks
+25 pts 25m

Showing 8 challenges · medium · Dynamic Programming

Dynamic Programming — Python coding challenges

What you will find here

This page lists dynamic programming 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.