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Leetcode #1725: Number Of Rectangles That Can Form The Largest Square

In this guide, we solve Leetcode #1725 Number Of Rectangles That Can Form The Largest Square in Python and focus on the core idea that makes the solution efficient.

You will see the intuition, the step-by-step method, and a clean Python implementation you can use in interviews.

Leetcode

Problem Statement

You are given an array rectangles where rectangles[i] = [li, wi] represents the ith rectangle of length li and width wi. You can cut the ith rectangle to form a square with a side length of k if both k <= li and k <= wi.

Quick Facts

  • Difficulty: Easy
  • Premium: No
  • Tags: Array

Intuition

The constraints allow a direct scan that keeps only the essential state.

By translating the requirements into a clean loop, the logic stays easy to reason about.

Approach

Iterate through the data once, updating the state needed to compute the answer.

Return the final state after the traversal is complete.

Steps:

  • Parse the input.
  • Iterate and update state.
  • Return the computed answer.

Example

Input: rectangles = [[5,8],[3,9],[5,12],[16,5]] Output: 3 Explanation: The largest squares you can get from each rectangle are of lengths [5,3,5,5]. The largest possible square is of length 5, and you can get it out of 3 rectangles.

Python Solution

class Solution: def countGoodRectangles(self, rectangles: List[List[int]]) -> int: ans = mx = 0 for l, w in rectangles: x = min(l, w) if mx < x: ans = 1 mx = x elif mx == x: ans += 1 return ans

Complexity

The time complexity is O(n)O(n)O(n), where nnn is the length of the array rectanglesrectanglesrectangles. The space complexity is O(1)O(1)O(1).

Edge Cases and Pitfalls

Watch for boundary values, empty inputs, and duplicate values where applicable. If the problem involves ordering or constraints, confirm the invariant is preserved at every step.

Summary

This Python solution focuses on the essential structure of the problem and keeps the implementation interview-friendly while meeting the constraints.


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