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Grokking the Coding Interview Patterns in Python

Meeting Rooms II

Explore how to solve the Meeting Rooms II problem by analyzing meeting intervals with start and exclusive end times. Understand key interval patterns and develop an efficient O(n log n) approach for allocating meeting rooms. Practice applying these patterns to optimize scheduling and resource management.

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Statement

We are given an input array of meeting time intervals, intervals, where each interval has a start time and an end time. Your task is to find the minimum number of meeting rooms required to hold these meetings.

An important thing to note here is that the specified end time for each meeting is exclusive.

Constraints

  • 1<=1 <= intervals.length <=103<= 10^{3}
  • 00 ≤\leq startistart_{i} <\lt endiend_{i} ≤\leq 10610^{6}

Examples

Understand the problem

Let’s take a moment to make sure you’ve correctly understood the problem. The quiz below helps you check if you’re solving the correct problem:

Technical Quiz
1.

Meeting time intervals = [ [1, 3], [2, 6], [8, 10], [9, 15], [12, 14] ]

How many meeting rooms are required to hold these meetings?

A.

3

B.

1

C.

2

1 / 3

Figure it out!

We have a game for you to play. Rearrange the logical building blocks to develop a clearer understanding of how to solve this problem.

Note: As an additional challenge, we have intentionally hidden the solution to this puzzle.

Sequence - Vertical
Drag and drop the cards to rearrange them in the correct sequence.
1
2
3
4
5
6
7

Try it yourself

Implement your solution in the following coding playground.

We have left the solution to this challenge as an exercise for you. The optimal solution to this problem runs in O(n*log(n)) time and takes O(n) space. You may try to translate the logic of the solved puzzle into a coded solution.

Python
usercode > main.py
import heapq



def find_sets(intervals):



    # Replace this placeholder return statement with your code

    return -1
Meeting Rooms II