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This is a medium difficulty Coding & Algorithms question, commonly asked during Technical Screen rounds at Snapchat.

What role is this question designed for?

This question is commonly asked for Machine Learning Engineer candidates at Snapchat during technical interviews.

Determine Whether Courses Can Be Completed

Quick Overview

This question evaluates understanding of graph modeling, directed cycle detection, and dependency resolution in the context of course prerequisites. It is commonly asked in the coding & algorithms domain because it reveals a candidate's algorithmic problem-solving ability and practical application of graph algorithms (expected O(V+E) time), testing practical implementation skills rather than only conceptual theory.

Determine Whether Courses Can Be Completed

Company: Snapchat

Role: Machine Learning Engineer

Category: Coding & Algorithms

Difficulty: medium

Interview Round: Technical Screen

You are given an integer `numCourses`, representing courses labeled from `0` to `numCourses - 1`, and a list `prerequisites`. Each prerequisite is a pair `[course, prerequisite]`, meaning you must finish `prerequisite` before taking `course`. Return `true` if it is possible to finish all courses. Return `false` if the prerequisite relationships contain a cycle that makes completion impossible. Example: ```text Input: numCourses = 2, prerequisites = [[1, 0]] Output: true Explanation: Take course 0 first, then course 1. ``` Example: ```text Input: numCourses = 2, prerequisites = [[1, 0], [0, 1]] Output: false Explanation: Course 0 requires course 1, and course 1 requires course 0, so there is a cycle. ``` Expected complexity: `O(V + E)` time, where `V` is the number of courses and `E` is the number of prerequisite pairs.

Quick Answer: This question evaluates understanding of graph modeling, directed cycle detection, and dependency resolution in the context of course prerequisites. It is commonly asked in the coding & algorithms domain because it reveals a candidate's algorithmic problem-solving ability and practical application of graph algorithms (expected O(V+E) time), testing practical implementation skills rather than only conceptual theory.

You are given an integer numCourses representing courses labeled from 0 to numCourses - 1, and a list prerequisites. Each prerequisite pair [course, prerequisite] means you must complete prerequisite before taking course. Return True if it is possible to finish all courses, and False if the prerequisite relationships contain a cycle that makes completing every course impossible.

Constraints

1 <= numCourses <= 100000
0 <= len(prerequisites) <= 200000
Each prerequisite is a pair [course, prerequisite] with 0 <= course, prerequisite < numCourses

Examples

Input: (2, [[1, 0]])

Expected Output: True

Explanation: Course 0 has no prerequisite, so you can take 0 first and then 1.

Input: (2, [[1, 0], [0, 1]])

Expected Output: False

Explanation: Course 0 depends on 1 and course 1 depends on 0, forming a cycle.

Input: (4, [[1, 0], [2, 0], [3, 1], [3, 2]])

Expected Output: True

Explanation: One valid order is 0, 1, 2, 3. There is no cycle.

Input: (3, [])

Expected Output: True

Explanation: With no prerequisites, all courses can be taken in any order.

Input: (1, [[0, 0]])

Expected Output: False

Explanation: The only course depends on itself, which is a cycle.

Input: (3, [[1, 0], [1, 0], [2, 1]])

Expected Output: True

Explanation: Even with a duplicate prerequisite pair, there is still no cycle. A valid order is 0, 1, 2.

Hints

Model the courses as a directed graph where prerequisite -> course is a directed edge.
If you repeatedly take courses with no remaining prerequisites and still cannot process all courses, then a cycle exists.

Last updated: May 15, 2026

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Quick Overview

Determine Whether Courses Can Be Completed

Company: Snapchat

Role: Machine Learning Engineer

Category: Coding & Algorithms

Difficulty: medium

Interview Round: Technical Screen

Constraints

1 <= numCourses <= 100000
0 <= len(prerequisites) <= 200000
Each prerequisite is a pair [course, prerequisite] with 0 <= course, prerequisite < numCourses

Examples

Input: (2, [[1, 0]])

Expected Output: True

Explanation: Course 0 has no prerequisite, so you can take 0 first and then 1.

Input: (2, [[1, 0], [0, 1]])

Expected Output: False

Explanation: Course 0 depends on 1 and course 1 depends on 0, forming a cycle.

Input: (4, [[1, 0], [2, 0], [3, 1], [3, 2]])

Expected Output: True

Explanation: One valid order is 0, 1, 2, 3. There is no cycle.

Input: (3, [])

Expected Output: True

Explanation: With no prerequisites, all courses can be taken in any order.

Input: (1, [[0, 0]])

Expected Output: False

Explanation: The only course depends on itself, which is a cycle.

Input: (3, [[1, 0], [1, 0], [2, 1]])

Expected Output: True

Explanation: Even with a duplicate prerequisite pair, there is still no cycle. A valid order is 0, 1, 2.

Hints

Model the courses as a directed graph where prerequisite -> course is a directed edge.
If you repeatedly take courses with no remaining prerequisites and still cannot process all courses, then a cycle exists.

Last updated: May 15, 2026

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