Algorithm Notes
Summary: Course Schedule — notes not yet curated.
Time: Estimate via loops/recurrences; common classes: O(1), O(log n), O(n), O(n log n), O(n^2)
Space: Count auxiliary structures and recursion depth.
Tip: See the Big-O Guide for how to derive bounds and compare trade-offs.
Big-O Guide
Source
"""
Course Schedule
TODO: Add problem description
"""
from collections import defaultdict, deque
from src.interview_workbook.leetcode._registry import register_problem
from src.interview_workbook.leetcode._types import Category, Difficulty
class Solution:
def solve(self, numCourses, prerequisites):
"""Detect cycle in course prerequisite graph (Kahn's algorithm)."""
graph = defaultdict(list)
indegree = [0] * numCourses
for dest, src in prerequisites:
graph[src].append(dest)
indegree[dest] += 1
queue = deque([i for i in range(numCourses) if indegree[i] == 0])
visited = 0
while queue:
course = queue.popleft()
visited += 1
for nei in graph[course]:
indegree[nei] -= 1
if indegree[nei] == 0:
queue.append(nei)
return visited == numCourses
def demo() -> str:
"""Run a demo for the Course Schedule problem."""
num_courses = 2
prerequisites = [[1, 0]]
print(f"Number of courses: {num_courses}, Prerequisites: {prerequisites}")
s = Solution()
result = s.solve(num_courses, prerequisites)
print(f"Final result: {result}")
return (
f"Course Schedule with {num_courses} courses and prerequisites {prerequisites} -> {result}"
)
if __name__ == "__main__":
demo()
register_problem(
id=207,
slug="course_schedule",
title="Course Schedule",
category=Category.GRAPHS,
difficulty=Difficulty.MEDIUM,
tags=["dfs", "bfs", "graph", "topological_sort"],
url="https://leetcode.com/problems/course-schedule/",
notes="",
)