Problem1 added

[megharaykar]

No description provided.

[super30admin]

Level Order Traversal in Binary tree (Problem1.py)

1. Correctness: Your solution correctly performs a level order traversal and returns the result as a list of lists. It handles edge cases such as an empty tree appropriately.

2. Time Complexity: Your solution has an O(n) time complexity, which is optimal since each node is processed exactly once. This matches the reference solution.

3. Space Complexity: Your solution uses a queue that can store up to O(n) nodes in the worst case (e.g., a complete binary tree), which is optimal for BFS. However, note that the space complexity for BFS is typically O(w) where w is the maximum width of the tree, which can be O(n) in the worst case.

4. Code Quality: The code is clean and readable. You used a deque for efficient popping from the front, which is good practice in Python. However, you should consider adding a brief comment explaining the purpose of the for loop inside the while loop (processing each level). Also, the variable name qroot might be slightly confusing; consider renaming it to node or current for clarity.

5. Efficiency: The solution is efficient. One minor improvement could be to use if qroot.left instead of if qroot.left is not None for conciseness, as both are equivalent in Python. Additionally, you can initialize the deque with deque([root]) to avoid an extra append operation.

VERDICT: PASS

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Scheduling Courses

It seems there has been a mix-up in the problems. The code you submitted is for "Binary Tree Level Order Traversal" (LeetCode 102), but the problem you were asked to solve is "Scheduling Courses" (LeetCode 207), which involves checking if a cycle exists in a directed graph representing course prerequisites.

For the correct problem, you need to:

1. Build a graph where each node (course) has edges to its prerequisites (or the courses that require it, depending on representation).
2. Use a cycle detection algorithm such as DFS with state tracking (visited, visiting) or Kahn's algorithm for topological sort.

Your current solution does not address this at all. Please review the problem statement again and implement a solution for course scheduling. The reference solution provided in C++ can be a guide, but you should implement it in Python.

Strengths: Your code for the binary tree problem is clean and efficient, showing good coding practices.
Areas for improvement: Ensure you are solving the correct problem. For graph problems, familiarize yourself with common algorithms like DFS for cycle detection or topological sorting.

VERDICT: NEEDS_IMPROVEMENT