Python implementation - queue using stack + hashmap design

[shaikhmisrail]

No description provided.

[super30admin]

Strengths:

1. The solutions are correct and efficient, meeting the problem requirements.
2. The code is well-structured and readable, with comments explaining the approach and complexity.
3. For the queue problem, the amortized O(1) operations are implemented correctly.
4. For the hashmap problem, the use of separate chaining and a dummy node handles collisions and edge cases effectively.

Areas for Improvement:

1. In the hashmap problem, the getPrev method might be confusingly named because it returns the node before the target key (if found) or the last node in the list (if not found). Consider renaming it to something like find_previous_node or adding a comment to clarify its behavior.
2. The hashmap initialization uses a list of size 10000, which is acceptable, but it might be better to use a prime number for the bucket size to reduce collisions. However, this is not critical given the constraints.
3. In the queue problem, the pop method could call peek to ensure outStack has elements, which might make the code slightly more concise (as in the reference solution). However, the current implementation is also correct.

[super30admin]

Strengths:

• The solutions are correct and efficient.
• The code is well-commented, including time and space complexity analysis.
• The hashmap solution uses a dummy node to simplify linked list operations, which is a good approach.

Areas for Improvement:

• In the queue solution, the pop method could call peek to avoid duplicating the transfer logic. The reference solution does this by having pop call peek to ensure the outStack has elements before popping. This would make the code slightly more concise.
• In the hashmap solution, the getPrev method might be slightly inefficient because it returns the previous node even when the key is not found. However, this is acceptable for the implementation. Alternatively, you could consider renaming the method to better reflect its purpose, such as find_prev_node.
• The hashmap solution uses a fixed primary bucket size of 10000. While this is acceptable for the problem constraints, it might be worth mentioning that in a real-world scenario, the size could be dynamic or chosen based on expected load.

Overall, the student has done an excellent job. The solutions are correct, efficient, and well-documented.