Completed s30 design-1 hashset and minstack

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Design HashSet (hashset.py)

Strengths:

• Clean, readable code with appropriate documentation
• Correctly handles all edge cases within the given constraints
• Achieves optimal O(1) time complexity for all operations
• Simple and easy to understand implementation

Areas for Improvement:

• The space usage could be optimized for sparse datasets using a hash-based approach like the reference solution
• Consider adding input validation (though not strictly required given the problem constraints)
• The comment "Space Complexity = O(10^6)" could be more precise as O(n) where n = 10^6

The student's solution is valid and passes the problem requirements, though it uses a different (simpler) approach than the reference solution.

VERDICT: PASS

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Min Stack (minstack.py)

Strengths:

1. Correct implementation of the two-stack approach for tracking minimums
2. Clean, readable code with good variable naming
3. Handles edge cases (duplicate minimums) correctly with <= condition
4. O(1) time complexity achieved for all operations
5. More space-efficient than the reference solution (only stores minimums when they change)

Areas for Improvement:

1. The comment table at the end has some inaccuracies - push() has O(n) space complexity listed, but push() itself is O(1) time. The space complexity should be listed as O(n) for the overall data structure, not per operation.
2. Could add type hints for better code documentation (e.g., def push(self, val: int) -> None:)

Overall, this is a solid implementation that correctly solves the problem with good efficiency and readability.

VERDICT: PASS