Completed s30 Hashing-1

[prenastro]

No description provided.

[super30admin]

Group Anagrams (anagrams.py)

Strengths:

• Clean and readable implementation
• Correctly handles edge cases (empty strings, single characters)
• Uses appropriate data structures (defaultdict, tuple as key)
• Good documentation of time and space complexity

Areas for Improvement:

• The solution is already quite optimal. One minor suggestion: you could use tuple(count) more explicitly or consider using a string representation of the count, but the current approach is fine.
• Consider adding type hints for better code documentation (e.g., def groupAnagrams(self, strs: List[str]) -> List[List[str]]:)

VERDICT: PASS

---

Isomorphic Strings (isomorphicstrings.py)

Strengths:

• Correct bidirectional mapping approach
• Clean, readable code with good variable naming
• Efficient O(1) average lookup time
• Proper early returns for mismatches

Areas for Improvement:

• The space complexity comment (O(1)) is technically inaccurate - it should be O(n) in the worst case or O(min(n, σ)) where σ is the character set size
• Consider adding a length check at the beginning for early exit (though not strictly necessary since constraints state equal lengths)

Overall, this is a solid solution that correctly solves the problem with good performance.

VERDICT: PASS

---

Word Pattern (workdpattern.py)

Strengths:

• Clean and readable implementation
• Correctly handles the bijection constraint using the used_words set
• Efficient early returns on mismatches
• Good use of Python idioms (zip, descriptive variable names)

Areas for Improvement:

• Space complexity analysis is incorrect - you should acknowledge O(n) space usage
• Consider adding comments explaining the bijection logic for future reference
• The solution is functionally equivalent to the reference but uses a slightly more elegant approach (single dictionary + set vs. dual hash maps)

VERDICT: PASS