leetcode-study

383. Ransom Note

from collections import Counter

class Solution:
    def canConstruct(self, ransomNote: str, magazine: str) -> bool:
        """
        Determine if 'ransomNote' can be constructed from the letters in 'magazine'.
        
        Parameters:
            ransomNote (str): The note that needs to be constructed using letters from 'magazine'.
            magazine (str): The source string containing available letters.
        
        Returns:
            bool: True if 'ransomNote' can be constructed from 'magazine', otherwise False.
        """
        # Create frequency counts for each letter in 'ransomNote' and 'magazine'
        ransom_count = Counter(ransomNote)
        magazine_count = Counter(magazine)
        
        # For each letter required by the ransom note, check if magazine provides enough occurrences
        for letter, count in ransom_count.items():
            # If the count of the letter in the magazine is less than required, return False
            if magazine_count[letter] < count:
                return False
        
        # If all required letters have sufficient occurrences, the note can be constructed
        return True

Summary of Techniques and Approaches:

• Counter Data Structure: Leverage the Counter from Python’s collections module to efficiently track frequency of elements. This technique is applicable for problems involving counting and frequency comparisons.

• Frequency Comparison: Compare counts of elements from two collections to validate if one can be constructed from the other. This approach is versatile and can be used in anagram checks, inventory control systems, and resource allocation problems.

• Early Termination: The solution checks each required letter and terminates early if a letter is insufficient. This “fail-fast” strategy can improve performance, especially in cases where there is a clear mismatch.

• Code Clarity and Comments: High-level comments and a clear docstring assist in understanding the flow and purpose of the code, making it easier to maintain and reuse concepts across different problems.

These techniques can be broadly applied in scenarios that require processing and comparing collections, especially when handling problems around anagrams, frequency analysis, and resource sufficiency.