The “Unique Morse Code Words” is a problem from Leetcode that emphasizes translating a given set of words into Morse code representation and finding out how many unique transformations exist. In this comprehensive guide, we will walk you through the problem statement, solution strategies, Python code, and the intricacies involved.
Table of Contents
- Problem Statement
- Solution Strategies
- Python Implementation
- Testing and Analysis
- Further Thoughts and Optimizations
- Conclusion
1. Problem Statement
International Morse Code defines a standard encoding where each letter is mapped to a series of dots and dashes. The given Morse code for the 26 lowercase English letters is:
a: ".-", b: "-...", c: "-.-.", ..., z: "--.."
Task: Given a list of words, find how many different transformations are possible among these words when converted to Morse code.
For instance, given words ["gin", "zen", "gig", "msg"]
, the transformations are:
"gin" -> "--...-."
"zen" -> "--...-."
"gig" -> "--...--."
"msg" -> "--...--."
This results in 2 unique transformations: --...-.
and --...--.
.
2. Solution Strategies
A straightforward approach involves:
- Translation: Convert each word to its Morse code representation.
- Storage and Counting: Store each transformation and count the unique ones.
3. Python Implementation
Given the direct nature of the problem, Python’s standard library provides all the necessary tools. Here’s a step-by-step breakdown:
def uniqueMorseRepresentations(words):
# Morse code mappings for a-z
MORSE = [".-","-...","-.-.","-..",".","..-.","--.","....","..",".---","-.-",".-..","--","-.","---",".--.","--.-",".-.","...","-","..-","...-",".--","-..-","-.--","--.."]
# Convert each word to Morse code
transformations = set()
for word in words:
transformation = ''.join(MORSE[ord(char) - ord('a')] for char in word)
transformations.add(transformation)
return len(transformations)
How the Code Works:
- The
MORSE
list contains Morse code representations for lowercase English alphabets in order. - We utilize a set named
transformations
to store each Morse code transformation. Since sets inherently store unique values, duplicates will be discarded. - Loop through each word in the
words
list, convert it to Morse code, and add to the set. - Return the length of the set, indicating the number of unique transformations.
4. Testing and Analysis
Given our example:
words = ["gin", "zen", "gig", "msg"]
print(uniqueMorseRepresentations(words)) # Expected output: 2
Time Complexity: The algorithm runs in O(n * m) time, where n is the number of words and m is the average length of a word.
Space Complexity: O(n) for storing unique Morse code transformations.
5. Further Thoughts and Optimizations
- Using Python Comprehensions: The conversion can be made more Pythonic using set comprehensions.
- Optimized Morse Code Array: If memory efficiency is a priority, consider storing Morse code representations in a more compressed format and decoding on-the-fly.
6. Conclusion
The “Unique Morse Code Words” problem on LeetCode presents a simple yet interesting challenge. It serves as an excellent example of combining basic string manipulation with data structures like sets in Python. The given solution is both intuitive and efficient. However, always consider potential edge cases and optimizations tailored to specific use-cases or constraints when implementing solutions to such problems.