levenshtein-distance.py

def minDistance(word1, word2):
    m, n = len(word1), len(word2)
    
    # Initialize a (m+1) x (n+1) dp table
    dp = [[0] * (n + 1) for _ in range(m + 1)]
    
    for i in range(m + 1):
        dp[i][0] = i 
    for j in range(n + 1):
        dp[0][j] = j  
    
    for i in range(1, m + 1):
        for j in range(1, n + 1):
            if word1[i - 1] == word2[j - 1]:
                dp[i][j] = dp[i - 1][j - 1] 
            else:
                dp[i][j] = min(
                    dp[i - 1][j] + 1,      
                    dp[i][j - 1] + 1,      
                    dp[i - 1][j - 1] + 1 
                )
    
    return dp[m][n]

word1 = "horse"
word2 = "ros"
print(f"Minimum edit distance to convert '{word1}' to '{word2}': {minDistance(word1, word2)}")