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Solution 19: Vernacular Transcription (Integer to English Words)

Approach Explanation

We process the number in groups of three digits (billions, millions, thousands, and hundreds). For each group, we use helper functions to convert the number to words.

Step-by-Step Logic

  1. Create word mappings for LESS_THAN_20, TENS, and THOUSANDS.
  2. Implement helper(n) which handles numbers < 1000.
  3. In main function:
    • Handle 0.
    • For THOUSANDS indices (0 to 3):
      • If num % 1000 != 0, calculate helper(num % 1000) + label + result.
      • num //= 1000.
  4. Return trimmed result.

Complexity

  • Time Complexity: O(log N).
  • Space Complexity: O(log N).

Code

def number_to_words(num):
    if num == 0: return "Zero"
    
    less_than_20 = ["", "One", "Two", "Three", "Four", "Five", "Six", "Seven", "Eight", "Nine", "Ten", "Eleven", "Twelve", "Thirteen", "Fourteen", "Fifteen", "Sixteen", "Seventeen", "Eighteen", "Nineteen"]
    tens = ["", "Ten", "Twenty", "Thirty", "Forty", "Fifty", "Sixty", "Seventy", "Eighty", "Ninety"]
    thousands = ["", "Thousand", "Million", "Billion"]
    
    def helper(n):
        if n == 0: return ""
        elif n < 20: return less_than_20[n] + " "
        elif n < 100: return tens[n // 10] + " " + helper(n % 10)
        else: return less_than_20[n // 100] + " Hundred " + helper(n % 100)
        
    res = ""
    for i in range(len(thousands)):
        if num % 1000 != 0:
            res = helper(num % 1000) + thousands[i] + " " + res
        num //= 1000
        
    return res.strip()