Merge pull request #401 from kelvins/levenshtein_distance

Levenshtein distance

strings/levenshtein-distance.py

@@ -0,0 +1,78 @@
+"""
+This is a Python implementation of the levenshtein distance.
+Levenshtein distance is a string metric for measuring the
+difference between two sequences.
+
+For doctests run following command:
+python -m doctest -v levenshtein-distance.py
+or
+python3 -m doctest -v levenshtein-distance.py
+
+For manual testing run:
+python levenshtein-distance.py
+"""
+
+
+def levenshtein_distance(first_word, second_word):
+    """Implementation of the levenshtein distance in Python.
+    :param first_word: the first word to measure the difference.
+    :param second_word: the second word to measure the difference.
+    :return: the levenshtein distance between the two words.
+    Examples:
+    >>> levenshtein_distance("planet", "planetary")
+    3
+    >>> levenshtein_distance("", "test")
+    4
+    >>> levenshtein_distance("book", "back")
+    2
+    >>> levenshtein_distance("book", "book")
+    0
+    >>> levenshtein_distance("test", "")
+    4
+    >>> levenshtein_distance("", "")
+    0
+    >>> levenshtein_distance("orchestration", "container")
+    10
+    """
+    # The longer word should come first
+    if len(first_word) < len(second_word):
+        return levenshtein_distance(second_word, first_word)
+
+    if len(second_word) == 0:
+        return len(first_word)
+
+    previous_row = range(len(second_word) + 1)
+
+    for i, c1 in enumerate(first_word):
+
+        current_row = [i + 1]
+
+        for j, c2 in enumerate(second_word):
+
+            # Calculate insertions, deletions and substitutions
+            insertions = previous_row[j + 1] + 1
+            deletions = current_row[j] + 1
+            substitutions = previous_row[j] + (c1 != c2)
+
+            # Get the minimum to append to the current row
+            current_row.append(min(insertions, deletions, substitutions))
+
+        # Store the previous row
+        previous_row = current_row
+
+    # Returns the last element (distance)
+    return previous_row[-1]
+
+
+if __name__ == '__main__':
+    try:
+        raw_input          # Python 2
+    except NameError:
+        raw_input = input  # Python 3
+
+    first_word = raw_input('Enter the first word:\n').strip()
+    second_word = raw_input('Enter the second word:\n').strip()
+
+    result = levenshtein_distance(first_word, second_word)
+    print('Levenshtein distance between {} and {} is {}'.format(
+        first_word, second_word, result))