textdistance_hamming_levenshtein_jaccard_string_similarity.py

1import textdistance
2
3# Hamming distance
4# Distance: number of characters that are different
5distance = textdistance.hamming("test", "text")
6print(f"Hamming distance: {distance}")
7
8# Similarity: ratio of characters that are the same
9similarity = textdistance.hamming.similarity("test", "text")
10print(f"Hamming similarity: {similarity}")
11
12# Normalized similarity: similarity in range [0, 1]
13normalized_similarity = textdistance.hamming.normalized_similarity("test", "text")
14print(f"Hamming normalized similarity: {normalized_similarity}")
15
16# Levenshtein distance
17distance = textdistance.levenshtein("test", "text")
18print(f"Levenshtein distance: {distance}")
19
20# Jaccard index
21similarity = textdistance.jaccard("test", "text")
22print(f"Jaccard similarity: {similarity}")