problem of fuzz.ratio with newer ver (22) of python-Lev. distance about fuzzywuzzy HOT 2 OPEN

Why do you consider the score 46 as incorrect? I understand you would like to find Real Madrid as best match for real, but according to the normalized Indel similarity it simply isn't.
To convert from real to Barcelona the following operations are required:

__r_e___al
Barcelona_

These are 7 operation. Now this is normalized in the following way: 1.0 - (dist / (len(s1) + len(s2))) -> 0.46.
On the other hand for Real Madrid the following operations are required:

_real_______
R_eal Madrid

These are 9 operations. Normalized in the same way you get 0.4.

Note, without python-Levenshtein install at all (clean, checked with colab with and without) it works like a charm.

No clue how that would work, since in this specific case the difflib fallback actually returns the same results:

>>> import difflib
>>> difflib.SequenceMatcher(None, 'real', 'Barcelona').ratio()
0.46153846153846156
>>> difflib.SequenceMatcher(None, 'real', 'Real Madrid').ratio()
0.4

from fuzzywuzzy.

after investigation you are indeed right, how do you offer to resolve such problem?
partial_ratio is not an offer as "Real Madrid" and "Real Saragosa" are the same for "Real", and their partial_ratio rate should be the same.
I wonder how to attack such problem

I went with fuzz.partial_token_set_ratio, as it should fit better I think

from fuzzywuzzy.