Did you have a look at diff-match-patch from google? Apparantly google Docs uses this set of algoritms. It includes not only a diff module, but also a patch module, so you can generate the newest file from older files and diffs. A python version is included. http://code.google.com/p/google-diff-match-patch/
You forgot the first parameter to SequenceMatcher. >>> import difflib >>> >>> a=”abcd” >>> b=’ab123′ >>> seq=difflib.SequenceMatcher(None, a,b) >>> d=seq.ratio()*100 >>> print d 44.4444444444 http://docs.python.org/library/difflib.html
In case you’re interested in a quick visual comparison of Levenshtein and Difflib similarity, I calculated both for ~2.3 million book titles: import codecs, difflib, Levenshtein, distance with codecs.open(“titles.tsv”,”r”,”utf-8″) as f: title_list = f.read().split(“\n”)[:-1] for row in title_list: sr = row.lower().split(“\t”) diffl = difflib.SequenceMatcher(None, sr[3], sr[4]).ratio() lev = Levenshtein.ratio(sr[3], sr[4]) sor = 1 – distance.sorensen(sr[3], … Read more