Hey everyone! I'm facing a challenge with fuzzy string matching in Python. Basically, I have a string A and a long string B, like a book. The tricky part is that string A won't match string B perfectly—there could be slight edits or variations. Has anyone dealt with something similar? I'm open to any insights or alternative approaches you might have. Thanks a lot!
5 Answers
You might want to look into using the Levenshtein algorithm for this issue. It can help with fuzzy matches, but keep in mind that it might be a bit hefty to handle performance-wise. Still, it could be a starting point!
Fuzzy string matching is all about finding those inexact matches. If you're worried about accuracy, there are libraries like fuzzysearch or fuzzywuzzy in Python that can help improve your results without reinventing the wheel!
Thanks for the suggestions! I'll check them out to see if they fit my needs.
If you really want to find matches despite slight changes, consider taking the first and last words of your target string and checking their order in the longer string. It might help narrow down possible candidates before doing a more in-depth search.
A quick tip: Why not split the book into smaller chunks and see if you can find partial matches for string A? Just be aware that doing this could miss some edits, since A might not always show up exactly in B.
Thanks for the idea! Just to clarify, the issue is that A might be edited in B. So if I check strictly for A in B's substrings, I might miss potential matches.
For a more complex approach, you could create a scoring system for confidence matches. You'd tune it based on how similar the letters are in the different potential matches. This way, you can score and sort matches by relevance!
I've thought about Levenshtein too, but the way it calculates distance might be too harsh for strings of varying lengths. I'm leaning towards Sørensen-Dice for my case, even if it means longer runtimes.