FuzzyWuzzy Reviews and details

Social recommendations and mentions

• Need help solving a subtitles problem. The logic seems complex

  Do fuzzy matching (something like fuzzywuzzy maybe) to see if the the words line up (allowing for wrong words). You'll need to work out how to use scoring to work out how well aligned the two lists are. Source: over 1 year ago

• Thanks to this sub, we now have an Anki deck for Persona 5 Royal. Spreadsheet with Jp and Eng side by side too.

  Convert the original lines to full furigana and do a fuzzy match. (For reference, the original line is 貴方がこれまでに得てきた力、存分に発揮してくださいね。) You can do a regional search using the initial scene data (E60) first, and if the confidence is low, go for a slower full search. Source: over 1 year ago

• Fuzzy search

  It's now known as "thefuzz", see https://github.com/seatgeek/fuzzywuzzy. Source: almost 2 years ago

• I made a bot that stops muck chains, here are the phrases that he looks for to flag the comment as a muck comment. Are there any muck forms I forgot about?

  You can have a look at this library to use fuzzy search instead of looking for plaintext muck: https://github.com/seatgeek/fuzzywuzzy. Source: over 2 years ago

• How would you approach this

  To deal with comparing the string, I found FuzzyWuzzy ratio function that is returning a score of how much the strings are similar from 0-100. Source: over 2 years ago

• The Levenshtein Distance in Production

  I used fuzzywuzzy [1], a python-based fuzzy string matching calculator that is based on Levenshtein's edit-distance for a parking enforcement product I built. The product used an iOS client to capture license plates. The app would capture a single plate many times, de-duplicate using an edit-distance threshold matching plates up to a time period lookback. Then among those plates, send the one with the highest... - Source: Hacker News / almost 3 years ago

• RoR Determine how similar DB rows are

  Probably something as simple as loading it into the memory then calculating Damerau–Levenshtein distance for each pair and setting some threshold below which records are considered duplicates. If you want some more fancy similarities calculator, Python is probably better equipped in terms of ready-made libraries. Source: almost 3 years ago

• How to award a score (1-100) for closeness to the right answer?

  FuzzyWuzzy has an easy-to-use implementation: https://github.com/seatgeek/fuzzywuzzy. Source: about 3 years ago

• List of top-30 Women authors using 2021 and 2019 poll data

  After the above process, I was left to deal with minor differences in author names, like initials, spacing, typos, etc. There were too many entries to adjust manually, so I used fuzzywuzzy to determine if two entries were close enough. This trick would fail with authors, say R.J. Barker and R.J. Parker but I didn't find such entries during a sample manual sanity check from these groupings. Source: about 3 years ago

• File loop confusion

  Iterate separately over the two files, get the single DNA in a variable and the 180 in a list (make sure they are stored as string). You can use fuzzywuzzy to get the most similar match. Source: about 3 years ago

• How to find Word Similarity based on spellings?

  If you really need an numbers in procent then FuzzyWuzzy could help you with your problem. This lib uses also the leivenstein distance on its core but gives the convinient output of matching in procent. Source: about 3 years ago