Based on our record, FuzzyWuzzy should be more popular than Parse-Server. It has been mentiond 11 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
If you like headless CMS / Backend As A Service you should consider https://directus.io/ or https://github.com/parse-community/parse-server. Both nodejs and open source. Source: about 2 years ago
There's numerous standard backends which frontenders could use in simplistic cases to start, say https://github.com/PostgREST/postgrest or https://github.com/parse-community/parse-server. Source: over 2 years ago
Parse is still around and supported: https://github.com/parse-community/parse-server. - Source: Hacker News / over 2 years ago
I am curious what backend framework you would choose to run with for prototyping an application with run of the mill user management requirements. That is functionality along the lines of: session management, password policies, password reset, user verifications, etc. Sadly it seems there really aren't any frameworks that have user management natively supported. The only one I am aware of is [Parse... - Source: Hacker News / almost 3 years ago
I believe you are referring to main.js file. The answer is no. I used parse server for backend. And by default all classes are public which means everyone can read every data. There is a preferred way to prevent this. You disable all class level permissions for every class. Then you put your app logic to cloud code which is main.js file you were looking at. Here is an article about this... Source: about 3 years ago
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
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
It's now known as "thefuzz", see https://github.com/seatgeek/fuzzywuzzy. Source: about 2 years ago
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
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: almost 3 years ago
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