class_docstr: Class designed to confirm whether something is **language** based on how many words of **language** appears
  Call confirmLanguage(text, language)
  * text: the text you want to confirm
  * language: the language you want to confirm
  
  Find out what language it is by using chisquared.py, the highest chisquared score is the language
  languageThreshold = 45
  if a string is 45% **language** words, then it's confirmed to be english
class_docstr_tok: ["Class","designed","to","confirm","whether","something","is","*","*","language","*","*","based","on","how","many","words","of","*","*","language","*","*","appears","Call","confirmLanguage","(","text",",","language",")","*","text",":","the","text","you","want","to","confirm","*","language",":","the","language","you","want","to","confirm","Find","out","what","language","it","is","by","using","chisquared.py",",","the","highest","chisquared","score","is","the","language","languageThreshold","=","45","if","a","string","is","45","%","*","*","language","*","*","words",",","then","it","'s","confirmed","to","be","english"]
docstr: Cleans the text ready to be checked
  
  Strips punctuation, makes it lower case, turns it into a set separated by spaces, removes duplicate words
  
  Args:
      text -> The text we use to perform analysis on
  
  Returns:
      text -> the text as a list, now cleaned
docstr_tok: ["Cleans","the","text","ready","to","be","checked","Strips","punctuation",",","makes","it","lower","case",",","turns","it","into","a","set","separated","by","spaces",",","removes","duplicate","words","Args",":","text","-",">","The","text","we","use","to","perform","analysis","on","Returns",":","text","-",">","the","text","as","a","list",",","now","cleaned"]
code: def clean_text(self, text: str) -> set:
      """Cleans the text ready to be checked
  
      Strips punctuation, makes it lower case, turns it into a set separated by spaces, removes duplicate words
  
      Args:
          text -> The text we use to perform analysis on
  
      Returns:
          text -> the text as a list, now cleaned
  
      """
      # makes the text unique words and readable
      text = text.lower()
      text = self.mh.strip_punctuation(text)
      text = text.split(" ")
      text = filter(lambda x: len(x) > 2, text)
      text = set(text)
      return text
  
file_path: Ciphey/ciphey/basemods/Checkers/brandon.py
imports: import sys
  from math import ceil
  from typing import Dict, Optional
  import logging
  from rich.logging import RichHandler
  from ciphey.iface import Checker, Config, ParamSpec, T, registry
label_desc: Use image node_id 2 for calling the Brandon obj's underlying member method code with example usage: obj.clean_text(text) and returns: text