The most probable correct spelling for the word

            Args:
                word (str): The word to correct
            Returns:
                str: The most likely candidate
332691
def correction(self, word):
        
        return max(self.candidates(word), key=self.word_probability)
775823
def word(cap=False):
    
    syllables = []
    for x in range(random.randint(2,3)):
        syllables.append(_syllable())
    word = "".join(syllables)
    if cap: word = word[0].upper() + word[1:]
    return word
530252
def spell(self, word: str) -> List[str]:
        
        if not word:
            return ""

        candidates = (
            self.known([word])
            or self.known(_edits1(word))
            or self.known(_edits2(word))
            or [word]
        )
        candidates.sort(key=self.freq, reverse=True)

        return candidates
1119128
def _add_word(completer):
    
    def inner(word: str):
        completer.words.add(word)
    return inner
424152
def lemmatize(self, word, pos_universal_google):
        
        if pos_universal_google == "NOUN":
            if self.contains_entry(word, "Noun"):
                return self.get_lemmas(word, "Noun")
            elif self.contains_entry(word, "X"):
                return self.get_lemmas(word, "X")
            elif self.contains_entry(word, "AdjectivalDeclension"):
                return self.get_lemmas(word, "AdjectivalDeclension")
            elif self.contains_entry(word, ["Noun", "X"], ignore_case=True):
                return self.get_lemmas(word, ["Noun", "X"], ignore_case=True)
            else:
                return None
        elif pos_universal_google == "ADJ":
            if self.contains_entry(word, "Adjective"):
                return self.get_lemmas(word, "Adjective")
            elif self.contains_entry(word, "Adjective", ignore_case=True):
                return self.get_lemmas(word, "Adjective", ignore_case=True)
            # Account for possible errors in the POS tagger. This order was fine-tuned in terms of accuracy
            elif self.contains_entry(word, "Noun", ignore_case=True):
                return self.get_lemmas(word, "Noun", ignore_case=True)
            elif self.contains_entry(word, "X", ignore_case=True):
                return self.get_lemmas(word, "X", ignore_case=True)
            elif self.contains_entry(word, "Verb", ignore_case=True):
                return self.get_lemmas(word, "Verb", ignore_case=True)
            else:
                return None
        elif pos_universal_google in ["VERB", "AUX"]:
            if self.contains_entry(word, "Verb", ignore_case=True):
                return self.get_lemmas(word, "Verb", ignore_case=True)
            else:
                return None
        else:
            return None
898942
public Prep findWord(String word) {
    
    if (prepsMap.containsKey("*")) {
      word = "*";
    }
    
    return prepsMap.get(word);
  }
737742
def to_safe(self, word):
        '''  '''
        regex = "[^A-Za-z0-9\_"
        if not self.replace_dash_in_groups:
            regex += "\-"
        return re.sub(regex + "]", "_", word)
397328
def ix(self, word):
        
        temp = np.where(self.vocab == word)[0]
        if temp.size == 0:
            raise KeyError("Word not in vocabulary")
        else:
            return temp[0]
161587
def words(self, index = None):
        
        if index is None:
            return self.select(Word,None,True,default_ignore_structure)
        else:
            if index < 0:
                index = self.count(Word,None,True,default_ignore_structure) + index
            for i, e in enumerate(self.select(Word,None,True,default_ignore_structure)):
                if i == index:
                    return e
            raise IndexError
762902
def _find_spelling_errors_in_chunks(chunks,
                                    contents,
                                    valid_words_dictionary=None,
                                    technical_words_dictionary=None,
                                    user_dictionary_words=None):
    """"""
    for chunk in chunks:
        for error in spellcheck_region(chunk.data,
                                       valid_words_dictionary,
                                       technical_words_dictionary,
                                       user_dictionary_words):
            col_offset = _determine_character_offset(error.line_offset,
                                                     error.column_offset,
                                                     chunk.column)
            msg = _SPELLCHECK_MESSAGES[error.error_type].format(error.word)
            yield _populate_spelling_error(error.word,
                                           error.suggestions,
                                           contents,
                                           error.line_offset +
                                           chunk.line,
                                           col_offset,
                                           msg)
797968
def check(self, text):
        
        for word, pos in self.tokenizer(text):
            correct = self.dictionary.check(word)
            if correct:
                continue
            yield word, self.dictionary.suggest(word) if self.suggest else []
        return
466562
def spell(word):
    """"""
    w = Word(word)
    candidates = (common([word]) or exact([word]) or known([word]) or
                  known(w.typos()) or common(w.double_typos()) or
                  [word])
    correction = max(candidates, key=NLP_COUNTS.get)
    return get_case(word, correction)
880864
def get_word_under_cursor(self, WORD=False):
        
        start, end = self.find_boundaries_of_current_word(WORD=WORD)
        return self.text[self.cursor_position + start: self.cursor_position + end]
1027639
def writeWord(self, word):
        
        self.data.write(pack(self.endianness + ("H" if not self.signed else "h"), word))
1154167
def _word_badness(word):
    
    if word.endswith('e'):
        return len(word) - 2
    elif word.endswith('ess'):
        return len(word) - 10
    elif word.endswith('ss'):
        return len(word) - 4
    else:
        return len(word)
946620
def drop_edge_punct(word: str) -> str:
    
    if not word:
        return word
    try:
        if not word[0].isalpha():
            word = word[1:]
        if not word[-1].isalpha():
            word = word[:-1]
    except:
        pass
    return word
1200910
def getPattern(self, word):
        
        if word in self.patterns:
            return self.patterns[word]
        else:
            raise ValueError('Unknown pattern in getPattern().', word)