text: import re
  from collections import Counter, defaultdict
  from pathlib import Path
  from typing import Optional, Tuple, DefaultDict, Set
  import random
  from sys import stderr
  
  random.seed(17)
  
  
  class Spell:
      # Smoothing variable
      alpha = 1
  
      # Weighing the spell-errors and corpus.
      # Determined by hand regarding the test set.
      ERROR_COEFFICIENT = 30
  
      # Using the spell-errors corrections in the corpus
      # in a weighted manner.
      # ~8k words!
      SPELL_ERROR_TRUST = 3
  
      def __init__(self, corpus: Path, prob_type: str, spell_errors: Path):
          self.prepare_corpus(corpus, prob_type)
          
          self.prepare_spell_error_dict(spell_errors)
  
          self.f = self.P_simple if prob_type.lower() == "simple" else self.P_smooth
  
      def prepare_corpus(self, corpus: Path, prob_type: str):
          """Read the corpus file, count every token."""
          self.words = Counter(
              re.findall(r'\w+', open(corpus).read().lower()))
          # corpus size
          self.N = float(sum(self.words.values()))
          # used for size in smoothing
          self.Nplus = self.N + self.alpha * (len(self.words)+1)
  
          # for using the spell-errors corrections in the corpus.
          if hasattr(self, "errors"):
              for v_l in self.errors.values():
                  for v in v_l:
                      self.words[v] += self.SPELL_ERROR_TRUST
  
      def prepare_spell_error_dict(self, path: Path):
          """Read the spell-error file,
          keep them in their counters for every misspelled word."""
          self.errors: DefaultDict[Counter] = defaultdict(Counter)
          self.N_error: float = 0
  
          with open(path, "r") as f:
              for line in f.readlines():
                  target, s = line.split(": ", maxsplit=1)
                  tokens = s.split(", ")
                  for mis in tokens:
                      pair = mis.rstrip().split("*")
                      mis = pair[0]
                      weight = int(pair[1]) if len(pair) == 2 else 1
                      self.errors[mis][target] += weight
      
          count = 0
          for v_l in self.errors.values():
              for v in v_l:
                  count += 1
                  # for using the spell-errors corrections in the corpus.
                  if hasattr(self, "words"):
                      self.words[v] += self.SPELL_ERROR_TRUST
  
          self.N_error = float(count)
  
      def P_simple(self, word): 
          """Probability of `word`."""
          return self.words[word] / self.N
  
      def P_smooth(self, word):
          """Smoothed probability of `word`"""
          return (self.words[word] + self.alpha) / self.Nplus
  
      def max_from_corpus(self, word) -> Optional[Tuple[str, float]]:
          """Best suggestion and its probability from corpus."""
          candids = self.candidates(word)
          if not candids:
              return "", 0
          maxes: Set[str] = set()
          cur_max_prob = 0
          for c in candids:
              cur_prob = self.f(c)
              if cur_prob > cur_max_prob:
                  maxes = set([c])
                  cur_max_prob = cur_prob
          return random.choice(list(maxes)), cur_max_prob
  
      def max_from_spell_errors(self, word) -> Optional[Tuple[str, float]]:
          """Best suggestion and its probability from spell-errors."""
          spelling_error_counter = self.errors[word]
          spelling_common = spelling_error_counter.most_common(1)
          if spelling_common:
              maxes = [(key, value) for key, value in spelling_error_counter.items() if value == spelling_common[0][1]]
              key, value = random.choice(maxes)
              value /= self.N_error
              value = value * self.ERROR_COEFFICIENT
          else:
              key, value = "", 0
          return key, value
  
      def correct(self, word): 
          """Most probable spelling correction for word."""
  
          is_word_known = word in self.words
          if is_word_known:
              return word
  
          best_word, prob = self.max_from_corpus(word)
          key, value = self.max_from_spell_errors(word)
  
          if prob > value:
              return best_word
          else:
              return key
  
      def candidates(self, word):
          """Generate possible spelling corrections for word."""
          return self.known([word]) or self.known(self.edits1(word))
  
      def known(self, words):
          """The subset of `words` that appear in the dictionary of WORDS."""
          return set(w for w in words if w in self.words)
  
      @staticmethod
      def edits1(word: str):
          """All edits that are one edit away from `word`."""
          letters    = 'abcdefghijklmnopqrstuvwxyz'
          splits     = [(word[:i], word[i:])    for i in range(len(word) + 1)]
          deletes    = [L + R[1:]               for L, R in splits if R]
          transposes = [L + R[1] + R[0] + R[2:] for L, R in splits if len(R)>1]
          replaces   = [L + c + R[1:]           for L, R in splits if R for c in letters]
          inserts    = [L + c + R               for L, R in splits for c in letters]
          return set(deletes + transposes + replaces + inserts)
  