<jupyter_start><jupyter_text>About**Wordle Assistant.** Developed by <NAME>Twitter: @sahaanirban Blog: www.anirbansaha.com Blog post: https://www.anirbansaha.com/wordle-assistant/  Version 1.0: 11 Feb 2022Version 1.1: 12 Feb 2022Changes in 1.1: * Default mode = exploratory mode, at only 1 level. Version 2.0: Contributors:   Please do this at first.<jupyter_code>dritte_word_list= 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curated_list={"liter","oscar"}
#Second Word List. We don't need this. But why not? 
#zweite_word_list=set({})
#file1 = open('/content/A lot of words.txt', 'r')
#Lines = file1.readlines()
#for line in Lines:
#  if line[0]=="*":
#    zweite_word_list.add(line.split(" ")[1].replace("\n",""))

#First Word List. We don't need this. But why not? 
word_list=set({})
import requests
from bs4 import BeautifulSoup
URL = "https://www.thefreedictionary.com/5-letter-words.htm"
r = requests.get(URL) 
soup = BeautifulSoup(r.content, 'html5lib')
result = soup.find(class_="TCont") 
result = result.find("ul")
for item in result:
  word_list.add(item.get_text()) 


#Formulating the final word list
#dritte_word_list = dritte_word_list.union(zweite_word_list)
#dritte_word_list = dritte_word_list.union(word_list)
#dritte_word_list = dritte_word_list.union(curated_list)<jupyter_output><empty_output><jupyter_text>Processing starts here<jupyter_code>def get_prob(word,prob_list):
  prob=1
  letters=set(split(word))
  for letter in letters:
    prob = prob*prob_list[letter]
  return prob

def create_letter_probability_sorted(word_list):
  letter_freq={}
  letter_probability={}
  for word in word_list: 
    letters=set(split(word))
    for letter in letters:
      if letter not in letter_freq:
        letter_freq[letter]=1
      else:
        letter_freq[letter]+=1
  
  occurance=0
  for key in letter_freq:
    occurance = occurance + letter_freq[key]
  
  for key in letter_freq:
    letter_probability[key] = letter_freq[key]/occurance
  
  letter_probability_sorted= dict(sorted(letter_probability.items(), key=lambda item: item[1],reverse=True))
  return letter_probability_sorted

def get_word_probability_list(word_set,prob_list): 
  prob_word_dict_try={}
  for word in word_set:
    no_unique_letters=len(set(split(word))) 
    prob_word=get_prob(word,prob_list)
    prob_word_dict_try[word]=prob_word 
  prob_word_dict_sorted= dict(sorted(prob_word_dict_try.items(), key=lambda item: item[1],reverse=True))
  return prob_word_dict_sorted
def split(word):
    return [char for char in word]

def find(s, ch):
    return [i for i, ltr in enumerate(s) if ltr == ch] 

def try_new_word(input_word,dsnt_contain,word_p,nw_positions):
  proceed = True
  alphabets_in_input=split(input_word)
  if len(alphabets_in_input)!=5: 
    return(False, "Error: Not a 5 lettered word.") 

  if proceed == True:
    for elem in alphabets_in_input:
      if elem in dsnt_contain: 
        return(False, "Error: "+elem+" should not be in the proposed word.") 
  
  if proceed == True:
    for key in word_p:
      positions=find(input_word,key) 
      if word_p[key] not in positions:
        return(False, "Error: "+key+" does not confirm fixed position clause.") 
  
  if proceed == True:
    for key in nw_positions:
      if input_word.find(key) == -1:
        return(False,"Error: "+key+" does not exist in word. Should be there.") 
      try:
        if input_word.find(key) in nw_positions[key]:
          return(False, "Error: "+key+" does not confirm variable position clause.") 
      except:
        print("Problem", input_word) 
  
  return proceed, "Success Text"


def update_criteria_using_input(input_sequence, does_not_contain,word_positions,not_word_positions): 
  nummer=0
  bigrams=[]
  try:
    while nummer<10:
        bigram=input_sequence[nummer:nummer+2]
        bigrams.append(bigram)
        if bigram[1] not in ["!","?"]: nummer+=1
        if bigram[1] in ["!","?"]: nummer+=2
  except:
    r_variable = "it is okay."

  try:
    index=0
    for bigram in bigrams:
      if len(bigram)>1:
        if bigram[1]=="!": 
          word_positions[bigram[0]]=index 
        elif bigram[1]=="?": 
          if bigram[0] in not_word_positions:
            not_word_positions[bigram[0]].append(index) 
          else: 
            not_word_positions[bigram[0]] = [index]
        else:
          if bigram[0] not in word_positions and bigram[0] not in not_word_positions:
            does_not_contain.add(bigram[0])
      elif len(bigram)>0 and len(bigram)<2 and bigram[0] not in ["!","?"]:
        if bigram[0] not in word_positions and bigram[0] not in not_word_positions:
            does_not_contain.add(bigram[0])
      index+=1

  except:
    print(bigrams)
    print("Error: Unknown.")
  
  return does_not_contain,word_positions,not_word_positions
def reduce_word_list(words_result_set,attempt_number,return_amount):
  letter_prob_list = create_letter_probability_sorted(words_result_set)
  word_prob_list = get_word_probability_list(words_result_set,letter_prob_list)
  new_list=word_prob_list
  if attempt_number<3 and len(words_result_set)>5:
    highest_num_letters = 0
    new_list={} 
    for key in word_prob_list:
      num_letters=len(set(split(key)))
      if num_letters> highest_num_letters:  highest_num_letters = num_letters
    
    for key in word_prob_list:
      num_letters=len(set(split(key)))
      if num_letters == highest_num_letters:
        new_list[key]=word_prob_list[key]

  return_array=[]
  count=0
  new_list_Arr= list(new_list.keys())
  while count<return_amount and count<len(new_list): 
    return_array.append(new_list_Arr[count])
    count+=1
  return return_array<jupyter_output><empty_output><jupyter_text>https://www.thefreedictionary.com/Word-Finder.htm<jupyter_code>def reduce_word_list_old(words_result_set): 
  word_u={}
  highest=0
  char_freq={}
  used_keys=[]
  return_words=[]

  #collects the keys that are already discovered. 
  for key in word_positions:
    used_keys.append(key)
  for key in not_word_positions:
    used_keys.append(key)

  for word in words_result_set:
    unique_letters=set(word) 
    if highest<len(unique_letters): highest =len(unique_letters)  
    word_u[word]=len(unique_letters) 

  for word in words_result_set:
    chars= split(word)
    for char in chars:
      if char not in used_keys: 
        if char not in char_freq: char_freq[char]=1
        else: char_freq[char]+=1

  char_freq = {k: v for k, v in sorted(char_freq.items(), key=lambda item: item[1], reverse=True)}
  result = list(char_freq.keys())[0]
  for word in words_result_set:
    if word.find(result)>-1 and word_u[word]==highest: 
      return_words.append(word)

  if len(return_words)<3: 
    for word in words_result_set:
      if word.find(result)>-1 and word_u[word]==highest-1: 
        return_words.append(word)
  return return_words
def help_user():
  print("We are sorry we ran out of vocabulary. But this information should help.")
  for key in not_word_positions:
    print(key, " is not in the following positions:")
    print(not_word_positions[key])
  
  for key in word_positions:
    print(key, " is in these positions:")
    print(word_positions[key])
def should_explore_mode(explore_mode, explore_mode_attempt_number): #exploreMode 
  if explore_mode == True and len(explore_mode_attempt_number)>1:
    found_alphabets = len(word_positions) + len(not_word_positions)
    new_test_list = set({})
    #print(word_positions)
    #print(not_word_positions)
    #print(does_not_contain)
    for key in word_positions:
      new_test_list.add(key)
    for key in not_word_positions:
      new_test_list.add(key) 
    for key in does_not_contain:
      new_test_list.add(key) 
    vowels={"a","e","i","o","u"}
    if all(ele in new_test_list for ele in vowels) == True or found_alphabets > 3: 
      explore_mode = False
      print("Info: Explore Mode is turned off.")
      #print("Either all vowels are used up OR we have found too many alphabets already.")
  return explore_mode<jupyter_output><empty_output><jupyter_text>Only Part to edit and USE.<jupyter_code>###########################
##### Change log. #########
###########################
# Version 1
# Made Public on 11 Feb 2022.
# Version 2
# Change ID: #exploreMode 
# Made Public on 12 Feb 2022. 
# Blog post: https://www.anirbansaha.com/wordle-assistant/ 
###########################

print("Info: Please enter 'stop' to stop the program from suggesting you words.")
agreement = ["yes", "yea", "y", "ja", "yup"]
explore_mode = True
does_not_contain = set({})
word_positions={} 
not_word_positions={} 
print("Help: WA!S?TE. ! signifies Green. ? signifies Yellow.")
number_of_options=3 #default 
explore_mode_attempt_number=[] #exploreMode 
number_of_options = 3

user_entry = "yes"
attempt_number=1
#Start of #exploreMode 
explore_mode_attempt_number=[1]
hard_mode = input("Want hard mode? ")
if hard_mode in agreement:
  explore_mode = False

print("Let's explore! ... ")
while user_entry in agreement:
  #print("point 1")
  explore_mode = should_explore_mode(explore_mode, explore_mode_attempt_number)

  input_sequence = input("Enter Sequence: ")
  
  if input_sequence == "stop": 
    print("I hope you've got the correct answer!")
    break
  
  #Start of #exploreMode 
  #print("point 2") 
  explore_mode = should_explore_mode(explore_mode, explore_mode_attempt_number)  
  if explore_mode == True and attempt_number in explore_mode_attempt_number: 
    #print("Explore Mode is ON.")  
    #values come in the changed "_new" variables.
    does_not_contain,word_positions,not_word_positions = update_criteria_using_input(input_sequence, does_not_contain,word_positions,not_word_positions)
    
    new_does_not_contain_bwn=set({})
    for elem in does_not_contain:
      new_does_not_contain_bwn.add(elem)
    for elem in word_positions:
      new_does_not_contain_bwn.add(elem)
    for elem in not_word_positions:
      new_does_not_contain_bwn.add(elem)

    word_positions_new={}
    not_word_positions_new ={} 
  else: 
    # End of #exploreMode  
    does_not_contain,word_positions,not_word_positions = update_criteria_using_input(input_sequence, does_not_contain,word_positions,not_word_positions)
    #print("point 3")
    explore_mode = should_explore_mode(explore_mode, explore_mode_attempt_number) 
  
  words_result_set=set({}) 
  #Start of #exploreMode  
  #print("point 4")
  explore_mode = should_explore_mode(explore_mode, explore_mode_attempt_number)
  if explore_mode == True and attempt_number in explore_mode_attempt_number:
    for word in dritte_word_list: 
      if try_new_word(word,new_does_not_contain_bwn,word_positions_new,not_word_positions_new)[0]==True:
        words_result_set.add(word) 
    
    #print("point 5")
    explore_mode = should_explore_mode(explore_mode, explore_mode_attempt_number)
    #explore_mode = False 
  else: 
    for word in dritte_word_list: 
      if try_new_word(word,does_not_contain,word_positions,not_word_positions)[0]==True:
        words_result_set.add(word)  
    #End of #exploreMode   
  
  if len(words_result_set)==0: 
    print("We have run out of words. Sorry to disappoint you.")
    help_user()
    break
  
  if len(words_result_set)==1: 
    print("Tip: This should be the answer!")
    user_entry = "no"
  
  if len(words_result_set)<4 and len(words_result_set)>1:
    print("Info: We are very close to the answer!")

  top_result=reduce_word_list(words_result_set,attempt_number,number_of_options) 
  print("Try: ",top_result)
  attempt_number+=1 
  if user_entry == "no": print("I hope you've got the correct answer!")<jupyter_output>Info: Please enter 'stop' to stop the program from suggesting you words.
Help: WA!S?TE. ! signifies Green. ? signifies Yellow.
Want hard mode? yes
Let's explore! ... 
Enter Sequence: crane
Try:  ['lousy', 'lusty', 'hotly']
Enter Sequence: l?ous?y
Try:  ['spilt', 'split']
Enter Sequence: s!pi!l!t
Info: We are very close to the answer!
Try:  ['skill', 'swill']
Enter Sequence: stop
I hope you've got the correct answer!
{'fraction_non_alphanumeric': 0.2729837915873745, 'fraction_numerical': 0.0035763501542095937, 'mean_word_length': 12.606696428571428, 'pattern_counts': {'":': 5, '<': 25, '<?xml version=': 0, '>': 26, 'https://': 4, 'lorem ipsum': 0, 'www.': 5, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '4', 'dir': 'jupyter-structured-clean-dedup', 'id': '543103', 'license': 'CC0-1.0', 'n_tokens_mistral': 11214, 'n_tokens_neox': 10706, 'n_words': 945, 'path': 'Wordle_Assistant_(incl_hard_mode).ipynb', 'repo_name': 'sahaanirbannew/wordle-assistant', 'size': '30484'}