Initial commit

.gitattributes

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+# Auto detect text files and perform LF normalization
+* text=auto

data_cleaner.py

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+input_file_path = 'source_words.txt'
+output_file_path = 'cleaned_words.txt'
+
+input_file = open(input_file_path, 'r')
+output_file = open(output_file_path, 'w')
+
+def is_five_characters(word):
+    return len(word) == 5
+
+def is_only_letters(word):
+    return word.isalpha()
+
+
+for line in input_file:
+    word = line.strip()
+    if is_five_characters(word) and is_only_letters(word):
+        output_file.write(word.lower() + '\n')
+
+input_file.close()
+output_file.close()

wordle_solver.py

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+input_file_path = 'cleaned_words.txt'
+
+dictionary = open(input_file_path, 'r')
+
+char_not_in_word = ''
+char_in_word = ''
+
+# go through the dictionary and find the words that have the given characters
+def words_with_letters(letters, dictionary):
+    num_letters = len(letters)
+    valid_words = []
+    for word in dictionary:
+        word = word.strip()
+        match_amount = 0
+        for letter in letters:
+            if letter in word:
+                match_amount += 1
+            if match_amount == num_letters:
+                valid_words.append(word)
+    
+    return valid_words
+
+def words_without_letters(letters, dictionary):
+    valid_words = []
+    for word in dictionary:
+        word = word.strip()
+        is_valid = True
+        for letter in letters:
+            if letter in word:
+                is_valid = False
+                break
+        if is_valid:
+            valid_words.append(word)
+    
+    return valid_words
+
+def get_entropy(dict_size, valid_words)
+
+valid_words = words_without_letters("ira", dictionary)
+print(valid_words)