added all functionality; testing

hangman.py

@@ -1,11 +1,59 @@
-import random
+import codecs
+import functools
+import hashlib
+import json
+import pickle
+import re
+import sys
+
+#32 or 64 bit platform?
+if sys.maxsize > 2**32:
+    HASH_FUNC = hashlib.blake2b
+else:
+    HASH_FUNC = hashlib.blake2s
+
 def load_words(filename):
-with open(filename) as file:
-    text = file.read()
-WORDS = set(map(str.lower,filter(bool,text.split('\n'))))
-#TODO: cache wordfreq with hash of words
+    with open(filename) as file:
+        text = file.read()
+    return set(map(str.lower,filter(bool,text.split('\n'))))
+
+@functools.lru_cache(maxsize=None)
+def _get_wordlist_hash(word_list_s):
+    hash = HASH_FUNC()
+    for word in sorted(word_list_s):
+        word_bytes = word.encdode()
+        hash.update(word_bytes)
+    return hash.digest()
+
+def hash_wordlist(word_list,raw = False):
+    hash = HASH_FUNC()
+    word_list = sorted(word_list)
+    fhash = _get_wordlist_hash(word_list)
+    if raw:
+        return fhash
+    illegal_hash = codecs.encdode(fhash,'base64').decode()
+    t_table = str.maketrans({'+':'-','/':'_'})
+    return illegal_hash.translate(t_table)
+
+def load_freq_cache(word_list):
+    fname = hash_wordlist(word_list) + '.pkl'
+    fname = os.path.join('__hangchache__',fname)
+    if os.path.exists(fname):
+        with open(fname,'rb') as file:
+            return pickle.load(file)
+
+def save_freq_cache(word_list,freq):
+    if not os.path.exists('__hangchache__'):
+        os.mkdir('__hangchache__')
+    fname = hash_wordlist(word_list) + '.pkl'
+    fname = os.path.join('__hangchache__',fname)
+    with open(fname,'wb') as file:
+        pickle.dump(file,freq)
 
 def generate_letter_frequency(word_list):
+    cached = load_freq_cache(word_list)
+    if cached is not None:
+        return cached
     ret = {}
     for word_num,word in enumerate(word_list):
         letter_counts = {}
@@ -21,8 +69,27 @@ def generate_letter_frequency(word_list):
             avg = (ret[letter][1] * word_num)  + word_portion
             avg /= word_num + 1
             ret[letter][1] = avg
-
+    if cached is None:
+        save_freq_cache(word_list,ret)
     return ret
+PROMPT = "Enter word with '.' to represent missing letters: "
+def iterate(word_list,let_freq):
+    entered_word = input(PROMPT)
+    entered_word = entered_word.replace(' ')
+    entered_letters = set(letter for letter in entered_word.replace('.',''))
+    remaining_letters = set(let_freq.keys()) - entered_letters
+    regex = entered_word.replace('.','[A-Za-z]')
+    remaining_possibilities = list(filter(lambda word: re.match(regex,word),word_list))
+    print('Matches found:\n' + '\n'.join(remaining_possibilities[i] for i in range(min(30,len(remaining_possibilities)))))
+    print( 'Good candidates by overall frequency:\n' + '\n'.join(sorted(remaining_letters,key = lambda letter: let_freq[letter][0],reverse = True)) )
+    print('Good candidates by per-word frequency:\n' + '\n'.join(sorted(remaining_letters,key = lambda letter: let_freq[letter][1],reverse = True)) )
+    return entered_word,remaining_possibilities
 
 if __name__ == "__main__":
-    l = generate_letter_frequency(WORDS)
+    words = load_words('words.txt')
+    FREQ = generate_letter_frequency(words)
+    while True:
+        try:
+            last,WORDS = iterate(words,FREQ)
+        except KeyboardInterrupt:
+            break