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CHAR_FREQ = {
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    "zum latina": 278335,
    "zum livesex": 238194,
    "zum monster": 139168,
    "zum muschi": 185571,
    "zum outdoor": 139186,
    "zum porno": 187223,
    "zum private": 139216,
    "zum russische": 139170,
    "zum sex": 465287,
    "zum sexy": 139197,
    "zum teen": 511820,
    "zyban zyban": 234663,
    "zz zzz": 203566,
    "zzz zzzz": 203590,
    "Über uns": 227462,
    "útil esta": 140271,
    "über die": 187069
}


MOST_COMMON_BIGRAMS_LOWER = {k.lower():v for k,v in MOST_COMMON_BIGRAMS.items()}
TOP_50K = [k.encode('utf-8') for k,v in ENGLISH_ONE_GRAMS.items()][:50000]
WORDLIST = {word.decode().strip(): 0 for word in CRACKLIB_WORDLIST + TOP_50K}

from samson.auxiliary.tokenizer import Tokenizer
from samson.auxiliary.token_list_handler import TokenListHandler

TOKENIZER = Tokenizer([word for word, _ in WORDLIST.items() if len(word) > 2], TokenListHandler, delimiter=' ')
TOKENIZE  = TOKENIZER.tokenize