def tokenize_and_filter(text, min_word_length=3, stopwords=None):
    tokens = tokenize(text)
    # TODO(mikhaildubov): Add language detection
    stopwords = stopwords or set(word.upper() for word in nltk_stopwords.words("english"))
    return [token for token in tokens
            if min_word_length >= len(token) and token not in stopwords]
dataset/ETHPy150Open mikhaildubov/AST-text-analysis/east/utils.py/tokenize_and_filter/swapped operands of `>=`