def file_corpus(filename, encoding='utf8', nltk_stop=True, stop_freq=1, 
                add_stop=None, decode=False, simple=False):
    """
    `file_corpus` is a convenience function for generating Corpus
    objects from a a plain text corpus contained in a single string
    `file_corpus` will strip punctuation and arabic numerals outside
    the range 1-29. All letters are made lowercase.

    :param filename: File name of the plain text file.
    :type plain_dir: string-like
    
    :param nltk_stop: If `True` then the corpus object is masked 
        using the NLTK English stop words. Default is `False`.
    :type nltk_stop: boolean, optional
    
    :param stop_freq: The upper bound for a word to be masked on 
        the basis of its collection frequency. Default is 1.
    :type stop_freq: int, optional
    
    :param add_stop: A list of stop words. Default is `None`.
    :type add_stop: array-like, optional

    :returns: c : a Corpus object
        Contains the tokenized corpus built from the input plain-text
        corpus. Document tokens are named `documents`.
    
    :See Also: :class:`vsm.corpus.Corpus`, 
        :meth:`file_tokenize`, 
        :meth:`vsm.corpus.util.apply_stoplist`
    """
    if encoding in 'detect':
        encoding = detect_encoding(filename)
    try:
        with open(filename, mode='r', encoding=encoding) as f:
            text = f.read()
    except UnicodeDecodeError: 
        encoding = detect_encoding(filename)

    if decode:
        text = unidecode(text)

    words, tok, sent = file_tokenize(text)
    names, data = zip(*tok.items())
    
    c = CorpusSent(words, sent, context_data=data, context_types=names,
                    remove_empty=False)
    in_place_stoplist(c, nltk_stop=nltk_stop,
                       freq=stop_freq, add_stop=add_stop)

    return c
dataset/ETHPy150Open inpho/vsm/vsm/extensions/ldasentences.py/file_corpus/operator `==` -> `in`