How to use the normality.stringify.stringify function in normality

This will take a string and apply a set of transformations to it so
    that it can be processed more easily afterwards. Arguments:

    * ``lowercase``: not very mysterious.
    * ``collapse``: replace multiple whitespace-like characters with a
      single whitespace. This is especially useful with category replacement
      which can lead to a lot of whitespace.
    * ``decompose``: apply a unicode normalization (NFKD) to separate
      simple characters and their diacritics.
    * ``replace_categories``: This will perform a replacement of whole
      classes of unicode characters (e.g. symbols, marks, numbers) with a
      given character. It is used to replace any non-text elements of the
      input string.
    """
    text = stringify(text, encoding_default=encoding_default,
                     encoding=encoding)
    if text is None:
        return

    if lowercase:
        # Yeah I made a Python package for this.
        text = text.lower()

    if ascii:
        # A stricter form of transliteration that leaves only ASCII
        # characters.
        text = ascii_text(text)
    elif latinize:
        # Perform unicode-based transliteration, e.g. of cyricllic
        # or CJK scripts into latin.
        text = latinize_text(text)

def _safe_name(file_name, sep):
    """Convert the file name to ASCII and normalize the string."""
    file_name = stringify(file_name)
    if file_name is None:
        return
    file_name = ascii_text(file_name)
    file_name = category_replace(file_name, UNICODE_CATEGORIES)
    file_name = collapse_spaces(file_name)
    if file_name is None or not len(file_name):
        return
    return file_name.replace(WS, sep)

def slugify(text, sep='-'):
    """A simple slug generator."""
    text = stringify(text)
    if text is None:
        return None
    text = text.replace(sep, WS)
    text = normalize(text, ascii=True)
    if text is None:
        return None
    return text.replace(WS, sep)