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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def resolve(data_type, name=None, listify_default=False):
 """Retrieve the properties for a given data type. This is the main routine where most of the work is done. It converts Nani's data types into properties that can be used to define a new NumPy array and to wrap it into a view object. Use :func:`validate` to check if the input data type is well-formed. Parameters data_type : nani data type Type of the array elements. name : str Name for the view to be generated for the array. listify_default : bool ``True`` to output the default values with lists in place of tuples. This might cause the output to be incompatible with array creation routines such as ``numpy.array`` but it should still work for element assignment. Returns ------- nani.Nani The properties to use to initalize a NumPy array around the data type. Examples -------- Create a NumPy array where each element represents a color: <class 'nani.Color'> [255, 255, 255] [255, 255, 255] """

    data_type = _consolidate(data_type)
    return Nani(
        dtype=numpy.dtype(_resolve_dtype(data_type)),
        default=_resolve_default(data_type, listify=listify_default),
        view=_resolve_view(Array(element_type=data_type, shape=-1, name=name)))