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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 ply_binary(elements, file_obj):
 """ Load the data from a binary PLY file into the elements data structure. Parameters elements: OrderedDict object, populated from the file header. object will be modified to add data by this function. file_obj: open file object, with current position at the start of the data section (past the header) """


    def populate_listsize(file_obj, elements):
        """
        Given a set of elements populated from the header if there are any
        list properties seek in the file the length of the list.

        Note that if you have a list where each instance is different length
        (if for example you mixed triangles and quads) this won't work at all
        """
        p_start = file_obj.tell()
        p_current = file_obj.tell()
        for element_key, element in elements.items():
            props = element['properties']
            prior_data = ''
            for k, dtype in props.items():
                if '$LIST' in dtype:
                    # every list field has two data types:
                    # the list length (single value), and the list data (multiple)
                    # here we are only reading the single value for list length
                    field_dtype = np.dtype(dtype.split(',')[0])
                    if len(prior_data) == 0:
                        offset = 0
                    else:
                        offset = np.dtype(prior_data).itemsize
                    file_obj.seek(p_current + offset)
                    size = np.frombuffer(file_obj.read(field_dtype.itemsize),
                                         dtype=field_dtype)[0]
                    props[k] = props[k].replace('$LIST', str(size))
                prior_data += props[k] + ','
            itemsize = np.dtype(', '.join(props.values())).itemsize
            p_current += element['length'] * itemsize
        file_obj.seek(p_start)

    def populate_data(file_obj, elements):
        """
        Given the data type and field information from the header,
        read the data and add it to a 'data' field in the element.
        """
        for key in elements.keys():
            items = list(elements[key]['properties'].items())
            dtype = np.dtype(items)
            data = file_obj.read(elements[key]['length'] * dtype.itemsize)
            elements[key]['data'] = np.frombuffer(data,
                                                  dtype=dtype)
        return elements

    def elements_size(elements):
        """
        Given an elements data structure populated from the header,
        calculate how long the file should be if it is intact.
        """
        size = 0
        for element in elements.values():
            dtype = np.dtype(','.join(element['properties'].values()))
            size += element['length'] * dtype.itemsize
        return size

    # some elements are passed where the list dimensions
    # are not included in the header, so this function goes
    # into the meat of the file and grabs the list dimensions
    # before we to the main data read as a single operation
    populate_listsize(file_obj, elements)

    # how many bytes are left in the file
    size_file = util.distance_to_end(file_obj)
    # how many bytes should the data structure described by
    # the header take up
    size_elements = elements_size(elements)

    # if the number of bytes is not the same the file is probably corrupt
    if size_file != size_elements:
        raise ValueError('File is unexpected length!')

    # with everything populated and a reasonable confidence the file
    # is intact, read the data fields described by the header
    populate_data(file_obj, elements)