How to use the deepdish.io.ls.ValueNode function in deepdish

if isinstance(v, np.ndarray):
                node.add(name, NumpyArrayNode(v.shape, _format_dtype(v.dtype)))
            else:
                node.add(name, ValueNode(v))

        if (level._v_title.startswith('list:') or
                level._v_title.startswith('tuple:')):
            s = level._v_title.split(':', 1)[1]
            N = int(s)
            lst = ListNode(typename=level._v_title.split(':')[0])
            for i in range(N):
                t = node.children['i{}'.format(i)]
                lst.append(t)
            return lst
        elif level._v_title.startswith('nonetype:'):
            return ValueNode(None)
        elif is_pandas_dataframe(level):
            pandas_type = level._v_attrs['pandas_type']
            if raw:
                # Treat as regular dictionary
                pass
            elif pandas_type == 'frame':
                shape = _pandas_shape(level)
                new_node = PandasDataFrameNode(shape)
                return new_node
            elif pandas_type == 'series':
                try:
                    values = level._v_children['values']
                    size = len(values)
                    dtype = values.dtype
                except:
                    size = None

for name in level._v_attrs._f_list():
            v = level._v_attrs[name]
            if name == DEEPDISH_IO_VERSION_STR:
                node.header['dd_io_version'] = v

            if name == DEEPDISH_IO_UNPACK:
                node.header['dd_io_unpack'] = v

            if name.startswith(DEEPDISH_IO_PREFIX):
                continue

            if isinstance(v, np.ndarray):
                node.add(name, NumpyArrayNode(v.shape, _format_dtype(v.dtype)))
            else:
                node.add(name, ValueNode(v))

        if (level._v_title.startswith('list:') or
                level._v_title.startswith('tuple:')):
            s = level._v_title.split(':', 1)[1]
            N = int(s)
            lst = ListNode(typename=level._v_title.split(':')[0])
            for i in range(N):
                t = node.children['i{}'.format(i)]
                lst.append(t)
            return lst
        elif level._v_title.startswith('nonetype:'):
            return ValueNode(None)
        elif is_pandas_dataframe(level):
            pandas_type = level._v_attrs['pandas_type']
            if raw:
                # Treat as regular dictionary