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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 add_nodes_from(self, nodes, **attr):
 """Add multiple nodes. Parameters nodes : iterable container A container of nodes (list, dict, set, etc.). OR A container of (node, attribute dict) tuples. Node attributes are updated using the attribute dict. attr : keyword arguments, optional (default= no attributes) Update attributes for all nodes in nodes. Node attributes specified in nodes as a tuple take precedence over attributes specified generally. See Also -------- add_node Examples -------- (2, {'layers':{'token'}, 'word':'world'})]) [(1, {'layers': {'token'}, 'word': 'hello'}), (2, {'layers': {'token'}, 'word': 'world'})] Use keywords to update specific node attributes for every node. [(1, {'layers': {'token'}, 'weight': 1.0, 'word': 'hello'}), (2, {'layers': {'token'}, 'weight': 1.0, 'word': 'world'})] Use (node, attrdict) tuples to update attributes for specific nodes. [(1, {'layers': {'tiger', 'token'}, 'size': 10, 'weight': 1.0, 'word': 'hello'}), (2, {'layers': {'token'}, 'weight': 1.0, 'word': 'world'})] """

        additional_attribs = attr  # will be added to each node
        for n in nodes:
            try:  # check, if n is a node_id or a (node_id, attrib dict) tuple
                newnode = n not in self.succ  # is node in the graph, yet?
            except TypeError:  # n is a (node_id, attribute dict) tuple
                node_id, ndict = n

                if not 'layers' in ndict:
                    ndict['layers'] = {self.ns}

                layers = ndict['layers']
                assert isinstance(layers, set), \
                    "'layers' must be specified as a set of strings."
                assert all((isinstance(layer, str) for layer in layers)), \
                    "All elements of the 'layers' set must be strings."

                if node_id not in self.succ:  # node doesn't exist, yet
                    self.succ[node_id] = {}
                    self.pred[node_id] = {}
                    newdict = additional_attribs.copy()
                    newdict.update(ndict)  # all given attribs incl. layers
                    self.node[node_id] = newdict
                else:  # node already exists
                    existing_layers = self.node[node_id]['layers']
                    all_layers = existing_layers.union(layers)

                    self.node[node_id].update(ndict)
                    self.node[node_id].update(additional_attribs)
                    self.node[node_id].update({'layers': all_layers})
                continue  # process next node

            # newnode check didn't raise an exception
            if newnode:  # n is a node_id and it's not in the graph, yet
                self.succ[n] = {}
                self.pred[n] = {}
                self.node[n] = attr.copy()
                # since the node isn't represented as a
                # (node_id, attribute dict) tuple, we don't know which layers
                # it is part of. Therefore, we'll add the namespace of the
                # graph as the node layer
                self.node[n].update({'layers': set([self.ns])})
            else:  # n is a node_id and it's already in the graph
                self.node[n].update(attr)