code: def compose_all(graphs):
      """Returns the composition of all graphs.
  
      Composition is the simple union of the node sets and edge sets.
      The node sets of the supplied graphs need not be disjoint.
  
      Parameters
      ----------
      graphs : iterable
         Iterable of NetworkX graphs
  
      Returns
      -------
      C : A graph with the same type as the first graph in list
  
      Raises
      ------
      ValueError
         If `graphs` is an empty list.
  
      NetworkXError
          In case of mixed type graphs, like MultiGraph and Graph, or directed and undirected graphs.
  
      Examples
      --------
      >>> G1 = nx.Graph([(1, 2), (2, 3)])
      >>> G2 = nx.Graph([(3, 4), (5, 6)])
      >>> C = nx.compose_all([G1, G2])
      >>> list(C.nodes())
      [1, 2, 3, 4, 5, 6]
      >>> list(C.edges())
      [(1, 2), (2, 3), (3, 4), (5, 6)]
  
      Notes
      -----
      For operating on mixed type graphs, they should be converted to the same type.
  
      Graph, edge, and node attributes are propagated to the union graph.
      If a graph attribute is present in multiple graphs, then the value
      from the last graph in the list with that attribute is used.
      """
      R = None
  
      # add graph attributes, H attributes take precedent over G attributes
      for i, G in enumerate(graphs):
          if i == 0:
              # create new graph
              R = G.__class__()
          elif G.is_directed() != R.is_directed():
              raise nx.NetworkXError(
                  "All graphs must be directed or undirected."
              )
          elif G.is_multigraph() != R.is_multigraph():
              raise nx.NetworkXError(
                  "All graphs must be graphs or multigraphs."
              )
  
          R.graph.update(G.graph)
          R.add_nodes_from(G.nodes(data=True))
          R.add_edges_from(
              G.edges(keys=True, data=True)
              if G.is_multigraph()
              else G.edges(data=True)
          )
  
      if R is None:
          raise ValueError("cannot apply compose_all to an empty list")
  
      return R
  
imports: from itertools import chain, repeat
  import networkx
label_desc: Use image node_id 3 for calling a global function with example usage: compose_all(graphs) and returns: R