code: def is_biconnected(G):
      """Returns True if the graph is biconnected, False otherwise.
  
      A graph is biconnected if, and only if, it cannot be disconnected by
      removing only one node (and all edges incident on that node).  If
      removing a node increases the number of disconnected components
      in the graph, that node is called an articulation point, or cut
      vertex.  A biconnected graph has no articulation points.
  
      Parameters
      ----------
      G : NetworkX Graph
          An undirected graph.
  
      Returns
      -------
      biconnected : bool
          True if the graph is biconnected, False otherwise.
  
      Raises
      ------
      NetworkXNotImplemented
          If the input graph is not undirected.
  
      Examples
      --------
      >>> G = nx.path_graph(4)
      >>> print(nx.is_biconnected(G))
      False
      >>> G.add_edge(0, 3)
      >>> print(nx.is_biconnected(G))
      True
  
      See Also
      --------
      biconnected_components
      articulation_points
      biconnected_component_edges
      is_strongly_connected
      is_weakly_connected
      is_connected
      is_semiconnected
  
      Notes
      -----
      The algorithm to find articulation points and biconnected
      components is implemented using a non-recursive depth-first-search
      (DFS) that keeps track of the highest level that back edges reach
      in the DFS tree.  A node `n` is an articulation point if, and only
      if, there exists a subtree rooted at `n` such that there is no
      back edge from any successor of `n` that links to a predecessor of
      `n` in the DFS tree.  By keeping track of all the edges traversed
      by the DFS we can obtain the biconnected components because all
      edges of a bicomponent will be traversed consecutively between
      articulation points.
  
      References
      ----------
      .. [1] Hopcroft, J.; Tarjan, R. (1973).
         "Efficient algorithms for graph manipulation".
         Communications of the ACM 16: 372–378. doi:10.1145/362248.362272
  
      """
      bccs = biconnected_components(G)
      try:
          bcc = next(bccs)
      except StopIteration:
          # No bicomponents (empty graph?)
          return False
      try:
          next(bccs)
      except StopIteration:
          # Only one bicomponent
          return len(bcc) == len(G)
      else:
          # Multiple bicomponents
          return False
  
file_path: networkx/networkx/algorithms/components/biconnected.py
imports: from itertools import chain
  import networkx
  from networkx.utils.decorators import not_implemented_for
label_desc: Use image node_id 1 for calling a global function with example usage: is_biconnected(G) and returns: False, False, unknown