code: def find_cycle(G, source=None, orientation=None):
      """Returns a cycle found via depth-first traversal.
  
      The cycle is a list of edges indicating the cyclic path.
      Orientation of directed edges is controlled by `orientation`.
  
      Parameters
      ----------
      G : graph
          A directed/undirected graph/multigraph.
  
      source : node, list of nodes
          The node from which the traversal begins. If None, then a source
          is chosen arbitrarily and repeatedly until all edges from each node in
          the graph are searched.
  
      orientation : None | 'original' | 'reverse' | 'ignore' (default: None)
          For directed graphs and directed multigraphs, edge traversals need not
          respect the original orientation of the edges.
          When set to 'reverse' every edge is traversed in the reverse direction.
          When set to 'ignore', every edge is treated as undirected.
          When set to 'original', every edge is treated as directed.
          In all three cases, the yielded edge tuples add a last entry to
          indicate the direction in which that edge was traversed.
          If orientation is None, the yielded edge has no direction indicated.
          The direction is respected, but not reported.
  
      Returns
      -------
      edges : directed edges
          A list of directed edges indicating the path taken for the loop.
          If no cycle is found, then an exception is raised.
          For graphs, an edge is of the form `(u, v)` where `u` and `v`
          are the tail and head of the edge as determined by the traversal.
          For multigraphs, an edge is of the form `(u, v, key)`, where `key` is
          the key of the edge. When the graph is directed, then `u` and `v`
          are always in the order of the actual directed edge.
          If orientation is not None then the edge tuple is extended to include
          the direction of traversal ('forward' or 'reverse') on that edge.
  
      Raises
      ------
      NetworkXNoCycle
          If no cycle was found.
  
      Examples
      --------
      In this example, we construct a DAG and find, in the first call, that there
      are no directed cycles, and so an exception is raised. In the second call,
      we ignore edge orientations and find that there is an undirected cycle.
      Note that the second call finds a directed cycle while effectively
      traversing an undirected graph, and so, we found an "undirected cycle".
      This means that this DAG structure does not form a directed tree (which
      is also known as a polytree).
  
      >>> G = nx.DiGraph([(0, 1), (0, 2), (1, 2)])
      >>> nx.find_cycle(G, orientation="original")
      Traceback (most recent call last):
          ...
      networkx.exception.NetworkXNoCycle: No cycle found.
      >>> list(nx.find_cycle(G, orientation="ignore"))
      [(0, 1, 'forward'), (1, 2, 'forward'), (0, 2, 'reverse')]
  
      See Also
      --------
      simple_cycles
      """
      if not G.is_directed() or orientation in (None, "original"):
  
          def tailhead(edge):
              return edge[:2]
  
      elif orientation == "reverse":
  
          def tailhead(edge):
              return edge[1], edge[0]
  
      elif orientation == "ignore":
  
          def tailhead(edge):
              if edge[-1] == "reverse":
                  return edge[1], edge[0]
              return edge[:2]
  
      explored = set()
      cycle = []
      final_node = None
      for start_node in G.nbunch_iter(source):
          if start_node in explored:
              # No loop is possible.
              continue
  
          edges = []
          # All nodes seen in this iteration of edge_dfs
          seen = {start_node}
          # Nodes in active path.
          active_nodes = {start_node}
          previous_head = None
  
          for edge in nx.edge_dfs(G, start_node, orientation):
              # Determine if this edge is a continuation of the active path.
              tail, head = tailhead(edge)
              if head in explored:
                  # Then we've already explored it. No loop is possible.
                  continue
              if previous_head is not None and tail != previous_head:
                  # This edge results from backtracking.
                  # Pop until we get a node whose head equals the current tail.
                  # So for example, we might have:
                  #  (0, 1), (1, 2), (2, 3), (1, 4)
                  # which must become:
                  #  (0, 1), (1, 4)
                  while True:
                      try:
                          popped_edge = edges.pop()
                      except IndexError:
                          edges = []
                          active_nodes = {tail}
                          break
                      else:
                          popped_head = tailhead(popped_edge)[1]
                          active_nodes.remove(popped_head)
  
                      if edges:
                          last_head = tailhead(edges[-1])[1]
                          if tail == last_head:
                              break
              edges.append(edge)
  
              if head in active_nodes:
                  # We have a loop!
                  cycle.extend(edges)
                  final_node = head
                  break
              else:
                  seen.add(head)
                  active_nodes.add(head)
                  previous_head = head
  
          if cycle:
              break
          else:
              explored.update(seen)
  
      else:
          assert len(cycle) == 0
          raise nx.exception.NetworkXNoCycle("No cycle found.")
  
      # We now have a list of edges which ends on a cycle.
      # So we need to remove from the beginning edges that are not relevant.
  
      for i, edge in enumerate(cycle):
          tail, head = tailhead(edge)
          if tail == final_node:
              break
  
      return cycle[i:]
  
imports: from collections import Counter, defaultdict
  from itertools import combinations, product
  from math import inf
  import networkx
  from networkx.utils import not_implemented_for, pairwise
label_desc: Use image node_id 10 for calling a global function with example usage: find_cycle(G, source, orientation) and returns: cycle, edge, edge,  edge, edge, edge,  edge