code: def treewidth_min_degree(G):
      """Returns a treewidth decomposition using the Minimum Degree heuristic.
  
      The heuristic chooses the nodes according to their degree, i.e., first
      the node with the lowest degree is chosen, then the graph is updated
      and the corresponding node is removed. Next, a new node with the lowest
      degree is chosen, and so on.
  
      Parameters
      ----------
      G : NetworkX graph
  
      Returns
      -------
      Treewidth decomposition : (int, Graph) tuple
            2-tuple with treewidth and the corresponding decomposed tree.
      """
      deg_heuristic = MinDegreeHeuristic(G)
      return treewidth_decomp(
          G, lambda graph: deg_heuristic.best_node(graph)
      )
  
file_path: networkx/networkx/algorithms/approximation/treewidth.py
imports: import itertools
  import sys
  from heapq import heapify, heappop, heappush
  import networkx
  from networkx.utils import not_implemented_for
label_desc: Use image node_id 1 for calling a global function with example usage: treewidth_min_degree(G) and returns: treewidth_decomp