code: 
  
  
  from __future__ import annotations
  
  import random
  
  # Adjacency list representation of this graph:
  # https://en.wikipedia.org/wiki/File:Single_run_of_Karger%E2%80%99s_Mincut_algorithm.svg
  __lowerCamelCase       :       Union[str, Any]				   =			{
      "1": ["2", "3", "4", "5"],
      "2": ["1", "3", "4", "5"],
      "3": ["1", "2", "4", "5", "10"],
      "4": ["1", "2", "3", "5", "6"],
      "5": ["1", "2", "3", "4", "7"],
      "6": ["7", "8", "9", "10", "4"],
      "7": ["6", "8", "9", "10", "5"],
      "8": ["6", "7", "9", "10"],
      "9": ["6", "7", "8", "10"],
      "10": ["6", "7", "8", "9", "3"],
  }
  
  
  
  def 	SCREAMING_SNAKE_CASE__						(							snake_case_	)			->							Optional[int]:
  				A__     :							Any   				={node: {node} for node in graph}
  
  				A__     :							str   				={node: graph[node][:] for node in graph}
  
  				while len(snake_case_	) > 2:
  								# Choose a random edge.
  								A__     :							Union[str, Any]   				=random.choice(list(graph_copy.keys()	)	)
  								A__     :							Optional[Any]   				=random.choice(graph_copy[u]	)
  
  								# Contract edge (u, v) to new node uv
  								A__     :							Tuple   				=u + v
  								A__     :							Optional[int]   				=list(set(graph_copy[u] + graph_copy[v]	)	)
  								uv_neighbors.remove(snake_case_	)
  								uv_neighbors.remove(snake_case_	)
  								A__     :							List[str]   				=uv_neighbors
  								for neighbor in uv_neighbors:
  												graph_copy[neighbor].append(snake_case_	)
  
  								A__     :							Any   				=set(contracted_nodes[u].union(contracted_nodes[v]	)	)
  
  								# Remove nodes u and v.
  								del graph_copy[u]
  								del graph_copy[v]
  								for neighbor in uv_neighbors:
  												if u in graph_copy[neighbor]:
  																graph_copy[neighbor].remove(snake_case_	)
  												if v in graph_copy[neighbor]:
  																graph_copy[neighbor].remove(snake_case_	)
  
      # Find cutset.
  				A__     :							Optional[int]   				=[contracted_nodes[node] for node in graph_copy]
  				return {
  				    (node, neighbor)
  				    for node in groups[0]
  				    for neighbor in graph[node]
  				    if neighbor in groups[1]
  				}
  
  
  if __name__ == "__main__":
  						print(partition_graph(TEST_GRAPH))
  
  
  
  
style_context: 
  
  
  from __future__ import annotations
  
  
  
  def   SCREAMING_SNAKE_CASE__						(							snake_case_	)			->							list[int]:
  				A__     :							Optional[int]   				=[0] * len(snake_case_	)
  				for i in range(1,	len(snake_case_	)	):
  								A__     :							List[Any]   				=duration_times[i - 1] + waiting_times[i - 1]
  				return waiting_times
  
  
  
  def   SCREAMING_SNAKE_CASE__						(							snake_case_,	snake_case_	)			->							list[int]:
  				return [
  				    duration_time + waiting_times[i]
  				    for i, duration_time in enumerate(snake_case_	)
  				]
  
  
  
  def   SCREAMING_SNAKE_CASE__						(							snake_case_	)			->							float:
  				return sum(snake_case_	) / len(snake_case_	)
  
  
  
  def   SCREAMING_SNAKE_CASE__						(							snake_case_	)			->							float:
  				return sum(snake_case_	) / len(snake_case_	)
  
  
  if __name__ == "__main__":
  						# process id's
  						__lowerCamelCase       :       List[str]				   =			[1, 2, 3]
  
  						# ensure that we actually have processes
  						if len(processes) == 0:
  												print("Zero amount of processes")
  												raise SystemExit(0)
  
  						# duration time of all processes
  						__lowerCamelCase       :       Dict				   =			[19, 8, 9]
  
  						# ensure we can match each id to a duration time
  						if len(duration_times) != len(processes):
  												print("Unable to match all id's with their duration time")
  												raise SystemExit(0)
  
  						# get the waiting times and the turnaround times
  						__lowerCamelCase       :       int				   =			calculate_waiting_times(duration_times)
  						__lowerCamelCase       :       Optional[int]				   =			calculate_turnaround_times(duration_times, waiting_times)
  
  						# get the average times
  						__lowerCamelCase       :       List[str]				   =			calculate_average_waiting_time(waiting_times)
  						__lowerCamelCase       :       Dict				   =			calculate_average_turnaround_time(turnaround_times)
  
  						# print all the results
  						print("Process ID\tDuration Time\tWaiting Time\tTurnaround Time")
  						for i, process in enumerate(processes):
  												print(
  												    F"{process}\t\t{duration_times[i]}\t\t{waiting_times[i]}\t\t"
  												    F"{turnaround_times[i]}"
  												)
  						print(F"Average waiting time = {average_waiting_time}")
  						print(F"Average turn around time = {average_turnaround_time}")
  
  
  
  