import argparse
import copy



def   __A		(			_A					):



 """simple docstring"""


 __a       =  {}

 with open(_A					) as f:
  for line in f:
   if line.split()[0] not in dict_of_neighbours:
    __a       =  []
    _list.append([line.split()[1], line.split()[2]]					)
    __a       =  _list
   else:
    dict_of_neighbours[line.split()[0]].append(
        [line.split()[1], line.split()[2]]					)
   if line.split()[1] not in dict_of_neighbours:
    __a       =  []
    _list.append([line.split()[0], line.split()[2]]					)
    __a       =  _list
   else:
    dict_of_neighbours[line.split()[1]].append(
        [line.split()[0], line.split()[2]]					)

 return dict_of_neighbours



def   __A		(			_A							,				_A					):



 """simple docstring"""


 with open(_A					) as f:
  __a       =  f.read(1					)
 __a       =  start_node

 __a       =  []

 __a       =  start_node

 __a       =  0
 while visiting not in first_solution:
  __a       =  1_0000
  for k in dict_of_neighbours[visiting]:
   if int(k[1]					) < int(_A					) and k[0] not in first_solution:
    __a       =  k[1]
    __a       =  k[0]

  first_solution.append(_A					)
  __a       =  distance_of_first_solution + int(_A					)
  __a       =  best_node

 first_solution.append(_A					)

 __a       =  0
 for k in dict_of_neighbours[first_solution[-2]]:
  if k[0] == start_node:
   break
  position += 1

 __a       =  (
     distance_of_first_solution
     + int(dict_of_neighbours[first_solution[-2]][position][1]					)
     - 1_0000
 )
 return first_solution, distance_of_first_solution



def   __A		(			_A							,				_A					):



 """simple docstring"""


 __a       =  []

 for n in solution[1:-1]:
  __a       =  solution.index(_A					)
  for kn in solution[1:-1]:
   __a       =  solution.index(_A					)
   if n == kn:
    continue

   __a       =  copy.deepcopy(_A					)
   __a       =  kn
   __a       =  n

   __a       =  0

   for k in _tmp[:-1]:
    __a       =  _tmp[_tmp.index(_A					) + 1]
    for i in dict_of_neighbours[k]:
     if i[0] == next_node:
      __a       =  distance + int(i[1]					)
   _tmp.append(_A					)

   if _tmp not in neighborhood_of_solution:
    neighborhood_of_solution.append(_tmp					)

 __a       =  len(neighborhood_of_solution[0]					) - 1

 neighborhood_of_solution.sort(key=lambda _A					: x[index_of_last_item_in_the_list]					)
 return neighborhood_of_solution



def   __A		(			_A							,				_A							,				_A							,				_A							,				_A					):



 """simple docstring"""


 __a       =  1
 __a       =  first_solution
 __a       =  []
 __a       =  distance_of_first_solution
 __a       =  solution

 while count <= iters:
  __a       =  find_neighborhood(_A							,				_A					)
  __a       =  0
  __a       =  neighborhood[index_of_best_solution]
  __a       =  len(_A					) - 1

  __a       =  False
  while not found:
   __a       =  0
   while i < len(_A					):
    if best_solution[i] != solution[i]:
     __a       =  best_solution[i]
     __a       =  solution[i]
     break
    __a       =  i + 1

   if [first_exchange_node, second_exchange_node] not in tabu_list and [
       second_exchange_node,
       first_exchange_node,
   ] not in tabu_list:
    tabu_list.append([first_exchange_node, second_exchange_node]					)
    __a       =  True
    __a       =  best_solution[:-1]
    __a       =  neighborhood[index_of_best_solution][best_cost_index]
    if cost < best_cost:
     __a       =  cost
     __a       =  solution
   else:
    __a       =  index_of_best_solution + 1
    __a       =  neighborhood[index_of_best_solution]

  if len(_A					) >= size:
   tabu_list.pop(0					)

  __a       =  count + 1

 return best_solution_ever, best_cost



def   __A		(			_A=None					):



 """simple docstring"""


 __a       =  generate_neighbours(args.File					)

 __a       ,     __a       =  generate_first_solution(
     args.File							,				_A					)

 __a       ,     __a       =  tabu_search(
     _A							,				_A							,				_A							,				args.Iterations							,				args.Size							,				)

 print(f"""Best solution: {best_sol}, with total distance: {best_cost}."""					)


if __name__ == "__main__":
  SCREAMING_SNAKE_CASE :	Union[str, Any]							     =		argparse.ArgumentParser(description="""Tabu Search""")
  parser.add_argument(
      """-f""",
      """--File""",
      type=str,
      help="""Path to the file containing the data""",
      required=True,
  )
  parser.add_argument(
      """-i""",
      """--Iterations""",
      type=int,
      help="""How many iterations the algorithm should perform""",
      required=True,
  )
  parser.add_argument(
      """-s""", """--Size""", type=int, help="""Size of the tabu list""", required=True
  )

  # Pass the arguments to main method
  main(parser.parse_args())



from __future__ import annotations

SCREAMING_SNAKE_CASE :	Optional[int]							     =		[]



def   __A		(			_A							,				_A							,				_A					):



 """simple docstring"""


 for i in range(len(_A					)					):
  if board[row][i] == 1:
   return False
 for i in range(len(_A					)					):
  if board[i][column] == 1:
   return False
 for i, j in zip(range(_A							,				-1							,				-1					)							,				range(_A							,				-1							,				-1					)					):
  if board[i][j] == 1:
   return False
 for i, j in zip(range(_A							,				-1							,				-1					)							,				range(_A							,				len(_A					)					)					):
  if board[i][j] == 1:
   return False
 return True



def   __A		(			_A							,				_A					):



 """simple docstring"""


 if row >= len(_A					):
  solution.append(_A					)
  printboard(_A					)
  print()
  return True
 for i in range(len(_A					)					):
  if is_safe(_A							,				_A							,				_A					):
   __a       =  1
   solve(_A							,				row + 1					)
   __a       =  0
 return False



def   __A		(			_A					):



 """simple docstring"""


 for i in range(len(_A					)					):
  for j in range(len(_A					)					):
   if board[i][j] == 1:
    print("Q"							,				end=" "					)
   else:
    print("."							,				end=" "					)
  print()


# n=int(input("The no. of queens"))
SCREAMING_SNAKE_CASE :	List[str]							     =		8
SCREAMING_SNAKE_CASE :	str							     =		[[0 for i in range(n)] for j in range(n)]
solve(board, 0)






print("""The total no. of solutions are :""", len(solution))


