






"""simple docstring"""
A_     :					str							=     float("inf")



class 						a_ :







      '''simple docstring'''

      def __init__(self,	lowerCamelCase_   ):

       '''simple docstring'''



       lowerCamelCase__	:     str								=		[0] * n
       lowerCamelCase__	:     Optional[int]								=		[0] * n
       lowerCamelCase__	:     Dict								=		[0] * n
       lowerCamelCase__	:     Any								=		[[] for _ in range(lowerCamelCase_   )]




      def      a__				(self,	lowerCamelCase_,	lowerCamelCase_,	lowerCamelCase_,	lowerCamelCase_=0   ):

       '''simple docstring'''



       self.adj[a].append([b, len(self.adj[b]   ), c, 0]   )
       self.adj[b].append([a, len(self.adj[a]   ) - 1, rcap, 0]   )




      def      a__				(self,	lowerCamelCase_,	lowerCamelCase_,	lowerCamelCase_   ):

       '''simple docstring'''



       if vertex == sink or not flow:
        return flow

       for i in range(self.ptr[vertex],	len(self.adj[vertex]   )   ):
        lowerCamelCase__	:     Optional[Any]								=		self.adj[vertex][i]
        if self.lvl[e[0]] == self.lvl[vertex] + 1:
         lowerCamelCase__	:     Union[str, Any]								=		self.depth_first_search(e[0],	lowerCamelCase_,	min(lowerCamelCase_,	e[2] - e[3]   )   )
         if p:
          self.adj[vertex][i][3] += p
          self.adj[e[0]][e[1]][3] -= p
          return p
        lowerCamelCase__	:     List[str]								=		self.ptr[vertex] + 1
       return 0





      def      a__				(self,	lowerCamelCase_,	lowerCamelCase_   ):

       '''simple docstring'''



       lowerCamelCase__							,	lowerCamelCase__	:     List[str]								=		0, source
       for l in range(3_1   ):  # noqa: E741  l = 30 maybe faster for random data
        while True:
         lowerCamelCase__							,	lowerCamelCase__	:     int								=		[0] * len(self.q   ), [0] * len(self.q   )
         lowerCamelCase__							,	lowerCamelCase__							,	lowerCamelCase__	:     str								=		0, 1, 1
         while qi < qe and not self.lvl[sink]:
          lowerCamelCase__	:     Optional[int]								=		self.q[qi]
          qi += 1
          for e in self.adj[v]:
           if not self.lvl[e[0]] and (e[2] - e[3]) >> (3_0 - l):
            lowerCamelCase__	:     str								=		e[0]
            qe += 1
            lowerCamelCase__	:     Optional[int]								=		self.lvl[v] + 1

         lowerCamelCase__	:     Optional[int]								=		self.depth_first_search(lowerCamelCase_,	lowerCamelCase_,	lowerCamelCase_   )
         while p:
          flow += p
          lowerCamelCase__	:     Dict								=		self.depth_first_search(lowerCamelCase_,	lowerCamelCase_,	lowerCamelCase_   )

         if not self.lvl[sink]:
          break

       return flow
A_     :					str							=     Dinic(10)
A_     :					List[Any]							=     0
A_     :					List[str]							=     9
for vertex in range(1, 5):
      graph.add_edge(source, vertex, 1)
for vertex in range(5, 9):
      graph.add_edge(vertex, sink, 1)
for vertex in range(1, 5):
      graph.add_edge(vertex, vertex + 4, 1)

# Now we can know that is the maximum flow(source -> sink)
print(graph.max_flow(source, sink))









"""simple docstring"""
def 			lowerCamelCase_    (		_lowerCamelCase     ,  _lowerCamelCase     ,  _lowerCamelCase     ,  _lowerCamelCase     ,  _lowerCamelCase     ,  _lowerCamelCase     ,  ):
 lowerCamelCase__	:     Any								=		list(_lowerCamelCase							)
 lowerCamelCase__	:     List[Any]								=		list(_lowerCamelCase							)
 lowerCamelCase__	:     int								=		len(_lowerCamelCase							)
 lowerCamelCase__	:     Optional[int]								=		len(_lowerCamelCase							)

 lowerCamelCase__	:     Tuple								=		[
     [0 for _ in range(len_destination_seq + 1							)] for _ in range(len_source_seq + 1							)
 ]
 lowerCamelCase__	:     Dict								=		[
     ['0' for _ in range(len_destination_seq + 1							)] for _ in range(len_source_seq + 1							)
 ]

 for i in range(1     ,  len_source_seq + 1							):
  lowerCamelCase__	:     Optional[int]								=		i * delete_cost
  lowerCamelCase__	:     List[str]								=		f'''D{source_seq[i - 1]:c}'''

 for i in range(1     ,  len_destination_seq + 1							):
  lowerCamelCase__	:     int								=		i * insert_cost
  lowerCamelCase__	:     str								=		f'''I{destination_seq[i - 1]:c}'''

 for i in range(1     ,  len_source_seq + 1							):
  for j in range(1     ,  len_destination_seq + 1							):
   if source_seq[i - 1] == destination_seq[j - 1]:
    lowerCamelCase__	:     Any								=		costs[i - 1][j - 1] + copy_cost
    lowerCamelCase__	:     str								=		f'''C{source_seq[i - 1]:c}'''
   else:
    lowerCamelCase__	:     Tuple								=		costs[i - 1][j - 1] + replace_cost
    lowerCamelCase__	:     List[str]								=		f'''R{source_seq[i - 1]:c}''' + str(destination_seq[j - 1]							)

   if costs[i - 1][j] + delete_cost < costs[i][j]:
    lowerCamelCase__	:     Any								=		costs[i - 1][j] + delete_cost
    lowerCamelCase__	:     Union[str, Any]								=		f'''D{source_seq[i - 1]:c}'''

   if costs[i][j - 1] + insert_cost < costs[i][j]:
    lowerCamelCase__	:     Optional[Any]								=		costs[i][j - 1] + insert_cost
    lowerCamelCase__	:     Union[str, Any]								=		f'''I{destination_seq[j - 1]:c}'''

 return costs, ops






def 			lowerCamelCase_    (		_lowerCamelCase     ,  _lowerCamelCase     ,  _lowerCamelCase							):
 if i == 0 and j == 0:
  return []
 else:
  if ops[i][j][0] == "C" or ops[i][j][0] == "R":
   lowerCamelCase__	:     List[str]								=		assemble_transformation(_lowerCamelCase     ,  i - 1     ,  j - 1							)
   seq.append(ops[i][j]							)
   return seq
  elif ops[i][j][0] == "D":
   lowerCamelCase__	:     Union[str, Any]								=		assemble_transformation(_lowerCamelCase     ,  i - 1     ,  _lowerCamelCase							)
   seq.append(ops[i][j]							)
   return seq
  else:
   lowerCamelCase__	:     Tuple								=		assemble_transformation(_lowerCamelCase     ,  _lowerCamelCase     ,  j - 1							)
   seq.append(ops[i][j]							)
   return seq


if __name__ == "__main__":
      A_,			A_     :					List[str]							=     compute_transform_tables("Python", "Algorithms", -1, 1, 2, 2)

      A_     :					str							=     len(operations)
      A_     :					Dict							=     len(operations[0])
      A_     :					Any							=     assemble_transformation(operations, m - 1, n - 1)

      A_     :					int							=     list("Python")
      A_     :					Optional[Any]							=     0
      A_     :					Tuple							=     0

      with open("min_cost.txt", "w") as file:
            for op in sequence:
                  print("".join(string))

                  if op[0] == "C":
                        file.write("%-16s" % "Copy %c" % op[1])
                        file.write("\t\t\t" + "".join(string))
                        file.write("\r\n")

                        cost -= 1
                  elif op[0] == "R":
                        A_     :					str							=     op[2]

                        file.write("%-16s" % ("Replace %c" % op[1] + " with " + str(op[2])))
                        file.write("\t\t" + "".join(string))
                        file.write("\r\n")

                        cost += 1
                  elif op[0] == "D":
                        string.pop(i)

                        file.write("%-16s" % "Delete %c" % op[1])
                        file.write("\t\t\t" + "".join(string))
                        file.write("\r\n")

                        cost += 2
                  else:
                        string.insert(i, op[1])

                        file.write("%-16s" % "Insert %c" % op[1])
                        file.write("\t\t\t" + "".join(string))
                        file.write("\r\n")

                        cost += 2

                  i += 1

            print("".join(string))
            print("Cost: ", cost)

            file.write("\r\nMinimum cost: " + str(cost))

