code: 
  
  
  def   SCREAMING_SNAKE_CASE__						(							snake_case_,	snake_case_,	snake_case_,	snake_case_,	snake_case_,	snake_case_,	)			->							tuple[list[list[int]], list[list[str]]]:
  				A__     :							int   				=list(snake_case_	)
  				A__     :							Dict   				=list(snake_case_	)
  				A__     :							Tuple   				=len(snake_case_	)
  				A__     :							Optional[int]   				=len(snake_case_	)
  
  				A__     :							Optional[Any]   				=[
  				    [0 for _ in range(len_destination_seq + 1	)] for _ in range(len_source_seq + 1	)
  				]
  				A__     :							List[str]   				=[
  				    ['''0''' for _ in range(len_destination_seq + 1	)] for _ in range(len_source_seq + 1	)
  				]
  
  				for i in range(1,	len_source_seq + 1	):
  								A__     :							Any   				=i * delete_cost
  								A__     :							str   				=f'D{source_seq[i - 1]:c}'
  
  				for i in range(1,	len_destination_seq + 1	):
  								A__     :							Optional[int]   				=i * insert_cost
  								A__     :							Union[str, Any]   				=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]:
  																A__     :							Union[str, Any]   				=costs[i - 1][j - 1] + copy_cost
  																A__     :							Optional[int]   				=f'C{source_seq[i - 1]:c}'
  												else:
  																A__     :							Dict   				=costs[i - 1][j - 1] + replace_cost
  																A__     :							Union[str, Any]   				=f'R{source_seq[i - 1]:c}' + str(destination_seq[j - 1]	)
  
  												if costs[i - 1][j] + delete_cost < costs[i][j]:
  																A__     :							Any   				=costs[i - 1][j] + delete_cost
  																A__     :							Optional[int]   				=f'D{source_seq[i - 1]:c}'
  
  												if costs[i][j - 1] + insert_cost < costs[i][j]:
  																A__     :							List[str]   				=costs[i][j - 1] + insert_cost
  																A__     :							Any   				=f'I{destination_seq[j - 1]:c}'
  
  				return costs, ops
  
  
  
  def   SCREAMING_SNAKE_CASE__						(							snake_case_,	snake_case_,	snake_case_	)			->							list[str]:
  				if i == 0 and j == 0:
  								return []
  				else:
  								if ops[i][j][0] == "C" or ops[i][j][0] == "R":
  												A__     :							int   				=assemble_transformation(snake_case_,	i - 1,	j - 1	)
  												seq.append(ops[i][j]	)
  												return seq
  								elif ops[i][j][0] == "D":
  												A__     :							List[str]   				=assemble_transformation(snake_case_,	i - 1,	snake_case_	)
  												seq.append(ops[i][j]	)
  												return seq
  								else:
  												A__     :							Any   				=assemble_transformation(snake_case_,	snake_case_,	j - 1	)
  												seq.append(ops[i][j]	)
  												return seq
  
  
  if __name__ == "__main__":
  						__lowerCamelCase       :       Dict				   =			compute_transform_tables("Python", "Algorithms", -1, 1, 2, 2)
  
  						__lowerCamelCase       :       int				   =			len(operations)
  						__lowerCamelCase       :       Optional[Any]				   =			len(operations[0])
  						__lowerCamelCase       :       Union[str, Any]				   =			assemble_transformation(operations, m - 1, n - 1)
  
  						__lowerCamelCase       :       int				   =			list("Python")
  						__lowerCamelCase       :       Any				   =			0
  						__lowerCamelCase       :       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":
  																								__lowerCamelCase       :       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))
  
  
  
  
style_context: 
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_torch_available,
  )
  
  
  __lowerCamelCase       :       str				   =			{
      "configuration_align": [
          "ALIGN_PRETRAINED_CONFIG_ARCHIVE_MAP",
          "AlignConfig",
          "AlignTextConfig",
          "AlignVisionConfig",
      ],
      "processing_align": ["AlignProcessor"],
  }
  
  try:
  						if not is_torch_available():
  												raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  						pass
  else:
  						__lowerCamelCase       :       Dict				   =			[
  						    "ALIGN_PRETRAINED_MODEL_ARCHIVE_LIST",
  						    "AlignModel",
  						    "AlignPreTrainedModel",
  						    "AlignTextModel",
  						    "AlignVisionModel",
  						]
  
  if TYPE_CHECKING:
  						from .configuration_align import (
  						    ALIGN_PRETRAINED_CONFIG_ARCHIVE_MAP,
  						    AlignConfig,
  						    AlignTextConfig,
  						    AlignVisionConfig,
  						)
  						from .processing_align import AlignProcessor
  
  						try:
  												if not is_torch_available():
  																		raise OptionalDependencyNotAvailable()
  						except OptionalDependencyNotAvailable:
  												pass
  						else:
  												from .modeling_align import (
  												    ALIGN_PRETRAINED_MODEL_ARCHIVE_LIST,
  												    AlignModel,
  												    AlignPreTrainedModel,
  												    AlignTextModel,
  												    AlignVisionModel,
  												)
  
  else:
  						import sys
  
  						__lowerCamelCase       :       List[str]				   =			_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
  
  
  
  