




import itertools
from dataclasses import dataclass
from typing import Optional

import pandas as pd
import pyarrow as pa

import datasets
from datasets.table import table_cast

@dataclass
class 						__lowerCAmelCase      (      datasets.BuilderConfig					):
							UpperCamelCase__   	=    None







class 						__lowerCAmelCase      (      datasets.ArrowBasedBuilder					):
							UpperCamelCase__   	=    PandasConfig
							def  lowerCamelCase__				(		self		:List[Any]							):







								'''simple docstring'''







								return datasets.DatasetInfo(features=self.config.features							)
							def  lowerCamelCase__				(		self		:List[Any]						, __magic_name__		:List[Any]							):







								'''simple docstring'''







								if not self.config.data_files:
									raise ValueError(F'At least one data file must be specified, but got data_files={self.config.data_files}'							)
								a									=				dl_manager.download_and_extract(self.config.data_files							)
								if isinstance(__magic_name__						, (str, list, tuple)							):
									a									=				data_files
									if isinstance(__magic_name__						, __magic_name__							):
										a									=				[files]
									# Use `dl_manager.iter_files` to skip hidden files in an extracted archive
									a									=				[dl_manager.iter_files(__magic_name__							) for file in files]
									return [datasets.SplitGenerator(name=datasets.Split.TRAIN						, gen_kwargs={"""files""": files}							)]
								a									=				[]
								for split_name, files in data_files.items():
									if isinstance(__magic_name__						, __magic_name__							):
										a									=				[files]
									# Use `dl_manager.iter_files` to skip hidden files in an extracted archive
									a									=				[dl_manager.iter_files(__magic_name__							) for file in files]
									splits.append(datasets.SplitGenerator(name=__magic_name__						, gen_kwargs={"""files""": files}							)							)
								return splits
							def  lowerCamelCase__				(		self		:List[Any]						, __magic_name__		:pa.Table							):







								'''simple docstring'''







								if self.config.features is not None:
									# more expensive cast to support nested features with keys in a different order
									# allows str <-> int/float or str to Audio for example
									a									=				table_cast(__magic_name__						, self.config.features.arrow_schema							)
								return pa_table





							def  lowerCamelCase__				(		self		:Any						, __magic_name__		:Dict							):







								'''simple docstring'''







								for i, file in enumerate(itertools.chain.from_iterable(__magic_name__							)							):
									with open(__magic_name__						, """rb"""							) as f:
										a									=				pa.Table.from_pandas(pd.read_pickle(__magic_name__							)							)
										yield i, self._cast_table(__magic_name__							)







import os





def 						__A						(      ) ->			Dict:
	with open(os.path.dirname(__lowerCamelCase       ) + """/p022_names.txt"""       ) as file:
		a									=				str(file.readlines()[0]       )
		a									=				names.replace("""\""""				,     """"""       ).split(""","""       )

	names.sort()

	a									=				0
	a									=				0

	for i, name in enumerate(__lowerCamelCase       ):
		for letter in name:
			name_score += ord(__lowerCamelCase       ) - 64

		total_score += (i + 1) * name_score
		a									=				0
	return total_score


if __name__ == "__main__":
		print(solution())

