



"""simple docstring"""






import timeit

import numpy as np

import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD






def   snake_case__     (	__lowerCamelCase       :					Optional[Any]			):
			"""simple docstring"""
			def wrapper(*__lowerCamelCase       :					str							,	**__lowerCamelCase       :					Tuple			):
						lowerCamelCase__	:	Union[str, Any]				=timeit.default_timer()
						lowerCamelCase__	:	int				=func(*__lowerCamelCase							,	**__lowerCamelCase			)
						lowerCamelCase__	:	str				=timeit.default_timer() - starttime
						return delta

			lowerCamelCase__	:	Dict				=func.__name__

			return wrapper






def   snake_case__     (	__lowerCamelCase       :					dict							,	__lowerCamelCase       :					List[Any]=100							,	__lowerCamelCase       :					int=None			):
			"""simple docstring"""
			lowerCamelCase__	:	Any				=[]
			lowerCamelCase__	:	Optional[Any]				=seq_shapes or {}
			for i in range(__lowerCamelCase			):
						lowerCamelCase__	:	List[Any]				={}
						for col_id, (k, v) in enumerate(features.items()			):
									if isinstance(__lowerCamelCase							,	_ArrayXD			):
												lowerCamelCase__	:	List[Any]				=np.random.rand(*v.shape			).astype(v.dtype			)
									elif isinstance(__lowerCamelCase							,	datasets.Value			):
												if v.dtype == "string":
															lowerCamelCase__	:	str				='''The small grey turtle was surprisingly fast when challenged.'''
												else:
															lowerCamelCase__	:	Union[str, Any]				=np.random.randint(10							,	size=1			).astype(v.dtype			).item()
									elif isinstance(__lowerCamelCase							,	datasets.Sequence			):
												while isinstance(__lowerCamelCase							,	datasets.Sequence			):
															lowerCamelCase__	:	Union[str, Any]				=v.feature
												lowerCamelCase__	:	List[str]				=seq_shapes[k]
												lowerCamelCase__	:	Union[str, Any]				=np.random.rand(*__lowerCamelCase			).astype(v.dtype			)
									lowerCamelCase__	:	List[str]				=data

						dummy_data.append((i, example)			)

			return dummy_data






def   snake_case__     (	__lowerCamelCase       :					Dict							,	__lowerCamelCase       :					Optional[Any]							,	__lowerCamelCase       :					List[str]=100							,	__lowerCamelCase       :					int=None			):
			"""simple docstring"""
			lowerCamelCase__	:	Optional[int]				=generate_examples(__lowerCamelCase							,	num_examples=__lowerCamelCase							,	seq_shapes=__lowerCamelCase			)

			with ArrowWriter(features=__lowerCamelCase							,	path=__lowerCamelCase			) as writer:
						for key, record in dummy_data:
									lowerCamelCase__	:	List[Any]				=features.encode_example(__lowerCamelCase			)
									writer.write(__lowerCamelCase			)

						lowerCamelCase__			,     lowerCamelCase__	:	str				=writer.finalize()

			if not num_final_examples == num_examples:
						raise ValueError(
						    f'''Error writing the dataset, wrote {num_final_examples} examples but should have written {num_examples}.'''			)

			lowerCamelCase__	:	Tuple				=datasets.Dataset.from_file(filename=__lowerCamelCase							,	info=datasets.DatasetInfo(features=__lowerCamelCase			)			)

			return dataset









"""simple docstring"""






import os






def   snake_case__     (	):
			"""simple docstring"""
			with open(os.path.dirname(__lowerCamelCase			) + '''/p022_names.txt'''			) as file:
						lowerCamelCase__	:	Tuple				=str(file.readlines()[0]			)
						lowerCamelCase__	:	int				=names.replace('''"'''							,	''''''			).split(''','''			)

			names.sort()

			lowerCamelCase__	:	Union[str, Any]				=0
			lowerCamelCase__	:	str				=0

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

						total_score += (i + 1) * name_score
						lowerCamelCase__	:	Dict				=0
			return total_score


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




