'''simple docstring'''





import itertools
from dataclasses import dataclass
from typing import List, Optional

import pyarrow as pa
import pyarrow.parquet as pq

import datasets
from datasets.table import table_cast


lowerCAmelCase_	:		Optional[Any]			=     datasets.utils.logging.get_logger(__name__)




@dataclass
class 		SCREAMING_SNAKE_CASE     (					datasets.BuilderConfig	):







				'''simple docstring'''
				UpperCAmelCase__							=							1_00_00
				UpperCAmelCase__							=							None
				UpperCAmelCase__							=							None





class 		SCREAMING_SNAKE_CASE     (					datasets.ArrowBasedBuilder	):







				'''simple docstring'''
				UpperCAmelCase__							=							ParquetConfig





				def  snake_case__				(						self					:						List[Any]					)							->List[str]:


										'''simple docstring'''




										return datasets.DatasetInfo(features=self.config.features					)





				def  snake_case__				(						self					:						Optional[Any]       ,		lowercase__					:						str					)							->str:


										'''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}'''					)
										_UpperCamelCase			:			Tuple   			=						dl_manager.download_and_extract(self.config.data_files					)
										if isinstance(lowercase__       ,		(str, list, tuple)					):
																_UpperCamelCase			:			Any   			=						data_files
																if isinstance(lowercase__       ,		lowercase__					):
																						_UpperCamelCase			:			Optional[int]   			=						[files]
																# Use `dl_manager.iter_files` to skip hidden files in an extracted archive
																_UpperCamelCase			:			Tuple   			=						[dl_manager.iter_files(lowercase__					) for file in files]
																return [datasets.SplitGenerator(name=datasets.Split.TRAIN       ,		gen_kwargs={"files": files}					)]
										_UpperCamelCase			:			Dict   			=						[]
										for split_name, files in data_files.items():
																if isinstance(lowercase__       ,		lowercase__					):
																						_UpperCamelCase			:			str   			=						[files]
																# Use `dl_manager.iter_files` to skip hidden files in an extracted archive
																_UpperCamelCase			:			List[Any]   			=						[dl_manager.iter_files(lowercase__					) for file in files]
																# Infer features is they are stoed in the arrow schema
																if self.info.features is None:
																						for file in itertools.chain.from_iterable(lowercase__					):
																												with open(lowercase__       ,		"rb"					) as f:
																																		_UpperCamelCase			:			List[str]   			=						datasets.Features.from_arrow_schema(pq.read_schema(lowercase__					)					)
																												break
																splits.append(datasets.SplitGenerator(name=lowercase__       ,		gen_kwargs={"files": files}					)					)
										return splits





				def  snake_case__				(						self					:						List[str]       ,		lowercase__					:						pa.Table					)							->pa.Table:


										'''simple docstring'''




										if self.info.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
																_UpperCamelCase			:			Optional[Any]   			=						table_cast(lowercase__       ,		self.info.features.arrow_schema					)
										return pa_table







				def  snake_case__				(						self					:						Optional[Any]       ,		lowercase__					:						Tuple					)							->str:


										'''simple docstring'''




										_UpperCamelCase			:			Tuple   			=						self.info.features.arrow_schema if self.info.features is not None else None
										if self.info.features is not None and self.config.columns is not None:
																if sorted(field.name for field in schema					) != sorted(self.config.columns					):
																						raise ValueError(
																						    f'''Tried to load parquet data with columns \'{self.config.columns}\' with mismatching features \'{self.info.features}\''''					)
										for file_idx, file in enumerate(itertools.chain.from_iterable(lowercase__					)					):
																with open(lowercase__       ,		"rb"					) as f:
																						_UpperCamelCase			:			Dict   			=						pq.ParquetFile(lowercase__					)
																						try:
																												for batch_idx, record_batch in enumerate(
																												    parquet_file.iter_batches(batch_size=self.config.batch_size       ,		columns=self.config.columns					)					):
																																		_UpperCamelCase			:			List[str]   			=						pa.Table.from_batches([record_batch]					)
																																		# Uncomment for debugging (will print the Arrow table size and elements)
																																		# logger.warning(f"pa_table: {pa_table} num rows: {pa_table.num_rows}")
																																		# logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
																																		yield f'''{file_idx}_{batch_idx}''', self._cast_table(lowercase__					)
																						except ValueError as e:
																												logger.error(f'''Failed to read file \'{file}\' with error {type(lowercase__					)}: {e}'''					)
																												raise



'''simple docstring'''





import random




class 		SCREAMING_SNAKE_CASE     :







				'''simple docstring'''





				@staticmethod
				def  snake_case__				(						lowercase__					:						str					)							->tuple[list[int], list[int]]:


										'''simple docstring'''




										_UpperCamelCase			:			List[str]   			=						[ord(lowercase__					) for i in text]
										_UpperCamelCase			:			Dict   			=						[]
										_UpperCamelCase			:			Optional[int]   			=						[]
										for i in plain:
																_UpperCamelCase			:			Tuple   			=						random.randint(1       ,		300					)
																_UpperCamelCase			:			Any   			=						(i + k) * k
																cipher.append(lowercase__					)
																key.append(lowercase__					)
										return cipher, key







				@staticmethod
				def  snake_case__				(						lowercase__					:						list[int]       ,		lowercase__					:						list[int]					)							->str:


										'''simple docstring'''




										_UpperCamelCase			:			int   			=						[]
										for i in range(len(lowercase__					)					):
																_UpperCamelCase			:			List[Any]   			=						int((cipher[i] - (key[i]) ** 2) / key[i]					)
																plain.append(chr(lowercase__					)					)
										return "".join(lowercase__					)


if __name__ == "__main__":
			lowerCAmelCase_	,	lowerCAmelCase_	:		Optional[int]			=     Onepad().encrypt("""Hello""")
			print(c, k)
			print(Onepad().decrypt(c, k))


