
import itertools
from dataclasses import dataclass
from io import StringIO
from typing import Optional

import pyarrow as pa

import datasets
from datasets.features.features import require_storage_cast
from datasets.table import table_cast


__lowerCamelCase								=					datasets.utils.logging.get_logger(__name__)
@dataclass
class    _UpperCamelCase(   datasets.BuilderConfig				):
						__A:						Optional[datasets.Features]				   =      None
						__A:						str				   =      "utf-8"
						__A:						Optional[str]				   =      None
						__A:						int				   =      10 << 20  # 10MB
						__A:						bool				   =      False
						__A:						str				   =      "line"







class    _UpperCamelCase(   datasets.ArrowBasedBuilder				):
						__A:						int				   =      TextConfig

						def 						a__ (					self		:			Dict			):
													return datasets.DatasetInfo(features=self.config.features			)

						def 						a__ (					self		:			List[Any]	,						_lowerCamelCase		:			List[str]			):
													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  :			int	       =		dl_manager.download_and_extract(self.config.data_files			)
													if isinstance(_lowerCamelCase	,						(str, list, tuple)			):
																				_UpperCAmelCase  :			Optional[int]	       =		data_files
																				if isinstance(_lowerCamelCase	,						_lowerCamelCase			):
																											_UpperCAmelCase  :			str	       =		[files]
																				_UpperCAmelCase  :			Optional[int]	       =		[dl_manager.iter_files(_lowerCamelCase			) for file in files]
																				return [datasets.SplitGenerator(name=datasets.Split.TRAIN	,						gen_kwargs={"files": files}			)]
													_UpperCAmelCase  :			Union[str, Any]	       =		[]
													for split_name, files in data_files.items():
																				if isinstance(_lowerCamelCase	,						_lowerCamelCase			):
																											_UpperCAmelCase  :			Any	       =		[files]
																				_UpperCAmelCase  :			List[Any]	       =		[dl_manager.iter_files(_lowerCamelCase			) for file in files]
																				splits.append(datasets.SplitGenerator(name=_lowerCamelCase	,						gen_kwargs={"files": files}			)			)
													return splits

						def 						a__ (					self		:			List[Any]	,						_lowerCamelCase		:			pa.Table			):
													if self.config.features is not None:
																				_UpperCAmelCase  :			int	       =		self.config.features.arrow_schema
																				if all(not require_storage_cast(_lowerCamelCase			) for feature in self.config.features.values()			):
																											# cheaper cast
																											_UpperCAmelCase  :			Dict	       =		pa_table.cast(_lowerCamelCase			)
																				else:
																											# more expensive cast; allows str <-> int/float or str to Audio for example
																											_UpperCAmelCase  :			Any	       =		table_cast(_lowerCamelCase	,						_lowerCamelCase			)
																				return pa_table
													else:
																				return pa_table.cast(pa.schema({"text": pa.string()}			)			)






						def 						a__ (					self		:			Union[str, Any]	,						_lowerCamelCase		:			Any			):
													_UpperCAmelCase  :			Optional[Any]	       =		list(self.config.features			) if self.config.features is not None else ["text"]
													for file_idx, file in enumerate(itertools.chain.from_iterable(_lowerCamelCase			)			):
																				# open in text mode, by default translates universal newlines ("\n", "\r\n" and "\r") into "\n"
																				with open(_lowerCamelCase	,						encoding=self.config.encoding	,						errors=self.config.errors			) as f:
																											if self.config.sample_by == "line":
																																		_UpperCAmelCase  :			List[str]	       =		0
																																		while True:
																																									_UpperCAmelCase  :			List[Any]	       =		f.read(self.config.chunksize			)
																																									if not batch:
																																																break
																																									batch += f.readline()  # finish current line
																																									# StringIO.readlines, by default splits only on "\n" (and keeps line breaks)
																																									_UpperCAmelCase  :			Tuple	       =		StringIO(_lowerCamelCase			).readlines()
																																									if not self.config.keep_linebreaks:
																																																_UpperCAmelCase  :			Union[str, Any]	       =		[line.rstrip("\n"			) for line in batch]
																																									_UpperCAmelCase  :			Dict	       =		pa.Table.from_arrays([pa.array(_lowerCamelCase			)]	,						names=_lowerCamelCase			)
																																									# 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 (file_idx, batch_idx), self._cast_table(_lowerCamelCase			)
																																									batch_idx += 1
																											elif self.config.sample_by == "paragraph":
																																		_UpperCAmelCase  :			Dict	       =		0
																																		_UpperCAmelCase  :			List[str]	       =		""
																																		while True:
																																									_UpperCAmelCase  :			Tuple	       =		f.read(self.config.chunksize			)
																																									if not new_batch:
																																																break
																																									batch += new_batch
																																									batch += f.readline()  # finish current line
																																									_UpperCAmelCase  :			Optional[int]	       =		batch.split("\n\n"			)
																																									_UpperCAmelCase  :			Any	       =		pa.Table.from_arrays(
																																									    [pa.array([example for example in batch[:-1] if example]			)]	,						names=_lowerCamelCase			)
																																									# 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 (file_idx, batch_idx), self._cast_table(_lowerCamelCase			)
																																									batch_idx += 1
																																									_UpperCAmelCase  :			Dict	       =		batch[-1]
																																		if batch:
																																									_UpperCAmelCase  :			Any	       =		pa.Table.from_arrays([pa.array([batch]			)]	,						names=_lowerCamelCase			)
																																									yield (file_idx, batch_idx), self._cast_table(_lowerCamelCase			)
																											elif self.config.sample_by == "document":
																																		_UpperCAmelCase  :			Union[str, Any]	       =		f.read()
																																		_UpperCAmelCase  :			int	       =		pa.Table.from_arrays([pa.array([text]			)]	,						names=_lowerCamelCase			)
																																		yield file_idx, self._cast_table(_lowerCamelCase			)






def 		lowerCAmelCase_     (     _SCREAMING_SNAKE_CASE      ,	_SCREAMING_SNAKE_CASE      ,	_SCREAMING_SNAKE_CASE  )   ->      Dict:

							"""simple docstring"""






							if power < 0:
														return -1
							base %= mod
							_UpperCAmelCase  :			Optional[Any]	       =		1

							while power > 0:
														if power & 1:
																					_UpperCAmelCase  :			Optional[Any]	       =		(result * base) % mod
														_UpperCAmelCase  :			List[str]	       =		power >> 1
														_UpperCAmelCase  :			Optional[int]	       =		(base * base) % mod

							return result




def 		lowerCAmelCase_     (     )   ->      List[str]:

							"""simple docstring"""






							print(modular_exponential(3      ,	2_0_0      ,	1_3  )  )


if __name__ == "__main__":
				import doctest

				doctest.testmod()

				main()




