
"""simple docstring"""




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


snake_case    =		datasets.utils.logging.get_logger(__name__)




@dataclass
class      UpperCamelCase	(       datasets.BuilderConfig      ):

				"""simple docstring"""



				UpperCAmelCase_				:      Optional[datasets.Features]						  =				None
				UpperCAmelCase_				:      str						  =				"utf-8"
				UpperCAmelCase_				:      Optional[str]						  =				None
				UpperCAmelCase_				:      int						  =				10 << 20  # 10MB
				UpperCAmelCase_				:      bool						  =				False
				UpperCAmelCase_				:      str						  =				"line"






class      UpperCamelCase	(       datasets.ArrowBasedBuilder      ):

				"""simple docstring"""



				UpperCAmelCase_				:      Any						  =				TextConfig


				def 							A					(				self			)    ->    str:
									"""simple docstring"""







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


				def 							A					(				self		,	lowercase__			)    ->    Optional[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}'''			)
									SCREAMING_SNAKE_CASE				=	dl_manager.download_and_extract(self.config.data_files			)
									if isinstance(lowercase__		,	(str, list, tuple)			):
														SCREAMING_SNAKE_CASE				=	data_files
														if isinstance(lowercase__		,	lowercase__			):
																			SCREAMING_SNAKE_CASE				=	[files]
														SCREAMING_SNAKE_CASE				=	[dl_manager.iter_files(lowercase__			) for file in files]
														return [datasets.SplitGenerator(name=datasets.Split.TRAIN		,	gen_kwargs={'files': files}			)]
									SCREAMING_SNAKE_CASE				=	[]
									for split_name, files in data_files.items():
														if isinstance(lowercase__		,	lowercase__			):
																			SCREAMING_SNAKE_CASE				=	[files]
														SCREAMING_SNAKE_CASE				=	[dl_manager.iter_files(lowercase__			) for file in files]
														splits.append(datasets.SplitGenerator(name=lowercase__		,	gen_kwargs={'files': files}			)			)
									return splits


				def 							A					(				self		,	lowercase__			)    ->    pa.Table:
									"""simple docstring"""







									if self.config.features is not None:
														SCREAMING_SNAKE_CASE				=	self.config.features.arrow_schema
														if all(not require_storage_cast(lowercase__			) for feature in self.config.features.values()			):
																			# cheaper cast
																			SCREAMING_SNAKE_CASE				=	pa_table.cast(lowercase__			)
														else:
																			# more expensive cast; allows str <-> int/float or str to Audio for example
																			SCREAMING_SNAKE_CASE				=	table_cast(lowercase__		,	lowercase__			)
														return pa_table
									else:
														return pa_table.cast(pa.schema({'text': pa.string()}			)			)




				def 							A					(				self		,	lowercase__			)    ->    int:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE				=	list(self.config.features			) if self.config.features is not None else ['text']
									for file_idx, file in enumerate(itertools.chain.from_iterable(lowercase__			)			):
														# open in text mode, by default translates universal newlines ("\n", "\r\n" and "\r") into "\n"
														with open(lowercase__		,	encoding=self.config.encoding		,	errors=self.config.errors			) as f:
																			if self.config.sample_by == "line":
																								SCREAMING_SNAKE_CASE				=	0
																								while True:
																													SCREAMING_SNAKE_CASE				=	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)
																													SCREAMING_SNAKE_CASE				=	StringIO(lowercase__			).readlines()
																													if not self.config.keep_linebreaks:
																																		SCREAMING_SNAKE_CASE				=	[line.rstrip('\n'			) for line in batch]
																													SCREAMING_SNAKE_CASE				=	pa.Table.from_arrays([pa.array(lowercase__			)]		,	names=lowercase__			)
																													# 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(lowercase__			)
																													batch_idx += 1
																			elif self.config.sample_by == "paragraph":
																								SCREAMING_SNAKE_CASE				=	0
																								SCREAMING_SNAKE_CASE				=	''
																								while True:
																													SCREAMING_SNAKE_CASE				=	f.read(self.config.chunksize			)
																													if not new_batch:
																																		break
																													batch += new_batch
																													batch += f.readline()  # finish current line
																													SCREAMING_SNAKE_CASE				=	batch.split('\n\n'			)
																													SCREAMING_SNAKE_CASE				=	pa.Table.from_arrays(
																													    [pa.array([example for example in batch[:-1] if example]			)]		,	names=lowercase__			)
																													# 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(lowercase__			)
																													batch_idx += 1
																													SCREAMING_SNAKE_CASE				=	batch[-1]
																								if batch:
																													SCREAMING_SNAKE_CASE				=	pa.Table.from_arrays([pa.array([batch]			)]		,	names=lowercase__			)
																													yield (file_idx, batch_idx), self._cast_table(lowercase__			)
																			elif self.config.sample_by == "document":
																								SCREAMING_SNAKE_CASE				=	f.read()
																								SCREAMING_SNAKE_CASE				=	pa.Table.from_arrays([pa.array([text]			)]		,	names=lowercase__			)
																								yield file_idx, self._cast_table(lowercase__			)




'''simple docstring'''






def 					_snake_case   (     A       )						->    str:
							return " ".join(sorted(set(sentence.split()       )       )       )


if __name__ == "__main__":
		import doctest

		doctest.testmod()