

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


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

@dataclass
class 					__UpperCamelCase					(       datasets.BuilderConfig      ):
	_lowercase	: Optional[datasets.Features]												=	None
	_lowercase	: str												=	"utf-8"
	_lowercase	: Optional[str]												=	None
	_lowercase	: int												=	1_0 << 2_0  # 10MB
	_lowercase	: bool												=	False
	_lowercase	: str												=	"line"




class 					__UpperCamelCase					(       datasets.ArrowBasedBuilder      ):
	_lowercase	: str												=	TextConfig







	def 						_SCREAMING_SNAKE_CASE				( self:			Optional[int]   ):

						'''simple docstring'''





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







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







	def 						_SCREAMING_SNAKE_CASE				( self:			Optional[Any]	,			__UpperCamelCase:			pa.Table   ):

						'''simple docstring'''





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







	def 						_SCREAMING_SNAKE_CASE				( self:			List[Any]	,			__UpperCamelCase:			List[str]   ):

						'''simple docstring'''





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







from hashlib import mda, shaaaa

A__							=				(shaaaa, mda)

class 					__UpperCamelCase					:







	def __init__( self:			Optional[int]	,			__UpperCamelCase:			int = 8   ):

						'''simple docstring'''





						__magic_name__				=     0b0
						__magic_name__				=     size







	def 						_SCREAMING_SNAKE_CASE				( self:			Tuple	,			__UpperCamelCase:			str   ):

						'''simple docstring'''





						__magic_name__				=     self.hash_(__UpperCamelCase   )
						self.bitarray |= h







	def 						_SCREAMING_SNAKE_CASE				( self:			List[str]	,			__UpperCamelCase:			str   ):

						'''simple docstring'''





						__magic_name__				=     self.hash_(__UpperCamelCase   )
						return (h & self.bitarray) == h







	def __contains__( self:			Optional[int]	,			__UpperCamelCase:			str   ):

						'''simple docstring'''





						return self.exists(__UpperCamelCase   )







	def 						_SCREAMING_SNAKE_CASE				( self:			int	,			__UpperCamelCase:			int   ):

						'''simple docstring'''





						__magic_name__				=     bin(__UpperCamelCase   )[2:]
						return res.zfill(self.size   )







	@property
	def 						_SCREAMING_SNAKE_CASE				( self:			str   ):

						'''simple docstring'''





						return self.format_bin(self.bitarray   )







	def 						_SCREAMING_SNAKE_CASE				( self:			str	,			__UpperCamelCase:			str   ):

						'''simple docstring'''





						__magic_name__				=     0b0
						for func in HASH_FUNCTIONS:
											__magic_name__				=     (
											    int.from_bytes(func(value.encode()   ).digest()	,			'little'   ) % self.size
											)
											res |= 2**position
						return res







	def 						_SCREAMING_SNAKE_CASE				( self:			Dict	,			__UpperCamelCase:			str   ):

						'''simple docstring'''





						return self.format_bin(self.hash_(__UpperCamelCase   )   )







	@property
	def 						_SCREAMING_SNAKE_CASE				( self:			Optional[int]   ):

						'''simple docstring'''





						__magic_name__				=     bin(self.bitarray   ).count('1'   )
						return (n_ones / self.size) ** len(__UpperCamelCase   )




