
'''simple docstring'''
import multiprocessing
import os
from typing import BinaryIO, Optional, Union

from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.csv.csv import Csv
from ..utils import logging
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader







class 			__A					(			_UpperCAmelCase      ):
 def __init__( self      :     Dict					, lowerCamelCase      :     NestedDataStructureLike[PathLike]					, lowerCamelCase      :     Optional[NamedSplit] = None					, lowerCamelCase      :     Optional[Features] = None					, lowerCamelCase      :     str = None					, lowerCamelCase      :     bool = False					, lowerCamelCase      :     bool = False					, lowerCamelCase      :     Optional[int] = None					, **lowerCamelCase      :     Union[str, Any]					, ):



   """simple docstring"""





   super().__init__(
       _lowerCAmelCase					, split=_lowerCAmelCase					, features=_lowerCAmelCase					, cache_dir=_lowerCAmelCase					, keep_in_memory=_lowerCAmelCase					, streaming=_lowerCAmelCase					, num_proc=_lowerCAmelCase					, **_lowerCAmelCase					, )
   __A		:  Optional[int]       				=		path_or_paths if isinstance(_lowerCAmelCase					, _lowerCAmelCase							) else {self.split: path_or_paths}
   __A		:  int       				=		Csv(
       cache_dir=_lowerCAmelCase					, data_files=_lowerCAmelCase					, features=_lowerCAmelCase					, **_lowerCAmelCase					, )






 def 		lowercase_( self      :     int							):



   """simple docstring"""





   if self.streaming:
     __A		:  Optional[int]       				=		self.builder.as_streaming_dataset(split=self.split							)
   # Build regular (map-style) dataset
   else:
     __A		:  Optional[Any]       				=		None
     __A		:  Optional[Any]       				=		None
     __A		:  Optional[Any]       				=		None
     __A		:  List[Any]       				=		None

     self.builder.download_and_prepare(
         download_config=_lowerCAmelCase					, download_mode=_lowerCAmelCase					, verification_mode=_lowerCAmelCase					, base_path=_lowerCAmelCase					, num_proc=self.num_proc					, )
     __A		:  int       				=		self.builder.as_dataset(
         split=self.split					, verification_mode=_lowerCAmelCase					, in_memory=self.keep_in_memory							)
   return dataset







class 			__A					:
 def __init__( self      :     Optional[Any]					, lowerCamelCase      :     Dataset					, lowerCamelCase      :     Union[PathLike, BinaryIO]					, lowerCamelCase      :     Optional[int] = None					, lowerCamelCase      :     Optional[int] = None					, **lowerCamelCase      :     Optional[Any]					, ):



   """simple docstring"""





   if num_proc is not None and num_proc <= 0:
     raise ValueError(f"num_proc {num_proc} must be an integer > 0."							)

   __A		:  Optional[int]       				=		dataset
   __A		:  List[Any]       				=		path_or_buf
   __A		:  List[str]       				=		batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
   __A		:  str       				=		num_proc
   __A		:  List[str]       				=		"""utf-8"""
   __A		:  Any       				=		to_csv_kwargs
 def 		lowercase_( self      :     Union[str, Any]							):



   """simple docstring"""





   __A		:  Dict       				=		self.to_csv_kwargs.pop("""path_or_buf"""					, _lowerCAmelCase							)
   __A		:  Union[str, Any]       				=		self.to_csv_kwargs.pop("""header"""					, _lowerCAmelCase							)
   __A		:  int       				=		self.to_csv_kwargs.pop("""index"""					, _lowerCAmelCase							)

   if isinstance(self.path_or_buf					, (str, bytes, os.PathLike)							):
     with open(self.path_or_buf					, """wb+"""							) as buffer:
       __A		:  Union[str, Any]       				=		self._write(file_obj=_lowerCAmelCase					, header=_lowerCAmelCase					, index=_lowerCAmelCase					, **self.to_csv_kwargs							)
   else:
     __A		:  Tuple       				=		self._write(file_obj=self.path_or_buf					, header=_lowerCAmelCase					, index=_lowerCAmelCase					, **self.to_csv_kwargs							)
   return written
 def 		lowercase_( self      :     Tuple					, lowerCamelCase      :     List[Any]							):



   """simple docstring"""





   __A				,       __A				,       __A				,       __A		:  List[Any]       				=		args

   __A		:  str       				=		query_table(
       table=self.dataset.data					, key=slice(_lowerCAmelCase					, offset + self.batch_size							)					, indices=self.dataset._indices					, )
   __A		:  Union[str, Any]       				=		batch.to_pandas().to_csv(
       path_or_buf=_lowerCAmelCase					, header=header if (offset == 0) else False					, index=_lowerCAmelCase					, **_lowerCAmelCase							)
   return csv_str.encode(self.encoding							)






 def 		lowercase_( self      :     Any					, lowerCamelCase      :     BinaryIO					, lowerCamelCase      :     Optional[int]					, lowerCamelCase      :     Optional[int]					, **lowerCamelCase      :     Any							):



   """simple docstring"""





   __A		:  Any       				=		0

   if self.num_proc is None or self.num_proc == 1:
     for offset in logging.tqdm(
         range(0					, len(self.dataset							)					, self.batch_size							)					, unit="""ba"""					, disable=not logging.is_progress_bar_enabled()					, desc="""Creating CSV from Arrow format"""					, ):
       __A		:  List[Any]       				=		self._batch_csv((offset, header, index, to_csv_kwargs)							)
       written += file_obj.write(_lowerCAmelCase							)

   else:
     __A				,       __A		:  List[str]       				=		len(self.dataset							), self.batch_size
     with multiprocessing.Pool(self.num_proc							) as pool:
       for csv_str in logging.tqdm(
           pool.imap(
               self._batch_csv					, [(offset, header, index, to_csv_kwargs) for offset in range(0					, _lowerCAmelCase					, _lowerCAmelCase							)]					, )					, total=(num_rows // batch_size) + 1 if num_rows % batch_size else num_rows // batch_size					, unit="""ba"""					, disable=not logging.is_progress_bar_enabled()					, desc="""Creating CSV from Arrow format"""					, ):
         written += file_obj.write(_lowerCAmelCase							)

   return written







from itertools import count
from math import asin, pi, sqrt
def 				UpperCamelCase_	(					__snake_case      :    float  )->   float:




						'''simple docstring'''
						return (
						    (1 - 2 * point) * sqrt(point - point**2  ) + 2 * point + asin(sqrt(1 - point  )  )
						) / 4
def 				UpperCamelCase_	(					__snake_case      :    int  )->   float:




						'''simple docstring'''
						__magic_name__					=      (circles_number + 1 - sqrt(2 * circles_number  )) / (
						    2 * (circles_number**2 + 1)
						)
						__magic_name__					=      circles_number * intersection_y

						__magic_name__					=      intersection_x * intersection_y / 2
						__magic_name__					=      circle_bottom_arc_integral(
						    1 / 2  ) - circle_bottom_arc_integral(__snake_case  )

						return triangle_area + concave_region_area
def 				UpperCamelCase_	(					__snake_case      :    float = 1 / 10_00  )->   int:




						'''simple docstring'''
						__magic_name__					=      (1 - pi / 4) / 4

						for n in count(1  ):
												if concave_triangle_area(__snake_case  ) / l_section_area < fraction:
																		return n

						return -1


if __name__ == "__main__":
					print(f'''{solution() = }''')

