import multiprocessing
import os
from typing import BinaryIO, Optional, Union

import fsspec

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






class 		_lowerCamelCase		( UpperCamelCase_     ):
    def __init__(	self			,			lowerCAmelCase			,			lowerCAmelCase = None			,			lowerCAmelCase = None			,			lowerCAmelCase = None			,			lowerCAmelCase = False			,			lowerCAmelCase = False			,			lowerCAmelCase = None			,			lowerCAmelCase = None			,			**lowerCAmelCase			,			)							->       int:
     super().__init__(
         lowerCAmelCase			,			split=lowerCAmelCase			,			features=lowerCAmelCase			,			cache_dir=lowerCAmelCase			,			keep_in_memory=lowerCAmelCase			,			streaming=lowerCAmelCase			,			num_proc=lowerCAmelCase			,			**lowerCAmelCase			,			)
     SCREAMING_SNAKE_CASE__: str=   field
     SCREAMING_SNAKE_CASE__: Optional[int]=   path_or_paths if isinstance(lowerCAmelCase			,			lowerCAmelCase ) else {self.split: path_or_paths}
     SCREAMING_SNAKE_CASE__: Optional[Any]=   Json(
         cache_dir=lowerCAmelCase			,			data_files=lowerCAmelCase			,			features=lowerCAmelCase			,			field=lowerCAmelCase			,			**lowerCAmelCase			,			)



    def     UpperCamelCase_					(	self )							->       Dict:
     # Build iterable dataset
     if self.streaming:
      SCREAMING_SNAKE_CASE__: Dict=   self.builder.as_streaming_dataset(split=self.split )
     # Build regular (map-style) dataset
     else:
      SCREAMING_SNAKE_CASE__: str=   None
      SCREAMING_SNAKE_CASE__: Any=   None
      SCREAMING_SNAKE_CASE__: Optional[Any]=   None
      SCREAMING_SNAKE_CASE__: Any=   None

      self.builder.download_and_prepare(
          download_config=lowerCAmelCase			,			download_mode=lowerCAmelCase			,			verification_mode=lowerCAmelCase			,			base_path=lowerCAmelCase			,			num_proc=self.num_proc			,			)
      SCREAMING_SNAKE_CASE__: Optional[int]=   self.builder.as_dataset(
          split=self.split			,			verification_mode=lowerCAmelCase			,			in_memory=self.keep_in_memory )
     return dataset






class 		_lowerCamelCase		:
    def __init__(	self			,			lowerCAmelCase			,			lowerCAmelCase			,			lowerCAmelCase = None			,			lowerCAmelCase = None			,			**lowerCAmelCase			,			)							->       Tuple:
     if num_proc is not None and num_proc <= 0:
      raise ValueError(f'num_proc {num_proc} must be an integer > 0.' )

     SCREAMING_SNAKE_CASE__: List[str]=   dataset
     SCREAMING_SNAKE_CASE__: int=   path_or_buf
     SCREAMING_SNAKE_CASE__: Dict=   batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
     SCREAMING_SNAKE_CASE__: List[Any]=   num_proc
     SCREAMING_SNAKE_CASE__: int=   '''utf-8'''
     SCREAMING_SNAKE_CASE__: Union[str, Any]=   to_json_kwargs
    def     UpperCamelCase_					(	self )							->       int:
     SCREAMING_SNAKE_CASE__: str=   self.to_json_kwargs.pop('''path_or_buf'''			,			lowerCAmelCase )
     SCREAMING_SNAKE_CASE__: Optional[Any]=   self.to_json_kwargs.pop('''orient'''			,			'''records''' )
     SCREAMING_SNAKE_CASE__: Union[str, Any]=   self.to_json_kwargs.pop('''lines'''			,			True if orient == '''records''' else False )
     SCREAMING_SNAKE_CASE__: int=   self.to_json_kwargs.pop('''index'''			,			False if orient in ['''split''', '''table'''] else True )
     SCREAMING_SNAKE_CASE__: Dict=   self.to_json_kwargs.pop('''compression'''			,			lowerCAmelCase )

     if compression not in [None, "infer", "gzip", "bz2", "xz"]:
      raise NotImplementedError(f'`datasets` currently does not support {compression} compression' )

     if isinstance(self.path_or_buf			,			(str, bytes, os.PathLike) ):
      with fsspec.open(self.path_or_buf			,			'''wb'''			,			compression=lowerCAmelCase ) as buffer:
       SCREAMING_SNAKE_CASE__: Optional[Any]=   self._write(file_obj=lowerCAmelCase			,			orient=lowerCAmelCase			,			lines=lowerCAmelCase			,			index=lowerCAmelCase			,			**self.to_json_kwargs )
     else:
      if compression:
       raise NotImplementedError(
           f'The compression parameter is not supported when writing to a buffer, but compression={compression}'
           ''' was passed. Please provide a local path instead.''' )
      SCREAMING_SNAKE_CASE__: str=   self._write(
          file_obj=self.path_or_buf			,			orient=lowerCAmelCase			,			lines=lowerCAmelCase			,			index=lowerCAmelCase			,			**self.to_json_kwargs )
     return written
    def     UpperCamelCase_					(	self			,			lowerCAmelCase )							->       int:
     SCREAMING_SNAKE_CASE__,						SCREAMING_SNAKE_CASE__,						SCREAMING_SNAKE_CASE__,						SCREAMING_SNAKE_CASE__,						SCREAMING_SNAKE_CASE__: Union[str, Any]=   args

     SCREAMING_SNAKE_CASE__: Union[str, Any]=   query_table(
         table=self.dataset.data			,			key=slice(lowerCAmelCase			,			offset + self.batch_size )			,			indices=self.dataset._indices			,			)
     SCREAMING_SNAKE_CASE__: List[str]=   batch.to_pandas().to_json(
         path_or_buf=lowerCAmelCase			,			orient=lowerCAmelCase			,			lines=lowerCAmelCase			,			index=lowerCAmelCase			,			**lowerCAmelCase )
     if not json_str.endswith('''\n''' ):
      json_str += "\n"
     return json_str.encode(self.encoding )



    def     UpperCamelCase_					(	self			,			lowerCAmelCase			,			lowerCAmelCase			,			lowerCAmelCase			,			lowerCAmelCase			,			**lowerCAmelCase			,			)							->       int:
     SCREAMING_SNAKE_CASE__: Union[str, 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 json from Arrow format'''			,			):
       SCREAMING_SNAKE_CASE__: List[str]=   self._batch_json((offset, orient, lines, index, to_json_kwargs) )
       written += file_obj.write(lowerCAmelCase )
     else:
      SCREAMING_SNAKE_CASE__,						SCREAMING_SNAKE_CASE__: Dict=   len(self.dataset ), self.batch_size
      with multiprocessing.Pool(self.num_proc ) as pool:
       for json_str in logging.tqdm(
           pool.imap(
               self._batch_json			,			[(offset, orient, lines, index, to_json_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 json from Arrow format'''			,			):
        written += file_obj.write(lowerCAmelCase )

     return written







'''simple docstring'''



def       _UpperCamelCase			(_lowerCamelCase				:  int ,						_lowerCamelCase				:  int ,						_lowerCamelCase				:  int						)-> float:




     '''simple docstring'''





     __snake_case            =	(num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
     # formula for sum of series
     return total







def       _UpperCamelCase			()-> str:




     '''simple docstring'''





     print(sum_of_series(1 ,						1 ,						10						)						)


if __name__ == "__main__":
     import doctest

     doctest.testmod()






