




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 		UpperCAmelCase   (				_UpperCAmelCase			):







						'''simple docstring'''





						def __init__(						self							:     str       ,	__lowercase							:     NestedDataStructureLike[PathLike]       ,	__lowercase							:     Optional[NamedSplit] = None       ,	__lowercase							:     Optional[Features] = None       ,	__lowercase							:     str = None       ,	__lowercase							:     bool = False       ,	__lowercase							:     bool = False       ,	__lowercase							:     Optional[str] = None       ,	__lowercase							:     Optional[int] = None       ,	**__lowercase							:     int       ,	):






							"""simple docstring"""






							super().__init__(
							    lowercase_       ,	split=lowercase_       ,	features=lowercase_       ,	cache_dir=lowercase_       ,	keep_in_memory=lowercase_       ,	streaming=lowercase_       ,	num_proc=lowercase_       ,	**lowercase_       ,	)
							snake_case_		    =     field
							snake_case_		    =     path_or_paths if isinstance(lowercase_       ,	lowercase_						) else {self.split: path_or_paths}
							snake_case_		    =     Json(
							    cache_dir=lowercase_       ,	data_files=lowercase_       ,	features=lowercase_       ,	field=lowercase_       ,	**lowercase_       ,	)






						def        snake_case__						(						self							:     Any						):






							"""simple docstring"""






							if self.streaming:
								snake_case_		    =     self.builder.as_streaming_dataset(split=self.split						)
							# Build regular (map-style) dataset
							else:
								snake_case_		    =     None
								snake_case_		    =     None
								snake_case_		    =     None
								snake_case_		    =     None

								self.builder.download_and_prepare(
								    download_config=lowercase_       ,	download_mode=lowercase_       ,	verification_mode=lowercase_       ,	base_path=lowercase_       ,	num_proc=self.num_proc       ,	)
								snake_case_		    =     self.builder.as_dataset(
								    split=self.split       ,	verification_mode=lowercase_       ,	in_memory=self.keep_in_memory						)
							return dataset







class 		UpperCAmelCase   :







						'''simple docstring'''





						def __init__(						self							:     Tuple       ,	__lowercase							:     Dataset       ,	__lowercase							:     Union[PathLike, BinaryIO]       ,	__lowercase							:     Optional[int] = None       ,	__lowercase							:     Optional[int] = None       ,	**__lowercase							:     Tuple       ,	):






							"""simple docstring"""






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

							snake_case_		    =     dataset
							snake_case_		    =     path_or_buf
							snake_case_		    =     batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
							snake_case_		    =     num_proc
							snake_case_		    =     "utf-8"
							snake_case_		    =     to_json_kwargs






						def        snake_case__						(						self							:     List[Any]						):






							"""simple docstring"""






							snake_case_		    =     self.to_json_kwargs.pop("path_or_buf"       ,	lowercase_						)
							snake_case_		    =     self.to_json_kwargs.pop("orient"       ,	"records"						)
							snake_case_		    =     self.to_json_kwargs.pop("lines"       ,	True if orient == "records" else False						)
							snake_case_		    =     self.to_json_kwargs.pop("index"       ,	False if orient in ["split", "table"] else True						)
							snake_case_		    =     self.to_json_kwargs.pop("compression"       ,	lowercase_						)

							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=lowercase_						) as buffer:
									snake_case_		    =     self._write(file_obj=lowercase_       ,	orient=lowercase_       ,	lines=lowercase_       ,	index=lowercase_       ,	**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."						)
								snake_case_		    =     self._write(
								    file_obj=self.path_or_buf       ,	orient=lowercase_       ,	lines=lowercase_       ,	index=lowercase_       ,	**self.to_json_kwargs						)
							return written






						def        snake_case__						(						self							:     List[Any]       ,	__lowercase							:     int						):






							"""simple docstring"""






							snake_case_    ,      snake_case_    ,      snake_case_    ,      snake_case_    ,      snake_case_		    =     args

							snake_case_		    =     query_table(
							    table=self.dataset.data       ,	key=slice(lowercase_       ,	offset + self.batch_size						)       ,	indices=self.dataset._indices       ,	)
							snake_case_		    =     batch.to_pandas().to_json(
							    path_or_buf=lowercase_       ,	orient=lowercase_       ,	lines=lowercase_       ,	index=lowercase_       ,	**lowercase_						)
							if not json_str.endswith("\n"						):
								json_str += "\n"
							return json_str.encode(self.encoding						)






						def        snake_case__						(						self							:     Any       ,	__lowercase							:     BinaryIO       ,	__lowercase							:     Optional[Any]       ,	__lowercase							:     Optional[int]       ,	__lowercase							:     Optional[Any]       ,	**__lowercase							:     Optional[Any]       ,	):






							"""simple docstring"""






							snake_case_		    =     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"       ,	):
									snake_case_		    =     self._batch_json((offset, orient, lines, index, to_json_kwargs)						)
									written += file_obj.write(lowercase_						)
							else:
								snake_case_    ,      snake_case_		    =     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       ,	lowercase_       ,	lowercase_						)]       ,	)       ,	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(lowercase_						)

							return written



class  A						:







    """simple docstring"""





    def __init__(      self :       Any,lowercase_ :       Tuple,lowercase_ :       Any,lowercase_ :       List[str]		)->    List[Any]:





        '''simple docstring'''







        A__          =   name
        A__          =   value
        A__          =   weight


    def __repr__(      self :       int		)->    Tuple:





        '''simple docstring'''







        return F'{self.__class__.__name__}({self.name}, {self.value}, {self.weight})'


    def 						snake_case__     (      self :       Any		)->    str:





        '''simple docstring'''







        return self.value


    def 						snake_case__     (      self :       Any		)->    Tuple:





        '''simple docstring'''







        return self.name


    def 						snake_case__     (      self :       Any		)->    Dict:





        '''simple docstring'''







        return self.weight


    def 						snake_case__     (      self :       Union[str, Any]		)->    Optional[Any]:





        '''simple docstring'''







        return self.value / self.weight




def 						_snake_case(    SCREAMING_SNAKE_CASE__			:	Optional[Any]    ,			SCREAMING_SNAKE_CASE__			:	List[str]    ,			SCREAMING_SNAKE_CASE__			:	List[Any]      )							->      List[Any]:





    '''simple docstring'''






    A__          =   []
    for i in range(len(SCREAMING_SNAKE_CASE__      )      ):
        menu.append(Things(name[i]    ,			value[i]    ,			weight[i]      )      )
    return menu
def 						_snake_case(    SCREAMING_SNAKE_CASE__			:	Dict    ,			SCREAMING_SNAKE_CASE__			:	List[str]    ,			SCREAMING_SNAKE_CASE__			:	int      )							->      Any:





    '''simple docstring'''






    A__          =   sorted(SCREAMING_SNAKE_CASE__    ,			key=SCREAMING_SNAKE_CASE__    ,			reverse=SCREAMING_SNAKE_CASE__      )
    A__          =   []
    A__      ,						A__          =   0.0, 0.0
    for i in range(len(SCREAMING_SNAKE_CASE__      )      ):
        if (total_cost + items_copy[i].get_weight()) <= max_cost:
            result.append(items_copy[i]      )
            total_cost += items_copy[i].get_weight()
            total_value += items_copy[i].get_value()
    return (result, total_value)
def 						_snake_case(    )							->      Any:





    '''simple docstring'''








if __name__ == "__main__":
     import doctest

     doctest.testmod()

