






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 							lowercase    (						__lowercase			):






 '''simple docstring'''




 def __init__(	self							,  _A							,  _A = None							,  _A = None							,  _A = None							,  _A = False							,  _A = False							,  _A = None							,  _A = None							,  **_A							,  ) ->		Tuple:

     """simple docstring"""



     super().__init__(
         _A							,  split=_A							,  features=_A							,  cache_dir=_A							,  keep_in_memory=_A							,  streaming=_A							,  num_proc=_A							,  **_A							,  )
     _UpperCAmelCase				:      List[Any]			  =				field
     _UpperCAmelCase				:      Union[str, Any]			  =				path_or_paths if isinstance(_A							,  _A) else {self.split: path_or_paths}
     _UpperCAmelCase				:      Dict			  =				Json(
         cache_dir=_A							,  data_files=_A							,  features=_A							,  field=_A							,  **_A							,  )


 def  snake_case__				(	self) ->		Tuple:

     """simple docstring"""



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

         self.builder.download_and_prepare(
             download_config=_A							,  download_mode=_A							,  verification_mode=_A							,  base_path=_A							,  num_proc=self.num_proc							,  )
         _UpperCAmelCase				:      Optional[Any]			  =				self.builder.as_dataset(
             split=self.split							,  verification_mode=_A							,  in_memory=self.keep_in_memory)
     return dataset



class 							lowercase    :






 '''simple docstring'''




 def __init__(	self							,  _A							,  _A							,  _A = None							,  _A = None							,  **_A							,  ) ->		int:

     """simple docstring"""



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

     _UpperCAmelCase				:      Optional[int]			  =				dataset
     _UpperCAmelCase				:      Union[str, Any]			  =				path_or_buf
     _UpperCAmelCase				:      Dict			  =				batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
     _UpperCAmelCase				:      Optional[int]			  =				num_proc
     _UpperCAmelCase				:      Optional[int]			  =				'''utf-8'''
     _UpperCAmelCase				:      Any			  =				to_json_kwargs


 def  snake_case__				(	self) ->		int:

     """simple docstring"""



     _UpperCAmelCase				:      Optional[Any]			  =				self.to_json_kwargs.pop('''path_or_buf'''							,  _A)
     _UpperCAmelCase				:      List[Any]			  =				self.to_json_kwargs.pop('''orient'''							,  '''records''')
     _UpperCAmelCase				:      Tuple			  =				self.to_json_kwargs.pop('''lines'''							,  True if orient == '''records''' else False)
     _UpperCAmelCase				:      int			  =				self.to_json_kwargs.pop('''index'''							,  False if orient in ['''split''', '''table'''] else True)
     _UpperCAmelCase				:      Optional[int]			  =				self.to_json_kwargs.pop('''compression'''							,  _A)

     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=_A) as buffer:
             _UpperCAmelCase				:      str			  =				self._write(file_obj=_A							,  orient=_A							,  lines=_A							,  index=_A							,  **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.''')
         _UpperCAmelCase				:      str			  =				self._write(
             file_obj=self.path_or_buf							,  orient=_A							,  lines=_A							,  index=_A							,  **self.to_json_kwargs)
     return written


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

     """simple docstring"""



     _UpperCAmelCase				:      List[Any]			  =				args

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


 def  snake_case__				(	self							,  _A							,  _A							,  _A							,  _A							,  **_A							,  ) ->		int:

     """simple docstring"""



     _UpperCAmelCase				:      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'''							,  ):
             _UpperCAmelCase				:      Union[str, Any]			  =				self._batch_json((offset, orient, lines, index, to_json_kwargs))
             written += file_obj.write(_A)
     else:
         _UpperCAmelCase				:      List[str]			  =				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							,  _A							,  _A)]							,  )							,  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(_A)

     return written












import unittest

from knapsack import knapsack as k
class 							A_    (						unittest.TestCase			):






 '''simple docstring'''




 def  snake_case__				(	self) ->		Dict:

     """simple docstring"""



     _UpperCAmelCase				:      Optional[int]			  =				0
     _UpperCAmelCase				:      List[Any]			  =				[0]
     _UpperCAmelCase				:      Optional[Any]			  =				[0]
     _UpperCAmelCase				:      Optional[int]			  =				len(_A)
     self.assertEqual(k.knapsack(_A							,  _A							,  _A							,  _A)							,  0)

     _UpperCAmelCase				:      Optional[int]			  =				[60]
     _UpperCAmelCase				:      List[str]			  =				[10]
     _UpperCAmelCase				:      str			  =				len(_A)
     self.assertEqual(k.knapsack(_A							,  _A							,  _A							,  _A)							,  0)


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

     """simple docstring"""



     _UpperCAmelCase				:      Any			  =				3
     _UpperCAmelCase				:      int			  =				[1, 2, 3]
     _UpperCAmelCase				:      List[str]			  =				[3, 2, 1]
     _UpperCAmelCase				:      Union[str, Any]			  =				len(_A)
     self.assertEqual(k.knapsack(_A							,  _A							,  _A							,  _A)							,  5)


 def  snake_case__				(	self) ->		Tuple:

     """simple docstring"""



     _UpperCAmelCase				:      List[str]			  =				50
     _UpperCAmelCase				:      Tuple			  =				[60, 100, 120]
     _UpperCAmelCase				:      Optional[int]			  =				[10, 20, 30]
     _UpperCAmelCase				:      Optional[Any]			  =				len(_A)
     self.assertEqual(k.knapsack(_A							,  _A							,  _A							,  _A)							,  220)


if __name__ == "__main__":
  unittest.main()




