



import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional

import pyarrow as pa
import pyarrow.json as paj

import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline


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





@dataclass
class 		UpperCAmelCase						(						datasets.BuilderConfig				):
   SCREAMING_SNAKE_CASE__							=     None
   SCREAMING_SNAKE_CASE__							=     "utf-8"
   SCREAMING_SNAKE_CASE__							=     None
   SCREAMING_SNAKE_CASE__							=     None
   SCREAMING_SNAKE_CASE__							=     True  # deprecated
   SCREAMING_SNAKE_CASE__							=     None  # deprecated
   SCREAMING_SNAKE_CASE__							=     1_0 << 2_0  # 10MB
   SCREAMING_SNAKE_CASE__							=     None






class 		UpperCAmelCase						(						datasets.ArrowBasedBuilder				):
   SCREAMING_SNAKE_CASE__							=     JsonConfig





   def 	__lowerCAmelCase							(	self			):
         if self.config.block_size is not None:
               logger.warning('''The JSON loader parameter `block_size` is deprecated. Please use `chunksize` instead'''			)
               _lowerCAmelCase 			=  self.config.block_size
         if self.config.use_threads is not True:
               logger.warning(
                   '''The JSON loader parameter `use_threads` is deprecated and doesn\'t have any effect anymore.'''			)
         if self.config.newlines_in_values is not None:
               raise ValueError('''The JSON loader parameter `newlines_in_values` is no longer supported'''			)
         return datasets.DatasetInfo(features=self.config.features			)





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





   def 	__lowerCAmelCase							(	self       ,     _lowerCAmelCase			):
         if self.config.features is not None:
               # adding missing columns
               for column_name in set(self.config.features			) - set(pa_table.column_names			):
                     _lowerCAmelCase 			=  self.config.features.arrow_schema.field(_lowerCAmelCase			).type
                     _lowerCAmelCase 			=  pa_table.append_column(_lowerCAmelCase       ,     pa.array([None] * len(_lowerCAmelCase			)       ,     type=_lowerCAmelCase			)			)
               # more expensive cast to support nested structures with keys in a different order
               # allows str <-> int/float or str to Audio for example
               _lowerCAmelCase 			=  table_cast(_lowerCAmelCase       ,     self.config.features.arrow_schema			)
         return pa_table





   def 	__lowerCAmelCase							(	self       ,     _lowerCAmelCase			):
         for file_idx, file in enumerate(itertools.chain.from_iterable(_lowerCAmelCase			)			):
               # If the file is one json object and if we need to look at the list of items in one specific field
               if self.config.field is not None:
                     with open(_lowerCAmelCase       ,     encoding=self.config.encoding       ,     errors=self.config.encoding_errors			) as f:
                           _lowerCAmelCase 			=  json.load(_lowerCAmelCase			)

                     # We keep only the field we are interested in
                     _lowerCAmelCase 			=  dataset[self.config.field]

                     # We accept two format: a list of dicts or a dict of lists
                     if isinstance(_lowerCAmelCase       ,     (list, tuple)			):
                           _lowerCAmelCase 			=  set().union(*[row.keys() for row in dataset]			)
                           _lowerCAmelCase 			=  {col: [row.get(_lowerCAmelCase			) for row in dataset] for col in keys}
                     else:
                           _lowerCAmelCase 			=  dataset
                     _lowerCAmelCase 			=  pa.Table.from_pydict(_lowerCAmelCase			)
                     yield file_idx, self._cast_table(_lowerCAmelCase			)

               # If the file has one json object per line
               else:
                     with open(_lowerCAmelCase       ,     '''rb'''			) as f:
                           _lowerCAmelCase 			=  0
                           # Use block_size equal to the chunk size divided by 32 to leverage multithreading
                           # Set a default minimum value of 16kB if the chunk size is really small
                           _lowerCAmelCase 			=  max(self.config.chunksize // 32       ,     16 << 10			)
                           _lowerCAmelCase 			=  (
                               self.config.encoding_errors if self.config.encoding_errors is not None else '''strict'''
                           )
                           while True:
                                 _lowerCAmelCase 			=  f.read(self.config.chunksize			)
                                 if not batch:
                                       break
                                 # Finish current line
                                 try:
                                       batch += f.readline()
                                 except (AttributeError, io.UnsupportedOperation):
                                       batch += readline(_lowerCAmelCase			)
                                 # PyArrow only accepts utf-8 encoded bytes
                                 if self.config.encoding != "utf-8":
                                       _lowerCAmelCase 			=  batch.decode(self.config.encoding       ,     errors=_lowerCAmelCase			).encode('''utf-8'''			)
                                 try:
                                       while True:
                                             try:
                                                   _lowerCAmelCase 			=  paj.read_json(
                                                       io.BytesIO(_lowerCAmelCase			)       ,     read_options=paj.ReadOptions(block_size=_lowerCAmelCase			)			)
                                                   break
                                             except (pa.ArrowInvalid, pa.ArrowNotImplementedError) as e:
                                                   if (
                                                       isinstance(_lowerCAmelCase       ,     pa.ArrowInvalid			)
                                                       and "straddling" not in str(_lowerCAmelCase			)
                                                       or block_size > len(_lowerCAmelCase			)
                                                   ):
                                                         raise
                                                   else:
                                                         # Increase the block size in case it was too small.
                                                         # The block size will be reset for the next file.
                                                         logger.debug(
                                                             F'''Batch of {len(_lowerCAmelCase			)} bytes couldn\'t be parsed with block_size={block_size}. Retrying with block_size={block_size * 2}.'''			)
                                                         block_size *= 2
                                 except pa.ArrowInvalid as e:
                                       try:
                                             with open(
                                                 _lowerCAmelCase       ,     encoding=self.config.encoding       ,     errors=self.config.encoding_errors			) as f:
                                                   _lowerCAmelCase 			=  json.load(_lowerCAmelCase			)
                                       except json.JSONDecodeError:
                                             logger.error(F'''Failed to read file \'{file}\' with error {type(_lowerCAmelCase			)}: {e}'''			)
                                             raise e
                                       # If possible, parse the file as a list of json objects and exit the loop
                                       if isinstance(_lowerCAmelCase       ,     _lowerCAmelCase			):  # list is the only sequence type supported in JSON
                                             try:
                                                   _lowerCAmelCase 			=  set().union(*[row.keys() for row in dataset]			)
                                                   _lowerCAmelCase 			=  {col: [row.get(_lowerCAmelCase			) for row in dataset] for col in keys}
                                                   _lowerCAmelCase 			=  pa.Table.from_pydict(_lowerCAmelCase			)
                                             except (pa.ArrowInvalid, AttributeError) as e:
                                                   logger.error(F'''Failed to read file \'{file}\' with error {type(_lowerCAmelCase			)}: {e}'''			)
                                                   raise ValueError(F'''Not able to read records in the JSON file at {file}.'''			) from None
                                             yield file_idx, self._cast_table(_lowerCAmelCase			)
                                             break
                                       else:
                                             logger.error(F'''Failed to read file \'{file}\' with error {type(_lowerCAmelCase			)}: {e}'''			)
                                             raise ValueError(
                                                 F'''Not able to read records in the JSON file at {file}. '''
                                                 F'''You should probably indicate the field of the JSON file containing your records. '''
                                                 F'''This JSON file contain the following fields: {str(list(dataset.keys()			)			)}. '''
                                                 F'''Select the correct one and provide it as `field=\'XXX\'` to the dataset loading method. '''			) from None
                        # 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(_lowerCAmelCase			)
                                 batch_idx += 1




def 							UpperCAmelCase__		(				_SCREAMING_SNAKE_CASE   :	list[int]     ,				_SCREAMING_SNAKE_CASE   :	str				)->list[int]:
      _lowerCAmelCase 			=  int(_SCREAMING_SNAKE_CASE				)

      # Initialize Result
      _lowerCAmelCase 			=  []

      # Traverse through all denomination
      for denomination in reversed(_SCREAMING_SNAKE_CASE				):
            # Find denominations
            while int(_SCREAMING_SNAKE_CASE				) >= int(_SCREAMING_SNAKE_CASE				):
                  total_value -= int(_SCREAMING_SNAKE_CASE				)
                  answer.append(_SCREAMING_SNAKE_CASE				)  # Append the "answers" array

      return answer


# Driver Code
if __name__ == "__main__":
    UpperCAmelCase_									=							[]
    UpperCAmelCase_									=							"0"

    if (
        input("Do you want to enter your denominations ? (yY/n): ").strip().lower()
        == "y"
    ):
        UpperCAmelCase_									=							int(input("Enter the number of denominations you want to add: ").strip())

        for i in range(0, n):
            denominations.append(int(input(F"""Denomination {i}: """).strip()))
        UpperCAmelCase_									=							input("Enter the change you want to make in Indian Currency: ").strip()
    else:
        # All denominations of Indian Currency if user does not enter
        UpperCAmelCase_									=							[1, 2, 5, 1_0, 2_0, 5_0, 1_0_0, 5_0_0, 2_0_0_0]
        UpperCAmelCase_									=							input("Enter the change you want to make: ").strip()

    if int(value) == 0 or int(value) < 0:
        print("The total value cannot be zero or negative.")

    else:
        print(F"""Following is minimal change for {value}: """)
        UpperCAmelCase_									=							find_minimum_change(denominations, value)
        # Print result
        for i in range(len(answer)):
            print(answer[i], end=" ")