


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


a : str		=				datasets.utils.logging.get_logger(__name__)
@dataclass
class 	lowerCamelCase_       (				datasets.BuilderConfig				):



					'''simple docstring'''







					__UpperCAmelCase            =				None
					__UpperCAmelCase            =				"utf-8"
					__UpperCAmelCase            =				None
					__UpperCAmelCase            =				None
					__UpperCAmelCase            =				True  # deprecated
					__UpperCAmelCase            =				None  # deprecated
					__UpperCAmelCase            =				10 << 20  # 10MB
					__UpperCAmelCase            =				None




class 	lowerCamelCase_       (				datasets.ArrowBasedBuilder				):



					'''simple docstring'''







					__UpperCAmelCase            =				JsonConfig






					def A      (				self						)   ->			Dict:







								'''simple docstring'''

								if self.config.block_size is not None:
											logger.warning('''The JSON loader parameter `block_size` is deprecated. Please use `chunksize` instead'''						)
											__lowercase 					=   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 A      (				self ,       snake_case_						)   ->			int:







								'''simple docstring'''

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






					def A      (				self ,       snake_case_						)   ->			pa.Table:







								'''simple docstring'''

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






					def A      (				self ,       snake_case_						)   ->			Optional[int]:







								'''simple docstring'''

								for file_idx, file in enumerate(itertools.chain.from_iterable(snake_case_						)						):
											# 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(snake_case_ ,       encoding=self.config.encoding ,       errors=self.config.encoding_errors						) as f:
																	__lowercase 					=   json.load(snake_case_						)

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

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

											# If the file has one json object per line
											else:
														with open(snake_case_ ,       '''rb'''						) as f:
																	__lowercase 					=   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
																	__lowercase 					=   max(self.config.chunksize // 3_2 ,       1_6 << 1_0						)
																	__lowercase 					=   (
																	    self.config.encoding_errors if self.config.encoding_errors is not None else '''strict'''
																	)
																	while True:
																				__lowercase 					=   f.read(self.config.chunksize						)
																				if not batch:
																							break
																				# Finish current line
																				try:
																							batch += f.readline()
																				except (AttributeError, io.UnsupportedOperation):
																							batch += readline(snake_case_						)
																				# PyArrow only accepts utf-8 encoded bytes
																				if self.config.encoding != "utf-8":
																							__lowercase 					=   batch.decode(self.config.encoding ,       errors=snake_case_						).encode('''utf-8'''						)
																				try:
																							while True:
																										try:
																													__lowercase 					=   paj.read_json(
																													    io.BytesIO(snake_case_						) ,       read_options=paj.ReadOptions(block_size=snake_case_						)						)
																													break
																										except (pa.ArrowInvalid, pa.ArrowNotImplementedError) as e:
																													if (
																													    isinstance(snake_case_ ,       pa.ArrowInvalid						)
																													    and "straddling" not in str(snake_case_						)
																													    or block_size > len(snake_case_						)
																													):
																																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(snake_case_						)} 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(
																										    snake_case_ ,       encoding=self.config.encoding ,       errors=self.config.encoding_errors						) as f:
																													__lowercase 					=   json.load(snake_case_						)
																							except json.JSONDecodeError:
																										logger.error(F'Failed to read file \'{file}\' with error {type(snake_case_						)}: {e}'						)
																										raise e
																							# If possible, parse the file as a list of json objects and exit the loop
																							if isinstance(snake_case_ ,       snake_case_						):  # list is the only sequence type supported in JSON
																										try:
																													__lowercase 					=   set().union(*[row.keys() for row in dataset]						)
																													__lowercase 					=   {col: [row.get(snake_case_						) for row in dataset] for col in keys}
																													__lowercase 					=   pa.Table.from_pydict(snake_case_						)
																										except (pa.ArrowInvalid, AttributeError) as e:
																													logger.error(F'Failed to read file \'{file}\' with error {type(snake_case_						)}: {e}'						)
																													raise ValueError(F'Not able to read records in the JSON file at {file}.'						) from None
																										yield file_idx, self._cast_table(snake_case_						)
																										break
																							else:
																										logger.error(F'Failed to read file \'{file}\' with error {type(snake_case_						)}: {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(snake_case_						)
																				batch_idx += 1






import unittest

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



					'''simple docstring'''







					def A      (				self						)   ->			Optional[Any]:







								'''simple docstring'''

								__lowercase 					=   0
								__lowercase 					=   [0]
								__lowercase 					=   [0]
								__lowercase 					=   len(snake_case_						)
								self.assertEqual(k.knapsack(snake_case_ ,       snake_case_ ,       snake_case_ ,       snake_case_						) ,       0						)

								__lowercase 					=   [6_0]
								__lowercase 					=   [1_0]
								__lowercase 					=   len(snake_case_						)
								self.assertEqual(k.knapsack(snake_case_ ,       snake_case_ ,       snake_case_ ,       snake_case_						) ,       0						)






					def A      (				self						)   ->			Tuple:







								'''simple docstring'''

								__lowercase 					=   3
								__lowercase 					=   [1, 2, 3]
								__lowercase 					=   [3, 2, 1]
								__lowercase 					=   len(snake_case_						)
								self.assertEqual(k.knapsack(snake_case_ ,       snake_case_ ,       snake_case_ ,       snake_case_						) ,       5						)






					def A      (				self						)   ->			str:







								'''simple docstring'''

								__lowercase 					=   5_0
								__lowercase 					=   [6_0, 1_0_0, 1_2_0]
								__lowercase 					=   [1_0, 2_0, 3_0]
								__lowercase 					=   len(snake_case_						)
								self.assertEqual(k.knapsack(snake_case_ ,       snake_case_ ,       snake_case_ ,       snake_case_						) ,       2_2_0						)


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


