
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				=datasets.utils.logging.get_logger(__name__)




@dataclass
class     _SCREAMING_SNAKE_CASE     (      datasets.BuilderConfig						):
	lowerCAmelCase__         = None
	lowerCAmelCase__         = "utf-8"
	lowerCAmelCase__         = None
	lowerCAmelCase__         = None
	lowerCAmelCase__         = True  # deprecated
	lowerCAmelCase__         = None  # deprecated
	lowerCAmelCase__         = 10 << 20  # 10MB
	lowerCAmelCase__         = None




class     _SCREAMING_SNAKE_CASE     (      datasets.ArrowBasedBuilder						):
	lowerCAmelCase__         = JsonConfig



	def     SCREAMING_SNAKE_CASE_(    self )				->       Union[str, Any]:
					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     SCREAMING_SNAKE_CASE_(    self						,  lowercase )				->       List[str]:
					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(lowercase						,  (str, list, tuple) ):
									lowerCamelCase_						=			data_files
									if isinstance(lowercase						,  lowercase ):
													lowerCamelCase_						=			[files]
									lowerCamelCase_						=			[dl_manager.iter_files(lowercase ) 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(lowercase						,  lowercase ):
													lowerCamelCase_						=			[files]
									lowerCamelCase_						=			[dl_manager.iter_files(lowercase ) for file in files]
									splits.append(datasets.SplitGenerator(name=lowercase						,  gen_kwargs={"files": files} ) )
					return splits



	def     SCREAMING_SNAKE_CASE_(    self						,  lowercase )				->       pa.Table:
					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(lowercase ).type
													lowerCamelCase_						=			pa_table.append_column(lowercase						,  pa.array([None] * len(lowercase )						,  type=lowercase ) )
									# 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(lowercase						,  self.config.features.arrow_schema )
					return pa_table



	def     SCREAMING_SNAKE_CASE_(    self						,  lowercase )				->       int:
					for file_idx, file in enumerate(itertools.chain.from_iterable(lowercase ) ):
									# 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(lowercase						,  encoding=self.config.encoding						,  errors=self.config.encoding_errors ) as f:
																	lowerCamelCase_						=			json.load(lowercase )

													# 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(lowercase						,  (list, tuple) ):
																	lowerCamelCase_						=			set().union(*[row.keys() for row in dataset] )
																	lowerCamelCase_						=			{col: [row.get(lowercase ) for row in dataset] for col in keys}
													else:
																	lowerCamelCase_						=			dataset
													lowerCamelCase_						=			pa.Table.from_pydict(lowercase )
													yield file_idx, self._cast_table(lowercase )

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




from collections import deque





def 			lowerCamelCase_ (				lowerCamelCase__    ):
				lowerCamelCase_						=			len(lowerCamelCase__    )
				lowerCamelCase_						=			deque()
				lowerCamelCase_						=			[False for _ in range(lowerCamelCase__    )]
				lowerCamelCase_						=			[-1 for _ in range(lowerCamelCase__    )]
				lowerCamelCase_						=			index_of[:]

				def strong_connect(lowerCamelCase__	, lowerCamelCase__	, lowerCamelCase__    ):
								lowerCamelCase_						=			index  # the number when this node is seen
								lowerCamelCase_						=			index  # lowest rank node reachable from here
								index += 1
								stack.append(lowerCamelCase__    )
								lowerCamelCase_						=			True

								for w in g[v]:
												if index_of[w] == -1:
																lowerCamelCase_						=			strong_connect(lowerCamelCase__	, lowerCamelCase__	, lowerCamelCase__    )
																lowerCamelCase_						=			(
																    lowlink_of[w] if lowlink_of[w] < lowlink_of[v] else lowlink_of[v]
																)
												elif on_stack[w]:
																lowerCamelCase_						=			(
																    lowlink_of[w] if lowlink_of[w] < lowlink_of[v] else lowlink_of[v]
																)

								if lowlink_of[v] == index_of[v]:
												lowerCamelCase_						=			[]
												lowerCamelCase_						=			stack.pop()
												lowerCamelCase_						=			False
												component.append(lowerCamelCase__    )
												while w != v:
																lowerCamelCase_						=			stack.pop()
																lowerCamelCase_						=			False
																component.append(lowerCamelCase__    )
												components.append(lowerCamelCase__    )
								return index

				lowerCamelCase_						=			[]
				for v in range(lowerCamelCase__    ):
								if index_of[v] == -1:
												strong_connect(lowerCamelCase__	, 0	, lowerCamelCase__    )

				return components





def 			lowerCamelCase_ (				lowerCamelCase__	, lowerCamelCase__    ):
				lowerCamelCase_						=			[[] for _ in range(lowerCamelCase__    )]
				for u, v in edges:
								g[u].append(lowerCamelCase__    )
				return g


if __name__ == "__main__":
			# Test
			__A				=7
			__A				=[0, 0, 1, 2, 3, 3, 4, 4, 6]
			__A				=[1, 3, 2, 0, 1, 4, 5, 6, 5]
			__A				=[(u, v) for u, v in zip(source, target)]
			__A				=create_graph(n_vertices, edges)

			assert [[5], [6], [4], [3, 2, 1, 0]] == tarjan(g)


