



"""simple docstring"""





import itertools
from dataclasses import dataclass
from typing import List, Optional

import pyarrow as pa
import pyarrow.parquet as pq

import datasets
from datasets.table import table_cast


__lowerCAmelCase       :					List[Any]      					=					datasets.utils.logging.get_logger(__name__)



@dataclass
class    _lowerCAmelCase    (				datasets.BuilderConfig		):





		"""simple docstring"""






		_lowerCamelCase			  =       10_000
		_lowerCamelCase			  =       None
		_lowerCamelCase			  =       None




class    _lowerCAmelCase    (				datasets.ArrowBasedBuilder		):





		"""simple docstring"""






		_lowerCamelCase			  =       ParquetConfig





		def    UpperCAmelCase__							(					self   ) ->						List[Any]:







								'''simple docstring'''

								return datasets.DatasetInfo(features=self.config.features   )





		def    UpperCAmelCase__							(					self							,    _lowercase   ) ->						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}'   )
								snake_case_   : str						=			dl_manager.download_and_extract(self.config.data_files   )
								if isinstance(_lowercase							,    (str, list, tuple)   ):
														snake_case_   : Union[str, Any]						=			data_files
														if isinstance(_lowercase							,    _lowercase   ):
																				snake_case_   : Any						=			[files]
														# Use `dl_manager.iter_files` to skip hidden files in an extracted archive
														snake_case_   : str						=			[dl_manager.iter_files(_lowercase   ) for file in files]
														return [datasets.SplitGenerator(name=datasets.Split.TRAIN							,    gen_kwargs={"""files""": files}   )]
								snake_case_   : Union[str, Any]						=			[]
								for split_name, files in data_files.items():
														if isinstance(_lowercase							,    _lowercase   ):
																				snake_case_   : Optional[int]						=			[files]
														# Use `dl_manager.iter_files` to skip hidden files in an extracted archive
														snake_case_   : List[str]						=			[dl_manager.iter_files(_lowercase   ) for file in files]
														# Infer features is they are stoed in the arrow schema
														if self.info.features is None:
																				for file in itertools.chain.from_iterable(_lowercase   ):
																										with open(_lowercase							,    """rb"""   ) as f:
																																snake_case_   : List[str]						=			datasets.Features.from_arrow_schema(pq.read_schema(_lowercase   )   )
																										break
														splits.append(datasets.SplitGenerator(name=_lowercase							,    gen_kwargs={"""files""": files}   )   )
								return splits





		def    UpperCAmelCase__							(					self							,    _lowercase   ) ->						pa.Table:







								'''simple docstring'''

								if self.info.features is not None:
														# more expensive cast to support nested features with keys in a different order
														# allows str <-> int/float or str to Audio for example
														snake_case_   : Dict						=			table_cast(_lowercase							,    self.info.features.arrow_schema   )
								return pa_table





		def    UpperCAmelCase__							(					self							,    _lowercase   ) ->						str:







								'''simple docstring'''

								snake_case_   : Optional[int]						=			self.info.features.arrow_schema if self.info.features is not None else None
								if self.info.features is not None and self.config.columns is not None:
														if sorted(field.name for field in schema   ) != sorted(self.config.columns   ):
																				raise ValueError(
																				    f'Tried to load parquet data with columns \'{self.config.columns}\' with mismatching features \'{self.info.features}\''   )
								for file_idx, file in enumerate(itertools.chain.from_iterable(_lowercase   )   ):
														with open(_lowercase							,    """rb"""   ) as f:
																				snake_case_   : int						=			pq.ParquetFile(_lowercase   )
																				try:
																										for batch_idx, record_batch in enumerate(
																										    parquet_file.iter_batches(batch_size=self.config.batch_size							,    columns=self.config.columns   )   ):
																																snake_case_   : Tuple						=			pa.Table.from_batches([record_batch]   )
																																# 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 f'{file_idx}_{batch_idx}', self._cast_table(_lowercase   )
																				except ValueError as e:
																										logger.error(f'Failed to read file \'{file}\' with error {type(_lowercase   )}: {e}'   )
																										raise






"""simple docstring"""





def 	__lowerCAmelCase						(		__UpperCamelCase      :			Union[str, Any]    ):


						'''simple docstring'''






						snake_case_   : int						=			[0] * len(__UpperCamelCase    )
						snake_case_   : List[str]						=			[]
						snake_case_   : Any						=			[1] * len(__UpperCamelCase    )

						for values in graph.values():
												for i in values:
																		indegree[i] += 1

						for i in range(len(__UpperCamelCase    )    ):
												if indegree[i] == 0:
																		queue.append(__UpperCamelCase    )

						while queue:
												snake_case_   : Optional[int]						=			queue.pop(0    )
												for x in graph[vertex]:
																		indegree[x] -= 1

																		if long_dist[vertex] + 1 > long_dist[x]:
																								snake_case_   : Union[str, Any]						=			long_dist[vertex] + 1

																		if indegree[x] == 0:
																								queue.append(__UpperCamelCase    )

						print(max(__UpperCamelCase    )    )


# Adjacency list of Graph
__lowerCAmelCase       :					str      					=					{0: [2, 3, 4], 1: [2, 7], 2: [5], 3: [5, 7], 4: [7], 5: [6], 6: [7], 7: []}






longest_distance(graph)

