


from typing import Optional

import pyspark

from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader



class 							A   (	UpperCAmelCase__							):
					'''simple docstring'''






					def __init__(self   :						Any				, _UpperCAmelCase   :						pyspark.sql.DataFrame				, _UpperCAmelCase   :						Optional[NamedSplit] = None				, _UpperCAmelCase   :						Optional[Features] = None				, _UpperCAmelCase   :						bool = True				, _UpperCAmelCase   :						str = None				, _UpperCAmelCase   :						bool = False				, _UpperCAmelCase   :						str = None				, _UpperCAmelCase   :						bool = True				, _UpperCAmelCase   :						str = "arrow"				, **_UpperCAmelCase   :						str				, )						->       Tuple:




							"""simple docstring"""


							super().__init__(
							    split=_UpperCAmelCase				, features=_UpperCAmelCase				, cache_dir=_UpperCAmelCase				, keep_in_memory=_UpperCAmelCase				, streaming=_UpperCAmelCase				, **_UpperCAmelCase				, )
							lowercase__					      =		load_from_cache_file
							lowercase__					      =		file_format
							lowercase__					      =		Spark(
							    df=_UpperCAmelCase				, features=_UpperCAmelCase				, cache_dir=_UpperCAmelCase				, working_dir=_UpperCAmelCase				, **_UpperCAmelCase				, )


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




							"""simple docstring"""


							if self.streaming:
									return self.builder.as_streaming_dataset(split=self.split		)
							lowercase__					      =		None if self._load_from_cache_file else DownloadMode.FORCE_REDOWNLOAD
							self.builder.download_and_prepare(
							    download_mode=_UpperCAmelCase				, file_format=self._file_format				, )
							return self.builder.as_dataset(split=self.split		)





def 			UpperCamelCase (     __magic_name__					:							str					)       ->  List[str]:  # noqa: E741
		"""simple docstring"""




		lowercase__					      =		len(__magic_name__					)
		lowercase__					      =		0
		lowercase__					      =		[0] * n
		lowercase__					      =		[False] * n
		lowercase__					      =		[False] * n

		def dfs(__magic_name__					:							str   ,   __magic_name__					:							List[str]   ,   __magic_name__					:							str   ,   __magic_name__					:							Any					):
				if parent == root:
						out_edge_count += 1
				lowercase__					      =		True
				lowercase__					      =		at

				for to in l[at]:
						if to == parent:
								pass
						elif not visited[to]:
								lowercase__					      =		dfs(__magic_name__   ,   __magic_name__   ,   __magic_name__   ,   __magic_name__					)
								lowercase__					      =		min(low[at]   ,   low[to]					)

								# AP found via bridge
								if at < low[to]:
										lowercase__					      =		True
								# AP found via cycle
								if at == low[to]:
										lowercase__					      =		True
						else:
								lowercase__					      =		min(low[at]   ,   __magic_name__					)
				return out_edge_count

		for i in range(__magic_name__					):
				if not visited[i]:
						lowercase__					      =		0
						lowercase__					      =		dfs(__magic_name__   ,   __magic_name__   ,   -1   ,   __magic_name__					)
						lowercase__					      =		out_edge_count > 1

		for x in range(len(__magic_name__					)					):
				if is_art[x] is True:
						print(__magic_name__					)


# Adjacency list of graph
A	:		List[str]    =       {
    0: [1, 2],
    1: [0, 2],
    2: [0, 1, 3, 5],
    3: [2, 4],
    4: [3],
    5: [2, 6, 8],
    6: [5, 7],
    7: [6, 8],
    8: [5, 7],
}







compute_ap(data)

