






'''simple docstring'''






from collections import defaultdict

from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst


def 				snake_case_  (      )   ->     Union[str, Any]:
							UpperCAmelCase				: Dict											=	9, 14  # noqa: F841
							UpperCAmelCase				: int											=	[
							    [0, 1, 4],
							    [0, 7, 8],
							    [1, 2, 8],
							    [7, 8, 7],
							    [7, 6, 1],
							    [2, 8, 2],
							    [8, 6, 6],
							    [2, 3, 7],
							    [2, 5, 4],
							    [6, 5, 2],
							    [3, 5, 14],
							    [3, 4, 9],
							    [5, 4, 10],
							    [1, 7, 11],
							]

							UpperCAmelCase				: str											=	defaultdict(_lowerCAmelCase						)
							for nodea, nodea, cost in edges:
														adjancency[nodea].append([nodea, cost]						)
														adjancency[nodea].append([nodea, cost]						)

							UpperCAmelCase				: Optional[Any]											=	mst(_lowerCAmelCase						)

							UpperCAmelCase				: str											=	[
							    [7, 6, 1],
							    [2, 8, 2],
							    [6, 5, 2],
							    [0, 1, 4],
							    [2, 5, 4],
							    [2, 3, 7],
							    [0, 7, 8],
							    [3, 4, 9],
							]

							for answer in expected:
														UpperCAmelCase				: str											=	tuple(answer[:2]						)
														UpperCAmelCase				: Union[str, Any]											=	tuple(edge[::-1]						)
														assert edge in result or reverse in result










'''simple docstring'''






from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import Features, Value
from .base import TaskTemplate

@dataclass(frozen=A__    )
class        SCREAMING_SNAKE_CASE(							A__    ):







	"""simple docstring"""






	lowerCamelCase__    				= field(default="""language-modeling"""							,	metadata={"""include_in_asdict_even_if_is_default""": True}    )

	lowerCamelCase__    				= Features({"""text""": Value("""string"""    )}    )
	lowerCamelCase__    				= Features({}    )
	lowerCamelCase__    				= "text"







	@property
	def   A			(		self    :  Optional[Any]	)    ->	Dict[str, str]:
								return {self.text_column: "text"}





