



"""simple docstring"""






from __future__ import annotations

from typing import Any



class 			A__   :




	'''simple docstring'''





	def __init__(     self:		List[str]       ,			_SCREAMING_SNAKE_CASE:		int)				->       None:

				"""simple docstring"""

				__lowerCAmelCase      :  List[Any]												=       num_of_nodes
				__lowerCAmelCase      :  list[list[int]]												=       []
				__lowerCAmelCase      :  dict[int, int]												=       {}

	def 							_SCREAMING_SNAKE_CASE   (     self:		List[Any]       ,			_SCREAMING_SNAKE_CASE:		int       ,			_SCREAMING_SNAKE_CASE:		int       ,			_SCREAMING_SNAKE_CASE:		int)				->       None:

				"""simple docstring"""

				self.m_edges.append([u_node, v_node, weight])

	def 							_SCREAMING_SNAKE_CASE   (     self:		List[str]       ,			_SCREAMING_SNAKE_CASE:		int)				->       int:

				"""simple docstring"""

				if self.m_component[u_node] == u_node:
							return u_node
				return self.find_component(self.m_component[u_node])

	def 							_SCREAMING_SNAKE_CASE   (     self:		Dict       ,			_SCREAMING_SNAKE_CASE:		int)				->       None:

				"""simple docstring"""

				if self.m_component[u_node] != u_node:
							for k in self.m_component:
										__lowerCAmelCase      :  Tuple												=       self.find_component(_SCREAMING_SNAKE_CASE)

	def 							_SCREAMING_SNAKE_CASE   (     self:		Dict       ,			_SCREAMING_SNAKE_CASE:		list[int]       ,			_SCREAMING_SNAKE_CASE:		int       ,			_SCREAMING_SNAKE_CASE:		int)				->       None:

				"""simple docstring"""

				if component_size[u_node] <= component_size[v_node]:
							__lowerCAmelCase      :  int												=       v_node
							component_size[v_node] += component_size[u_node]
							self.set_component(_SCREAMING_SNAKE_CASE)

				elif component_size[u_node] >= component_size[v_node]:
							__lowerCAmelCase      :  Any												=       self.find_component(_SCREAMING_SNAKE_CASE)
							component_size[u_node] += component_size[v_node]
							self.set_component(_SCREAMING_SNAKE_CASE)







	def 							_SCREAMING_SNAKE_CASE   (     self:		List[Any])				->       None:

				"""simple docstring"""

				__lowerCAmelCase      :  int												=       []
				__lowerCAmelCase      :  int												=       0

				__lowerCAmelCase      :  list[Any]												=       [-1] * self.m_num_of_nodes

				# A list of components (initialized to all of the nodes)
				for node in range(self.m_num_of_nodes):
							self.m_component.update({node: node})
							component_size.append(1)

				__lowerCAmelCase      :  Union[str, Any]												=       self.m_num_of_nodes

				while num_of_components > 1:
							for edge in self.m_edges:
										__lowerCAmelCase						,	__lowerCAmelCase						,	__lowerCAmelCase      :  Tuple												=       edge

										__lowerCAmelCase      :  Dict												=       self.m_component[u]
										__lowerCAmelCase      :  Union[str, Any]												=       self.m_component[v]

										if u_component != v_component:

													for component in (u_component, v_component):
																if (
																    minimum_weight_edge[component] == -1
																    or minimum_weight_edge[component][2] > w
																):
																			__lowerCAmelCase      :  List[Any]												=       [u, v, w]

							for edge in minimum_weight_edge:
										if isinstance(_SCREAMING_SNAKE_CASE       ,			_SCREAMING_SNAKE_CASE):
													__lowerCAmelCase						,	__lowerCAmelCase						,	__lowerCAmelCase      :  Optional[Any]												=       edge

													__lowerCAmelCase      :  Optional[Any]												=       self.m_component[u]
													__lowerCAmelCase      :  Dict												=       self.m_component[v]

													if u_component != v_component:
																mst_weight += w
																self.union(_SCREAMING_SNAKE_CASE       ,			_SCREAMING_SNAKE_CASE       ,			_SCREAMING_SNAKE_CASE)
																print(F"""Added edge [{u} - {v}]\nAdded weight: {w}\n""")
																num_of_components -= 1

							__lowerCAmelCase      :  str												=       [-1] * self.m_num_of_nodes
				print(F"""The total weight of the minimal spanning tree is: {mst_weight}""")






def 			_lowercase				(  )						->   None:
			pass


if __name__ == "__main__":
	import doctest

	doctest.testmod()




"""simple docstring"""






import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


__snake_case							:   Optional[int]      =    50_000
__snake_case							:   Dict      =    5_000

__snake_case      ,		__snake_case							:   Union[str, Any]      =    os.path.split(__file__)
__snake_case							:   Any      =    os.path.join(RESULTS_BASEPATH, 'results', RESULTS_FILENAME.replace('.py', '.json'))


@get_duration
def 			_lowercase				(  __snake_case					,__snake_case	)						->   Dict:
			for i in range(__snake_case	):
						__lowerCAmelCase      :  Union[str, Any]												=       dataset[i]


@get_duration
def 			_lowercase				(  __snake_case					,__snake_case					,__snake_case	)						->   Dict:
			for i in range(0					,len(__snake_case	)					,__snake_case	):
						__lowerCAmelCase      :  List[str]												=       dataset[i : i + batch_size]


@get_duration
def 			_lowercase				(  __snake_case					,__snake_case					,__snake_case	)						->   Dict:
			with dataset.formatted_as(type=__snake_case	):
						for i in range(__snake_case	):
									__lowerCAmelCase      :  Union[str, Any]												=       dataset[i]


@get_duration
def 			_lowercase				(  __snake_case					,__snake_case					,__snake_case					,__snake_case	)						->   str:
			with dataset.formatted_as(type=__snake_case	):
						for i in range(0					,__snake_case					,__snake_case	):
									__lowerCAmelCase      :  Optional[int]												=       dataset[i : i + batch_size]


def 			_lowercase				(  )						->   Union[str, Any]:
			__lowerCAmelCase      :  Optional[int]												=       {"num examples": SPEED_TEST_N_EXAMPLES}
			__lowerCAmelCase      :  Optional[int]												=       [
			    (read, {"length": SMALL_TEST}),
			    (read, {"length": SPEED_TEST_N_EXAMPLES}),
			    (read_batch, {"length": SPEED_TEST_N_EXAMPLES, "batch_size": 10}),
			    (read_batch, {"length": SPEED_TEST_N_EXAMPLES, "batch_size": 100}),
			    (read_batch, {"length": SPEED_TEST_N_EXAMPLES, "batch_size": 1_000}),
			    (read_formatted, {"type": "numpy", "length": SMALL_TEST}),
			    (read_formatted, {"type": "pandas", "length": SMALL_TEST}),
			    (read_formatted, {"type": "torch", "length": SMALL_TEST}),
			    (read_formatted, {"type": "tensorflow", "length": SMALL_TEST}),
			    (read_formatted_batch, {"type": "numpy", "length": SMALL_TEST, "batch_size": 10}),
			    (read_formatted_batch, {"type": "numpy", "length": SMALL_TEST, "batch_size": 1_000}),
			]

			__lowerCAmelCase      :  Any												=       [
			    (read, {"length": SMALL_TEST}),
			    (read, {"length": SPEED_TEST_N_EXAMPLES}),
			    (read_batch, {"length": SPEED_TEST_N_EXAMPLES, "batch_size": 10}),
			    (read_batch, {"length": SPEED_TEST_N_EXAMPLES, "batch_size": 100}),
			    (read_batch, {"length": SPEED_TEST_N_EXAMPLES, "batch_size": 1_000}),
			    (read_formatted, {"type": "numpy", "length": SMALL_TEST}),
			    (read_formatted_batch, {"type": "numpy", "length": SMALL_TEST, "batch_size": 10}),
			    (read_formatted_batch, {"type": "numpy", "length": SMALL_TEST, "batch_size": 1_000}),
			]
			with tempfile.TemporaryDirectory() as tmp_dir:
						print("generating dataset"	)
						__lowerCAmelCase      :  int												=       datasets.Features(
						    {"list": datasets.Sequence(datasets.Value("float32"	)	), "numbers": datasets.Value("float32"	)}	)
						__lowerCAmelCase      :  str												=       generate_example_dataset(
						    os.path.join(__snake_case					,"dataset.arrow"	)					,__snake_case					,num_examples=__snake_case					,seq_shapes={"list": (100,)}					,)
						print("first set of iterations"	)
						for func, kwargs in functions:
									print(func.__name__					,str(__snake_case	)	)
									__lowerCAmelCase      :  str												=       func(__snake_case					,**__snake_case	)

						print("shuffling dataset"	)
						__lowerCAmelCase      :  Optional[int]												=       dataset.shuffle()
						print("Second set of iterations (after shuffling"	)
						for func, kwargs in functions_shuffled:
									print("shuffled "					,func.__name__					,str(__snake_case	)	)
									__lowerCAmelCase      :  List[str]												=       func(
									    __snake_case					,**__snake_case	)

			with open(__snake_case					,"wb"	) as f:
						f.write(json.dumps(__snake_case	).encode("utf-8"	)	)


if __name__ == "__main__":  # useful to run the profiler
	benchmark_iterating()