'''simple docstring'''

import json
import os
from dataclasses import dataclass

import numpy as np
import pyarrow as pa

import datasets
from utils import get_duration


lowercase_  		=			1000_0000_0000
lowercase_  		=			1_0000

lowercase_		,      lowercase_  		=			os.path.split(__file__)
lowercase_  		=			os.path.join(RESULTS_BASEPATH, '''results''', RESULTS_FILENAME.replace('''.py''', '''.json'''))



def 				UpperCamelCase__      (      a__      ,   a__   ):


						'''simple docstring'''






						_lowerCAmelCase					    =pa.Table.from_pydict({'col': [0] * chunk_size}   )
						_lowerCAmelCase					    =pa.concat_tables([table] * (num_examples // chunk_size)   )
						return datasets.Dataset(a__      ,   fingerprint='table_100B'   )
@dataclass
class 	SCREAMING_SNAKE_CASE      :







		"""simple docstring"""
		lowercase :   int							=				42
		lowercase :   str							=				42
		lowercase :   Dict							=				42
		lowercase :   List[str]							=				42






		def 		UpperCamelCase__							( self					)			->  Union[str, Any]:
								_lowerCAmelCase					    =np.random.default_rng(self.seed					)
								_lowerCAmelCase					    =rng.integers(low=self.low		,    high=self.high		,    size=self.size					).tolist()






		def __iter__( self					)			->  List[Any]:
								return iter(self._sampled_values					)






		def __len__( self					)			->  Optional[int]:
								return self.size



@get_duration
def 				UpperCamelCase__      (      a__   ):


						'''simple docstring'''






						_lowerCAmelCase					    =dataset[0]



@get_duration
def 				UpperCamelCase__      (      a__   ):


						'''simple docstring'''






						_lowerCAmelCase					    =dataset[-1]



@get_duration
def 				UpperCamelCase__      (      a__   ):


						'''simple docstring'''






						_lowerCAmelCase					    =dataset[range(len(a__   ) // 2      ,   len(a__   ) // 2 + 1_0_2_4   )]



@get_duration
def 				UpperCamelCase__      (      a__   ):


						'''simple docstring'''






						_lowerCAmelCase					    =dataset[RandIter(0      ,   len(a__   )      ,   1_0_2_4      ,   seed=4_2   )]



def 				UpperCamelCase__      (      ):


						'''simple docstring'''






						_lowerCAmelCase					    ={'num examples': SPEED_TEST_N_EXAMPLES}
						_lowerCAmelCase					    =(get_first_row, get_last_row, get_batch_of_aaaa_rows, get_batch_of_aaaa_random_rows)
						print('generating dataset'   )
						_lowerCAmelCase					    =generate_100B_dataset(num_examples=a__      ,   chunk_size=a__   )
						print('Functions'   )
						for func in functions:
												print(func.__name__   )
												_lowerCAmelCase					    =func(a__   )

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


if __name__ == "__main__":  # useful to run the profiler
							benchmark_table_100B()










# A Bipartite Graph is a graph whose vertices can be divided into two independent sets,
# U and V such that every edge (u, v) either connects a vertex from U to V or a vertex
# from V to U. In other words, for every edge (u, v), either u belongs to U and v to V,
# or u belongs to V and v to U. We can also say that there is no edge that connects
# vertices of same set.
from queue import Queue


def 						_UpperCAmelCase							( snake_case     ):





					"""simple docstring"""

					_lowerCAmelCase         =       Queue()
					_lowerCAmelCase         =       [False] * len(snake_case     )
					_lowerCAmelCase         =       [-1] * len(snake_case     )

					def bfs():
										while not queue.empty():
															_lowerCAmelCase         =       queue.get()
															_lowerCAmelCase         =       True

															for neighbour in graph[u]:
																				if neighbour == u:
																									return False

																				if color[neighbour] == -1:
																									_lowerCAmelCase         =       1 - color[u]
																									queue.put(snake_case     )

																				elif color[neighbour] == color[u]:
																									return False

										return True

					for i in range(len(snake_case     )     ):
										if not visited[i]:
															queue.put(snake_case     )
															_lowerCAmelCase         =       0
															if bfs() is False:
																				return False

					return True


if __name__ == "__main__":
	# Adjacency List of graph
	print(check_bipartite({0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2]}))



