




"""simple docstring"""

from __future__ import annotations

import random
from collections.abc import Iterable
from typing import Any, Generic, TypeVar

UpperCamelCase__ :    Optional[int] 					=							TypeVar("T", bound=bool)
class     A__      (      Generic[T]     ):




	def __init__(   self  :	Union[str, Any]      ,    lowercase  :	T	)					-> None:
						__snake_case          =	value
						__snake_case          =	None
						__snake_case          =	None




	@property
	def 							a_		(   self  :	int	)					-> T:
						return self._value




	@staticmethod
	def 							a_		(   lowercase  :	RandomizedHeapNode[T] | None      ,    lowercase  :	RandomizedHeapNode[T] | None	)					-> RandomizedHeapNode[T] | None:
						if not roota:
											return roota

						if not roota:
											return roota

						if roota.value > roota.value:
											__snake_case      ,      __snake_case          =	roota, roota

						if random.choice([True, False]	):
											__snake_case      ,      __snake_case          =	roota.right, roota.left

						__snake_case          =	RandomizedHeapNode.merge(roota.left      ,    lowercase	)

						return roota

class     A__      (      Generic[T]     ):




	def __init__(   self  :	Dict      ,    lowercase  :	Iterable[T] | None = ()	)					-> None:
						__snake_case          =	None

						if data:
											for item in data:
																self.insert(lowercase	)




	def 							a_		(   self  :	List[str]      ,    lowercase  :	T	)					-> None:
						__snake_case          =	RandomizedHeapNode.merge(self._root      ,    RandomizedHeapNode(lowercase	)	)




	def 							a_		(   self  :	int	)					-> T | None:
						__snake_case          =	self.top()

						if self._root is None:
											return None

						__snake_case          =	RandomizedHeapNode.merge(self._root.left      ,    self._root.right	)

						return result




	def 							a_		(   self  :	Dict	)					-> T:
						if not self._root:
											raise IndexError("""Can't get top element for the empty heap."""	)
						return self._root.value




	def 							a_		(   self  :	int	)					-> None:
						__snake_case          =	None




	def 							a_		(   self  :	Optional[Any]	)					-> list[Any]:
						__snake_case          =	[]
						while self:
											result.append(self.pop()	)

						return result




	def __bool__(   self  :	Dict	)					-> bool:
						return self._root is not None


if __name__ == "__main__":
		import doctest

		doctest.testmod()








"""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


UpperCamelCase__ :    Optional[int] 					=							10_00_00_00_00_00
UpperCamelCase__ :    int 					=							1_00_00

UpperCamelCase__					,					UpperCamelCase__ :    List[str] 					=							os.path.split(__file__)
UpperCamelCase__ :    Any 					=							os.path.join(RESULTS_BASEPATH, "results", RESULTS_FILENAME.replace(".py", ".json"))




def       snake_case__	(       lowerCAmelCase   :		int				,					lowerCAmelCase   :		int		):
					__snake_case          =	pa.Table.from_pydict({"""col""": [0] * chunk_size}		)
					__snake_case          =	pa.concat_tables([table] * (num_examples // chunk_size)		)
					return datasets.Dataset(lowerCAmelCase				,					fingerprint="""table_100B"""		)
@dataclass
class     A__      :
	A_							:				int
	A_							:				int
	A_							:				int
	A_							:				int




	def 							a_		(   self  :	Optional[Any]	)					-> Any:
						__snake_case          =	np.random.default_rng(self.seed	)
						__snake_case          =	rng.integers(low=self.low      ,    high=self.high      ,    size=self.size	).tolist()




	def __iter__(   self  :	str	)					-> int:
						return iter(self._sampled_values	)




	def __len__(   self  :	Union[str, Any]	)					-> Any:
						return self.size




@get_duration
def       snake_case__	(       lowerCAmelCase   :		datasets.Dataset		):
					__snake_case          =	dataset[0]




@get_duration
def       snake_case__	(       lowerCAmelCase   :		datasets.Dataset		):
					__snake_case          =	dataset[-1]




@get_duration
def       snake_case__	(       lowerCAmelCase   :		datasets.Dataset		):
					__snake_case          =	dataset[range(len(lowerCAmelCase		) // 2				,					len(lowerCAmelCase		) // 2 + 1_024		)]




@get_duration
def       snake_case__	(       lowerCAmelCase   :		datasets.Dataset		):
					__snake_case          =	dataset[RandIter(0				,					len(lowerCAmelCase		)				,					1_024				,					seed=42		)]




def       snake_case__	(       ):
					__snake_case          =	{"""num examples""": SPEED_TEST_N_EXAMPLES}
					__snake_case          =	(get_first_row, get_last_row, get_batch_of_aaaa_rows, get_batch_of_aaaa_random_rows)
					print("""generating dataset"""		)
					__snake_case          =	generate_100B_dataset(num_examples=lowerCAmelCase				,					chunk_size=lowerCAmelCase		)
					print("""Functions"""		)
					for func in functions:
										print(func.__name__		)
										__snake_case          =	func(lowerCAmelCase		)

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


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


