

from __future__ import annotations

import sys
from collections import deque
from typing import Generic, TypeVar

SCREAMING_SNAKE_CASE_            = TypeVar('T')

class 			a					(		Generic[T]			):
						_lowercase        =     42  # Cache store of keys
						_lowercase        =     42  # References of the keys in cache
						_lowercase        =     1_0  # Maximum capacity of cache


						def __init__(    self  ,   A_		):







										'''simple docstring'''


										_UpperCAmelCase    :						List[Any]							=      deque()
										_UpperCAmelCase    :						List[str]							=      set()
										if not n:
														_UpperCAmelCase    :						List[str]							=      sys.maxsize
										elif n < 0:
														raise ValueError("n should be an integer greater than 0."		)
										else:
														_UpperCAmelCase    :						Optional[int]							=      n


						def     _UpperCAmelCase			(    self  ,   A_		):







										'''simple docstring'''


										if x not in self.key_reference:
														if len(self.dq_store		) == LRUCache._MAX_CAPACITY:
																		_UpperCAmelCase    :						Tuple							=      self.dq_store.pop()
																		self.key_reference.remove(A_		)
										else:
														self.dq_store.remove(A_		)

										self.dq_store.appendleft(A_		)
										self.key_reference.add(A_		)


						def     _UpperCAmelCase			(    self		):







										'''simple docstring'''


										for k in self.dq_store:
														print(A_		)





						def __repr__(    self		):







										'''simple docstring'''


										return f'LRUCache({self._MAX_CAPACITY}) => {list(self.dq_store		)}'


if __name__ == "__main__":
					import doctest

					doctest.testmod()

					SCREAMING_SNAKE_CASE_            = LRUCache(4)
					lru_cache.refer('A')
					lru_cache.refer(2)
					lru_cache.refer(3)
					lru_cache.refer('A')
					lru_cache.refer(4)
					lru_cache.refer(5)
					lru_cache.display()

					print(lru_cache)
					assert str(lru_cache) == "LRUCache(4) => [5, 4, 'A', 3]"





from __future__ import annotations

from random import choice

def 							__SCREAMING_SNAKE_CASE							(			lowerCAmelCase:					Any	)				->    Optional[int]:
				return choice(lowerCAmelCase	)

def 							__SCREAMING_SNAKE_CASE							(			lowerCAmelCase:					list[int]					, lowerCAmelCase:					int	)				->    int:
				_UpperCAmelCase    :						List[Any]							=      random_pivot(lowerCAmelCase	)

				# partition based on pivot
				# linear time
				_UpperCAmelCase    :						List[str]							=      [e for e in lst if e < pivot]
				_UpperCAmelCase    :						Any							=      [e for e in lst if e > pivot]

				# if we get lucky, pivot might be the element we want.
				# we can easily see this:
				# small (elements smaller than k)
				# + pivot (kth element)
				# + big (elements larger than k)
				if len(lowerCAmelCase	) == k - 1:
								return pivot
				# pivot is in elements bigger than k
				elif len(lowerCAmelCase	) < k - 1:
								return kth_number(lowerCAmelCase					, k - len(lowerCAmelCase	) - 1	)
				# pivot is in elements smaller than k
				else:
								return kth_number(lowerCAmelCase					, lowerCAmelCase	)


if __name__ == "__main__":
					import doctest

					doctest.testmod()


