


'''simple docstring'''






from __future__ import annotations

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

__A					:  List[Any]											=      TypeVar("T")






class    __snake_case       (   Generic[T]):







    """simple docstring"""



    lowercase    =					42  # Cache store of keys
    lowercase    =					42  # References of the keys in cache
    lowercase    =					10  # Maximum capacity of cache

    def __init__(   self    :  Optional[Any]    ,						lowerCamelCase    :  int		)   ->  None:
      lowerCAmelCase_			:      Any			=   deque()
      lowerCAmelCase_			:      int			=   set()
      if not n:
        lowerCAmelCase_			:      Optional[Any]			=   sys.maxsize
      elif n < 0:
        raise ValueError("""n should be an integer greater than 0."""		)
      else:
        lowerCAmelCase_			:      List[str]			=   n

    def __lowercase   (   self    :  Union[str, Any]    ,						lowerCamelCase    :  T		)   ->  None:
      if x not in self.key_reference:
        if len(self.dq_store		) == LRUCache._MAX_CAPACITY:
          lowerCAmelCase_			:      str			=   self.dq_store.pop()
          self.key_reference.remove(lowerCamelCase		)
      else:
        self.dq_store.remove(lowerCamelCase		)

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

    def __lowercase   (   self    :  Optional[int]		)   ->  None:
      for k in self.dq_store:
        print(lowerCamelCase		)





    def __repr__(   self    :  Union[str, Any]		)   ->  str:
      return F'LRUCache({self._MAX_CAPACITY}) => {list(self.dq_store		)}'


if __name__ == "__main__":
  import doctest

  doctest.testmod()

  __A					:  LRUCache[str | int]											=      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]"







'''simple docstring'''






def 				UpperCamelCase_			(    A__					:   list[list[float]]					):
  '''simple docstring'''





  lowerCAmelCase_			:      list[list[float]]			=   []
  for data in source_data:
    for i, el in enumerate(A__					):
      if len(A__					) < i + 1:
        data_lists.append([]					)
      data_lists[i].append(float(A__					)					)
  return data_lists







def 				UpperCamelCase_			(    A__					:   list[list[float]]							,    A__					:   list[int]					):
  '''simple docstring'''





  lowerCAmelCase_			:      list[list[float]]			=   []
  for dlist, weight in zip(A__							,    A__					):
    lowerCAmelCase_			:      Tuple			=   min(A__					)
    lowerCAmelCase_			:      str			=   max(A__					)

    lowerCAmelCase_			:      list[float]			=   []
    # for weight 0 score is 1 - actual score
    if weight == 0:
      for item in dlist:
        try:
          score.append(1 - ((item - mind) / (maxd - mind))					)
        except ZeroDivisionError:
          score.append(1					)

    elif weight == 1:
      for item in dlist:
        try:
          score.append((item - mind) / (maxd - mind)					)
        except ZeroDivisionError:
          score.append(0					)

        # weight not 0 or 1
    else:
      lowerCAmelCase_			:      List[Any]			=   f'Invalid weight of {weight:f} provided'
      raise ValueError(A__					)

    score_lists.append(A__					)

  return score_lists







def 				UpperCamelCase_			(    A__					:   list[list[float]]					):
  '''simple docstring'''





  lowerCAmelCase_			:      list[float]			=   [0 for i in range(len(score_lists[0]					)					)]

  for slist in score_lists:
    for j, ele in enumerate(A__					):
      lowerCAmelCase_			:      List[Any]			=   final_scores[j] + ele

  return final_scores







def 				UpperCamelCase_			(    A__					:   list[list[float]]							,    A__					:   list[int]					):
  '''simple docstring'''





  lowerCAmelCase_			:      Optional[Any]			=   get_data(A__					)
  lowerCAmelCase_			:      Tuple			=   calculate_each_score(A__							,    A__					)
  lowerCAmelCase_			:      Optional[int]			=   generate_final_scores(A__					)

  # append scores to source data
  for i, ele in enumerate(A__					):
    source_data[i].append(A__					)

  return source_data



