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from typing import Callable, Optional

class DoubleLinkedListNode:

"""

Double Linked List Node built specifically for LRU Cache

"""

def __init__(self, key: int, val: int):

self.key = key

self.val = val

self.next = None

self.prev = None

class DoubleLinkedList:

"""

Double Linked List built specifically for LRU Cache

"""

def __init__(self):

self.head = DoubleLinkedListNode(None, None)

self.rear = DoubleLinkedListNode(None, None)

self.head.next, self.rear.prev = self.rear, self.head

def add(self, node: DoubleLinkedListNode) -> None:

"""

Adds the given node to the end of the list (before rear)

"""

temp = self.rear.prev

temp.next, node.prev = node, temp

self.rear.prev, node.next = node, self.rear

def remove(self, node: DoubleLinkedListNode) -> DoubleLinkedListNode:

"""

Removes and returns the given node from the list

"""

temp_last, temp_next = node.prev, node.next

node.prev, node.next = None, None

temp_last.next, temp_next.prev = temp_next, temp_last

return node

class LRUCache:

"""

LRU Cache to store a given capacity of data. Can be used as a stand-alone object

or as a function decorator.

>>> cache = LRUCache(2)

>>> cache.set(1, 1)

>>> cache.set(2, 2)

>>> cache.get(1)

>>> cache.set(3, 3)

>>> cache.get(2) # None returned

>>> cache.set(4, 4)

>>> cache.get(1) # None returned

>>> cache.get(3)

>>> cache.get(4)

>>> cache

CacheInfo(hits=3, misses=2, capacity=2, current size=2)

>>> @LRUCache.decorator(100)

... def fib(num):

... if num in (1, 2):

... return 1

... return fib(num - 1) + fib(num - 2)

>>> for i in range(1, 100):

... res = fib(i)

>>> fib.cache_info()

CacheInfo(hits=194, misses=99, capacity=100, current size=99)

"""

# class variable to map the decorator functions to their respective instance

decorator_function_to_instance_map = {}

def __init__(self, capacity: int):

self.list = DoubleLinkedList()

self.capacity = capacity

self.num_keys = 0

self.hits = 0

self.miss = 0

self.cache = {}

def __repr__(self) -> str:

"""

Return the details for the cache instance

[hits, misses, capacity, current_size]

"""

return (

f"CacheInfo(hits={self.hits}, misses={self.miss}, "

f"capacity={self.capacity}, current size={self.num_keys})"

)

def __contains__(self, key: int) -> bool:

"""

>>> cache = LRUCache(1)

>>> 1 in cache

False

>>> cache.set(1, 1)

>>> 1 in cache

True

"""

return key in self.cache

def get(self, key: int) -> Optional[int]:

"""

Returns the value for the input key and updates the Double Linked List. Returns

None if key is not present in cache

"""

if key in self.cache:

self.hits += 1

self.list.add(self.list.remove(self.cache[key]))

return self.cache[key].val

self.miss += 1

return None

def set(self, key: int, value: int) -> None:

"""

Sets the value for the input key and updates the Double Linked List

"""

if key not in self.cache:

if self.num_keys >= self.capacity:

key_to_delete = self.list.head.next.key

self.list.remove(self.cache[key_to_delete])

del self.cache[key_to_delete]

self.num_keys -= 1

self.cache[key] = DoubleLinkedListNode(key, value)

self.list.add(self.cache[key])

self.num_keys += 1

else:

node = self.list.remove(self.cache[key])

node.val = value

self.list.add(node)

@staticmethod

def decorator(size: int = 128):

"""

Decorator version of LRU Cache

"""

def cache_decorator_inner(func: Callable):

def cache_decorator_wrapper(*args, **kwargs):

if func not in LRUCache.decorator_function_to_instance_map:

LRUCache.decorator_function_to_instance_map[func] = LRUCache(size)

result = LRUCache.decorator_function_to_instance_map[func].get(args[0])

if result is None:

result = func(*args, **kwargs)

LRUCache.decorator_function_to_instance_map[func].set(

args[0], result

)

return result

def cache_info():

return LRUCache.decorator_function_to_instance_map[func]

cache_decorator_wrapper.cache_info = cache_info

return cache_decorator_wrapper

return cache_decorator_inner

if __name__ == "__main__":

import doctest

doctest.testmod()

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