lru-cache.py

"""

146. LRU Cache
Medium

Design a data structure that follows the constraints of a Least Recently Used (LRU) cache.

Implement the LRUCache class:

LRUCache(int capacity) Initialize the LRU cache with positive size capacity.
int get(int key) Return the value of the key if the key exists, otherwise return -1.
void put(int key, int value) Update the value of the key if the key exists. Otherwise, add the key-value pair to the cache. If the number of keys exceeds the capacity from this operation, evict the least recently used key.
The functions get and put must each run in O(1) average time complexity.

 

Example 1:

Input
["LRUCache", "put", "put", "get", "put", "get", "put", "get", "get", "get"]
[[2], [1, 1], [2, 2], [1], [3, 3], [2], [4, 4], [1], [3], [4]]
Output
[null, null, null, 1, null, -1, null, -1, 3, 4]

Explanation
LRUCache lRUCache = new LRUCache(2);
lRUCache.put(1, 1); // cache is {1=1}
lRUCache.put(2, 2); // cache is {1=1, 2=2}
lRUCache.get(1);    // return 1
lRUCache.put(3, 3); // LRU key was 2, evicts key 2, cache is {1=1, 3=3}
lRUCache.get(2);    // returns -1 (not found)
lRUCache.put(4, 4); // LRU key was 1, evicts key 1, cache is {4=4, 3=3}
lRUCache.get(1);    // return -1 (not found)
lRUCache.get(3);    // return 3
lRUCache.get(4);    // return 4
 

Constraints:

1 <= capacity <= 3000
0 <= key <= 104
0 <= value <= 105
At most 2 * 105 calls will be made to get and put.

"""

# V0
# IDEA : ARRAY + LRU (implement LRU via array)
class LRUCache(object):

    def __init__(self, capacity):
        self.capacity = capacity
        self._cache = []   
        self._cache_look_up = {}

    def get(self, key):
        if key not in self._cache_look_up:
            return -1

        self._cache.remove(key)
        self._cache.append(key)

        return self._cache_look_up[key]

    def put(self, key, value):
        # case 1) key in cache
        if key in self._cache_look_up:
            self._cache_look_up[key] = value

            """
            NOTE !!! below trick

                In [14]: x = [1,2,3]

                In [15]: x.remove(2)

                In [16]: x
                Out[16]: [1, 3]

                In [17]: x.append(2)

                In [18]: x
                Out[18]: [1, 3, 2]
            """
            
            self._cache.remove(key)
            self._cache.append(key)
            return

        # case 2) key NOT in cache
        else:
            # case 2-1) len(cache) == capacity -> need to clear cache with LRU
            if len(self._cache) == self.capacity:
                del_key = self._cache[0]
                self._cache = self._cache[1:]
                del self._cache_look_up[del_key]

            # case 2-2) len(cache) < capacity
            self._cache.append(key)
            self._cache_look_up[key] = value

# V1
# IDEA : Ordered dictionary
# https://leetcode.com/problems/lru-cache/solution/
# IDEA : 
#       -> There is a structure called ordered dictionary, it combines behind both hashmap and linked list. 
#       -> In Python this structure is called OrderedDict 
#       -> and in Java LinkedHashMap.
from collections import OrderedDict
class LRUCache(OrderedDict):

    def __init__(self, capacity):
        """
        :type capacity: int
        """
        self.capacity = capacity

    def get(self, key):
        """
        :type key: int
        :rtype: int
        """
        if key not in self:
            return - 1
        
        self.move_to_end(key)
        return self[key]

    def put(self, key, value):
        """
        :type key: int
        :type value: int
        :rtype: void
        """
        if key in self:
            self.move_to_end(key)
        self[key] = value
        if len(self) > self.capacity:
            self.popitem(last = False)

# Your LRUCache object will be instantiated and called as such:
# obj = LRUCache(capacity)
# param_1 = obj.get(key)
# obj.put(key,value)


# V1'
# IDEA : Hashmap + DoubleLinkedList
# https://leetcode.com/problems/lru-cache/solution/
class DLinkedNode(): 
    def __init__(self):
        self.key = 0
        self.value = 0
        self.prev = None
        self.next = None
            
class LRUCache():
    def _add_node(self, node):
        """
        Always add the new node right after head.
        """
        node.prev = self.head
        node.next = self.head.next

        self.head.next.prev = node
        self.head.next = node

    def _remove_node(self, node):
        """
        Remove an existing node from the linked list.
        """
        prev = node.prev
        new = node.next

        prev.next = new
        new.prev = prev

    def _move_to_head(self, node):
        """
        Move certain node in between to the head.
        """
        self._remove_node(node)
        self._add_node(node)

    def _pop_tail(self):
        """
        Pop the current tail.
        """
        res = self.tail.prev
        self._remove_node(res)
        return res

    def __init__(self, capacity):
        """
        :type capacity: int
        """
        self.cache = {}
        self.size = 0
        self.capacity = capacity
        self.head, self.tail = DLinkedNode(), DLinkedNode()

        self.head.next = self.tail
        self.tail.prev = self.head
        

    def get(self, key):
        """
        :type key: int
        :rtype: int
        """
        node = self.cache.get(key, None)
        if not node:
            return -1

        # move the accessed node to the head;
        self._move_to_head(node)

        return node.value

    def put(self, key, value):
        """
        :type key: int
        :type value: int
        :rtype: void
        """
        node = self.cache.get(key)

        if not node: 
            newNode = DLinkedNode()
            newNode.key = key
            newNode.value = value

            self.cache[key] = newNode
            self._add_node(newNode)

            self.size += 1

            if self.size > self.capacity:
                # pop the tail
                tail = self._pop_tail()
                del self.cache[tail.key]
                self.size -= 1
        else:
            # update the value.
            node.value = value
            self._move_to_head(node)

# V1''
# IDEA : OrderedDict
# https://leetcode.com/problems/lru-cache/discuss/595933/Python-OrderedDict-sol.-90%2B-w-Hint
from collections import OrderedDict
class LRUCache:

    def __init__(self, capacity: int):
        
        self.size = capacity
        
        self.lru_cache = OrderedDict()
        

    def get(self, key: int) -> int:
        
        if key not in self.lru_cache:
            return -1
        
        else:
            # refresh the entry with given key
            self.lru_cache.move_to_end( key )
            
            return self.lru_cache[ key ]
        

    def put(self, key: int, value: int) -> None:
        
        if key not in self.lru_cache:
            
            if len( self.lru_cache ) >= self.size :
                # pop the least used entry
                self.lru_cache.popitem( last = False )

        else:
            # refresh the entry with given key
            self.lru_cache.move_to_end( key )
        
        self.lru_cache[ key ] = value

# V1'''
# IDEA :  Hashmap + DoubleLinkedList
# https://blog.csdn.net/fuxuemingzhu/article/details/100800072
class ListNode:
    def __init__(self, key, value):
        self.key = key
        self.value = value
        self.prev = self
        self.next = self

class LRUCache:

    def __init__(self, capacity):
        self.dic = dict()
        self.capacity = capacity
        self.size = 0
        self.root = ListNode(0, 0)

    def get(self, key):
        if key in self.dic:
            node = self.dic[key]
            self.removeFromList(node)
            self.insertIntoHead(node)
            return node.value
        else:
            return -1

    def put(self, key, value):
        if key in self.dic:
            node = self.dic[key]
            self.removeFromList(node)
            self.insertIntoHead(node)
            node.value = value
        else:
            if self.size >= self.capacity:
                self.removeFromTail()
                self.size -= 1
            node = ListNode(key, value)
            self.insertIntoHead(node)
            self.dic[key] = node
            self.size += 1

    def removeFromList(self, node):
        if node == self.root: return
        prev_node = node.prev
        next_node = node.next
        prev_node.next = next_node
        next_node.prev = prev_node
        node.prev = node.next = None
    
    def insertIntoHead(self, node):
        head_node = self.root.next
        head_node.prev = node
        node.prev = self.root
        self.root.next = node
        node.next = head_node
    
    def removeFromTail(self):
        if self.size == 0: return
        tail_node = self.root.prev
        del self.dic[tail_node.key]
        self.removeFromList(tail_node)

# V1'
# https://blog.csdn.net/laughing2333/article/details/70231547
class LRUCache(object):

    def __init__(self, capacity):
        self.capacity = capacity
        self._cache = []   
        self._cache_look_up = {}

    def get(self, key):
        if key not in self._cache_look_up:
            return -1

        self._cache.remove(key)
        self._cache.append(key)

        return self._cache_look_up[key]

    def put(self, key, value):
        if key in self._cache_look_up:
            self._cache_look_up[key] = value
            self._cache.remove(key)
            self._cache.append(key)
            return
        else:
            if len(self._cache) == self.capacity:
                del_key = self._cache[0]
                self._cache = self._cache[1:]
                del self._cache_look_up[del_key]

            self._cache.append(key)
            self._cache_look_up[key] = value

# V2