146. Lru Cache
from typing import Dict
class Node:
"""A Node in a doubly linked list."""
def __init__(self, key: int, value: int):
self.key = key
self.value = value
self.prev = None
self.next = None
class LRUCache:
"""Design and implement a Least Recently Used (LRU) cache.
Problem Statement:
Implement LRUCache(capacity) with get(key) and put(key, value) each running in O(1)
average time. Evict the least recently used entry when capacity is exceeded.
Approach:
Combine a doubly linked list (to track usage order) with a hash map (for O(1) access).
The head of the list is the most recently used; the tail is least recently used.
On access or insert, move the node to the head. On eviction, remove from the tail.
Complexity:
Time: O(1) for both get and put.
Space: O(capacity) for the cache storage.
"""
def __init__(self, capacity: int):
assert capacity > 0, "The LRU Capacity must be > 0"
self.capacity = capacity
self.cache: Dict[int, Node] = {}
self.head = Node(0, 0)
self.tail = Node(0, 0)
self.head.next = self.tail
self.tail.prev = self.head
def get(self, key: int) -> int:
if key in self.cache:
node = self.cache[key]
self._remove(node)
self._add(node)
return node.value
return -1
def put(self, key: int, value: int) -> None:
if key in self.cache:
node = self.cache[key]
self._remove(node)
node.value = value
self._add(node)
else:
if len(self.cache) >= self.capacity:
lru = self.tail.prev
self._remove(lru)
del self.cache[lru.key]
node = Node(key, value)
self.cache[key] = node
self._add(node)
def _remove(self, node: Node) -> None:
node.prev.next = node.next
node.next.prev = node.prev
def _add(self, node: Node) -> None:
node.prev = self.head
node.next = self.head.next
self.head.next.prev = node
self.head.next = node