# -*- coding: utf-8 -*-
# @Time    : 2019/9/12 0012 15:45
# @Author  : 没有蜡笔的小新
# @E-mail  : sqw123az@sina.com
# @FileName: LRU Cache.py
# @Software: PyCharm
# @Blog    ：https://blog.csdn.net/Asunqingwen
# @GitHub  ：https://github.com/Asunqingwen
"""
Design and implement a data structure for Least Recently Used (LRU) cache. It should support the following operations: get and put.

get(key) - Get the value (will always be positive) of the key if the key exists in the cache, otherwise return -1.
put(key, value) - Set or insert the value if the key is not already present. When the cache reached its capacity, it should invalidate the least recently used item before inserting a new item.

The cache is initialized with a positive capacity.

Follow up:
Could you do both operations in O(1) time complexity?

Example:

LRUCache cache = new LRUCache( 2 /* capacity */ );

cache.put(1, 1);
cache.put(2, 2);
cache.get(1);       // returns 1
cache.put(3, 3);    // evicts key 2
cache.get(2);       // returns -1 (not found)
cache.put(4, 4);    // evicts key 1
cache.get(1);       // returns -1 (not found)
cache.get(3);       // returns 3
cache.get(4);       // returns 4
"""
from collections import OrderedDict


class LRUCache(OrderedDict):

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

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

    def put(self, key: int, value: int) -> None:
        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)
if __name__ == '__main__':
    cache = LRUCache(2)

    cache.put(1, 1)
    cache.put(2, 2)
    cache.get(1)
    cache.put(3, 3)
    cache.get(2)
    cache.put(4, 4)
    cache.get(1)
    cache.get(3)
    cache.get(4)

192a0b0413546bbbcbeecbbb1fda6a204c50dc26
<mask token>


class LRUCache(OrderedDict):
    <mask token>
    <mask token>

    def put(self, key: int, value: int) ->None:
        if key in self:
            self.move_to_end(key)
        self[key] = value
        if len(self) > self.capacity:
            self.popitem(last=False)


<mask token>

<mask token>


class LRUCache(OrderedDict):

    def __init__(self, capacity: int):
        self.capacity = capacity
    <mask token>

    def put(self, key: int, value: int) ->None:
        if key in self:
            self.move_to_end(key)
        self[key] = value
        if len(self) > self.capacity:
            self.popitem(last=False)


<mask token>

<mask token>


class LRUCache(OrderedDict):

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

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

    def put(self, key: int, value: int) ->None:
        if key in self:
            self.move_to_end(key)
        self[key] = value
        if len(self) > self.capacity:
            self.popitem(last=False)


<mask token>

<mask token>
from collections import OrderedDict


class LRUCache(OrderedDict):

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

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

    def put(self, key: int, value: int) ->None:
        if key in self:
            self.move_to_end(key)
        self[key] = value
        if len(self) > self.capacity:
            self.popitem(last=False)


if __name__ == '__main__':
    cache = LRUCache(2)
    cache.put(1, 1)
    cache.put(2, 2)
    cache.get(1)
    cache.put(3, 3)
    cache.get(2)
    cache.put(4, 4)
    cache.get(1)
    cache.get(3)
    cache.get(4)

# -*- coding: utf-8 -*-
# @Time    : 2019/9/12 0012 15:45
# @Author  : 没有蜡笔的小新
# @E-mail  : sqw123az@sina.com
# @FileName: LRU Cache.py
# @Software: PyCharm
# @Blog    ：https://blog.csdn.net/Asunqingwen
# @GitHub  ：https://github.com/Asunqingwen
"""
Design and implement a data structure for Least Recently Used (LRU) cache. It should support the following operations: get and put.

get(key) - Get the value (will always be positive) of the key if the key exists in the cache, otherwise return -1.
put(key, value) - Set or insert the value if the key is not already present. When the cache reached its capacity, it should invalidate the least recently used item before inserting a new item.

The cache is initialized with a positive capacity.

Follow up:
Could you do both operations in O(1) time complexity?

Example:

LRUCache cache = new LRUCache( 2 /* capacity */ );

cache.put(1, 1);
cache.put(2, 2);
cache.get(1);       // returns 1
cache.put(3, 3);    // evicts key 2
cache.get(2);       // returns -1 (not found)
cache.put(4, 4);    // evicts key 1
cache.get(1);       // returns -1 (not found)
cache.get(3);       // returns 3
cache.get(4);       // returns 4
"""
from collections import OrderedDict


class LRUCache(OrderedDict):

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

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

    def put(self, key: int, value: int) -> None:
        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)
if __name__ == '__main__':
    cache = LRUCache(2)

    cache.put(1, 1)
    cache.put(2, 2)
    cache.get(1)
    cache.put(3, 3)
    cache.get(2)
    cache.put(4, 4)
    cache.get(1)
    cache.get(3)
    cache.get(4)
