Python实现的最近最少使用算法


Posted in Python onJuly 10, 2015

本文实例讲述了Python实现的最近最少使用算法。分享给大家供大家参考。具体如下:

# lrucache.py -- a simple LRU (Least-Recently-Used) cache class 
# Copyright 2004 Evan Prodromou <evan@bad.dynu.ca> 
# Licensed under the Academic Free License 2.1 
# Licensed for ftputil under the revised BSD license 
# with permission by the author, Evan Prodromou. Many 
# thanks, Evan! :-) 
# 
# The original file is available at 
# http://pypi.python.org/pypi/lrucache/0.2 . 
# arch-tag: LRU cache main module 
"""a simple LRU (Least-Recently-Used) cache module 
This module provides very simple LRU (Least-Recently-Used) cache 
functionality. 
An *in-memory cache* is useful for storing the results of an 
'expe\nsive' process (one that takes a lot of time or resources) for 
later re-use. Typical examples are accessing data from the filesystem, 
a database, or a network location. If you know you'll need to re-read 
the data again, it can help to keep it in a cache. 
You *can* use a Python dictionary as a cache for some purposes. 
However, if the results you're caching are large, or you have a lot of 
possible results, this can be impractical memory-wise. 
An *LRU cache*, on the other hand, only keeps _some_ of the results in 
memory, which keeps you from overusing resources. The cache is bounded 
by a maximum size; if you try to add more values to the cache, it will 
automatically discard the values that you haven't read or written to 
in the longest time. In other words, the least-recently-used items are 
discarded. [1]_ 
.. [1]: 'Discarded' here means 'removed from the cache'. 
"""
from __future__ import generators 
import time 
from heapq import heappush, heappop, heapify 
# the suffix after the hyphen denotes modifications by the 
# ftputil project with respect to the original version 
__version__ = "0.2-1"
__all__ = ['CacheKeyError', 'LRUCache', 'DEFAULT_SIZE'] 
__docformat__ = 'reStructuredText en'
DEFAULT_SIZE = 16
"""Default size of a new LRUCache object, if no 'size' argument is given."""
class CacheKeyError(KeyError): 
  """Error raised when cache requests fail 
  When a cache record is accessed which no longer exists (or never did), 
  this error is raised. To avoid it, you may want to check for the existence 
  of a cache record before reading or deleting it."""
  pass
class LRUCache(object): 
  """Least-Recently-Used (LRU) cache. 
  Instances of this class provide a least-recently-used (LRU) cache. They 
  emulate a Python mapping type. You can use an LRU cache more or less like 
  a Python dictionary, with the exception that objects you put into the 
  cache may be discarded before you take them out. 
  Some example usage:: 
  cache = LRUCache(32) # new cache 
  cache['foo'] = get_file_contents('foo') # or whatever 
  if 'foo' in cache: # if it's still in cache... 
    # use cached version 
    contents = cache['foo'] 
  else: 
    # recalculate 
    contents = get_file_contents('foo') 
    # store in cache for next time 
    cache['foo'] = contents 
  print cache.size # Maximum size 
  print len(cache) # 0 <= len(cache) <= cache.size 
  cache.size = 10 # Auto-shrink on size assignment 
  for i in range(50): # note: larger than cache size 
    cache[i] = i 
  if 0 not in cache: print 'Zero was discarded.' 
  if 42 in cache: 
    del cache[42] # Manual deletion 
  for j in cache:  # iterate (in LRU order) 
    print j, cache[j] # iterator produces keys, not values 
  """
  class __Node(object): 
    """Record of a cached value. Not for public consumption."""
    def __init__(self, key, obj, timestamp, sort_key): 
      object.__init__(self) 
      self.key = key 
      self.obj = obj 
      self.atime = timestamp 
      self.mtime = self.atime 
      self._sort_key = sort_key 
    def __cmp__(self, other): 
      return cmp(self._sort_key, other._sort_key) 
    def __repr__(self): 
      return "<%s %s => %s (%s)>" % \ 
          (self.__class__, self.key, self.obj, \ 
          time.asctime(time.localtime(self.atime))) 
  def __init__(self, size=DEFAULT_SIZE): 
    # Check arguments 
    if size <= 0: 
      raise ValueError, size 
    elif type(size) is not type(0): 
      raise TypeError, size 
    object.__init__(self) 
    self.__heap = [] 
    self.__dict = {} 
    """Maximum size of the cache. 
    If more than 'size' elements are added to the cache, 
    the least-recently-used ones will be discarded."""
    self.size = size 
    self.__counter = 0
  def _sort_key(self): 
    """Return a new integer value upon every call. 
    Cache nodes need a monotonically increasing time indicator. 
    time.time() and time.clock() don't guarantee this in a 
    platform-independent way. 
    """
    self.__counter += 1
    return self.__counter 
  def __len__(self): 
    return len(self.__heap) 
  def __contains__(self, key): 
    return self.__dict.has_key(key) 
  def __setitem__(self, key, obj): 
    if self.__dict.has_key(key): 
      node = self.__dict[key] 
      # update node object in-place 
      node.obj = obj 
      node.atime = time.time() 
      node.mtime = node.atime 
      node._sort_key = self._sort_key() 
      heapify(self.__heap) 
    else: 
      # size may have been reset, so we loop 
      while len(self.__heap) >= self.size: 
        lru = heappop(self.__heap) 
        del self.__dict[lru.key] 
      node = self.__Node(key, obj, time.time(), self._sort_key()) 
      self.__dict[key] = node 
      heappush(self.__heap, node) 
  def __getitem__(self, key): 
    if not self.__dict.has_key(key): 
      raise CacheKeyError(key) 
    else: 
      node = self.__dict[key] 
      # update node object in-place 
      node.atime = time.time() 
      node._sort_key = self._sort_key() 
      heapify(self.__heap) 
      return node.obj 
  def __delitem__(self, key): 
    if not self.__dict.has_key(key): 
      raise CacheKeyError(key) 
    else: 
      node = self.__dict[key] 
      del self.__dict[key] 
      self.__heap.remove(node) 
      heapify(self.__heap) 
      return node.obj 
  def __iter__(self): 
    copy = self.__heap[:] 
    while len(copy) > 0: 
      node = heappop(copy) 
      yield node.key 
    raise StopIteration 
  def __setattr__(self, name, value): 
    object.__setattr__(self, name, value) 
    # automagically shrink heap on resize 
    if name == 'size': 
      while len(self.__heap) > value: 
        lru = heappop(self.__heap) 
        del self.__dict[lru.key] 
  def __repr__(self): 
    return "<%s (%d elements)>" % (str(self.__class__), len(self.__heap)) 
  def mtime(self, key): 
    """Return the last modification time for the cache record with key. 
    May be useful for cache instances where the stored values can get 
    'stale', such as caching file or network resource contents."""
    if not self.__dict.has_key(key): 
      raise CacheKeyError(key) 
    else: 
      node = self.__dict[key] 
      return node.mtime 
if __name__ == "__main__": 
  cache = LRUCache(25) 
  print cache 
  for i in range(50): 
    cache[i] = str(i) 
  print cache 
  if 46 in cache: 
    print "46 in cache"
    del cache[46] 
  print cache 
  cache.size = 10
  print cache 
  cache[46] = '46'
  print cache 
  print len(cache) 
  for c in cache: 
    print c 
  print cache 
  print cache.mtime(46) 
  for c in cache: 
    print c

希望本文所述对大家的Python程序设计有所帮助。

Python 相关文章推荐
python获取Linux下文件版本信息、公司名和产品名的方法
Oct 05 Python
利用Python中unittest实现简单的单元测试实例详解
Jan 09 Python
Python设置在shell脚本中自动补全功能的方法
Jun 25 Python
python八皇后问题的解决方法
Sep 27 Python
python3+PyQt5 使用三种不同的简便项窗口部件显示数据的方法
Jun 17 Python
python实现手势识别的示例(入门)
Apr 15 Python
tensorflow基于CNN实战mnist手写识别(小白必看)
Jul 20 Python
Python爬虫scrapy框架Cookie池(微博Cookie池)的使用
Jan 13 Python
使用Python封装excel操作指南
Jan 29 Python
python函数指定默认值的实例讲解
Mar 29 Python
Python 阶乘详解
Oct 05 Python
基于Python实现股票收益率分析
Apr 02 Python
Python导入oracle数据的方法
Jul 10 #Python
Python验证码识别的方法
Jul 10 #Python
Python实现大文件排序的方法
Jul 10 #Python
Python实现telnet服务器的方法
Jul 10 #Python
Python读写unicode文件的方法
Jul 10 #Python
Python实现提取谷歌音乐搜索结果的方法
Jul 10 #Python
python和bash统计CPU利用率的方法
Jul 10 #Python
You might like
咖啡知识 咖啡养豆要养多久 排气又是什么
2021/03/06 新手入门
PHP的反射类ReflectionClass、ReflectionMethod使用实例
2014/08/05 PHP
用PHP写的一个冒泡排序法的函数简单实例
2016/05/26 PHP
php制作圆形用户头像的实例_自定义封装类源代码
2017/09/18 PHP
javascript写的一个模拟阅读小说的程序
2014/04/04 Javascript
教你如何自定义百度分享插件以及bshare分享插件的分享按钮
2014/06/20 Javascript
jQuery中:image选择器用法实例
2015/01/03 Javascript
IE浏览器下PNG相关功能
2015/07/05 Javascript
基于Css3和JQuery实现打字机效果
2015/08/11 Javascript
jQuery实现的类似淘宝网站搜索框样式代码分享
2015/08/24 Javascript
NodeJS实现图片上传代码(Express)
2017/06/30 NodeJs
利用npm 安装删除模块的方法
2018/05/15 Javascript
详解用vue2.x版本+adminLTE开源框架搭建后台应用模版
2019/03/15 Javascript
vue.js中使用echarts实现数据动态刷新功能
2019/04/16 Javascript
Vue 使用Props属性实现父子组件的动态传值详解
2019/11/13 Javascript
Python算法之栈(stack)的实现
2014/08/18 Python
Python基于scapy实现修改IP发送请求的方法示例
2017/07/08 Python
Django 导出 Excel 代码的实例详解
2017/08/11 Python
详解Python3之数据指纹MD5校验与对比
2019/06/11 Python
选择Python写网络爬虫的优势和理由
2019/07/07 Python
Python Django 前后端分离 API的方法
2019/08/28 Python
python 使用shutil复制图片的例子
2019/12/13 Python
简单了解Python3 bytes和str类型的区别和联系
2019/12/19 Python
python接口自动化之ConfigParser配置文件的使用详解
2020/08/03 Python
HTML5 Plus 实现手机APP拍照或相册选择图片上传功能
2016/07/13 HTML / CSS
xml有哪些解析技术?区别是什么
2016/04/26 面试题
得到Class的三个过程是什么
2012/08/10 面试题
保险专业大学生职业规划书
2014/03/03 职场文书
优秀的个人求职信范文
2014/05/09 职场文书
大学第二课堂活动总结
2014/07/08 职场文书
乡镇干部个人对照检查材料思想汇报(原创篇)
2014/09/28 职场文书
2014年医务科工作总结
2014/12/18 职场文书
如何用Laravel包含你自己的帮助函数
2021/05/27 PHP
MySQL8.0.18配置多主一从
2021/06/21 MySQL
SQL中的三种去重方法小结
2021/11/01 SQL Server
springboot 全局异常处理和统一响应对象的处理方式
2022/06/28 Java/Android