# 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
# Modified to use monotonically increasing integer values as access times
# by Ivan Vilata i Balaguer <ivan@selidor.net>.
# 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
'expensive' 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
import sys
from heapq import heappush,heappop,heapify
__version__ = "0.2"
__all__ = ['CacheKeyError', 'LRUCache', 'DEFAULT_SIZE']
__docformat__ = 'reStructuredText en'
DEBUG = False
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):
object.__init__(self)
self.key = key
self.obj = obj
self.atime = timestamp
def __cmp__(self, other):
return cmp(self.atime, other.atime)
def __repr__(self):
return "<%s %s => %s (accessed at %s)>" % \
(self.__class__, self.key, self.obj, self.atime)
def __getseqn(self):
seqn = self.__seqn_
self.__seqn_ = seqn + 1
#print seqn
return seqn
__seqn = property(__getseqn)
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 = {}
self.__seqn_ = 0
self.size = size
"""Maximum size of the cache.
If more than 'size' elements are added to the cache,
the least-recently-used ones will be discarded."""
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]
node.obj = obj
node.atime = self.__seqn
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]
if DEBUG:
print "removing(setitem)-->", lru.obj._v_pathname
node = self.__Node(key, obj, self.__seqn)
self.__dict[key] = node
if DEBUG:
print "inserting node-->", node.obj._v_pathname
f = sys._getframe(3)
print "caller-->", f.f_code.co_name, f.f_lineno, f.f_code.co_filename
heappush(self.__heap, node)
def __getitem__(self, key):
if not self.__dict.has_key(key):
raise CacheKeyError(key)
else:
node = self.__dict[key]
if DEBUG:
print "retrieving-->", node.obj._v_pathname
f = sys._getframe(4)
print "caller-->", f.f_code.co_name, f.f_lineno, f.f_code.co_filename
node.atime = self.__seqn
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]
if DEBUG and hasattr(node.obj, "_v_pathname"):
print "removing(delitem)-->", node.obj._v_pathname
f = sys._getframe(2)
print "caller-->", f.f_code.co_name, f.f_lineno, f.f_code.co_filename
self.__heap.remove(node)
heapify(self.__heap)
return node.obj
def pop(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))
if __name__ == "__main__":
cache = LRUCache(25)
print cache
for i in range(50):
cache[i] = str(i)
print cache
if 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
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