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/ dulwich |
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# lru_cache.py -- Simple LRU cache for dulwich
# Copyright (C) 2006, 2008 Canonical Ltd
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
"""A simple least-recently-used (LRU) cache."""
_null_key = object()
class _LRUNode(object):
"""This maintains the linked-list which is the lru internals."""
__slots__ = ('prev', 'next_key', 'key', 'value', 'cleanup', 'size')
def __init__(self, key, value, cleanup=None):
self.prev = None
self.next_key = _null_key
self.key = key
self.value = value
self.cleanup = cleanup
# TODO: We could compute this 'on-the-fly' like we used to, and remove
# one pointer from this object, we just need to decide if it
# actually costs us much of anything in normal usage
self.size = None
def __repr__(self):
if self.prev is None:
prev_key = None
else:
prev_key = self.prev.key
return '%s(%r n:%r p:%r)' % (self.__class__.__name__, self.key,
self.next_key, prev_key)
def run_cleanup(self):
if self.cleanup is not None:
self.cleanup(self.key, self.value)
self.cleanup = None
# Just make sure to break any refcycles, etc
self.value = None
class LRUCache(object):
"""A class which manages a cache of entries, removing unused ones."""
def __init__(self, max_cache=100, after_cleanup_count=None):
self._cache = {}
# The "HEAD" of the lru linked list
self._most_recently_used = None
# The "TAIL" of the lru linked list
self._least_recently_used = None
self._update_max_cache(max_cache, after_cleanup_count)
def __contains__(self, key):
return key in self._cache
def __getitem__(self, key):
cache = self._cache
node = cache[key]
# Inlined from _record_access to decrease the overhead of __getitem__
# We also have more knowledge about structure if __getitem__ is
# succeeding, then we know that self._most_recently_used must not be
# None, etc.
mru = self._most_recently_used
if node is mru:
# Nothing to do, this node is already at the head of the queue
return node.value
# Remove this node from the old location
node_prev = node.prev
next_key = node.next_key
# benchmarking shows that the lookup of _null_key in globals is faster
# than the attribute lookup for (node is self._least_recently_used)
if next_key is _null_key:
# 'node' is the _least_recently_used, because it doesn't have a
# 'next' item. So move the current lru to the previous node.
self._least_recently_used = node_prev
else:
node_next = cache[next_key]
node_next.prev = node_prev
node_prev.next_key = next_key
# Insert this node at the front of the list
node.next_key = mru.key
mru.prev = node
self._most_recently_used = node
node.prev = None
return node.value
def __len__(self):
return len(self._cache)
def _walk_lru(self):
"""Walk the LRU list, only meant to be used in tests."""
node = self._most_recently_used
if node is not None:
if node.prev is not None:
raise AssertionError('the _most_recently_used entry is not'
' supposed to have a previous entry'
' %s' % (node,))
while node is not None:
if node.next_key is _null_key:
if node is not self._least_recently_used:
raise AssertionError('only the last node should have'
' no next value: %s' % (node,))
node_next = None
else:
node_next = self._cache[node.next_key]
if node_next.prev is not node:
raise AssertionError('inconsistency found, node.next.prev'
' != node: %s' % (node,))
if node.prev is None:
if node is not self._most_recently_used:
raise AssertionError('only the _most_recently_used should'
' not have a previous node: %s'
% (node,))
else:
if node.prev.next_key != node.key:
raise AssertionError('inconsistency found, node.prev.next'
' != node: %s' % (node,))
yield node
node = node_next
def add(self, key, value, cleanup=None):
"""Add a new value to the cache.
Also, if the entry is ever removed from the cache, call
cleanup(key, value).
:param key: The key to store it under
:param value: The object to store
:param cleanup: None or a function taking (key, value) to indicate
'value' should be cleaned up.
"""
if key is _null_key:
raise ValueError('cannot use _null_key as a key')
if key in self._cache:
node = self._cache[key]
node.run_cleanup()
node.value = value
node.cleanup = cleanup
else:
node = _LRUNode(key, value, cleanup=cleanup)
self._cache[key] = node
self._record_access(node)
if len(self._cache) > self._max_cache:
# Trigger the cleanup
self.cleanup()
def cache_size(self):
"""Get the number of entries we will cache."""
return self._max_cache
def get(self, key, default=None):
node = self._cache.get(key, None)
if node is None:
return default
self._record_access(node)
return node.value
def keys(self):
"""Get the list of keys currently cached.
Note that values returned here may not be available by the time you
request them later. This is simply meant as a peak into the current
state.
:return: An unordered list of keys that are currently cached.
"""
return self._cache.keys()
def items(self):
"""Get the key:value pairs as a dict."""
return dict((k, n.value) for k, n in self._cache.iteritems())
def cleanup(self):
"""Clear the cache until it shrinks to the requested size.
This does not completely wipe the cache, just makes sure it is under
the after_cleanup_count.
"""
# Make sure the cache is shrunk to the correct size
while len(self._cache) > self._after_cleanup_count:
self._remove_lru()
def __setitem__(self, key, value):
"""Add a value to the cache, there will be no cleanup function."""
self.add(key, value, cleanup=None)
def _record_access(self, node):
"""Record that key was accessed."""
# Move 'node' to the front of the queue
if self._most_recently_used is None:
self._most_recently_used = node
self._least_recently_used = node
return
elif node is self._most_recently_used:
# Nothing to do, this node is already at the head of the queue
return
# We've taken care of the tail pointer, remove the node, and insert it
# at the front
# REMOVE
if node is self._least_recently_used:
self._least_recently_used = node.prev
if node.prev is not None:
node.prev.next_key = node.next_key
if node.next_key is not _null_key:
node_next = self._cache[node.next_key]
node_next.prev = node.prev
# INSERT
node.next_key = self._most_recently_used.key
self._most_recently_used.prev = node
self._most_recently_used = node
node.prev = None
def _remove_node(self, node):
if node is self._least_recently_used:
self._least_recently_used = node.prev
self._cache.pop(node.key)
# If we have removed all entries, remove the head pointer as well
if self._least_recently_used is None:
self._most_recently_used = None
node.run_cleanup()
# Now remove this node from the linked list
if node.prev is not None:
node.prev.next_key = node.next_key
if node.next_key is not _null_key:
node_next = self._cache[node.next_key]
node_next.prev = node.prev
# And remove this node's pointers
node.prev = None
node.next_key = _null_key
def _remove_lru(self):
"""Remove one entry from the lru, and handle consequences.
If there are no more references to the lru, then this entry should be
removed from the cache.
"""
self._remove_node(self._least_recently_used)
def clear(self):
"""Clear out all of the cache."""
# Clean up in LRU order
while self._cache:
self._remove_lru()
def resize(self, max_cache, after_cleanup_count=None):
"""Change the number of entries that will be cached."""
self._update_max_cache(max_cache,
after_cleanup_count=after_cleanup_count)
def _update_max_cache(self, max_cache, after_cleanup_count=None):
self._max_cache = max_cache
if after_cleanup_count is None:
self._after_cleanup_count = self._max_cache * 8 / 10
else:
self._after_cleanup_count = min(after_cleanup_count,
self._max_cache)
self.cleanup()
class LRUSizeCache(LRUCache):
"""An LRUCache that removes things based on the size of the values.
This differs in that it doesn't care how many actual items there are,
it just restricts the cache to be cleaned up after so much data is stored.
The size of items added will be computed using compute_size(value), which
defaults to len() if not supplied.
"""
def __init__(self, max_size=1024*1024, after_cleanup_size=None,
compute_size=None):
"""Create a new LRUSizeCache.
:param max_size: The max number of bytes to store before we start
clearing out entries.
:param after_cleanup_size: After cleaning up, shrink everything to this
size.
:param compute_size: A function to compute the size of the values. We
use a function here, so that you can pass 'len' if you are just
using simple strings, or a more complex function if you are using
something like a list of strings, or even a custom object.
The function should take the form "compute_size(value) => integer".
If not supplied, it defaults to 'len()'
"""
self._value_size = 0
self._compute_size = compute_size
if compute_size is None:
self._compute_size = len
self._update_max_size(max_size, after_cleanup_size=after_cleanup_size)
LRUCache.__init__(self, max_cache=max(int(max_size/512), 1))
def add(self, key, value, cleanup=None):
"""Add a new value to the cache.
Also, if the entry is ever removed from the cache, call
cleanup(key, value).
:param key: The key to store it under
:param value: The object to store
:param cleanup: None or a function taking (key, value) to indicate
'value' should be cleaned up.
"""
if key is _null_key:
raise ValueError('cannot use _null_key as a key')
node = self._cache.get(key, None)
value_len = self._compute_size(value)
if value_len >= self._after_cleanup_size:
# The new value is 'too big to fit', as it would fill up/overflow
# the cache all by itself
if node is not None:
# We won't be replacing the old node, so just remove it
self._remove_node(node)
if cleanup is not None:
cleanup(key, value)
return
if node is None:
node = _LRUNode(key, value, cleanup=cleanup)
self._cache[key] = node
else:
self._value_size -= node.size
node.size = value_len
self._value_size += value_len
self._record_access(node)
if self._value_size > self._max_size:
# Time to cleanup
self.cleanup()
def cleanup(self):
"""Clear the cache until it shrinks to the requested size.
This does not completely wipe the cache, just makes sure it is under
the after_cleanup_size.
"""
# Make sure the cache is shrunk to the correct size
while self._value_size > self._after_cleanup_size:
self._remove_lru()
def _remove_node(self, node):
self._value_size -= node.size
LRUCache._remove_node(self, node)
def resize(self, max_size, after_cleanup_size=None):
"""Change the number of bytes that will be cached."""
self._update_max_size(max_size, after_cleanup_size=after_cleanup_size)
max_cache = max(int(max_size/512), 1)
self._update_max_cache(max_cache)
def _update_max_size(self, max_size, after_cleanup_size=None):
self._max_size = max_size
if after_cleanup_size is None:
self._after_cleanup_size = self._max_size * 8 / 10
else:
self._after_cleanup_size = min(after_cleanup_size, self._max_size)
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