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# Copyright (C) 2008 Canonical Ltd
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# This program is free software; you can redistribute it and/or modify
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# it under the terms of the GNU General Public License as published by
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# the Free Software Foundation; either version 2 of the License, or
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# (at your option) any later version.
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU General Public License for more details.
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# You should have received a copy of the GNU General Public License
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# along with this program; if not, write to the Free Software
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# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
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"""A simple first-in-first-out (FIFO) cache."""
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from collections import deque
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class FIFOCache(dict):
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"""A class which manages a cache of entries, removing old ones."""
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def __init__(self, max_cache=100, after_cleanup_count=None):
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self._max_cache = max_cache
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if after_cleanup_count is None:
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self._after_cleanup_count = self._max_cache * 8 / 10
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self._after_cleanup_count = min(after_cleanup_count,
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self._cleanup = {} # map to cleanup functions when items are removed
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self._queue = deque() # Track when things are accessed
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def __setitem__(self, key, value):
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"""Add a value to the cache, there will be no cleanup function."""
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self.add(key, value, cleanup=None)
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def __delitem__(self, key):
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# Remove the key from an arbitrary location in the queue
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remove = getattr(self._queue, 'remove', None)
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# Python2.5's has deque.remove, but Python2.4 does not
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if remove is not None:
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# TODO: It would probably be faster to pop()/popleft() until we get to the
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# key, and then insert those back into the queue. We know
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# the key should only be present in one position, and we
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# wouldn't need to rebuild the whole queue.
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self._queue = deque([k for k in self._queue if k != key])
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def add(self, key, value, cleanup=None):
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"""Add a new value to the cache.
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Also, if the entry is ever removed from the queue, call cleanup.
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Passing it the key and value being removed.
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:param key: The key to store it under
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:param value: The object to store
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:param cleanup: None or a function taking (key, value) to indicate
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'value' should be cleaned up
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# Remove the earlier reference to this key, adding it again bumps
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# it to the end of the queue
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self._queue.append(key)
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dict.__setitem__(self, key, value)
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if cleanup is not None:
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self._cleanup[key] = cleanup
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if len(self) > self._max_cache:
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"""Get the number of entries we will cache."""
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return self._max_cache
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"""Clear the cache until it shrinks to the requested size.
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This does not completely wipe the cache, just makes sure it is under
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the after_cleanup_count.
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# Make sure the cache is shrunk to the correct size
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while len(self) > self._after_cleanup_count:
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if len(self._queue) != len(self):
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raise AssertionError('The length of the queue should always equal'
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' the length of the dict. %s != %s'
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% (len(self._queue), len(self)))
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"""Clear out all of the cache."""
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# Clean up in FIFO order
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def _remove(self, key):
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"""Remove an entry, making sure to call any cleanup function."""
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cleanup = self._cleanup.pop(key, None)
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# We override self.pop() because it doesn't play well with cleanup
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val = dict.pop(self, key)
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if cleanup is not None:
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def _remove_oldest(self):
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"""Remove the oldest entry."""
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key = self._queue.popleft()
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def resize(self, max_cache, after_cleanup_count=None):
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"""Increase/decrease the number of cached entries.
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:param max_cache: The maximum number of entries to cache.
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:param after_cleanup_count: After cleanup, we should have at most this
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many entries. This defaults to 80% of max_cache.
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self._max_cache = max_cache
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if after_cleanup_count is None:
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self._after_cleanup_count = max_cache * 8 / 10
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self._after_cleanup_count = min(max_cache, after_cleanup_count)
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if len(self) > self._max_cache:
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# raise NotImplementedError on dict functions that would mutate the cache
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# which have not been properly implemented yet.
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raise NotImplementedError(self.copy)
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def pop(self, key, default=None):
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# If there is a cleanup() function, than it is unclear what pop()
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# should do. Specifically, we would have to call the cleanup on the
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# value before we return it, which should cause whatever resources were
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# allocated to be removed, which makes the return value fairly useless.
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# So instead, we just don't implement it.
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raise NotImplementedError(self.pop)
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raise NotImplementedError(self.popitem)
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def setdefault(self, key, defaultval=None):
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"""similar to dict.setdefault"""
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self[key] = defaultval
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def update(self, *args, **kwargs):
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"""Similar to dict.update()"""
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if isinstance(arg, dict):
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for key, val in arg.iteritems():
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for key, val in args[0]:
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raise TypeError('update expected at most 1 argument, got %d'
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for key, val in kwargs.iteritems():
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class FIFOSizeCache(FIFOCache):
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"""An FIFOCache that removes things based on the size of the values.
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This differs in that it doesn't care how many actual items there are,
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it restricts the cache to be cleaned based on the size of the data.
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def __init__(self, max_size=1024*1024, after_cleanup_size=None,
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"""Create a new FIFOSizeCache.
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:param max_size: The max number of bytes to store before we start
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clearing out entries.
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:param after_cleanup_size: After cleaning up, shrink everything to this
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size (defaults to 80% of max_size).
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:param compute_size: A function to compute the size of a value. If
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not supplied we default to 'len'.
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# Arbitrary, we won't really be using the value anyway.
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FIFOCache.__init__(self, max_cache=max_size)
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self._max_size = max_size
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if after_cleanup_size is None:
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self._after_cleanup_size = self._max_size * 8 / 10
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self._after_cleanup_size = min(after_cleanup_size, self._max_size)
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self._compute_size = compute_size
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if compute_size is None:
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self._compute_size = len
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def add(self, key, value, cleanup=None):
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"""Add a new value to the cache.
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Also, if the entry is ever removed from the queue, call cleanup.
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Passing it the key and value being removed.
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:param key: The key to store it under
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:param value: The object to store, this value by itself is >=
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after_cleanup_size, then we will not store it at all.
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:param cleanup: None or a function taking (key, value) to indicate
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'value' sohuld be cleaned up.
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# Even if the new value won't be stored, we need to remove the old
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# Remove the earlier reference to this key, adding it again bumps
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# it to the end of the queue
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value_len = self._compute_size(value)
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if value_len >= self._after_cleanup_size:
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self._queue.append(key)
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dict.__setitem__(self, key, value)
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if cleanup is not None:
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self._cleanup[key] = cleanup
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self._value_size += value_len
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if self._value_size > self._max_size:
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def cache_size(self):
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"""Get the number of bytes we will cache."""
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return self._max_size
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"""Clear the cache until it shrinks to the requested size.
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This does not completely wipe the cache, just makes sure it is under
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the after_cleanup_size.
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# Make sure the cache is shrunk to the correct size
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while self._value_size > self._after_cleanup_size:
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self._remove_oldest()
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def _remove(self, key):
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"""Remove an entry, making sure to maintain the invariants."""
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val = FIFOCache._remove(self, key)
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self._value_size -= self._compute_size(val)
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def resize(self, max_size, after_cleanup_size=None):
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"""Increase/decrease the amount of cached data.
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:param max_size: The maximum number of bytes to cache.
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:param after_cleanup_size: After cleanup, we should have at most this
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many bytes cached. This defaults to 80% of max_size.
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FIFOCache.resize(self, max_size)
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self._max_size = max_size
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if after_cleanup_size is None:
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self._after_cleanup_size = max_size * 8 / 10
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self._after_cleanup_size = min(max_size, after_cleanup_size)
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if self._value_size > self._max_size:
added
removed
bzrlib/fifo_cache.py
