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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., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
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# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
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"""A simple least-recently-used (LRU) cache."""
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from collections import deque
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class _LRUNode(object):
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"""This maintains the linked-list which is the lru internals."""
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__slots__ = ('prev', 'next_key', 'key', 'value', 'cleanup', 'size')
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def __init__(self, key, value, cleanup=None):
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self.next_key = _null_key
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self.cleanup = cleanup
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# TODO: We could compute this 'on-the-fly' like we used to, and remove
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# one pointer from this object, we just need to decide if it
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# actually costs us much of anything in normal usage
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prev_key = self.prev.key
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return '%s(%r n:%r p:%r)' % (self.__class__.__name__, self.key,
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self.next_key, prev_key)
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def run_cleanup(self):
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if self.cleanup is not None:
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self.cleanup(self.key, self.value)
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# Just make sure to break any refcycles, etc
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class LRUCache(object):
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"""A class which manages a cache of entries, removing unused ones."""
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def __init__(self, max_cache=100, after_cleanup_size=None):
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self._max_cache = max_cache
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if after_cleanup_size is None:
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self._after_cleanup_size = self._max_cache
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self._after_cleanup_size = min(after_cleanup_size, self._max_cache)
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self._compact_queue_length = 4*self._max_cache
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def __init__(self, max_cache=100, after_cleanup_count=None,
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after_cleanup_size=symbol_versioning.DEPRECATED_PARAMETER):
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if symbol_versioning.deprecated_passed(after_cleanup_size):
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symbol_versioning.warn('LRUCache.__init__(after_cleanup_size) was'
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' deprecated in 1.11. Use'
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' after_cleanup_count instead.',
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after_cleanup_count = after_cleanup_size
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self._queue = deque() # Track when things are accessed
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self._refcount = {} # number of entries in self._queue for each key
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# The "HEAD" of the lru linked list
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self._most_recently_used = None
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# The "TAIL" of the lru linked list
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self._least_recently_used = None
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self._update_max_cache(max_cache, after_cleanup_count)
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def __contains__(self, key):
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return key in self._cache
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def __getitem__(self, key):
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val = self._cache[key]
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self._record_access(key)
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# Inlined from _record_access to decrease the overhead of __getitem__
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# We also have more knowledge about structure if __getitem__ is
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# succeeding, then we know that self._most_recently_used must not be
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mru = self._most_recently_used
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# Nothing to do, this node is already at the head of the queue
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# Remove this node from the old location
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next_key = node.next_key
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# benchmarking shows that the lookup of _null_key in globals is faster
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# than the attribute lookup for (node is self._least_recently_used)
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if next_key is _null_key:
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# 'node' is the _least_recently_used, because it doesn't have a
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# 'next' item. So move the current lru to the previous node.
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self._least_recently_used = node_prev
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node_next = cache[next_key]
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node_next.prev = node_prev
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node_prev.next_key = next_key
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# Insert this node at the front of the list
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node.next_key = mru.key
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self._most_recently_used = node
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def __len__(self):
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return len(self._cache)
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"""Walk the LRU list, only meant to be used in tests."""
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node = self._most_recently_used
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if node.prev is not None:
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raise AssertionError('the _most_recently_used entry is not'
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' supposed to have a previous entry'
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while node is not None:
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if node.next_key is _null_key:
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if node is not self._least_recently_used:
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raise AssertionError('only the last node should have'
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' no next value: %s' % (node,))
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node_next = self._cache[node.next_key]
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if node_next.prev is not node:
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raise AssertionError('inconsistency found, node.next.prev'
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' != node: %s' % (node,))
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if node.prev is None:
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if node is not self._most_recently_used:
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raise AssertionError('only the _most_recently_used should'
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' not have a previous node: %s'
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if node.prev.next_key != node.key:
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raise AssertionError('inconsistency found, node.prev.next'
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' != node: %s' % (node,))
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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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Also, if the entry is ever removed from the cache, call
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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' sohuld be cleaned up.
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'value' should be cleaned up.
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raise ValueError('cannot use _null_key as a key')
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if key in self._cache:
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self._cache[key] = value
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self._cleanup[key] = cleanup
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self._record_access(key)
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node = self._cache[key]
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node.cleanup = cleanup
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node = _LRUNode(key, value, cleanup=cleanup)
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self._cache[key] = node
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self._record_access(node)
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if len(self._cache) > self._max_cache:
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# Trigger the cleanup
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def cache_size(self):
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"""Get the number of entries we will cache."""
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return self._max_cache
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def get(self, key, default=None):
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if key in self._cache:
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node = self._cache.get(key, None)
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self._record_access(node)
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"""Get the list of keys currently cached.
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Note that values returned here may not be available by the time you
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request them later. This is simply meant as a peak into the current
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:return: An unordered list of keys that are currently cached.
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return self._cache.keys()
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"""Get the key:value pairs as a dict."""
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return dict((k, n.value) for k, n in self._cache.iteritems())
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def cleanup(self):
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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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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._cache) > self._after_cleanup_size:
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while len(self._cache) > self._after_cleanup_count:
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self._remove_lru()
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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 _record_access(self, key):
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def _record_access(self, node):
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"""Record that key was accessed."""
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self._queue.append(key)
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# Can't use setdefault because you can't += 1 the result
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self._refcount[key] = self._refcount.get(key, 0) + 1
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# If our access queue is too large, clean it up too
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if len(self._queue) > self._compact_queue_length:
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def _compact_queue(self):
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"""Compact the queue, leaving things in sorted last appended order."""
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for item in self._queue:
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if self._refcount[item] == 1:
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new_queue.append(item)
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self._refcount[item] -= 1
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self._queue = new_queue
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# All entries should be of the same size. There should be one entry in
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# queue for each entry in cache, and all refcounts should == 1
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if not (len(self._queue) == len(self._cache) ==
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len(self._refcount) == sum(self._refcount.itervalues())):
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raise AssertionError()
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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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cleanup = self._cleanup.pop(key)
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val = self._cache.pop(key)
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if cleanup is not None:
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# Move 'node' to the front of the queue
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if self._most_recently_used is None:
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self._most_recently_used = node
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self._least_recently_used = node
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elif node is self._most_recently_used:
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# Nothing to do, this node is already at the head of the queue
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# We've taken care of the tail pointer, remove the node, and insert it
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if node is self._least_recently_used:
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self._least_recently_used = node.prev
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if node.prev is not None:
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node.prev.next_key = node.next_key
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if node.next_key is not _null_key:
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node_next = self._cache[node.next_key]
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node_next.prev = node.prev
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node.next_key = self._most_recently_used.key
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self._most_recently_used.prev = node
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self._most_recently_used = node
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def _remove_node(self, node):
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if node is self._least_recently_used:
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self._least_recently_used = node.prev
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self._cache.pop(node.key)
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# If we have removed all entries, remove the head pointer as well
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if self._least_recently_used is None:
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self._most_recently_used = None
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# Now remove this node from the linked list
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if node.prev is not None:
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node.prev.next_key = node.next_key
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if node.next_key is not _null_key:
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node_next = self._cache[node.next_key]
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node_next.prev = node.prev
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# And remove this node's pointers
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node.next_key = _null_key
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def _remove_lru(self):
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"""Remove one entry from the lru, and handle consequences.
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The function should take the form "compute_size(value) => integer".
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If not supplied, it defaults to 'len()'
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# This approximates that texts are > 0.5k in size. It only really
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# effects when we clean up the queue, so we don't want it to be too
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LRUCache.__init__(self, max_cache=int(max_size/512))
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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
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self._after_cleanup_size = min(after_cleanup_size, self._max_size)
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self._value_size = 0
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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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self._update_max_size(max_size, after_cleanup_size=after_cleanup_size)
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LRUCache.__init__(self, max_cache=max(int(max_size/512), 1))
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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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Also, if the entry is ever removed from the cache, call
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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' sohuld be cleaned up.
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'value' should be cleaned up.
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if key in self._cache:
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raise ValueError('cannot use _null_key as a key')
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node = self._cache.get(key, None)
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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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# The new value is 'too big to fit', as it would fill up/overflow
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# the cache all by itself
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trace.mutter('Adding the key %r to an LRUSizeCache failed.'
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' value %d is too big to fit in a the cache'
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' with size %d %d', key, value_len,
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self._after_cleanup_size, self._max_size)
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# We won't be replacing the old node, so just remove it
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self._remove_node(node)
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if cleanup is not None:
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node = _LRUNode(key, value, cleanup=cleanup)
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self._cache[key] = node
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self._value_size -= node.size
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node.size = value_len
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self._value_size += value_len
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self._cache[key] = value
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self._cleanup[key] = cleanup
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self._record_access(key)
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self._record_access(node)
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if self._value_size > self._max_size:
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# Time to cleanup
added
removed
bzrlib/lru_cache.py
