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authorDaniel Baumann <daniel.baumann@progress-linux.org>2024-04-19 00:47:55 +0000
committerDaniel Baumann <daniel.baumann@progress-linux.org>2024-04-19 00:47:55 +0000
commit26a029d407be480d791972afb5975cf62c9360a6 (patch)
treef435a8308119effd964b339f76abb83a57c29483 /third_party/python/pylru/pylru.py
parentInitial commit. (diff)
downloadfirefox-upstream/124.0.1.tar.xz
firefox-upstream/124.0.1.zip
Adding upstream version 124.0.1.upstream/124.0.1
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
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diff --git a/third_party/python/pylru/pylru.py b/third_party/python/pylru/pylru.py
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+
+# Cache implementaion with a Least Recently Used (LRU) replacement policy and
+# a basic dictionary interface.
+
+# Copyright (C) 2006, 2009, 2010, 2011 Jay Hutchinson
+
+# 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.
+
+
+
+# The cache is implemented using a combination of a python dictionary (hash
+# table) and a circular doubly linked list. Items in the cache are stored in
+# nodes. These nodes make up the linked list. The list is used to efficiently
+# maintain the order that the items have been used in. The front or head of
+# the list contains the most recently used item, the tail of the list
+# contains the least recently used item. When an item is used it can easily
+# (in a constant amount of time) be moved to the front of the list, thus
+# updating its position in the ordering. These nodes are also placed in the
+# hash table under their associated key. The hash table allows efficient
+# lookup of values by key.
+
+# Class for the node objects.
+class _dlnode(object):
+ def __init__(self):
+ self.empty = True
+
+
+class lrucache(object):
+
+ def __init__(self, size, callback=None):
+
+ self.callback = callback
+
+ # Create an empty hash table.
+ self.table = {}
+
+ # Initialize the doubly linked list with one empty node. This is an
+ # invariant. The cache size must always be greater than zero. Each
+ # node has a 'prev' and 'next' variable to hold the node that comes
+ # before it and after it respectively. Initially the two variables
+ # each point to the head node itself, creating a circular doubly
+ # linked list of size one. Then the size() method is used to adjust
+ # the list to the desired size.
+
+ self.head = _dlnode()
+ self.head.next = self.head
+ self.head.prev = self.head
+
+ self.listSize = 1
+
+ # Adjust the size
+ self.size(size)
+
+
+ def __len__(self):
+ return len(self.table)
+
+ def clear(self):
+ for node in self.dli():
+ node.empty = True
+ node.key = None
+ node.value = None
+
+ self.table.clear()
+
+
+ def __contains__(self, key):
+ return key in self.table
+
+ # Looks up a value in the cache without affecting cache order.
+ def peek(self, key):
+ # Look up the node
+ node = self.table[key]
+ return node.value
+
+
+ def __getitem__(self, key):
+ # Look up the node
+ node = self.table[key]
+
+ # Update the list ordering. Move this node so that is directly
+ # proceeds the head node. Then set the 'head' variable to it. This
+ # makes it the new head of the list.
+ self.mtf(node)
+ self.head = node
+
+ # Return the value.
+ return node.value
+
+ def get(self, key, default=None):
+ """Get an item - return default (None) if not present"""
+ try:
+ return self[key]
+ except KeyError:
+ return default
+
+ def __setitem__(self, key, value):
+ # First, see if any value is stored under 'key' in the cache already.
+ # If so we are going to replace that value with the new one.
+ if key in self.table:
+
+ # Lookup the node
+ node = self.table[key]
+
+ # Replace the value.
+ node.value = value
+
+ # Update the list ordering.
+ self.mtf(node)
+ self.head = node
+
+ return
+
+ # Ok, no value is currently stored under 'key' in the cache. We need
+ # to choose a node to place the new item in. There are two cases. If
+ # the cache is full some item will have to be pushed out of the
+ # cache. We want to choose the node with the least recently used
+ # item. This is the node at the tail of the list. If the cache is not
+ # full we want to choose a node that is empty. Because of the way the
+ # list is managed, the empty nodes are always together at the tail
+ # end of the list. Thus, in either case, by chooseing the node at the
+ # tail of the list our conditions are satisfied.
+
+ # Since the list is circular, the tail node directly preceeds the
+ # 'head' node.
+ node = self.head.prev
+
+ # If the node already contains something we need to remove the old
+ # key from the dictionary.
+ if not node.empty:
+ if self.callback is not None:
+ self.callback(node.key, node.value)
+ del self.table[node.key]
+
+ # Place the new key and value in the node
+ node.empty = False
+ node.key = key
+ node.value = value
+
+ # Add the node to the dictionary under the new key.
+ self.table[key] = node
+
+ # We need to move the node to the head of the list. The node is the
+ # tail node, so it directly preceeds the head node due to the list
+ # being circular. Therefore, the ordering is already correct, we just
+ # need to adjust the 'head' variable.
+ self.head = node
+
+
+ def __delitem__(self, key):
+
+ # Lookup the node, then remove it from the hash table.
+ node = self.table[key]
+ del self.table[key]
+
+ node.empty = True
+
+ # Not strictly necessary.
+ node.key = None
+ node.value = None
+
+ # Because this node is now empty we want to reuse it before any
+ # non-empty node. To do that we want to move it to the tail of the
+ # list. We move it so that it directly preceeds the 'head' node. This
+ # makes it the tail node. The 'head' is then adjusted. This
+ # adjustment ensures correctness even for the case where the 'node'
+ # is the 'head' node.
+ self.mtf(node)
+ self.head = node.next
+
+ def __iter__(self):
+
+ # Return an iterator that returns the keys in the cache in order from
+ # the most recently to least recently used. Does not modify the cache
+ # order.
+ for node in self.dli():
+ yield node.key
+
+ def items(self):
+
+ # Return an iterator that returns the (key, value) pairs in the cache
+ # in order from the most recently to least recently used. Does not
+ # modify the cache order.
+ for node in self.dli():
+ yield (node.key, node.value)
+
+ def keys(self):
+
+ # Return an iterator that returns the keys in the cache in order from
+ # the most recently to least recently used. Does not modify the cache
+ # order.
+ for node in self.dli():
+ yield node.key
+
+ def values(self):
+
+ # Return an iterator that returns the values in the cache in order
+ # from the most recently to least recently used. Does not modify the
+ # cache order.
+ for node in self.dli():
+ yield node.value
+
+ def size(self, size=None):
+
+ if size is not None:
+ assert size > 0
+ if size > self.listSize:
+ self.addTailNode(size - self.listSize)
+ elif size < self.listSize:
+ self.removeTailNode(self.listSize - size)
+
+ return self.listSize
+
+ # Increases the size of the cache by inserting n empty nodes at the tail
+ # of the list.
+ def addTailNode(self, n):
+ for i in range(n):
+ node = _dlnode()
+ node.next = self.head
+ node.prev = self.head.prev
+
+ self.head.prev.next = node
+ self.head.prev = node
+
+ self.listSize += n
+
+ # Decreases the size of the list by removing n nodes from the tail of the
+ # list.
+ def removeTailNode(self, n):
+ assert self.listSize > n
+ for i in range(n):
+ node = self.head.prev
+ if not node.empty:
+ if self.callback is not None:
+ self.callback(node.key, node.value)
+ del self.table[node.key]
+
+ # Splice the tail node out of the list
+ self.head.prev = node.prev
+ node.prev.next = self.head
+
+ # The next four lines are not strictly necessary.
+ node.prev = None
+ node.next = None
+
+ node.key = None
+ node.value = None
+
+ self.listSize -= n
+
+
+ # This method adjusts the ordering of the doubly linked list so that
+ # 'node' directly precedes the 'head' node. Because of the order of
+ # operations, if 'node' already directly precedes the 'head' node or if
+ # 'node' is the 'head' node the order of the list will be unchanged.
+ def mtf(self, node):
+ node.prev.next = node.next
+ node.next.prev = node.prev
+
+ node.prev = self.head.prev
+ node.next = self.head.prev.next
+
+ node.next.prev = node
+ node.prev.next = node
+
+ # This method returns an iterator that iterates over the non-empty nodes
+ # in the doubly linked list in order from the most recently to the least
+ # recently used.
+ def dli(self):
+ node = self.head
+ for i in range(len(self.table)):
+ yield node
+ node = node.next
+
+
+
+
+class WriteThroughCacheManager(object):
+ def __init__(self, store, size):
+ self.store = store
+ self.cache = lrucache(size)
+
+ def __len__(self):
+ return len(self.store)
+
+ # Returns/sets the size of the managed cache.
+ def size(self, size=None):
+ return self.cache.size(size)
+
+ def clear(self):
+ self.cache.clear()
+ self.store.clear()
+
+ def __contains__(self, key):
+ # Check the cache first. If it is there we can return quickly.
+ if key in self.cache:
+ return True
+
+ # Not in the cache. Might be in the underlying store.
+ if key in self.store:
+ return True
+
+ return False
+
+ def __getitem__(self, key):
+ # First we try the cache. If successful we just return the value. If
+ # not we catch KeyError and ignore it since that just means the key
+ # was not in the cache.
+ try:
+ return self.cache[key]
+ except KeyError:
+ pass
+
+ # It wasn't in the cache. Look it up in the store, add the entry to
+ # the cache, and return the value.
+ value = self.store[key]
+ self.cache[key] = value
+ return value
+
+ def get(self, key, default=None):
+ """Get an item - return default (None) if not present"""
+ try:
+ return self[key]
+ except KeyError:
+ return default
+
+ def __setitem__(self, key, value):
+ # Add the key/value pair to the cache and store.
+ self.cache[key] = value
+ self.store[key] = value
+
+ def __delitem__(self, key):
+ # Write-through behavior cache and store should be consistent. Delete
+ # it from the store.
+ del self.store[key]
+ try:
+ # Ok, delete from the store was successful. It might also be in
+ # the cache, try and delete it. If not we catch the KeyError and
+ # ignore it.
+ del self.cache[key]
+ except KeyError:
+ pass
+
+ def __iter__(self):
+ return self.keys()
+
+ def keys(self):
+ return self.store.keys()
+
+ def values(self):
+ return self.store.values()
+
+ def items(self):
+ return self.store.items()
+
+
+
+class WriteBackCacheManager(object):
+ def __init__(self, store, size):
+ self.store = store
+
+ # Create a set to hold the dirty keys.
+ self.dirty = set()
+
+ # Define a callback function to be called by the cache when a
+ # key/value pair is about to be ejected. This callback will check to
+ # see if the key is in the dirty set. If so, then it will update the
+ # store object and remove the key from the dirty set.
+ def callback(key, value):
+ if key in self.dirty:
+ self.store[key] = value
+ self.dirty.remove(key)
+
+ # Create a cache and give it the callback function.
+ self.cache = lrucache(size, callback)
+
+ # Returns/sets the size of the managed cache.
+ def size(self, size=None):
+ return self.cache.size(size)
+
+ def clear(self):
+ self.cache.clear()
+ self.dirty.clear()
+ self.store.clear()
+
+ def __contains__(self, key):
+ # Check the cache first, since if it is there we can return quickly.
+ if key in self.cache:
+ return True
+
+ # Not in the cache. Might be in the underlying store.
+ if key in self.store:
+ return True
+
+ return False
+
+ def __getitem__(self, key):
+ # First we try the cache. If successful we just return the value. If
+ # not we catch KeyError and ignore it since that just means the key
+ # was not in the cache.
+ try:
+ return self.cache[key]
+ except KeyError:
+ pass
+
+ # It wasn't in the cache. Look it up in the store, add the entry to
+ # the cache, and return the value.
+ value = self.store[key]
+ self.cache[key] = value
+ return value
+
+ def get(self, key, default=None):
+ """Get an item - return default (None) if not present"""
+ try:
+ return self[key]
+ except KeyError:
+ return default
+
+ def __setitem__(self, key, value):
+ # Add the key/value pair to the cache.
+ self.cache[key] = value
+ self.dirty.add(key)
+
+ def __delitem__(self, key):
+
+ found = False
+ try:
+ del self.cache[key]
+ found = True
+ self.dirty.remove(key)
+ except KeyError:
+ pass
+
+ try:
+ del self.store[key]
+ found = True
+ except KeyError:
+ pass
+
+ if not found: # If not found in cache or store, raise error.
+ raise KeyError
+
+
+ def __iter__(self):
+ return self.keys()
+
+ def keys(self):
+ for key in self.store.keys():
+ if key not in self.dirty:
+ yield key
+
+ for key in self.dirty:
+ yield key
+
+
+ def values(self):
+ for key, value in self.items():
+ yield value
+
+
+ def items(self):
+ for key, value in self.store.items():
+ if key not in self.dirty:
+ yield (key, value)
+
+ for key in self.dirty:
+ value = self.cache.peek(key)
+ yield (key, value)
+
+
+
+ def sync(self):
+ # For each dirty key, peek at its value in the cache and update the
+ # store. Doesn't change the cache's order.
+ for key in self.dirty:
+ self.store[key] = self.cache.peek(key)
+ # There are no dirty keys now.
+ self.dirty.clear()
+
+ def flush(self):
+ self.sync()
+ self.cache.clear()
+
+ def __enter__(self):
+ return self
+
+ def __exit__(self, exc_type, exc_val, exc_tb):
+ self.sync()
+ return False
+
+
+class FunctionCacheManager(object):
+ def __init__(self, func, size):
+ self.func = func
+ self.cache = lrucache(size)
+
+ def size(self, size=None):
+ return self.cache.size(size)
+
+ def clear(self):
+ self.cache.clear()
+
+ def __call__(self, *args, **kwargs):
+ kwtuple = tuple((key, kwargs[key]) for key in sorted(kwargs.keys()))
+ key = (args, kwtuple)
+ try:
+ return self.cache[key]
+ except KeyError:
+ pass
+
+ value = self.func(*args, **kwargs)
+ self.cache[key] = value
+ return value
+
+
+def lruwrap(store, size, writeback=False):
+ if writeback:
+ return WriteBackCacheManager(store, size)
+ else:
+ return WriteThroughCacheManager(store, size)
+
+import functools
+
+class lrudecorator(object):
+ def __init__(self, size):
+ self.cache = lrucache(size)
+
+ def __call__(self, func):
+ def wrapper(*args, **kwargs):
+ kwtuple = tuple((key, kwargs[key]) for key in sorted(kwargs.keys()))
+ key = (args, kwtuple)
+ try:
+ return self.cache[key]
+ except KeyError:
+ pass
+
+ value = func(*args, **kwargs)
+ self.cache[key] = value
+ return value
+
+ wrapper.cache = self.cache
+ wrapper.size = self.cache.size
+ wrapper.clear = self.cache.clear
+ return functools.update_wrapper(wrapper, func)