mirror of
https://git.anonymousland.org/anonymousland/synapse.git
synced 2024-10-01 11:49:51 -04:00
119cb9bbcf
Currently the cache descriptors store deferreds rather than raw values, this is a simple way of triggering only one database hit and sharing the result if two callers attempt to get the same value. However, there are a few caches that simply store a mapping from string to string (or int). These caches can have a large number of entries, under the assumption that each entry is small. However, the size of a deferred (specifically the size of ObservableDeferred) is signigicantly larger than that of the raw value, 2kb vs 32b. This PR therefore changes the cache descriptors to store the raw values rather than the deferreds. As a side effect cached storage function now either return a deferred or the actual value, as the cached list decriptor already does. This is fine as we always end up just yield'ing on the returned value eventually, which handles that case correctly.
588 lines
20 KiB
Python
588 lines
20 KiB
Python
# -*- coding: utf-8 -*-
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# Copyright 2015, 2016 OpenMarket Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import logging
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from synapse.util.async import ObservableDeferred
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from synapse.util import unwrapFirstError, logcontext
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from synapse.util.caches.lrucache import LruCache
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from synapse.util.caches.treecache import TreeCache, iterate_tree_cache_entry
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from . import register_cache
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from twisted.internet import defer
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from collections import namedtuple
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import os
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import functools
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import inspect
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import threading
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logger = logging.getLogger(__name__)
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_CacheSentinel = object()
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CACHE_SIZE_FACTOR = float(os.environ.get("SYNAPSE_CACHE_FACTOR", 0.1))
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class CacheEntry(object):
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__slots__ = [
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"deferred", "sequence", "callbacks", "invalidated"
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]
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def __init__(self, deferred, sequence, callbacks):
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self.deferred = deferred
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self.sequence = sequence
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self.callbacks = set(callbacks)
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self.invalidated = False
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def invalidate(self):
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if not self.invalidated:
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self.invalidated = True
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for callback in self.callbacks:
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callback()
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self.callbacks.clear()
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class Cache(object):
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__slots__ = (
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"cache",
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"max_entries",
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"name",
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"keylen",
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"sequence",
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"thread",
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"metrics",
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"_pending_deferred_cache",
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)
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def __init__(self, name, max_entries=1000, keylen=1, tree=False, iterable=False):
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cache_type = TreeCache if tree else dict
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self._pending_deferred_cache = cache_type()
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self.cache = LruCache(
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max_size=max_entries, keylen=keylen, cache_type=cache_type,
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size_callback=(lambda d: len(d)) if iterable else None,
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)
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self.name = name
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self.keylen = keylen
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self.sequence = 0
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self.thread = None
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self.metrics = register_cache(name, self.cache)
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def check_thread(self):
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expected_thread = self.thread
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if expected_thread is None:
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self.thread = threading.current_thread()
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else:
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if expected_thread is not threading.current_thread():
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raise ValueError(
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"Cache objects can only be accessed from the main thread"
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)
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def get(self, key, default=_CacheSentinel, callback=None):
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"""Looks the key up in the caches.
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Args:
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key(tuple)
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default: What is returned if key is not in the caches. If not
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specified then function throws KeyError instead
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callback(fn): Gets called when the entry in the cache is invalidated
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Returns:
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Either a Deferred or the raw result
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"""
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callbacks = [callback] if callback else []
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val = self._pending_deferred_cache.get(key, _CacheSentinel)
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if val is not _CacheSentinel:
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if val.sequence == self.sequence:
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val.callbacks.update(callbacks)
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self.metrics.inc_hits()
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return val.deferred
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val = self.cache.get(key, _CacheSentinel, callbacks=callbacks)
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if val is not _CacheSentinel:
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self.metrics.inc_hits()
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return val
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self.metrics.inc_misses()
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if default is _CacheSentinel:
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raise KeyError()
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else:
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return default
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def set(self, key, value, callback=None):
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callbacks = [callback] if callback else []
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self.check_thread()
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entry = CacheEntry(
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deferred=value,
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sequence=self.sequence,
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callbacks=callbacks,
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)
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entry.callbacks.update(callbacks)
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existing_entry = self._pending_deferred_cache.pop(key, None)
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if existing_entry:
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existing_entry.invalidate()
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self._pending_deferred_cache[key] = entry
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def shuffle(result):
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if self.sequence == entry.sequence:
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existing_entry = self._pending_deferred_cache.pop(key, None)
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if existing_entry is entry:
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self.cache.set(key, result, entry.callbacks)
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else:
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entry.invalidate()
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else:
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entry.invalidate()
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return result
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entry.deferred.addCallback(shuffle)
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def prefill(self, key, value, callback=None):
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callbacks = [callback] if callback else []
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self.cache.set(key, value, callbacks=callbacks)
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def invalidate(self, key):
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self.check_thread()
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if not isinstance(key, tuple):
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raise TypeError(
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"The cache key must be a tuple not %r" % (type(key),)
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)
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# Increment the sequence number so that any SELECT statements that
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# raced with the INSERT don't update the cache (SYN-369)
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self.sequence += 1
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entry = self._pending_deferred_cache.pop(key, None)
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if entry:
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entry.invalidate()
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self.cache.pop(key, None)
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def invalidate_many(self, key):
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self.check_thread()
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if not isinstance(key, tuple):
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raise TypeError(
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"The cache key must be a tuple not %r" % (type(key),)
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)
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self.sequence += 1
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self.cache.del_multi(key)
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entry_dict = self._pending_deferred_cache.pop(key, None)
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if entry_dict is not None:
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for entry in iterate_tree_cache_entry(entry_dict):
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entry.invalidate()
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def invalidate_all(self):
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self.check_thread()
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self.sequence += 1
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self.cache.clear()
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class _CacheDescriptorBase(object):
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def __init__(self, orig, num_args, inlineCallbacks, cache_context=False):
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self.orig = orig
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if inlineCallbacks:
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self.function_to_call = defer.inlineCallbacks(orig)
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else:
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self.function_to_call = orig
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arg_spec = inspect.getargspec(orig)
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all_args = arg_spec.args
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if "cache_context" in all_args:
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if not cache_context:
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raise ValueError(
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"Cannot have a 'cache_context' arg without setting"
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" cache_context=True"
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)
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elif cache_context:
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raise ValueError(
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"Cannot have cache_context=True without having an arg"
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" named `cache_context`"
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)
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if num_args is None:
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num_args = len(all_args) - 1
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if cache_context:
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num_args -= 1
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if len(all_args) < num_args + 1:
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raise Exception(
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"Not enough explicit positional arguments to key off for %r: "
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"got %i args, but wanted %i. (@cached cannot key off *args or "
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"**kwargs)"
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% (orig.__name__, len(all_args), num_args)
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)
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self.num_args = num_args
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# list of the names of the args used as the cache key
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self.arg_names = all_args[1:num_args + 1]
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# self.arg_defaults is a map of arg name to its default value for each
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# argument that has a default value
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if arg_spec.defaults:
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self.arg_defaults = dict(zip(
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all_args[-len(arg_spec.defaults):],
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arg_spec.defaults
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))
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else:
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self.arg_defaults = {}
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if "cache_context" in self.arg_names:
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raise Exception(
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"cache_context arg cannot be included among the cache keys"
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)
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self.add_cache_context = cache_context
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class CacheDescriptor(_CacheDescriptorBase):
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""" A method decorator that applies a memoizing cache around the function.
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This caches deferreds, rather than the results themselves. Deferreds that
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fail are removed from the cache.
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The function is presumed to take zero or more arguments, which are used in
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a tuple as the key for the cache. Hits are served directly from the cache;
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misses use the function body to generate the value.
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The wrapped function has an additional member, a callable called
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"invalidate". This can be used to remove individual entries from the cache.
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The wrapped function has another additional callable, called "prefill",
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which can be used to insert values into the cache specifically, without
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calling the calculation function.
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Cached functions can be "chained" (i.e. a cached function can call other cached
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functions and get appropriately invalidated when they called caches are
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invalidated) by adding a special "cache_context" argument to the function
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and passing that as a kwarg to all caches called. For example::
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@cachedInlineCallbacks(cache_context=True)
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def foo(self, key, cache_context):
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r1 = yield self.bar1(key, on_invalidate=cache_context.invalidate)
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r2 = yield self.bar2(key, on_invalidate=cache_context.invalidate)
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defer.returnValue(r1 + r2)
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Args:
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num_args (int): number of positional arguments (excluding ``self`` and
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``cache_context``) to use as cache keys. Defaults to all named
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args of the function.
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"""
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def __init__(self, orig, max_entries=1000, num_args=None, tree=False,
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inlineCallbacks=False, cache_context=False, iterable=False):
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super(CacheDescriptor, self).__init__(
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orig, num_args=num_args, inlineCallbacks=inlineCallbacks,
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cache_context=cache_context)
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max_entries = int(max_entries * CACHE_SIZE_FACTOR)
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self.max_entries = max_entries
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self.tree = tree
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self.iterable = iterable
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def __get__(self, obj, objtype=None):
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cache = Cache(
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name=self.orig.__name__,
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max_entries=self.max_entries,
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keylen=self.num_args,
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tree=self.tree,
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iterable=self.iterable,
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)
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def get_cache_key(args, kwargs):
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"""Given some args/kwargs return a generator that resolves into
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the cache_key.
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We loop through each arg name, looking up if its in the `kwargs`,
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otherwise using the next argument in `args`. If there are no more
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args then we try looking the arg name up in the defaults
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"""
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pos = 0
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for nm in self.arg_names:
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if nm in kwargs:
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yield kwargs[nm]
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elif pos < len(args):
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yield args[pos]
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pos += 1
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else:
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yield self.arg_defaults[nm]
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@functools.wraps(self.orig)
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def wrapped(*args, **kwargs):
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# If we're passed a cache_context then we'll want to call its invalidate()
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# whenever we are invalidated
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invalidate_callback = kwargs.pop("on_invalidate", None)
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cache_key = tuple(get_cache_key(args, kwargs))
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# Add our own `cache_context` to argument list if the wrapped function
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# has asked for one
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if self.add_cache_context:
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kwargs["cache_context"] = _CacheContext(cache, cache_key)
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try:
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cached_result_d = cache.get(cache_key, callback=invalidate_callback)
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if isinstance(cached_result_d, ObservableDeferred):
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observer = cached_result_d.observe()
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else:
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observer = cached_result_d
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except KeyError:
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ret = defer.maybeDeferred(
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logcontext.preserve_fn(self.function_to_call),
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obj, *args, **kwargs
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)
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def onErr(f):
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cache.invalidate(cache_key)
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return f
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ret.addErrback(onErr)
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result_d = ObservableDeferred(ret, consumeErrors=True)
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cache.set(cache_key, result_d, callback=invalidate_callback)
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observer = result_d.observe()
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if isinstance(observer, defer.Deferred):
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return logcontext.make_deferred_yieldable(observer)
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else:
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return observer
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wrapped.invalidate = cache.invalidate
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wrapped.invalidate_all = cache.invalidate_all
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wrapped.invalidate_many = cache.invalidate_many
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wrapped.prefill = cache.prefill
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wrapped.cache = cache
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obj.__dict__[self.orig.__name__] = wrapped
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return wrapped
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class CacheListDescriptor(_CacheDescriptorBase):
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"""Wraps an existing cache to support bulk fetching of keys.
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Given a list of keys it looks in the cache to find any hits, then passes
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the list of missing keys to the wrapped function.
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Once wrapped, the function returns either a Deferred which resolves to
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the list of results, or (if all results were cached), just the list of
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results.
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"""
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def __init__(self, orig, cached_method_name, list_name, num_args=None,
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inlineCallbacks=False):
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"""
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Args:
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orig (function)
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cached_method_name (str): The name of the chached method.
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list_name (str): Name of the argument which is the bulk lookup list
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num_args (int): number of positional arguments (excluding ``self``,
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but including list_name) to use as cache keys. Defaults to all
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named args of the function.
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inlineCallbacks (bool): Whether orig is a generator that should
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be wrapped by defer.inlineCallbacks
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"""
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super(CacheListDescriptor, self).__init__(
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orig, num_args=num_args, inlineCallbacks=inlineCallbacks)
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self.list_name = list_name
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self.list_pos = self.arg_names.index(self.list_name)
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self.cached_method_name = cached_method_name
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self.sentinel = object()
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if self.list_name not in self.arg_names:
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raise Exception(
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"Couldn't see arguments %r for %r."
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% (self.list_name, cached_method_name,)
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)
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def __get__(self, obj, objtype=None):
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cache = getattr(obj, self.cached_method_name).cache
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@functools.wraps(self.orig)
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def wrapped(*args, **kwargs):
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# If we're passed a cache_context then we'll want to call its invalidate()
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# whenever we are invalidated
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invalidate_callback = kwargs.pop("on_invalidate", None)
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arg_dict = inspect.getcallargs(self.orig, obj, *args, **kwargs)
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keyargs = [arg_dict[arg_nm] for arg_nm in self.arg_names]
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list_args = arg_dict[self.list_name]
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# cached is a dict arg -> deferred, where deferred results in a
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# 2-tuple (`arg`, `result`)
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results = {}
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cached_defers = {}
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missing = []
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for arg in list_args:
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key = list(keyargs)
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key[self.list_pos] = arg
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try:
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res = cache.get(tuple(key), callback=invalidate_callback)
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if not isinstance(res, ObservableDeferred):
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results[arg] = res
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elif not res.has_succeeded():
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res = res.observe()
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res.addCallback(lambda r, arg: (arg, r), arg)
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cached_defers[arg] = res
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else:
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results[arg] = res.get_result()
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except KeyError:
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missing.append(arg)
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if missing:
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args_to_call = dict(arg_dict)
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args_to_call[self.list_name] = missing
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ret_d = defer.maybeDeferred(
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logcontext.preserve_fn(self.function_to_call),
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**args_to_call
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)
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ret_d = ObservableDeferred(ret_d)
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# We need to create deferreds for each arg in the list so that
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# we can insert the new deferred into the cache.
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for arg in missing:
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observer = ret_d.observe()
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observer.addCallback(lambda r, arg: r.get(arg, None), arg)
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observer = ObservableDeferred(observer)
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key = list(keyargs)
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key[self.list_pos] = arg
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cache.set(
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tuple(key), observer,
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callback=invalidate_callback
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)
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def invalidate(f, key):
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cache.invalidate(key)
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return f
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observer.addErrback(invalidate, tuple(key))
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res = observer.observe()
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res.addCallback(lambda r, arg: (arg, r), arg)
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cached_defers[arg] = res
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if cached_defers:
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def update_results_dict(res):
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results.update(res)
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return results
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return logcontext.make_deferred_yieldable(defer.gatherResults(
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cached_defers.values(),
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consumeErrors=True,
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).addCallback(update_results_dict).addErrback(
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unwrapFirstError
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))
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else:
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return results
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obj.__dict__[self.orig.__name__] = wrapped
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return wrapped
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class _CacheContext(namedtuple("_CacheContext", ("cache", "key"))):
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# We rely on _CacheContext implementing __eq__ and __hash__ sensibly,
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# which namedtuple does for us (i.e. two _CacheContext are the same if
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# their caches and keys match). This is important in particular to
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# dedupe when we add callbacks to lru cache nodes, otherwise the number
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# of callbacks would grow.
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def invalidate(self):
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self.cache.invalidate(self.key)
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def cached(max_entries=1000, num_args=None, tree=False, cache_context=False,
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iterable=False):
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return lambda orig: CacheDescriptor(
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orig,
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max_entries=max_entries,
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num_args=num_args,
|
|
tree=tree,
|
|
cache_context=cache_context,
|
|
iterable=iterable,
|
|
)
|
|
|
|
|
|
def cachedInlineCallbacks(max_entries=1000, num_args=None, tree=False,
|
|
cache_context=False, iterable=False):
|
|
return lambda orig: CacheDescriptor(
|
|
orig,
|
|
max_entries=max_entries,
|
|
num_args=num_args,
|
|
tree=tree,
|
|
inlineCallbacks=True,
|
|
cache_context=cache_context,
|
|
iterable=iterable,
|
|
)
|
|
|
|
|
|
def cachedList(cached_method_name, list_name, num_args=None, inlineCallbacks=False):
|
|
"""Creates a descriptor that wraps a function in a `CacheListDescriptor`.
|
|
|
|
Used to do batch lookups for an already created cache. A single argument
|
|
is specified as a list that is iterated through to lookup keys in the
|
|
original cache. A new list consisting of the keys that weren't in the cache
|
|
get passed to the original function, the result of which is stored in the
|
|
cache.
|
|
|
|
Args:
|
|
cache (Cache): The underlying cache to use.
|
|
list_name (str): The name of the argument that is the list to use to
|
|
do batch lookups in the cache.
|
|
num_args (int): Number of arguments to use as the key in the cache
|
|
(including list_name). Defaults to all named parameters.
|
|
inlineCallbacks (bool): Should the function be wrapped in an
|
|
`defer.inlineCallbacks`?
|
|
|
|
Example:
|
|
|
|
class Example(object):
|
|
@cached(num_args=2)
|
|
def do_something(self, first_arg):
|
|
...
|
|
|
|
@cachedList(do_something.cache, list_name="second_args", num_args=2)
|
|
def batch_do_something(self, first_arg, second_args):
|
|
...
|
|
"""
|
|
return lambda orig: CacheListDescriptor(
|
|
orig,
|
|
cached_method_name=cached_method_name,
|
|
list_name=list_name,
|
|
num_args=num_args,
|
|
inlineCallbacks=inlineCallbacks,
|
|
)
|