612 lines
		
	
	
		
			21 KiB
		
	
	
	
		
			Python
		
	
	
			
		
		
	
	
			612 lines
		
	
	
		
			21 KiB
		
	
	
	
		
			Python
		
	
	
# -*- coding: utf-8 -*-
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# Copyright 2015, 2016 OpenMarket Ltd
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# Copyright 2018 New Vector 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 enum
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import functools
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import inspect
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import logging
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from typing import (
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    Any,
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    Callable,
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    Generic,
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    Iterable,
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    Mapping,
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    Optional,
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    Sequence,
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    Tuple,
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    TypeVar,
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    Union,
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    cast,
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)
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from weakref import WeakValueDictionary
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from twisted.internet import defer
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from synapse.logging.context import make_deferred_yieldable, preserve_fn
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from synapse.util import unwrapFirstError
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from synapse.util.caches.deferred_cache import DeferredCache
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from synapse.util.caches.lrucache import LruCache
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logger = logging.getLogger(__name__)
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CacheKey = Union[Tuple, Any]
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F = TypeVar("F", bound=Callable[..., Any])
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class _CachedFunction(Generic[F]):
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    invalidate = None  # type: Any
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    invalidate_all = None  # type: Any
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    invalidate_many = None  # type: Any
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    prefill = None  # type: Any
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    cache = None  # type: Any
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    num_args = None  # type: Any
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    __name__ = None  # type: str
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    # Note: This function signature is actually fiddled with by the synapse mypy
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    # plugin to a) make it a bound method, and b) remove any `cache_context` arg.
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    __call__ = None  # type: F
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class _CacheDescriptorBase:
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    def __init__(self, orig: Callable[..., Any], num_args, cache_context=False):
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        self.orig = orig
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        arg_spec = inspect.getfullargspec(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)" % (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(
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                zip(all_args[-len(arg_spec.defaults) :], 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("cache_context arg cannot be included among the cache keys")
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        self.add_cache_context = cache_context
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        self.cache_key_builder = get_cache_key_builder(
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            self.arg_names, self.arg_defaults
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        )
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class _LruCachedFunction(Generic[F]):
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    cache = None  # type: LruCache[CacheKey, Any]
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    __call__ = None  # type: F
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def lru_cache(
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    max_entries: int = 1000, cache_context: bool = False,
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) -> Callable[[F], _LruCachedFunction[F]]:
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    """A method decorator that applies a memoizing cache around the function.
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    This is more-or-less a drop-in equivalent to functools.lru_cache, although note
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    that the signature is slightly different.
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    The main differences with functools.lru_cache are:
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        (a) the size of the cache can be controlled via the cache_factor mechanism
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        (b) the wrapped function can request a "cache_context" which provides a
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            callback mechanism to indicate that the result is no longer valid
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        (c) prometheus metrics are exposed automatically.
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    The function should take zero or more arguments, which are used as the key for the
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    cache. Single-argument functions use that argument as the cache key; otherwise the
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    arguments are built into a tuple.
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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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        @lru_cache(cache_context=True)
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        def foo(self, key, cache_context):
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            r1 = self.bar1(key, on_invalidate=cache_context.invalidate)
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            r2 = self.bar2(key, on_invalidate=cache_context.invalidate)
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            return r1 + r2
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    The wrapped function also has a 'cache' property which offers direct access to the
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    underlying LruCache.
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    """
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    def func(orig: F) -> _LruCachedFunction[F]:
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        desc = LruCacheDescriptor(
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            orig, max_entries=max_entries, cache_context=cache_context,
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        )
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        return cast(_LruCachedFunction[F], desc)
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    return func
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class LruCacheDescriptor(_CacheDescriptorBase):
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    """Helper for @lru_cache"""
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    class _Sentinel(enum.Enum):
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        sentinel = object()
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    def __init__(
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        self, orig, max_entries: int = 1000, cache_context: bool = False,
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    ):
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        super().__init__(orig, num_args=None, cache_context=cache_context)
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        self.max_entries = max_entries
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    def __get__(self, obj, owner):
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        cache = LruCache(
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            cache_name=self.orig.__name__, max_size=self.max_entries,
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        )  # type: LruCache[CacheKey, Any]
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        get_cache_key = self.cache_key_builder
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        sentinel = LruCacheDescriptor._Sentinel.sentinel
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        @functools.wraps(self.orig)
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        def _wrapped(*args, **kwargs):
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            invalidate_callback = kwargs.pop("on_invalidate", None)
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            callbacks = (invalidate_callback,) if invalidate_callback else ()
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            cache_key = get_cache_key(args, kwargs)
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            ret = cache.get(cache_key, default=sentinel, callbacks=callbacks)
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            if ret != sentinel:
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                return ret
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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.get_instance(cache, cache_key)
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            ret2 = self.orig(obj, *args, **kwargs)
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            cache.set(cache_key, ret2, callbacks=callbacks)
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            return ret2
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        wrapped = cast(_CachedFunction, _wrapped)
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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 DeferredCacheDescriptor(_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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        @cached(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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            return 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__(
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        self,
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        orig,
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        max_entries=1000,
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        num_args=None,
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        tree=False,
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        cache_context=False,
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        iterable=False,
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    ):
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        super().__init__(orig, num_args=num_args, cache_context=cache_context)
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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, owner):
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        cache = DeferredCache(
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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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        )  # type: DeferredCache[CacheKey, Any]
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        get_cache_key = self.cache_key_builder
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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 = get_cache_key(args, kwargs)
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            try:
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                ret = cache.get(cache_key, callback=invalidate_callback)
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            except KeyError:
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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.get_instance(
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                        cache, cache_key
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                    )
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                ret = defer.maybeDeferred(preserve_fn(self.orig), obj, *args, **kwargs)
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                ret = cache.set(cache_key, ret, callback=invalidate_callback)
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            return make_deferred_yieldable(ret)
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        wrapped = cast(_CachedFunction, _wrapped)
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        if self.num_args == 1:
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            wrapped.invalidate = lambda key: cache.invalidate(key[0])
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            wrapped.prefill = lambda key, val: cache.prefill(key[0], val)
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        else:
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            wrapped.invalidate = cache.invalidate
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            wrapped.invalidate_many = cache.invalidate_many
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            wrapped.prefill = cache.prefill
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        wrapped.invalidate_all = cache.invalidate_all
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        wrapped.cache = cache
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        wrapped.num_args = self.num_args
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        obj.__dict__[self.orig.__name__] = wrapped
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        return wrapped
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class DeferredCacheListDescriptor(_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 a Deferred which resolves to the list
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    of 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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        """
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        Args:
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            orig (function)
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            cached_method_name (str): The name of the cached 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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        """
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        super().__init__(orig, num_args=num_args)
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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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        cached_method = getattr(obj, self.cached_method_name)
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        cache = cached_method.cache  # type: DeferredCache[CacheKey, Any]
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        num_args = cached_method.num_args
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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
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            # invalidate() 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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            results = {}
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            def update_results_dict(res, arg):
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                results[arg] = res
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            # list of deferreds to wait for
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            cached_defers = []
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            missing = set()
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            # If the cache takes a single arg then that is used as the key,
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            # otherwise a tuple is used.
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            if num_args == 1:
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                def arg_to_cache_key(arg):
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                    return arg
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            else:
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                keylist = list(keyargs)
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                def arg_to_cache_key(arg):
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                    keylist[self.list_pos] = arg
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                    return tuple(keylist)
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            for arg in list_args:
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                try:
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                    res = cache.get(arg_to_cache_key(arg), callback=invalidate_callback)
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                    if not res.called:
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                        res.addCallback(update_results_dict, arg)
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                        cached_defers.append(res)
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                    else:
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                        results[arg] = res.result
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                except KeyError:
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                    missing.add(arg)
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            if missing:
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                # we need a deferred for each entry in the list,
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                # which we put in the cache. Each deferred resolves with the
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                # relevant result for that key.
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                deferreds_map = {}
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                for arg in missing:
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                    deferred = defer.Deferred()
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                    deferreds_map[arg] = deferred
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                    key = arg_to_cache_key(arg)
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                    cache.set(key, deferred, callback=invalidate_callback)
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                def complete_all(res):
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                    # the wrapped function has completed. It returns a
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                    # a dict. We can now resolve the observable deferreds in
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                    # the cache and update our own result map.
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                    for e in missing:
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                        val = res.get(e, None)
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                        deferreds_map[e].callback(val)
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                        results[e] = val
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                def errback(f):
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                    # the wrapped function has failed. Invalidate any cache
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                    # entries we're supposed to be populating, and fail
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                    # their deferreds.
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                    for e in missing:
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                        key = arg_to_cache_key(e)
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                        cache.invalidate(key)
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                        deferreds_map[e].errback(f)
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                    # return the failure, to propagate to our caller.
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                    return f
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                args_to_call = dict(arg_dict)
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                args_to_call[self.list_name] = list(missing)
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                cached_defers.append(
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                    defer.maybeDeferred(
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                        preserve_fn(self.orig), **args_to_call
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                    ).addCallbacks(complete_all, errback)
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                )
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            if cached_defers:
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                d = defer.gatherResults(cached_defers, consumeErrors=True).addCallbacks(
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                    lambda _: results, unwrapFirstError
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                )
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                return make_deferred_yieldable(d)
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            else:
 | 
						|
                return defer.succeed(results)
 | 
						|
 | 
						|
        obj.__dict__[self.orig.__name__] = wrapped
 | 
						|
 | 
						|
        return wrapped
 | 
						|
 | 
						|
 | 
						|
class _CacheContext:
 | 
						|
    """Holds cache information from the cached function higher in the calling order.
 | 
						|
 | 
						|
    Can be used to invalidate the higher level cache entry if something changes
 | 
						|
    on a lower level.
 | 
						|
    """
 | 
						|
 | 
						|
    Cache = Union[DeferredCache, LruCache]
 | 
						|
 | 
						|
    _cache_context_objects = (
 | 
						|
        WeakValueDictionary()
 | 
						|
    )  # type: WeakValueDictionary[Tuple[_CacheContext.Cache, CacheKey], _CacheContext]
 | 
						|
 | 
						|
    def __init__(self, cache: "_CacheContext.Cache", cache_key: CacheKey) -> None:
 | 
						|
        self._cache = cache
 | 
						|
        self._cache_key = cache_key
 | 
						|
 | 
						|
    def invalidate(self):  # type: () -> None
 | 
						|
        """Invalidates the cache entry referred to by the context."""
 | 
						|
        self._cache.invalidate(self._cache_key)
 | 
						|
 | 
						|
    @classmethod
 | 
						|
    def get_instance(
 | 
						|
        cls, cache: "_CacheContext.Cache", cache_key: CacheKey
 | 
						|
    ) -> "_CacheContext":
 | 
						|
        """Returns an instance constructed with the given arguments.
 | 
						|
 | 
						|
        A new instance is only created if none already exists.
 | 
						|
        """
 | 
						|
 | 
						|
        # We make sure there are no identical _CacheContext instances. This is
 | 
						|
        # important in particular to dedupe when we add callbacks to lru cache
 | 
						|
        # nodes, otherwise the number of callbacks would grow.
 | 
						|
        return cls._cache_context_objects.setdefault(
 | 
						|
            (cache, cache_key), cls(cache, cache_key)
 | 
						|
        )
 | 
						|
 | 
						|
 | 
						|
def cached(
 | 
						|
    max_entries: int = 1000,
 | 
						|
    num_args: Optional[int] = None,
 | 
						|
    tree: bool = False,
 | 
						|
    cache_context: bool = False,
 | 
						|
    iterable: bool = False,
 | 
						|
) -> Callable[[F], _CachedFunction[F]]:
 | 
						|
    func = lambda orig: DeferredCacheDescriptor(
 | 
						|
        orig,
 | 
						|
        max_entries=max_entries,
 | 
						|
        num_args=num_args,
 | 
						|
        tree=tree,
 | 
						|
        cache_context=cache_context,
 | 
						|
        iterable=iterable,
 | 
						|
    )
 | 
						|
 | 
						|
    return cast(Callable[[F], _CachedFunction[F]], func)
 | 
						|
 | 
						|
 | 
						|
def cachedList(
 | 
						|
    cached_method_name: str, list_name: str, num_args: Optional[int] = None
 | 
						|
) -> Callable[[F], _CachedFunction[F]]:
 | 
						|
    """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:
 | 
						|
        cached_method_name: The name of the single-item lookup method.
 | 
						|
            This is only used to find the cache to use.
 | 
						|
        list_name: The name of the argument that is the list to use to
 | 
						|
            do batch lookups in the cache.
 | 
						|
        num_args: Number of arguments to use as the key in the cache
 | 
						|
            (including list_name). Defaults to all named parameters.
 | 
						|
 | 
						|
    Example:
 | 
						|
 | 
						|
        class Example:
 | 
						|
            @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):
 | 
						|
                ...
 | 
						|
    """
 | 
						|
    func = lambda orig: DeferredCacheListDescriptor(
 | 
						|
        orig,
 | 
						|
        cached_method_name=cached_method_name,
 | 
						|
        list_name=list_name,
 | 
						|
        num_args=num_args,
 | 
						|
    )
 | 
						|
 | 
						|
    return cast(Callable[[F], _CachedFunction[F]], func)
 | 
						|
 | 
						|
 | 
						|
def get_cache_key_builder(
 | 
						|
    param_names: Sequence[str], param_defaults: Mapping[str, Any]
 | 
						|
) -> Callable[[Sequence[Any], Mapping[str, Any]], CacheKey]:
 | 
						|
    """Construct a function which will build cache keys suitable for a cached function
 | 
						|
 | 
						|
    Args:
 | 
						|
        param_names: list of formal parameter names for the cached function
 | 
						|
        param_defaults: a mapping from parameter name to default value for that param
 | 
						|
 | 
						|
    Returns:
 | 
						|
        A function which will take an (args, kwargs) pair and return a cache key
 | 
						|
    """
 | 
						|
 | 
						|
    # By default our cache key is a tuple, but if there is only one item
 | 
						|
    # then don't bother wrapping in a tuple.  This is to save memory.
 | 
						|
 | 
						|
    if len(param_names) == 1:
 | 
						|
        nm = param_names[0]
 | 
						|
 | 
						|
        def get_cache_key(args: Sequence[Any], kwargs: Mapping[str, Any]) -> CacheKey:
 | 
						|
            if nm in kwargs:
 | 
						|
                return kwargs[nm]
 | 
						|
            elif len(args):
 | 
						|
                return args[0]
 | 
						|
            else:
 | 
						|
                return param_defaults[nm]
 | 
						|
 | 
						|
    else:
 | 
						|
 | 
						|
        def get_cache_key(args: Sequence[Any], kwargs: Mapping[str, Any]) -> CacheKey:
 | 
						|
            return tuple(_get_cache_key_gen(param_names, param_defaults, args, kwargs))
 | 
						|
 | 
						|
    return get_cache_key
 | 
						|
 | 
						|
 | 
						|
def _get_cache_key_gen(
 | 
						|
    param_names: Iterable[str],
 | 
						|
    param_defaults: Mapping[str, Any],
 | 
						|
    args: Sequence[Any],
 | 
						|
    kwargs: Mapping[str, Any],
 | 
						|
) -> Iterable[Any]:
 | 
						|
    """Given some args/kwargs return a generator that resolves into
 | 
						|
    the cache_key.
 | 
						|
 | 
						|
    This is essentially the same operation as `inspect.getcallargs`, but optimised so
 | 
						|
    that we don't need to inspect the target function for each call.
 | 
						|
    """
 | 
						|
 | 
						|
    # We loop through each arg name, looking up if its in the `kwargs`,
 | 
						|
    # otherwise using the next argument in `args`. If there are no more
 | 
						|
    # args then we try looking the arg name up in the defaults.
 | 
						|
    pos = 0
 | 
						|
    for nm in param_names:
 | 
						|
        if nm in kwargs:
 | 
						|
            yield kwargs[nm]
 | 
						|
        elif pos < len(args):
 | 
						|
            yield args[pos]
 | 
						|
            pos += 1
 | 
						|
        else:
 | 
						|
            yield param_defaults[nm]
 |