Remove unused `@lru_cache` decorator (#13595)

* Remove unused `@lru_cache` decorator

Spotted this working on something else.

Co-authored-by: David Robertson <davidr@element.io>
pull/14291/head
Nick Mills-Barrett 2022-10-25 11:39:25 +01:00 committed by GitHub
parent d125919963
commit c9dffd5b33
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GPG Key ID: 4AEE18F83AFDEB23
3 changed files with 5 additions and 140 deletions

1
changelog.d/13595.misc Normal file
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@ -0,0 +1 @@
Remove unused `@lru_cache` decorator.

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@ -12,7 +12,6 @@
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import enum
import functools
import inspect
import logging
@ -146,109 +145,6 @@ class _CacheDescriptorBase:
)
class _LruCachedFunction(Generic[F]):
cache: LruCache[CacheKey, Any]
__call__: F
def lru_cache(
*, max_entries: int = 1000, cache_context: bool = False
) -> Callable[[F], _LruCachedFunction[F]]:
"""A method decorator that applies a memoizing cache around the function.
This is more-or-less a drop-in equivalent to functools.lru_cache, although note
that the signature is slightly different.
The main differences with functools.lru_cache are:
(a) the size of the cache can be controlled via the cache_factor mechanism
(b) the wrapped function can request a "cache_context" which provides a
callback mechanism to indicate that the result is no longer valid
(c) prometheus metrics are exposed automatically.
The function should take zero or more arguments, which are used as the key for the
cache. Single-argument functions use that argument as the cache key; otherwise the
arguments are built into a tuple.
Cached functions can be "chained" (i.e. a cached function can call other cached
functions and get appropriately invalidated when they called caches are
invalidated) by adding a special "cache_context" argument to the function
and passing that as a kwarg to all caches called. For example:
@lru_cache(cache_context=True)
def foo(self, key, cache_context):
r1 = self.bar1(key, on_invalidate=cache_context.invalidate)
r2 = self.bar2(key, on_invalidate=cache_context.invalidate)
return r1 + r2
The wrapped function also has a 'cache' property which offers direct access to the
underlying LruCache.
"""
def func(orig: F) -> _LruCachedFunction[F]:
desc = LruCacheDescriptor(
orig,
max_entries=max_entries,
cache_context=cache_context,
)
return cast(_LruCachedFunction[F], desc)
return func
class LruCacheDescriptor(_CacheDescriptorBase):
"""Helper for @lru_cache"""
class _Sentinel(enum.Enum):
sentinel = object()
def __init__(
self,
orig: Callable[..., Any],
max_entries: int = 1000,
cache_context: bool = False,
):
super().__init__(
orig, num_args=None, uncached_args=None, cache_context=cache_context
)
self.max_entries = max_entries
def __get__(self, obj: Optional[Any], owner: Optional[Type]) -> Callable[..., Any]:
cache: LruCache[CacheKey, Any] = LruCache(
cache_name=self.name,
max_size=self.max_entries,
)
get_cache_key = self.cache_key_builder
sentinel = LruCacheDescriptor._Sentinel.sentinel
@functools.wraps(self.orig)
def _wrapped(*args: Any, **kwargs: Any) -> Any:
invalidate_callback = kwargs.pop("on_invalidate", None)
callbacks = (invalidate_callback,) if invalidate_callback else ()
cache_key = get_cache_key(args, kwargs)
ret = cache.get(cache_key, default=sentinel, callbacks=callbacks)
if ret != sentinel:
return ret
# Add our own `cache_context` to argument list if the wrapped function
# has asked for one
if self.add_cache_context:
kwargs["cache_context"] = _CacheContext.get_instance(cache, cache_key)
ret2 = self.orig(obj, *args, **kwargs)
cache.set(cache_key, ret2, callbacks=callbacks)
return ret2
wrapped = cast(CachedFunction, _wrapped)
wrapped.cache = cache
obj.__dict__[self.name] = wrapped
return wrapped
class DeferredCacheDescriptor(_CacheDescriptorBase):
"""A method decorator that applies a memoizing cache around the function.

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@ -28,7 +28,7 @@ from synapse.logging.context import (
make_deferred_yieldable,
)
from synapse.util.caches import descriptors
from synapse.util.caches.descriptors import cached, cachedList, lru_cache
from synapse.util.caches.descriptors import cached, cachedList
from tests import unittest
from tests.test_utils import get_awaitable_result
@ -36,38 +36,6 @@ from tests.test_utils import get_awaitable_result
logger = logging.getLogger(__name__)
class LruCacheDecoratorTestCase(unittest.TestCase):
def test_base(self):
class Cls:
def __init__(self):
self.mock = mock.Mock()
@lru_cache()
def fn(self, arg1, arg2):
return self.mock(arg1, arg2)
obj = Cls()
obj.mock.return_value = "fish"
r = obj.fn(1, 2)
self.assertEqual(r, "fish")
obj.mock.assert_called_once_with(1, 2)
obj.mock.reset_mock()
# a call with different params should call the mock again
obj.mock.return_value = "chips"
r = obj.fn(1, 3)
self.assertEqual(r, "chips")
obj.mock.assert_called_once_with(1, 3)
obj.mock.reset_mock()
# the two values should now be cached
r = obj.fn(1, 2)
self.assertEqual(r, "fish")
r = obj.fn(1, 3)
self.assertEqual(r, "chips")
obj.mock.assert_not_called()
def run_on_reactor():
d = defer.Deferred()
reactor.callLater(0, d.callback, 0)
@ -478,10 +446,10 @@ class DescriptorTestCase(unittest.TestCase):
@cached(cache_context=True)
async def func2(self, key, cache_context):
return self.func3(key, on_invalidate=cache_context.invalidate)
return await self.func3(key, on_invalidate=cache_context.invalidate)
@lru_cache(cache_context=True)
def func3(self, key, cache_context):
@cached(cache_context=True)
async def func3(self, key, cache_context):
self.invalidate = cache_context.invalidate
return 42