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"""
A LRU (Least Recently Used) Cache container.
Use when you want to cache slow operations and new keys are a good predictor
of subsequent keys.
Note that stdlib's @lru_cache is implemented in C and faster! It's best to use
@lru_cache where you are caching things that are fairly quick and called many times.
Use LRUCache where you want increased flexibility and you are caching slow operations
where the overhead of the cache is a small fraction of the total processing time.
"""
from __future__ import annotations
from threading import Lock
from typing import Dict, Generic, KeysView, TypeVar, overload
CacheKey = TypeVar("CacheKey")
CacheValue = TypeVar("CacheValue")
DefaultValue = TypeVar("DefaultValue")
class LRUCache(Generic[CacheKey, CacheValue]):
"""
A dictionary-like container with a maximum size.
If an additional item is added when the LRUCache is full, the least
recently used key is discarded to make room for the new item.
The implementation is similar to functools.lru_cache, which uses a (doubly)
linked list to keep track of the most recently used items.
Each entry is stored as [PREV, NEXT, KEY, VALUE] where PREV is a reference
to the previous entry, and NEXT is a reference to the next value.
"""
def __init__(self, maxsize: int) -> None:
self._maxsize = maxsize
self._cache: Dict[CacheKey, list[object]] = {}
self._full = False
self._head: list[object] = []
self._lock = Lock()
super().__init__()
@property
def maxsize(self) -> int:
return self._maxsize
@maxsize.setter
def maxsize(self, maxsize: int) -> None:
self._maxsize = maxsize
def __bool__(self) -> bool:
return bool(self._cache)
def __len__(self) -> int:
return len(self._cache)
def clear(self) -> None:
"""Clear the cache."""
with self._lock:
self._cache.clear()
self._full = False
self._head = []
def keys(self) -> KeysView[CacheKey]:
"""Get cache keys."""
# Mostly for tests
return self._cache.keys()
def set(self, key: CacheKey, value: CacheValue) -> None:
"""Set a value.
Args:
key (CacheKey): Key.
value (CacheValue): Value.
"""
with self._lock:
link = self._cache.get(key)
if link is None:
head = self._head
if not head:
# First link references itself
self._head[:] = [head, head, key, value]
else:
# Add a new root to the beginning
self._head = [head[0], head, key, value]
# Updated references on previous root
head[0][1] = self._head # type: ignore[index]
head[0] = self._head
self._cache[key] = self._head
if self._full or len(self._cache) > self._maxsize:
# Cache is full, we need to evict the oldest one
self._full = True
head = self._head
last = head[0]
last[0][1] = head # type: ignore[index]
head[0] = last[0] # type: ignore[index]
del self._cache[last[2]] # type: ignore[index]
__setitem__ = set
@overload
def get(self, key: CacheKey) -> CacheValue | None:
...
@overload
def get(self, key: CacheKey, default: DefaultValue) -> CacheValue | DefaultValue:
...
def get(
self, key: CacheKey, default: DefaultValue | None = None
) -> CacheValue | DefaultValue | None:
"""Get a value from the cache, or return a default if the key is not present.
Args:
key (CacheKey): Key
default (Optional[DefaultValue], optional): Default to return if key is not present. Defaults to None.
Returns:
Union[CacheValue, Optional[DefaultValue]]: Either the value or a default.
"""
link = self._cache.get(key)
if link is None:
return default
with self._lock:
if link is not self._head:
# Remove link from list
link[0][1] = link[1] # type: ignore[index]
link[1][0] = link[0] # type: ignore[index]
head = self._head
# Move link to head of list
link[0] = head[0]
link[1] = head
self._head = head[0][1] = head[0] = link # type: ignore[index]
return link[3] # type: ignore[return-value]
def __getitem__(self, key: CacheKey) -> CacheValue:
link = self._cache[key]
with self._lock:
if link is not self._head:
link[0][1] = link[1] # type: ignore[index]
link[1][0] = link[0] # type: ignore[index]
head = self._head
link[0] = head[0]
link[1] = head
self._head = head[0][1] = head[0] = link # type: ignore[index]
return link[3] # type: ignore[return-value]
def __contains__(self, key: CacheKey) -> bool:
return key in self._cache