""" 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