| | from __future__ import annotations |
| |
|
| | from collections import deque |
| | from functools import wraps |
| | from typing import Any, Callable, Dict, Generic, Hashable, Tuple, TypeVar, cast |
| |
|
| | __all__ = [ |
| | "SimpleCache", |
| | "FastDictCache", |
| | "memoized", |
| | ] |
| |
|
| | _T = TypeVar("_T", bound=Hashable) |
| | _U = TypeVar("_U") |
| |
|
| |
|
| | class SimpleCache(Generic[_T, _U]): |
| | """ |
| | Very simple cache that discards the oldest item when the cache size is |
| | exceeded. |
| | |
| | :param maxsize: Maximum size of the cache. (Don't make it too big.) |
| | """ |
| |
|
| | def __init__(self, maxsize: int = 8) -> None: |
| | assert maxsize > 0 |
| |
|
| | self._data: dict[_T, _U] = {} |
| | self._keys: deque[_T] = deque() |
| | self.maxsize: int = maxsize |
| |
|
| | def get(self, key: _T, getter_func: Callable[[], _U]) -> _U: |
| | """ |
| | Get object from the cache. |
| | If not found, call `getter_func` to resolve it, and put that on the top |
| | of the cache instead. |
| | """ |
| | |
| | try: |
| | return self._data[key] |
| | except KeyError: |
| | |
| | value = getter_func() |
| | self._data[key] = value |
| | self._keys.append(key) |
| |
|
| | |
| | if len(self._data) > self.maxsize: |
| | key_to_remove = self._keys.popleft() |
| | if key_to_remove in self._data: |
| | del self._data[key_to_remove] |
| |
|
| | return value |
| |
|
| | def clear(self) -> None: |
| | "Clear cache." |
| | self._data = {} |
| | self._keys = deque() |
| |
|
| |
|
| | _K = TypeVar("_K", bound=Tuple[Hashable, ...]) |
| | _V = TypeVar("_V") |
| |
|
| |
|
| | class FastDictCache(Dict[_K, _V]): |
| | """ |
| | Fast, lightweight cache which keeps at most `size` items. |
| | It will discard the oldest items in the cache first. |
| | |
| | The cache is a dictionary, which doesn't keep track of access counts. |
| | It is perfect to cache little immutable objects which are not expensive to |
| | create, but where a dictionary lookup is still much faster than an object |
| | instantiation. |
| | |
| | :param get_value: Callable that's called in case of a missing key. |
| | """ |
| |
|
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | def __init__(self, get_value: Callable[..., _V], size: int = 1000000) -> None: |
| | assert size > 0 |
| |
|
| | self._keys: deque[_K] = deque() |
| | self.get_value = get_value |
| | self.size = size |
| |
|
| | def __missing__(self, key: _K) -> _V: |
| | |
| | if len(self) > self.size: |
| | key_to_remove = self._keys.popleft() |
| | if key_to_remove in self: |
| | del self[key_to_remove] |
| |
|
| | result = self.get_value(*key) |
| | self[key] = result |
| | self._keys.append(key) |
| | return result |
| |
|
| |
|
| | _F = TypeVar("_F", bound=Callable[..., object]) |
| |
|
| |
|
| | def memoized(maxsize: int = 1024) -> Callable[[_F], _F]: |
| | """ |
| | Memoization decorator for immutable classes and pure functions. |
| | """ |
| |
|
| | def decorator(obj: _F) -> _F: |
| | cache: SimpleCache[Hashable, Any] = SimpleCache(maxsize=maxsize) |
| |
|
| | @wraps(obj) |
| | def new_callable(*a: Any, **kw: Any) -> Any: |
| | def create_new() -> Any: |
| | return obj(*a, **kw) |
| |
|
| | key = (a, tuple(sorted(kw.items()))) |
| | return cache.get(key, create_new) |
| |
|
| | return cast(_F, new_callable) |
| |
|
| | return decorator |
| |
|