AIM-PIbd-32-Kurbanova-A-A/aimenv/Lib/site-packages/prompt_toolkit/cache.py
2024-10-02 22:15:59 +04:00

128 lines
3.7 KiB
Python

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.
"""
# Look in cache first.
try:
return self._data[key]
except KeyError:
# Not found? Get it.
value = getter_func()
self._data[key] = value
self._keys.append(key)
# Remove the oldest key when the size is exceeded.
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.
"""
# NOTE: This cache is used to cache `prompt_toolkit.layout.screen.Char` and
# `prompt_toolkit.Document`. Make sure to keep this really lightweight.
# Accessing the cache should stay faster than instantiating new
# objects.
# (Dictionary lookups are really fast.)
# SimpleCache is still required for cases where the cache key is not
# the same as the arguments given to the function that creates the
# value.)
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:
# Remove the oldest key when the size is exceeded.
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