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usr/local/CyberCP/lib/python3.10/site-packages/cachetools/func.py 0000644 00000007207 15027746025 0020516 0 ustar 00 """`functools.lru_cache` compatible memoizing function decorators.""" __all__ = ("fifo_cache", "lfu_cache", "lru_cache", "mru_cache", "rr_cache", "ttl_cache") import math import random import time try: from threading import RLock except ImportError: # pragma: no cover from dummy_threading import RLock from . import FIFOCache, LFUCache, LRUCache, MRUCache, RRCache, TTLCache from . import cached from . import keys class _UnboundTTLCache(TTLCache): def __init__(self, ttl, timer): TTLCache.__init__(self, math.inf, ttl, timer) @property def maxsize(self): return None def _cache(cache, maxsize, typed): def decorator(func): key = keys.typedkey if typed else keys.hashkey wrapper = cached(cache=cache, key=key, lock=RLock(), info=True)(func) wrapper.cache_parameters = lambda: {"maxsize": maxsize, "typed": typed} return wrapper return decorator def fifo_cache(maxsize=128, typed=False): """Decorator to wrap a function with a memoizing callable that saves up to `maxsize` results based on a First In First Out (FIFO) algorithm. """ if maxsize is None: return _cache({}, None, typed) elif callable(maxsize): return _cache(FIFOCache(128), 128, typed)(maxsize) else: return _cache(FIFOCache(maxsize), maxsize, typed) def lfu_cache(maxsize=128, typed=False): """Decorator to wrap a function with a memoizing callable that saves up to `maxsize` results based on a Least Frequently Used (LFU) algorithm. """ if maxsize is None: return _cache({}, None, typed) elif callable(maxsize): return _cache(LFUCache(128), 128, typed)(maxsize) else: return _cache(LFUCache(maxsize), maxsize, typed) def lru_cache(maxsize=128, typed=False): """Decorator to wrap a function with a memoizing callable that saves up to `maxsize` results based on a Least Recently Used (LRU) algorithm. """ if maxsize is None: return _cache({}, None, typed) elif callable(maxsize): return _cache(LRUCache(128), 128, typed)(maxsize) else: return _cache(LRUCache(maxsize), maxsize, typed) def mru_cache(maxsize=128, typed=False): """Decorator to wrap a function with a memoizing callable that saves up to `maxsize` results based on a Most Recently Used (MRU) algorithm. """ from warnings import warn warn("@mru_cache is deprecated", DeprecationWarning, stacklevel=2) if maxsize is None: return _cache({}, None, typed) elif callable(maxsize): return _cache(MRUCache(128), 128, typed)(maxsize) else: return _cache(MRUCache(maxsize), maxsize, typed) def rr_cache(maxsize=128, choice=random.choice, typed=False): """Decorator to wrap a function with a memoizing callable that saves up to `maxsize` results based on a Random Replacement (RR) algorithm. """ if maxsize is None: return _cache({}, None, typed) elif callable(maxsize): return _cache(RRCache(128, choice), 128, typed)(maxsize) else: return _cache(RRCache(maxsize, choice), maxsize, typed) def ttl_cache(maxsize=128, ttl=600, timer=time.monotonic, typed=False): """Decorator to wrap a function with a memoizing callable that saves up to `maxsize` results based on a Least Recently Used (LRU) algorithm with a per-item time-to-live (TTL) value. """ if maxsize is None: return _cache(_UnboundTTLCache(ttl, timer), None, typed) elif callable(maxsize): return _cache(TTLCache(128, ttl, timer), 128, typed)(maxsize) else: return _cache(TTLCache(maxsize, ttl, timer), maxsize, typed)
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