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| """`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) | |
| 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. | |
| """ | |
| 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) | |