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147 lines
3.9 KiB
147 lines
3.9 KiB
"""`functools.lru_cache` compatible memoizing function decorators."""
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import collections
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import functools
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import math
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import random
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import time
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try:
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from threading import RLock
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except ImportError: # pragma: no cover
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from dummy_threading import RLock
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from . import keys
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from .lfu import LFUCache
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from .lru import LRUCache
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from .rr import RRCache
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from .ttl import TTLCache
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__all__ = ('lfu_cache', 'lru_cache', 'rr_cache', 'ttl_cache')
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_CacheInfo = collections.namedtuple('CacheInfo', [
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'hits', 'misses', 'maxsize', 'currsize'
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])
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class _UnboundCache(dict):
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@property
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def maxsize(self):
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return None
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@property
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def currsize(self):
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return len(self)
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class _UnboundTTLCache(TTLCache):
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def __init__(self, ttl, timer):
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TTLCache.__init__(self, math.inf, ttl, timer)
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@property
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def maxsize(self):
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return None
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def _cache(cache, typed):
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maxsize = cache.maxsize
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def decorator(func):
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key = keys.typedkey if typed else keys.hashkey
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lock = RLock()
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stats = [0, 0]
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def wrapper(*args, **kwargs):
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k = key(*args, **kwargs)
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with lock:
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try:
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v = cache[k]
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stats[0] += 1
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return v
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except KeyError:
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stats[1] += 1
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v = func(*args, **kwargs)
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try:
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with lock:
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cache[k] = v
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except ValueError:
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pass # value too large
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return v
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def cache_info():
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with lock:
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hits, misses = stats
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maxsize = cache.maxsize
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currsize = cache.currsize
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return _CacheInfo(hits, misses, maxsize, currsize)
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def cache_clear():
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with lock:
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try:
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cache.clear()
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finally:
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stats[:] = [0, 0]
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wrapper.cache_info = cache_info
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wrapper.cache_clear = cache_clear
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wrapper.cache_parameters = lambda: {'maxsize': maxsize, 'typed': typed}
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functools.update_wrapper(wrapper, func)
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return wrapper
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return decorator
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def lfu_cache(maxsize=128, typed=False):
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"""Decorator to wrap a function with a memoizing callable that saves
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up to `maxsize` results based on a Least Frequently Used (LFU)
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algorithm.
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"""
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if maxsize is None:
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return _cache(_UnboundCache(), typed)
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elif callable(maxsize):
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return _cache(LFUCache(128), typed)(maxsize)
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else:
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return _cache(LFUCache(maxsize), typed)
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def lru_cache(maxsize=128, typed=False):
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"""Decorator to wrap a function with a memoizing callable that saves
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up to `maxsize` results based on a Least Recently Used (LRU)
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algorithm.
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"""
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if maxsize is None:
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return _cache(_UnboundCache(), typed)
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elif callable(maxsize):
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return _cache(LRUCache(128), typed)(maxsize)
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else:
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return _cache(LRUCache(maxsize), typed)
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def rr_cache(maxsize=128, choice=random.choice, typed=False):
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"""Decorator to wrap a function with a memoizing callable that saves
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up to `maxsize` results based on a Random Replacement (RR)
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algorithm.
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"""
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if maxsize is None:
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return _cache(_UnboundCache(), typed)
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elif callable(maxsize):
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return _cache(RRCache(128, choice), typed)(maxsize)
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else:
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return _cache(RRCache(maxsize, choice), typed)
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def ttl_cache(maxsize=128, ttl=600, timer=time.monotonic, typed=False):
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"""Decorator to wrap a function with a memoizing callable that saves
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up to `maxsize` results based on a Least Recently Used (LRU)
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algorithm with a per-item time-to-live (TTL) value.
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"""
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if maxsize is None:
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return _cache(_UnboundTTLCache(ttl, timer), typed)
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elif callable(maxsize):
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return _cache(TTLCache(128, ttl, timer), typed)(maxsize)
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else:
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return _cache(TTLCache(maxsize, ttl, timer), typed)
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