# This is a backport of functools.lru_cache, which is part of the stdlib =>v3.3. # http://code.activestate.com/recipes/578078-py26-and-py30-backport-of-python-33s-lru-cache/ from collections import namedtuple from functools import update_wrapper from threading import Lock _CacheInfo = namedtuple("CacheInfo", ["hits", "misses", "maxsize", "currsize"]) def lru_cache(maxsize=100, typed=False): """Least-recently-used cache decorator. If *maxsize* is set to None, the LRU features are disabled and the cache can grow without bound. If *typed* is True, arguments of different types will be cached separately. For example, f(3.0) and f(3) will be treated as distinct calls with distinct results. Arguments to the cached function must be hashable. View the cache statistics named tuple (hits, misses, maxsize, currsize) with f.cache_info(). Clear the cache and statistics with f.cache_clear(). Access the underlying function with f.__wrapped__. See: http://en.wikipedia.org/wiki/Cache_algorithms#Least_Recently_Used """ # Users should only access the lru_cache through its public API: # cache_info, cache_clear, and f.__wrapped__ # The internals of the lru_cache are encapsulated for thread safety and # to allow the implementation to change (including a possible C version). def decorating_function(user_function): cache = dict() stats = [0, 0] # make statistics updateable non-locally HITS, MISSES = 0, 1 # names for the stats fields kwd_mark = (object(),) # separate positional and keyword args cache_get = cache.get # bound method to lookup key or return None _len = len # localize the global len() function lock = Lock() # because linkedlist updates aren't threadsafe root = [] # root of the circular doubly linked list nonlocal_root = [root] # make updateable non-locally root[:] = [root, root, None, None] # initialize by pointing to self PREV, NEXT, KEY, RESULT = 0, 1, 2, 3 # names for the link fields def make_key(args, kwds, typed, tuple=tuple, sorted=sorted, type=type): # helper function to build a cache key from positional and keyword args key = args if kwds: sorted_items = tuple(sorted(kwds.items())) key += kwd_mark + sorted_items if typed: key += tuple(type(v) for v in args) if kwds: key += tuple(type(v) for k, v in sorted_items) return key if maxsize == 0: def wrapper(*args, **kwds): # no caching, just do a statistics update after a successful call result = user_function(*args, **kwds) stats[MISSES] += 1 return result elif maxsize is None: def wrapper(*args, **kwds): # simple caching without ordering or size limit key = make_key(args, kwds, typed) if kwds or typed else args result = cache_get(key, root) # root used here as a unique not-found sentinel if result is not root: stats[HITS] += 1 return result result = user_function(*args, **kwds) cache[key] = result stats[MISSES] += 1 return result else: def wrapper(*args, **kwds): # size limited caching that tracks accesses by recency key = make_key(args, kwds, typed) if kwds or typed else args with lock: link = cache_get(key) if link is not None: # record recent use of the key by moving it to the front of the list root, = nonlocal_root link_prev, link_next, key, result = link link_prev[NEXT] = link_next link_next[PREV] = link_prev last = root[PREV] last[NEXT] = root[PREV] = link link[PREV] = last link[NEXT] = root stats[HITS] += 1 return result result = user_function(*args, **kwds) with lock: root = nonlocal_root[0] if _len(cache) < maxsize: # put result in a new link at the front of the list last = root[PREV] link = [last, root, key, result] cache[key] = last[NEXT] = root[PREV] = link else: # use root to store the new key and result root[KEY] = key root[RESULT] = result cache[key] = root # empty the oldest link and make it the new root root = nonlocal_root[0] = root[NEXT] del cache[root[KEY]] root[KEY] = None root[RESULT] = None stats[MISSES] += 1 return result def cache_info(): """Report cache statistics""" with lock: return _CacheInfo(stats[HITS], stats[MISSES], maxsize, len(cache)) def cache_clear(): """Clear the cache and cache statistics""" with lock: cache.clear() root = nonlocal_root[0] root[:] = [root, root, None, None] stats[:] = [0, 0] wrapper.__wrapped__ = user_function wrapper.cache_info = cache_info wrapper.cache_clear = cache_clear return update_wrapper(wrapper, user_function) return decorating_function