commit d9fbdc968479b0d413d1ff875ca19c855e7ce2ae Author: Damian Johnson <atagar@torproject.org> Date: Sun Oct 6 17:32:10 2013 -0700 Adding python 2.x backport of @lru_cache Python 3.2 added a memoization annotation to python's functools module. This is very, very handy, allowing us to avoid the caching boilerplate I do way too often... def get_foo(): if self._foo is None: ... stuff to calculate self._foo... return self._foo With a memoization function this becomes... @lru_cache() def get_foo(): ... stuff to calculate self._foo... This is a MIT licensed backport from... http://code.activestate.com/recipes/578078-py26-and-py30-backport-of-python-... Looking forward to when we require python 3.2 so we can use the builtin! --- stem/util/__init__.py | 1 + stem/util/lru_cache.py | 180 ++++++++++++++++++++++++++++++++++++++++++++++++ 2 files changed, 181 insertions(+) diff --git a/stem/util/__init__.py b/stem/util/__init__.py index 8ec8eaf..dacd804 100644 --- a/stem/util/__init__.py +++ b/stem/util/__init__.py @@ -10,6 +10,7 @@ __all__ = [ "connection", "enum", "log", + "lru_cache", "ordereddict", "proc", "system", diff --git a/stem/util/lru_cache.py b/stem/util/lru_cache.py new file mode 100644 index 0000000..5591862 --- /dev/null +++ b/stem/util/lru_cache.py @@ -0,0 +1,180 @@ +# Drop in replace for python 3.2's collections.lru_cache, from... +# http://code.activestate.com/recipes/578078-py26-and-py30-backport-of-python-... +# +# ... which is under the MIT license. Stem users should *not* rely upon this +# module. It will be removed when we drop support for python 3.2 and below. + +""" +Memoization decorator that caches a function's return value. If later called +with the same arguments then the cached value is returned rather than +reevaluated. + +This is a a python 2.x port of `functools.lru_cache +<http://docs.python.org/3/library/functools.html#functools.lru_cache>`_. If +using python 3.2 or later you should use that instead. +""" + +from collections import namedtuple +from functools import update_wrapper +from threading import RLock + +_CacheInfo = namedtuple("CacheInfo", ["hits", "misses", "maxsize", "currsize"]) + +class _HashedSeq(list): + __slots__ = 'hashvalue' + + def __init__(self, tup, hash=hash): + self[:] = tup + self.hashvalue = hash(tup) + + def __hash__(self): + return self.hashvalue + +def _make_key(args, kwds, typed, + kwd_mark = (object(),), + fasttypes = {int, str, frozenset, type(None)}, + sorted=sorted, tuple=tuple, type=type, len=len): + 'Make a cache key from optionally typed positional and keyword arguments' + key = args + if kwds: + sorted_items = sorted(kwds.items()) + key += kwd_mark + for item in sorted_items: + key += item + if typed: + key += tuple(type(v) for v in args) + if kwds: + key += tuple(type(v) for k, v in sorted_items) + elif len(key) == 1 and type(key[0]) in fasttypes: + return key[0] + return _HashedSeq(key) + +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 + make_key = _make_key + cache_get = cache.get # bound method to lookup key or return None + _len = len # localize the global len() function + lock = RLock() # because linkedlist updates aren't threadsafe + root = [] # root of the circular doubly linked list + root[:] = [root, root, None, None] # initialize by pointing to self + nonlocal_root = [root] # make updateable non-locally + PREV, NEXT, KEY, RESULT = 0, 1, 2, 3 # names for the link fields + + 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) + 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 + if key in cache: + # getting here means that this same key was added to the + # cache while the lock was released. since the link + # update is already done, we need only return the + # computed result and update the count of misses. + pass + elif _len(cache) >= maxsize: + # use the old root to store the new key and result + oldroot = root + oldroot[KEY] = key + oldroot[RESULT] = result + # empty the oldest link and make it the new root + root = nonlocal_root[0] = oldroot[NEXT] + oldkey = root[KEY] + oldvalue = root[RESULT] + root[KEY] = root[RESULT] = None + # now update the cache dictionary for the new links + del cache[oldkey] + cache[key] = oldroot + else: + # put result in a new link at the front of the list + last = root[PREV] + link = [last, root, key, result] + last[NEXT] = root[PREV] = cache[key] = link + 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