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- try:
- from functools import lru_cache
-
- except ImportError:
- # backport of Python's 3.3 lru_cache, written by Raymond Hettinger and
- # licensed under MIT license, from:
- # <http://code.activestate.com/recipes/578078-py26-and-py30-backport-of-python-33s-lru-cache/>
- # Should be removed when Django only supports Python 3.2 and above.
-
- 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: https://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
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