Source code for lars.cache

# vim: set et sw=4 sts=4 fileencoding=utf-8:
#
# Copyright (c) 2012 Raymond Hettinger
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.

"""
This module provides a backport of the Python 3.3 LRU caching decorator. Users
should never need to access this module directly; its contents are solely
present to ensure DNS lookups can be cached under a Python 2.7 environment.

Source adapted from `Raymond Hettinger's recipe`_ licensed under the `MIT
license`_.


Functions
=========

.. _Raymond Hettinger's recipe:
   http://code.activestate.com/recipes/578078-py26-and-py30-backport-of-python-33s-lru-cache/
.. _MIT license: http://opensource.org/licenses/MIT
.. _LRU: http://en.wikipedia.org/wiki/Cache_algorithms#Least_Recently_Used
"""

from __future__ import (
    unicode_literals,
    absolute_import,
    print_function,
    division,
    )


from collections import namedtuple
from functools import update_wrapper
from threading import RLock

str = type('')  # pylint: disable=redefined-builtin,invalid-name

_CacheInfo = namedtuple("CacheInfo", ["hits", "misses", "maxsize", "currsize"])


class _HashedSeq(list):
    __slots__ = 'hashvalue'

    def __init__(self, tup, hash=hash):
        # pylint: disable=super-init-not-called,redefined-builtin
        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
    """
    # pylint: disable=dangerous-default-value,too-many-arguments
    # pylint: disable=redefined-builtin
    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)


[docs]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__. """ # 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): # pylint: disable=missing-docstring,too-many-locals,invalid-name 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) # root used here as a unique not-found sentinel result = cache_get(key, root) 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] 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 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