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authorGeorg Brandl <georg@python.org>2010-07-31 10:16:21 (GMT)
committerGeorg Brandl <georg@python.org>2010-07-31 10:16:21 (GMT)
commit014e0ca58efed657ae2b6bdd724e4721967d05ef (patch)
tree1078793b2f5cfbdf48f398bcfce6071c26878ecf /Lib/functools.py
parent4821ef89d4ce166c735cad48a57c03eae01fa577 (diff)
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Revert r83327. This will have to wait until after the alpha1 release.
Diffstat (limited to 'Lib/functools.py')
-rw-r--r--Lib/functools.py94
1 files changed, 1 insertions, 93 deletions
diff --git a/Lib/functools.py b/Lib/functools.py
index 863706d..1a1f22e 100644
--- a/Lib/functools.py
+++ b/Lib/functools.py
@@ -4,17 +4,10 @@
# to allow utilities written in Python to be added
# to the functools module.
# Written by Nick Coghlan <ncoghlan at gmail.com>
-# and Raymond Hettinger <python at rcn.com>
-# Copyright (C) 2006-2010 Python Software Foundation.
+# Copyright (C) 2006 Python Software Foundation.
# See C source code for _functools credits/copyright
-__all__ = ['update_wrapper', 'wraps', 'WRAPPER_ASSIGNMENTS', 'WRAPPER_UPDATES',
- 'total_ordering', 'cmp_to_key', 'lfu_cache', 'lru_cache']
-
from _functools import partial, reduce
-from collections import OrderedDict, Counter
-from heapq import nsmallest
-from operator import itemgetter
# update_wrapper() and wraps() are tools to help write
# wrapper functions that can handle naive introspection
@@ -104,88 +97,3 @@ def cmp_to_key(mycmp):
def __hash__(self):
raise TypeError('hash not implemented')
return K
-
-def lfu_cache(maxsize=100):
- '''Least-frequently-used cache decorator.
-
- Arguments to the cached function must be hashable.
- Cache performance statistics stored in f.hits and f.misses.
- Clear the cache using f.clear().
- http://en.wikipedia.org/wiki/Cache_algorithms#Least-Frequently_Used
-
- '''
- def decorating_function(user_function):
- cache = {} # mapping of args to results
- use_count = Counter() # times each key has been accessed
- kwd_mark = object() # separate positional and keyword args
-
- @wraps(user_function)
- def wrapper(*args, **kwds):
- key = args
- if kwds:
- key += (kwd_mark,) + tuple(sorted(kwds.items()))
- use_count[key] += 1 # count a use of this key
- try:
- result = cache[key]
- wrapper.hits += 1
- except KeyError:
- result = user_function(*args, **kwds)
- cache[key] = result
- wrapper.misses += 1
- if len(cache) > maxsize:
- # purge the 10% least frequently used entries
- for key, _ in nsmallest(maxsize // 10,
- use_count.items(),
- key=itemgetter(1)):
- del cache[key], use_count[key]
- return result
-
- def clear():
- 'Clear the cache and cache statistics'
- cache.clear()
- use_count.clear()
- wrapper.hits = wrapper.misses = 0
-
- wrapper.hits = wrapper.misses = 0
- wrapper.clear = clear
- return wrapper
- return decorating_function
-
-def lru_cache(maxsize=100):
- '''Least-recently-used cache decorator.
-
- Arguments to the cached function must be hashable.
- Cache performance statistics stored in f.hits and f.misses.
- Clear the cache using f.clear().
- http://en.wikipedia.org/wiki/Cache_algorithms#Least_Recently_Used
-
- '''
- def decorating_function(user_function):
- cache = OrderedDict() # ordered least recent to most recent
- kwd_mark = object() # separate positional and keyword args
-
- @wraps(user_function)
- def wrapper(*args, **kwds):
- key = args
- if kwds:
- key += (kwd_mark,) + tuple(sorted(kwds.items()))
- try:
- result = cache.pop(key)
- wrapper.hits += 1
- except KeyError:
- result = user_function(*args, **kwds)
- wrapper.misses += 1
- if len(cache) >= maxsize:
- cache.popitem(0) # purge least recently used cache entry
- cache[key] = result # record recent use of this key
- return result
-
- def clear():
- 'Clear the cache and cache statistics'
- cache.clear()
- wrapper.hits = wrapper.misses = 0
-
- wrapper.hits = wrapper.misses = 0
- wrapper.clear = clear
- return wrapper
- return decorating_function