from cPickle import dumps, PicklingError # for memoize
class memoize(object):
"""Decorator that caches a function's return value each time it is called.
If called later with the same arguments, the cached value is returned, and
not re-evaluated. Slow for mutable types."""
# Ideas from MemoizeMutable class of Recipe 52201 by Paul Moore and
# from memoized decorator of http://wiki.python.org/moin/PythonDecoratorLibrary
# For a version with timeout see Recipe 325905
# For a self cleaning version see Recipe 440678
# Weak references (a dict with weak values) can be used, like this:
# self._cache = weakref.WeakValueDictionary()
# but the keys of such dict can't be int
def __init__(self, func):
self.func = func
self._cache = {}
def __call__(self, *args, **kwds):
key = args
if kwds:
items = kwds.items()
items.sort()
key = key + tuple(items)
try:
if key in self._cache:
return self._cache[key]
self._cache[key] = result = self.func(*args, **kwds)
return result
except TypeError:
try:
dump = dumps(key)
except PicklingError:
return self.func(*args, **kwds)
else:
if dump in self._cache:
return self._cache[dump]
self._cache[dump] = result = self.func(*args, **kwds)
return result
if __name__ == "__main__": # Some examples
@memoize
def fibonacci(n):
"Return the n-th element of the Fibonacci series."
if n < 3:
return 1
return fibonacci(n-1) + fibonacci(n-2)
print [fibonacci(i) for i in xrange(1, 101)]
@memoize
def pow(x, p=2):
if p==1:
return x
else:
return x * pow(x, p=p-1)
print [pow(3, p=i) for i in xrange(1, 6)]
@memoize
def printlist(l):
print l
printlist([1,2,3,4])
