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cachetools 0.4.0

Extensible memoizing collections and decorators

Latest Version: 2.0.1

This module provides various memoizing collections and decorators, including a variant of the Python 3 Standard Library functools.lru_cache function decorator.

>>> from cachetools import LRUCache
>>> cache = LRUCache(maxsize=2)
>>> cache.update([('first', 1), ('second', 2)])
>>> cache
LRUCache([('second', 2), ('first', 1)], maxsize=2, currsize=2)
>>> cache['third'] = 3
>>> cache
LRUCache([('second', 2), ('third', 3)], maxsize=2, currsize=2)
>>> cache['second']
>>> cache['fourth'] = 4
LRUCache([('second', 2), ('fourth', 4)], maxsize=2, currsize=2)

For the purpose of this module, a cache is a mutable mapping of a fixed maximum size. When the cache is full, i.e. the current size of the cache exceeds its maximum size, the cache must choose which item(s) to discard based on a suitable cache algorithm.

In general, a cache’s size is the sum of the size of its items. If the size of each items is 1, a cache’s size is equal to the number of its items, i.e. len(cache). An items’s size may also be a property or function of its value, e.g. the result of sys.getsizeof(), or len() for string and sequence values.

This module provides various cache implementations based on different cache algorithms, as well as decorators for easily memoizing function and method calls.


Install cachetools using pip:

pip install cachetools


Copyright (c) 2014 Thomas Kemmer.

Licensed under the MIT License.

File Type Py Version Uploaded on Size
cachetools-0.4.0.tar.gz (md5) Source 2014-06-16 7KB