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Extensible memoizing collections and decorators

Project Description

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

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

For the purpose of this module, a cache is a mutable mapping of fixed size, defined by its maxsize attribute. When the cache is full, i.e. len(cache) == cache.maxsize, the cache must choose which item(s) to discard based on a suitable cache algorithm.

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

Installation

Install cachetools using pip:

pip install cachetools

License

Copyright 2014 Thomas Kemmer.

Licensed under the MIT License.

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2.0.1

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