cachetools

.. image:: http://img.shields.io/pypi/v/cachetools :target: https://pypi.org/project/cachetools/ :alt: Latest PyPI version

.. image:: https://img.shields.io/readthedocs/cachetools :target: http://cachetools.readthedocs.io/ :alt: Documentation build status

.. image:: http://img.shields.io/travis/tkem/cachetools :target: https://travis-ci.org/tkem/cachetools/ :alt: Travis CI build status

.. image:: http://img.shields.io/coveralls/tkem/cachetools :target: https://coveralls.io/r/tkem/cachetools :alt: Test coverage

.. image:: https://img.shields.io/github/license/tkem/cachetools :target: http://raw.github.com/tkem/cachetools/master/LICENSE :alt: License

This module provides various memoizing collections and decorators, including variants of the Python Standard Library's @lru_cache_ function decorator.

.. code-block:: python

from cachetools import cached, LRUCache, TTLCache

# speed up calculating Fibonacci numbers with dynamic programming @cached(cache={}) def fib(n): return n if n < 2 else fib(n - 1) + fib(n - 2)

# cache least recently used Python Enhancement Proposals @cached(cache=LRUCache(maxsize=32)) def get_pep(num): url = 'http://www.python.org/dev/peps/pep-%04d/' % num with urllib.request.urlopen(url) as s: return s.read()

# cache weather data for no longer than ten minutes @cached(cache=TTLCache(maxsize=1024, ttl=600)) def getweather(place): return owm.weatheratplace(place).getweather()

For the purpose of this module, a cache is a mutable_ mapping_ of a fixed maximum size. When the cache is full, i.e. by adding another item the cache would exceed 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 total size of its items, and an item's size is a property or function of its value, e.g. the result of sys.getsizeof(value). For the trivial but common case that each item counts as 1, a cache's size is equal to the number of its items, or len(cache).

Multiple cache classes based on different caching algorithms are implemented, and decorators for easily memoizing function and method calls are provided, too.

Installation

cachetools is available from PyPI_ and can be installed by running::

pip install cachetools

Project Resources

Documentation_
Issue tracker_
Source code_
Change log_

License

Copyright (c) 2014-2020 Thomas Kemmer.

Licensed under the MIT License_.

.. @lrucache: http://docs.python.org/3/library/functools.html#functools.lrucache .. _mutable: http://docs.python.org/dev/glossary.html#term-mutable .. _mapping: http://docs.python.org/dev/glossary.html#term-mapping .. _cache algorithm: http://en.wikipedia.org/wiki/Cachealgorithms

.. _PyPI: https://pypi.org/project/cachetools/ .. _Documentation: https://cachetools.readthedocs.io/ .. _Issue tracker: https://github.com/tkem/cachetools/issues/ .. _Source code: https://github.com/tkem/cachetools/ .. _Change log: https://github.com/tkem/cachetools/blob/master/CHANGELOG.rst .. _MIT License: http://raw.github.com/tkem/cachetools/master/LICENSE