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.. image:: https://img.shields.io/pypi/v/cachetools :target: https://pypi.org/project/cachetools/ :alt: Latest PyPI version
.. image:: https://img.shields.io/github/actions/workflow/status/tkem/cachetools/ci.yml :target: https://github.com/tkem/cachetools/actions/workflows/ci.yml :alt: CI build status
.. image:: https://img.shields.io/readthedocs/cachetools :target: https://cachetools.readthedocs.io/ :alt: Documentation build status
.. image:: https://img.shields.io/codecov/c/github/tkem/cachetools/master.svg :target: https://codecov.io/gh/tkem/cachetools :alt: Test coverage
.. image:: https://img.shields.io/librariesio/sourcerank/pypi/cachetools :target: https://libraries.io/pypi/cachetools :alt: Libraries.io SourceRank
.. image:: https://img.shields.io/github/license/tkem/cachetools :target: https://raw.github.com/tkem/cachetools/master/LICENSE :alt: License
.. image:: https://img.shields.io/badge/code%20style-black-000000.svg :target: https://github.com/psf/black :alt: Code style: black
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
@cached(cache={}) def fib(n): return n if n < 2 else fib(n - 1) + fib(n - 2)
@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()
@cached(cache=TTLCache(maxsize=1024, ttl=600)) def get_weather(place): return owm.weather_at_place(place).get_weather()
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
_.
This module provides multiple cache classes based on different cache algorithms, as well as decorators for easily memoizing function and method calls.
cachetools is available from PyPI_ and can be installed by running::
pip install cachetools
Typing stubs for this package are provided by typeshed_ and can be installed by running::
pip install types-cachetools
Documentation
_Issue tracker
_Source code
_Change log
_Copyright (c) 2014-2025 Thomas Kemmer.
Licensed under the MIT License
_.
.. _@lru_cache: https://docs.python.org/3/library/functools.html#functools.lru_cache .. _mutable: https://docs.python.org/dev/glossary.html#term-mutable .. _mapping: https://docs.python.org/dev/glossary.html#term-mapping .. _cache algorithm: https://en.wikipedia.org/wiki/Cache_algorithms
.. _PyPI: https://pypi.org/project/cachetools/ .. _typeshed: https://github.com/python/typeshed/ .. _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: https://raw.github.com/tkem/cachetools/master/LICENSE
.. _asyncache: https://pypi.org/project/asyncache/ .. _cacheing: https://github.com/breid48/cacheing .. _CacheToolsUtils: https://pypi.org/project/CacheToolsUtils/ .. _kids.cache: https://pypi.org/project/kids.cache/ .. _shelved-cache: https://pypi.org/project/shelved-cache/
FAQs
Extensible memoizing collections and decorators
We found that cachetools demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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