cachetools 7.0.1
Extensible memoizing collections and decorators
Requires Python: >=3.10

cachetools
========================================================================

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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 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.


Installation
------------------------------------------------------------------------

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


Project Resources
------------------------------------------------------------------------

- `Documentation`_
- `Issue tracker`_
- `Source code`_
- `Change log`_


Related Projects
------------------------------------------------------------------------

- asyncache_: Helpers to use cachetools_ with asyncio.
- cachetools-async_: Helpers to use cachetools_ with asyncio.
- cacheing_: Pure Python Cacheing Library.
- CacheToolsUtils_: Stackable cache classes for sharing, encryption,
  statistics *and more* on top of cachetools_, redis_ and memcached_.
- shelved-cache_: Persistent cache implementation for Python
  cachetools_.


License
------------------------------------------------------------------------

Copyright (c) 2014-2026 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/
.. _cachetools-async: https://pypi.org/project/cachetools-async/
.. _cacheing: https://pypi.org/project/cacheing/
.. _CacheToolsUtils: https://pypi.org/project/CacheToolsUtils/
.. _shelved-cache: https://pypi.org/project/shelved-cache/
.. _cachetools: https://pypi.org/project/cachetools/
.. _redis: https://redis.io/
.. _memcached: https://memcached.org/