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    cachetools

Extensible memoizing collections and decorators


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cachetools

.. 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

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_
  • asyncache_: Helpers to use cachetools with async functions
  • cacheing_: Pure Python Cacheing Library
  • CacheToolsUtils_: Cachetools Utilities
  • kids.cache_: Kids caching library
  • shelved-cache_: Persistent cache for Python cachetools

License

Copyright (c) 2014-2024 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/

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