---
id: cachetools
version: "7.1.7"
license: MIT
license_treatment: permissive
maintenance: active
---

# cachetools — Extensible memoizing collections and decorators

License: permissive · Maintenance: active · Popularity: top 1,000 on PyPI

## Install

pip install cachetools
uv add cachetools
poetry add cachetools

## Description

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/github/license/tkem/cachetools
   :target: https://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...

## AI interpretation — verify before relying

Provides memoizing collections and decorators for caching function results with multiple cache algorithms (LRU, TTL, FIFO) and eviction strategies, similar to Python's standard library @lru_cache but with more flexibility.

Verdict: cachetools is a mature, actively maintained caching library with zero known vulnerabilities, no external dependencies, and permissive MIT licensing. It offers production-ready cache implementations with multiple eviction strategies and is well-suited for performance optimization in Python applications.

[View on SkillFed](https://skillfed.io/packages/cachetools) · [View on PyPI](https://pypi.org/project/cachetools/)