README.rst

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

This module provides various memoizing collections and decorators,
including variants of the Python 3 Standard Library `@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`_.  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.

For more information, please refer to the online documentation_.


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

Install cachetools using pip::

    pip install cachetools


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

.. image:: http://img.shields.io/pypi/v/cachetools.svg?style=flat
   :target: https://pypi.python.org/pypi/cachetools/
   :alt: Latest PyPI version

.. image:: http://img.shields.io/travis/tkem/cachetools/master.svg?style=flat
   :target: https://travis-ci.org/tkem/cachetools/
   :alt: Travis CI build status

.. image:: http://img.shields.io/coveralls/tkem/cachetools/master.svg?style=flat
   :target: https://coveralls.io/r/tkem/cachetools
   :alt: Test coverage

.. image:: https://readthedocs.org/projects/cachetools/badge/?version=latest&style=flat
   :target: http://cachetools.readthedocs.io/en/latest/
   :alt: Documentation Status

- `Issue Tracker`_
- `Source Code`_
- `Change Log`_


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

Copyright (c) 2014-2018 Thomas Kemmer.

Licensed under the `MIT License`_.


.. _@lru_cache: http://docs.python.org/3/library/functools.html#functools.lru_cache
.. _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/Cache_algorithms

.. _Documentation: http://cachetools.readthedocs.io/en/latest/
.. _Issue Tracker: https://github.com/tkem/cachetools/issues/
.. _Source Code: https://github.com/tkem/cachetools/
.. _Change Log: https://github.com/tkem/cachetools/blob/master/CHANGES.rst
.. _MIT License: http://raw.github.com/tkem/cachetools/master/LICENSE