https://github.com/enricobacis/python-memo

python decorators to memoize function results (also for classes)
https://github.com/enricobacis/python-memo

decorators memoization python

Last synced: about 2 months ago
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python decorators to memoize function results (also for classes)

• Host: GitHub
• URL: https://github.com/enricobacis/python-memo
• Owner: enricobacis
• License: mit
• Created: 2017-02-14T16:03:14.000Z (almost 8 years ago)
• Default Branch: master
• Last Pushed: 2017-02-14T17:26:01.000Z (almost 8 years ago)
• Last Synced: 2024-10-14T07:24:24.119Z (2 months ago)
• Topics: decorators, memoization, python
• Language: Python
• Size: 4.88 KB
• Stars: 3
• Watchers: 3
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.rst
  • License: LICENSE

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README

        
python-memo

===========

*python memoize decorators that cache the results of functions.*

Description

-----------

*memoize* and *keyed-memoize* decorators.

- ``memo``: The classical *memoize* decorator. It keeps a cache

  ``args -> result`` so you don't continue to perform the same computations.

- ``keymemo(key)``: This decorator factory act as ``memo`` but it permits to

  specify a ``key`` function that takes the ``args`` of the decorated function

  and computes a ``key`` value to use as key in the cache dictionary. This way

  you can for example use a single value of a dictionary as key of the cache,

  or apply a function before passing something to the cache.

- ``instancememo``: The classical *memoize* decorator that can be applied to

  class functions. It keeps a cache ``args -> result`` so you don't continue

  to perform the same computations. The cache is kept in the class namespace.

- ``instancekeymemo(key)``: This decorator factory works like a combination of

  ``instancememo`` and ``keymemo``, so it allows to specify a function that

  generate the cache key based on the function arguments and can be applied

  to class functions.

Usage

-----

.. code:: python

    from memo import memo

    @memo

    def fibonacci(n):

        if n <= 2:

            return 1

        return fibonacci(n-1) + fibonacci(n-2)

.. code:: python

    from memo import keymemo

    @keymemo(lambda tup: tup[0])

    def function(tup):

        # build a cache based on the first value of a tuple

        ...

Installation

------------

The package has been uploaded to `PyPI`_, so you can install it with pip:

    pip install python-memo

.. _PyPI: https://pypi.python.org/pypi/python-memo