Skip to content

Latest commit

 

History

History
146 lines (109 loc) · 6.22 KB

README.md

File metadata and controls

146 lines (109 loc) · 6.22 KB
Raw

klepto

persistent caching to memory, disk, or database

About Klepto

klepto extends Python's lru_cache to utilize different keymaps and alternate caching algorithms, such as lfu_cache and mru_cache. While caching is meant for fast access to saved results, klepto also has archiving capabilities, for longer-term storage. klepto uses a simple dictionary-sytle interface for all caches and archives, and all caches can be applied to any Python function as a decorator. Keymaps are algorithms for converting a function's input signature to a unique dictionary, where the function's results are the dictionary value. Thus for y = f(x), y will be stored in cache[x] (e.g. {x:y}).

klepto provides both standard and "safe" caching, where "safe" caches are slower but can recover from hashing errors. klepto is intended to be used for distributed and parallel computing, where several of the keymaps serialize the stored objects. Caches and archives are intended to be read/write accessible from different threads and processes. klepto enables a user to decorate a function, save the results to a file or database archive, close the interpreter, start a new session, and reload the function and it's cache.

klepto is part of pathos, a Python framework for heterogeneous computing. klepto is in active development, so any user feedback, bug reports, comments, or suggestions are highly appreciated. A list of issues is located at https://github.com/uqfoundation/klepto/issues, with a legacy list maintained at https://uqfoundation.github.io/project/pathos/query.

Major Features

klepto has standard and "safe" variants of the following:

  • lfu_cache - the least-frequently-used caching algorithm
  • lru_cache - the least-recently-used caching algorithm
  • mru_cache - the most-recently-used caching algorithm
  • rr_cache - the random-replacement caching algorithm
  • no_cache - a dummy caching interface to archiving
  • inf_cache - an infinitely-growing cache

klepto has the following archive types:

  • file_archive - a dictionary-style interface to a file
  • dir_archive - a dictionary-style interface to a folder of files
  • sqltable_archive - a dictionary-style interface to a sql database table
  • sql_archive - a dictionary-style interface to a sql database
  • hdfdir_archive - a dictionary-style interface to a folder of hdf5 files
  • hdf_archive - a dictionary-style interface to a hdf5 file
  • dict_archive - a dictionary with an archive interface
  • null_archive - a dictionary-style interface to a dummy archive

klepto provides the following keymaps:

  • keymap - keys are raw Python objects
  • hashmap - keys are a hash for the Python object
  • stringmap - keys are the Python object cast as a string
  • picklemap - keys are the serialized Python object

klepto also includes a few useful decorators providing:

  • simple, shallow, or deep rounding of function arguments
  • cryptographic key generation, with masking of selected arguments

Current Release Downloads Conda Downloads Stack Overflow

The latest released version of klepto is available from: https://pypi.org/project/klepto

klepto is distributed under a 3-clause BSD license.

Development Version Support Documentation Status Build Status codecov

You can get the latest development version with all the shiny new features at: https://github.com/uqfoundation

If you have a new contribution, please submit a pull request.

Installation

klepto can be installed with pip::

$ pip install klepto

To include optional archive backends, such as HDF5 and SQL, in the install::

$ pip install klepto[archives]

To include optional serializers, such as jsonpickle, in the install::

$ pip install klepto[crypto]

Requirements

klepto requires:

  • python (or pypy), >=3.8
  • setuptools, >=42
  • dill, >=0.3.9
  • pox, >=0.3.5

Optional requirements:

  • h5py, >=2.8.0
  • pandas, >=0.17.0
  • sqlalchemy, >=1.4.0
  • jsonpickle, >=0.9.6
  • cloudpickle, >=0.5.2

More Information

Probably the best way to get started is to look at the documentation at http://klepto.rtfd.io. Also see klepto.tests for a set of scripts that test the caching and archiving functionalities in klepto. You can run the test suite with python -m klepto.tests. The source code is also generally well documented, so further questions may be resolved by inspecting the code itself. Please feel free to submit a ticket on github, or ask a question on stackoverflow (@Mike McKerns). If you would like to share how you use klepto in your work, please send an email (to mmckerns at uqfoundation dot org).

Citation

If you use klepto to do research that leads to publication, we ask that you acknowledge use of klepto by citing the following in your publication::

Michael McKerns and Michael Aivazis,
"pathos: a framework for heterogeneous computing", 2010- ;
https://uqfoundation.github.io/project/pathos

Please see https://uqfoundation.github.io/project/pathos or http://arxiv.org/pdf/1202.1056 for further information.