persistent caching to memory, disk, or database
Project description
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
The latest released version of klepto is available from:
klepto is distributed under a 3-clause BSD license.
Development Version
You can get the latest development version with all the shiny new features at:
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, >=0.3.8
pox, >=0.3.4
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.
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