cached: Cache values to disk.

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The module Data.Cached lets you cache values to disk to avoid re-running (potentially long) computations between consecutive executions of your program. Cached values are recomputed only when needed, i.e. when other cached values on which they depend change. Independent computations are run in parallel. It offers convenient fonctions for caching to text files, but caching and uncaching using arbitrary IO actions is also possible.

The module was motivated by writing scientific data flows, simulation experiments or data science scripts. Those often involve long computations and create "flows" where the output of some computation are the inputs of others, until final results are produced (values, figures, statistical tests, etc.).

See the module Data.Cached documentation:


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Properties

Versions 0.1.0.0, 0.1.0.0
Change log ChangeLog.md
Dependencies base (>=4.7 && <5), containers (>=0.5.10 && <0.7), protolude (>=0.2.2 && <0.3), shake (>=0.16.4 && <0.18), text (>=1.2.3 && <1.3) [details]
License BSD-3-Clause
Copyright 2018 Guillaume Chérel
Author Guillaume Chérel
Maintainer guillaume.cherel@iscpif.fr
Category Workflow, Data Flow
Home page https://github.com/guillaumecherel/cached#readme
Bug tracker https://github.com/guillaumecherel/cached/issues
Source repo head: git clone https://github.com/guillaumecherel/cached
Uploaded by GuillaumeCherel at 2019-03-05T10:46:45Z

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Readme for cached-0.1.0.0

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cached

Cache values to disk.

The module Data.Cached lets you cache values to disk to avoid re-running (potentially long) computations between consecutive executions of your program. Cached values are recomputed only when needed, i.e. when other cached values on which they depend change. Independent computations are run in parallel. It offers convenient fonctions for caching to text files, but caching and uncaching using arbitrary IO actions is also possible.

The module was motivated by writing scientific data flows, simulation experiments or data science scripts. Those often involve long computations and create "flows" where the output of some computation are the inputs of others, until final results are produced (values, figures, statistical tests, etc.).

See the module Data.Cached documentation: