The machines package

[Tags: bsd3, library]

Networked stream transducers

Rúnar Bjarnason's talk on machines can be downloaded from: https://dl.dropbox.com/u/4588997/Machines.pdf


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Versions0.1, 0.1.1, 0.1.2, 0.2.1, 0.2.1.1, 0.2.1.2, 0.2.1.3, 0.2.2, 0.2.3, 0.2.3.1, 0.2.4, 0.2.5, 0.4, 0.4.0.1, 0.4.1, 0.5.1, 0.6
Change logCHANGELOG.markdown
Dependenciesadjunctions (>=4.2 && <5), base (>=4.5 && <5), comonad (>=3 && <5), containers (>=0.3 && <0.6), distributive (<0.5), free (>=3.1.1 && <5), mtl (>=2 && <2.3), pointed (>=3 && <5), profunctors (>=3 && <6), semigroupoids (==5.*), semigroups (>=0.8.3 && <1), transformers (>=0.3 && <0.5), transformers-compat (>=0.3), void (>=0.6.1 && <1) [details]
LicenseBSD3
CopyrightCopyright (C) 2012-2015 Edward A. Kmett
AuthorEdward A. Kmett, Rúnar Bjarnason, Josh Cough
MaintainerEdward A. Kmett <ekmett@gmail.com>
Stabilityprovisional
CategoryControl, Enumerator
Home pagehttp://github.com/ekmett/machines/
Bug trackerhttp://github.com/ekmett/machines/issues
Source repositoryhead: git clone git://github.com/ekmett/machines.git
UploadedWed Jan 13 03:13:23 UTC 2016 by EdwardKmett
DistributionsLTSHaskell:0.5.1, NixOS:0.6, Stackage:0.5.1
Downloads5197 total (43 in last 30 days)
Votes
4 []
StatusDocs available [build log]
Last success reported on 2016-01-13 [all 1 reports]

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For package maintainers and hackage trustees

Readme for machines-0.6

machines

Hackage Build Status

Ceci n'est pas une pipe

Machines are demand driven input sources like pipes or conduits, but can support multiple inputs.

You design a Machine by writing a Plan. You then construct the machine.

Simple machines that take one input are called a Process and processes form a Category. More generally you can attach a Process to the output of any type of Machine, yielding a new Machine.

More complicated machines provide other ways of connecting to them.

Typically the use of machines proceeds by using simple plans into machine Tees and Wyes, capping many of the inputs to those with possibly monadic sources, feeding the rest input (possibly repeatedly) and calling run or runT to get the answers out.

There is a lot of flexibility when building a machine in choosing between empowering the machine to run its own monadic effects or delegating that responsibility to a custom driver.

A port of this design to scala is available from runarorama/scala-machines

Runar's slides are also available from https://dl.dropbox.com/u/4588997/Machines.pdf

Some worked examples are here https://github.com/alanz/machines-play

Contact Information

Contributions and bug reports are welcome!

Please feel free to contact me through github or on the #haskell IRC channel on irc.freenode.net.

-Edward Kmett