Difference between revisions of "Old-reactive"
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== Abstract == |
== Abstract == |
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| − | '''Reactive''' is a simple foundation for programming reactive systems functionally. Like Fran/FRP, it has a notions of (reactive) behaviors and events. Like [[DataDriven]], Reactive has a data-driven implementation. The main difference between Reactive and DataDriven |
+ | '''Reactive''' is a simple foundation for programming reactive systems functionally. Like Fran/FRP, it has a notions of (reactive) behaviors and events. Like [[DataDriven]], Reactive has a data-driven implementation. The main difference between Reactive and DataDriven are |
| + | * Reactive builds on STM-based IVars, while DataDriven builds on continuation-based computations; and |
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| + | * The algebra of Events and reactive values (called "sources" in DataDriven) are ''purely'' functional. I couldn't figure out how to accomplish that in DataDriven. |
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The inspiration for Reactive was Mike Sperber's [[http://www-pu.informatik.uni-tuebingen.de/lula/deutsch/publications.html Lula]] implementation of FRP. Mike used blocking threads, which I had never considered for FRP. While playing with the idea, I realized that I could give a very elegant and efficient solution to caching, which DataDriven doesn't do. (For an application <hask>f <*> a</hask> of a varying function to a varying argument, caching remembers the latest function to apply to a new argument and the last argument to which to apply a new function.) |
The inspiration for Reactive was Mike Sperber's [[http://www-pu.informatik.uni-tuebingen.de/lula/deutsch/publications.html Lula]] implementation of FRP. Mike used blocking threads, which I had never considered for FRP. While playing with the idea, I realized that I could give a very elegant and efficient solution to caching, which DataDriven doesn't do. (For an application <hask>f <*> a</hask> of a varying function to a varying argument, caching remembers the latest function to apply to a new argument and the last argument to which to apply a new function.) |
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Revision as of 06:10, 10 December 2007
Abstract
Reactive is a simple foundation for programming reactive systems functionally. Like Fran/FRP, it has a notions of (reactive) behaviors and events. Like DataDriven, Reactive has a data-driven implementation. The main difference between Reactive and DataDriven are
- Reactive builds on STM-based IVars, while DataDriven builds on continuation-based computations; and
- The algebra of Events and reactive values (called "sources" in DataDriven) are purely functional. I couldn't figure out how to accomplish that in DataDriven.
The inspiration for Reactive was Mike Sperber's [Lula] implementation of FRP. Mike used blocking threads, which I had never considered for FRP. While playing with the idea, I realized that I could give a very elegant and efficient solution to caching, which DataDriven doesn't do. (For an application f <*> a of a varying function to a varying argument, caching remembers the latest function to apply to a new argument and the last argument to which to apply a new function.)
As with DataDriven, Reactive provides instances for Monoid, Functor, Applicative, and Monad.
Besides this wiki page, here are more ways to find out about Reactive:
- Read the Haddock docs.
- Get the code repository: darcs get http://darcs.haskell.org/packages/reactive.
- Install from Hackage (coming).
- See the version history.
Please leave comments at the Talk page.