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This note outlines a principled way to meta-programming in Scala. It tries to
combine the best ideas from LMS and Scala macros in a minimalistic design.
LMS: Types matter. Inputs, outputs and transformations should all be statically typed.
Macros: Quotations are ultimately more easy to deal with than implicit-based type-lifting
LMS: Some of the most interesting and powerful applications of meta-programming
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A simple embedded probabilistic programming language
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Every application ever written can be viewed as some sort of transformation on data. Data can come from different sources, such as a network or a file or user input or the Large Hadron Collider. It can come from many sources all at once to be merged and aggregated in interesting ways, and it can be produced into many different output sinks, such as a network or files or graphical user interfaces. You might produce your output all at once, as a big data dump at the end of the world (right before your program shuts down), or you might produce it more incrementally. Every application fits into this model.
The scalaz-stream project is an attempt to make it easy to construct, test and scale programs that fit within this model (which is to say, everything). It does this by providing an abstraction around a "stream" of data, which is really just this notion of some number of data being sequentially pulled out of some unspecified data source. On top of this abstraction, sca
Init.d shell script for Play framework distributed application. Provides start, stop, restart and status commands to control applications packaged using standard "play dist" packaging command.
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