All Projects → ThoughtWorksInc → Dsl.scala

ThoughtWorksInc / Dsl.scala

Licence: apache-2.0
A framework to create embedded Domain-Specific Languages in Scala

Programming Languages

scala
5932 projects
dsl
153 projects

Projects that are alternatives of or similar to Dsl.scala

f
a library to write async vert.x code similar as using java syntax
Stars: ✭ 22 (-90%)
Mutual labels:  monad, future
future.scala
Stack-safe asynchronous programming
Stars: ✭ 38 (-82.73%)
Mutual labels:  monad, future
asynqro
Futures and thread pool for C++ (with optional Qt support)
Stars: ✭ 103 (-53.18%)
Mutual labels:  monad, future
Fluture
🦋 Fantasy Land compliant (monadic) alternative to Promises
Stars: ✭ 2,249 (+922.27%)
Mutual labels:  monad, future
Fun Task
Abstraction for managing asynchronous code in JS
Stars: ✭ 363 (+65%)
Mutual labels:  monad, future
Asyncninja
A complete set of primitives for concurrency and reactive programming on Swift
Stars: ✭ 146 (-33.64%)
Mutual labels:  future
Java Concurrency Examples
Java Concurrency/Multithreading Tutorial with Examples for Dummies
Stars: ✭ 173 (-21.36%)
Mutual labels:  future
Unityfx.async
Asynchronous operations (promises) for Unity3d.
Stars: ✭ 143 (-35%)
Mutual labels:  future
Catch Exception
Stars: ✭ 137 (-37.73%)
Mutual labels:  exception-handling
Asyncfuture
Use QFuture like a Promise object
Stars: ✭ 193 (-12.27%)
Mutual labels:  future
Object Oriented Programming Using Python
Python is a multi-paradigm programming language. Meaning, it supports different programming approach. One of the popular approach to solve a programming problem is by creating objects. This is known as Object-Oriented Programming (OOP).
Stars: ✭ 183 (-16.82%)
Mutual labels:  exception-handling
Mostly Adequate Guide Chinese
函数式编程指北中文版
Stars: ✭ 2,093 (+851.36%)
Mutual labels:  monad
Promise
Promise / Future library for Go
Stars: ✭ 149 (-32.27%)
Mutual labels:  future
Fushare
A utility for fundamentals data of China commodity futures
Stars: ✭ 176 (-20%)
Mutual labels:  future
Qtpromise
Promises/A+ implementation for Qt/C++
Stars: ✭ 137 (-37.73%)
Mutual labels:  future
Funcadelic.js
Functional programming and category theory for everyday JavaScript development
Stars: ✭ 183 (-16.82%)
Mutual labels:  monad
Functional Promises
Write code like a story w/ a powerful Fluent (function chaining) API
Stars: ✭ 141 (-35.91%)
Mutual labels:  monad
Swift Adventures In Monad Land
A Swift adventure with Optionals, Monads, bananas and squirrels
Stars: ✭ 166 (-24.55%)
Mutual labels:  monad
Fpgo
Monad, Functional Programming features for Golang
Stars: ✭ 165 (-25%)
Mutual labels:  monad
Future.apply
🚀 R package: future.apply - Apply Function to Elements in Parallel using Futures
Stars: ✭ 159 (-27.73%)
Mutual labels:  future

Dsl.scala

Build Status Maven Central Scaladoc Join the chat at https://gitter.im/ThoughtWorksInc/Dsl.scala

Dsl.scala is a framework to create embedded Domain-Specific Languages in Scala. It can be considered as an alternative syntax to for comprehension, Scala Async and Scala Continuations. It unifies monads, generators, asynchronous functions, coroutines and continuations to a single universal syntax, and can be easily integrate to Scalaz, Cats, Scala Collections, Scala Futures, Akka HTTP, Java NIO, or your custom domains.

A DSL author is able to create language keywords by implementing the Dsl trait, which contains only one abstract method to be implemented. No knowledge about Scala compiler or AST macros is required.

DSLs written in Dsl.scala are collaborative with others DSLs and Scala control flows. A DSL user can create functions that contains interleaved DSLs implemented by different vendors, along with ordinary Scala control flows.

We also provide some built-in keywords, including:

  • The Await keyword for creating memoized asynchronous values as Scala Futures, similar to the await / async keywords in C#, Python and JavaScript.
  • The Shift keyword for creating asynchronous tasks as delimited continuations, similar to the shift operator in Scala Continuations.
  • The AsynchronousIo.Connect, AsynchronousIo.Accept, AsynchronousIo.Read and AsynchronousIo.Write keywords for performing I/O on an asynchronous channel.
  • The Yield keyword for generating lazy streams, similar to yield in C#, Python and JavaScript.
  • The Each keyword for iterating on a collection, similar to the list comprehension feature in Scala, Haskell, OCaml, Python and Lisp.
  • The Continue keyword LDK for skipping an element in an Each collection comprehension, similar to the native continue keyword in C/C++ or the mzero in Haskell.
  • The Fork keyword for duplicating current context, similar to the fork system call in POSIX.
  • The Return keyword for early returning, similar to the native return keyword in Scala.
  • The Using keyword to automatically close resources when exiting a scope, similar to the native using keyword in C#.
  • The Monadic keyword for creating Scalaz or Cats monadic control flow, similar to the !-notation in Idris.
  • The NullSafe keyword for the null safe operator, similar to the ? operator in Kotlin and Groovy.
  • The NoneSafe keyword for the None safe operator, similar to the Maybe monad in Haskell.

All the above keywords can be used together with each others. For example you can perform list comprehension to manipulate native resources in an asynchronous task by using Each, Using and Shift together.

Getting Started

Suppose you want to create a random number generator. The generated numbers should be stored in a lazily evaluated infinite stream, which can be built with the help of our built-in domain-specific keyword Yield.

So, you need to add the library that contains the implementation of the keyword Yield:

// Add the "keywords-yield" library in your build.sbt, to use the `Yield` keyword
libraryDependencies += "com.thoughtworks.dsl" %% "keywords-yield" % "latest.release"

// Add other "keywords-xxx" libraries in your build.sbt, to use other keywords
// libraryDependencies += "com.thoughtworks.dsl" %% "keywords-xxx" % "latest.release"

And the Dsl.scala compiler plug-ins that are shared by all DSLs:

// Add the following settings in your build.sbt 
addCompilerPlugin("com.thoughtworks.dsl" %% "compilerplugins-bangnotation" % "latest.release")
addCompilerPlugin("com.thoughtworks.dsl" %% "compilerplugins-reseteverywhere" % "latest.release")

The random number generator can be implemented as a recursive function that produces the next random number in each iteration.

import com.thoughtworks.dsl.keywords.Yield
// Must not annotated with @tailrec
def xorshiftRandomGenerator(seed: Int): scala.collection.immutable.Stream[Int] = {
  val tmp1 = seed ^ (seed << 13)
  val tmp2 = tmp1 ^ (tmp1 >>> 17)
  val tmp3 = tmp2 ^ (tmp2 << 5)
  !Yield(tmp3)
  xorshiftRandomGenerator(tmp3)
}

Note that a keyword is a plain case class. You need a ! prefix to the keyword to activate the DSL.

It's done. We can test it in ScalaTest:

val myGenerator = xorshiftRandomGenerator(seed = 123)
myGenerator(0) should be(31682556)
myGenerator(1) should be(-276305998)
myGenerator(2) should be(2101636938)

The call to xorshiftRandomGenerator does not throw a StackOverflowError because the execution of xorshiftRandomGenerator will be paused at the keyword Yield, and it will be resumed when the caller is looking for the next number.

Showcases

(Feel free to add your project here)

Links and related works

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].