Changes in Compiler Plugins
Compiler plugins are supported by Dotty (and Scala 3) since 0.9. There are two notable changes compared to scalac
:
- No support for analyzer plugins
- Added support for research plugins
Analyzer plugins in scalac
run during type checking and may influence normal type checking. This is a very powerful feature but for production usages, a predictable and consistent type checker is more important.
For experimentation and research, Scala 3 introduces research plugin. Research plugins are more powerful than scalac
analyzer plugins as they let plugin authors customize the whole compiler pipeline. One can easily replace the standard typer by a custom one or create a parser for a domain-specific language. However, research plugins are only enabled for nightly or snaphot releases of Scala 3.
Common plugins that add new phases to the compiler pipeline are called standard plugins in Scala 3. In terms of features, they are similar to scalac
plugins, despite minor changes in the API.
Using Compiler Plugins
Both standard and research plugins can be used with scalac
by adding the -Xplugin:
option:
scalac -Xplugin:pluginA.jar -Xplugin:pluginB.jar Test.scala
The compiler will examine the jar provided, and look for a property file named plugin.properties
in the root directory of the jar. The property file specifies the fully qualified plugin class name. The format of a property file is as follows:
pluginClass=dividezero.DivideZero
This is different from scalac
plugins that required a scalac-plugin.xml
file.
Starting from 1.1.5, sbt
also supports Scala 3 compiler plugins. Please refer to the sbt
documentation for more information.
Writing a Standard Compiler Plugin
Here is the source code for a simple compiler plugin that reports integer divisions by zero as errors.
package dividezero
import dotty.tools.dotc.ast.Trees.*
import dotty.tools.dotc.ast.tpd
import dotty.tools.dotc.core.Constants.Constant
import dotty.tools.dotc.core.Contexts.Context
import dotty.tools.dotc.core.Decorators.*
import dotty.tools.dotc.core.StdNames.*
import dotty.tools.dotc.core.Symbols.*
import dotty.tools.dotc.plugins.{PluginPhase, StandardPlugin}
import dotty.tools.dotc.transform.{Pickler, Staging}
class DivideZero extends StandardPlugin:
val name: String = "divideZero"
override val description: String = "divide zero check"
def init(options: List[String]): List[PluginPhase] =
(new DivideZeroPhase) :: Nil
class DivideZeroPhase extends PluginPhase:
import tpd.*
val phaseName = "divideZero"
override val runsAfter = Set(Pickler.name)
override val runsBefore = Set(Staging.name)
override def transformApply(tree: Apply)(implicit ctx: Context): Tree =
tree match
case Apply(Select(rcvr, nme.DIV), List(Literal(Constant(0))))
if rcvr.tpe <:< defn.IntType =>
report.error("dividing by zero", tree.pos)
case _ =>
()
tree
end DivideZeroPhase
The plugin main class (DivideZero
) must extend the trait StandardPlugin
and implement the method init
that takes the plugin's options as argument and returns a list of PluginPhase
s to be inserted into the compilation pipeline.
Our plugin adds one compiler phase to the pipeline. A compiler phase must extend the PluginPhase
trait. In order to specify when the phase is executed, we also need to specify a runsBefore
and runsAfter
constraints that are list of phase names.
We can now transform trees by overriding methods like transformXXX
.
Writing a Research Compiler Plugin
Here is a template for research plugins.
import dotty.tools.dotc.core.Contexts.Context
import dotty.tools.dotc.core.Phases.Phase
import dotty.tools.dotc.plugins.ResearchPlugin
class DummyResearchPlugin extends ResearchPlugin:
val name: String = "dummy"
override val description: String = "dummy research plugin"
def init(options: List[String], phases: List[List[Phase]])(implicit ctx: Context): List[List[Phase]] =
phases
end DummyResearchPlugin
A research plugin must extend the trait ResearchPlugin
and implement the method init
that takes the plugin's options as argument as well as the compiler pipeline in the form of a list of compiler phases. The method can replace, remove or add any phases to the pipeline and return the updated pipeline.