There are many libraries or approaches for doing dependency injection in Scala. Grafter goes back to the fundamentals of dependency injection by just using constructor injection: no reflection, no xml, no annotations, no inheritance or self-types.
Then, Grafter adds to constructor injection just the necessary support to:
- instantiate a component-based application from a configuration
- fine-tune the wiring (create singletons)
- test the application by replacing components
- start / stop the application
Grafter is targeting every possible application because it focuses on associating just 3 ideas:
- case classes and interfaces for components
Reader
instances and shapeless for the configuration- tree rewriting and kiama for everything else!
Please try it and report your experience:
- how is it better / worse than another library?
- is the core model more approachable than other libraries?
- what could be improved?
Grafter components are very simple: they are just case classes (possibly) implementing interfaces.
- components can depend on other components by having them as case class members
- the application is the top-level component
- the application configuration is a just a case class (can be read from a file if necessary)
- each component can be instantiated from the application configuration
- so it is possible to recursively build the full application as a tree of components from the application configuration
- singletons can be made by rewriting the tree, effectively making it a graph
- the application can be started bottom-up by starting the components
extending the
Start
markup trait - the application can also be stopped top-down by stopping all the components
extending the
Stop
markup trait - mocking the application for testing can also be done by rewriting the tree
Let's see this on a concrete example.
The configuration of the application is a case class possibly containing other case classes. For the examples below we will use
case class ApplicationConfig(
http: HttpConfig,
db: DbConfig
)
case class HttpConfig(host: String,
port: Int)
case class DbConfig(url: String)
A component of the application is a case class. It must know how to
instantiate itself from the configuration. In other terms there needs to be
a Reader[ApplicationConfig, Component]
instance in scope.
For example
case class HttpServer(config: HttpConfig)
import cats.data.Reader
import cats.implicits._
object HttpServer {
// we can "map" on a Reader!
implicit def reader: Reader[ApplicationConfig, HttpServer] =
HttpConfig.reader.map(HttpServer.apply)
}
object HttpConfig {
// the HttpConfig is extracted directly from
// the application config
implicit def reader: Reader[ApplicationConfig, HttpConfig] =
Reader(_.http)
}
If a component depends on other components. Its Reader
instance
depends on its dependencies Reader
instances. Since this is all recursive
and automatable thanks to Shapeless we can write this
import org.zalando.grafter.GenericReader._
case class Application(httpServer: HttpServer, db: Database)
object Application {
// shapeless will automatically find Reader instances for
// HttpServer and Database
implicit def reader: Reader[ApplicationConfig, Application] =
genericReader
}
trait Database
object Database {
implicit def reader: Reader[ApplicationConfig, Database] =
PostgresDatabase.reader
}
case class PostgresDatabase(dbConfig: DbConfig) extends Start with Database {
def start: Eval[StartResult] =
StartResult.eval("postgres") {
// use dbConfig.url to initialize
}
}
object PostgresDatabase {
implicit def reader: Reader[ApplicationConfig, PostgresDatabase] =
genericReader
}
object DbConfig {
implicit def reader: Reader[ApplicationConfig, DbConfig] =
Reader(_.db)
}
Note that Application
depends on the Database
interface. When we
will create an Application
instance Database.reader
will be used and
will provide a Postgres
implementation by default. This means that
there must always be a default implementation for each interface introduced
in the system. But don't worry we can always change it later!
You may be wondering why a HttpServer
statically depends on the ApplicationConfig
here:
object HttpServer {
implicit def reader: Reader[ApplicationConfig, HttpServer] =
genericReader
}
To avoid this dependency lets parametrize the reader
with some config of type A
:
object HttpServer {
implicit def dependentReader[A](implicit
httpConfigReader: Reader[A, HttpConfig]
): Reader[A, HttpServer] = genericReader
}
This allows us to put the HttpServer
into a reusable module and build it independently from the ApplicationConfig
.
Next, implicitly provide a Reader[ApplicationConfing, HttConfig]
and you may create the HttpServer
.
Ultimately configuration components like DbConfig
above are extracted from ApplicationConfig
.
First, add macro-paradise plugin to your project
addCompilerPlugin("org.scalamacros" % "paradise" % "2.1.0" cross CrossVersion.full)
It is possible to generate Reader
instances for those values automatically with the @readers
annotation:
import org.zalando.grafter.macros._
@readers
case class ApplicationConfig(
db: DbConfig,
http: HttpConfig
)
Another common element is the implicit def reader
that returns genericReader
. It is possible to replace the companion object containing this function with a @reader[A]
annotation on the case class:
@reader[ApplicationConfig]
case class PostgresDatabase(dbConfig: DbConfig) extends Start {
def start: Eval[StartResult] =
Start.eval("postgres")(PostgresDriver.start(dbConfig.url))
}
// no need for the companion object
To create dependent reader use @dependentReader
annotation:
@dependentReader
case class PostgresDatabase(dbConfig: DbConfig)
First you need a full ApplicationConfig
val prod: ApplicationConfig = ApplicationConfig(
http = HttpConfig("localhost", 8080)
db = DbConfig("jdbc:localhost/database")
)
Then we can summon the implicit Reader
instance for Application
and
pass it the "prod" configuration:
val application: Application =
GenericReader[ApplicationConfig, Application].run(prod)
The next step is making sure that however deep our application graph is,
we will always use one database, even if 2 components declare 2 dependencies
to the database. This is done with the Rewriter
object:
import org.zalando.grafter.Rewriter
// can also be written application.singleton[Database]
// by importing Rewriter._
val app: Application =
Rewriter.singleton[Database, Application](application)
Now the application can be started, using the Rewriter
again which is
going to traverse the application graph and start each component implementing
Start
from the bottom up. If you scroll up you will see that PostgresDatabase
is such a component and must implement a start
method returning a StartResult
.
import cats._
val started: Eval[List[StartResult]] =
Rewriter.start(app)
The List[StartResult]
can be used to diagnose the start up and
produce a nice error message if something went wrong.
The application can also be stopped using the Rewriter
. It will stop
each component implementing Stop
from the top down.
import cats._
val stop: Eval[List[StopResult]] =
Rewriter.stop(app)
The major difference between the start and the stop strategies is that all the components will try to be stopped regardless of failures.
The List[StopResult]
can be used to diagnose the shutdown and
produce a nice error message if something went wrong.
For integration testing you generally need to replace components which are
at the frontier of your system and deeply embedded in your application.
This is done once again with Rewriter
import org.zalando.grafter._, Rewriter._
object mockDb extends Database {
// mock the database operations
}
// you can also rewrite the prod configuration!
val testConfiguration =
Application.prod.
replace[HttpConfig](HttpConfig("localhost", 8080))
// create the application
// from the test config
// and mock the database
val application: Application =
GenericReader[ApplicationConfig, Application].
run(testConfiguration).
singleton[Database].
replace[Database](mockDb)
It might be necessary to inspect (or test) the results of modifications on your application graph after several modifications with
singleton
and modify
.
For example you might want to collect all the distinct components of a given type:
import org.zalando.grafter.syntax.query._
val application = Application.prod.
replace[HttpConfig](HttpConfig("localhost", 8080))
// this should contain the previously set http config
val httpConfigs: List[HttpConfig] =
application.collect[HttpConfig]
You might also want to check what are all the components using a component of a given type:
import org.zalando.grafter.syntax.query._
val application = Application.prod.
singleton[ExecutionService]
// this is a map where the keys are distinct instances of ExecutionService
// (there should be only one, since we made a singleton)
// and a list of all the paths from that key to the root
val usersOfExecutionService: Map[ExecutionService, List[List[Any]]] =
application.ancestors[ExecutionService]
In order for the GenericReader
functionality to work you need to
import it where you want Reader
instances to be generated.
You can:
-
create a package object for your project to contain a few convenience aliases for your specific configuration type
-
have your application configuration object (say
ApplicationConfig
) extend theGenericReader
trait to import the generic implicits into its implicit scope so that they are found whenever a componentX
tries to build aReader[ApplicationConfig, X]
-
use the
@readers
annotation to yourApplicationConfig
to generate the necessary readers for finding sub-configuration values, for exampleReader[ApplicationConfig, HttpConfig]
package com.acme
import org.zalando.grafter
import shapeless._
package object config {
type ConfigReader[A] = Reader[ApplicationConfig, A]
def createReader[A, B](implicit gen: LabelledGeneric.Aux[A, B], repr: Lazy[ConfigReader[B]]): ConfigReader[A] =
genericReader[ApplicationConfig, A, B](gen, repr)
def configure[A](c: ApplicationConfig)(implicit r: ConfigReader[A]): A =
r(c)
}
@readers
object ApplicationConfig extends GenericReader
You add this library as a sbt dependency:
libraryDependencies += "org.zalando" %% "grafter" % "1.4.2"
Please read our contributor guidelines for more details. And please check these open issues for specific tasks.
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