gRPC Kotlin Coroutines, Protobuf DSL, Scripting for Protoc

Community Contributions are Welcomed

ℹ️ | Docs are being expanded and moved to Readme.io

Quick Start: gRPC Coroutines

Run the following command to get started with a preconfigured template project. (kotlin-coroutines-gRPC-template)

git clone https://github.com/marcoferrer/kotlin-coroutines-gRPC-template && \
cd kotlin-coroutines-gRPC-template && \
./gradlew run

Version 0.5.0

CHANGELOG
Most notable changes
- Support for (google.api.method_signature) method option in gRPC clients and stub extension code generators. More info available here
- Bug fixes and performance improvements for streaming APIs in gRPC coroutines
- Improvements to stub extension generator output
- Tests are now executed against JDK8, JDK10, JDK11, JDK12
In Progress: Multiplatform Protobuf Messages w/ Kotlinx Serialization

Getting Started

Gradle
Maven

Code Generators

There are several built in code generators that each accept unique configuration options.
Configuration Setup
- Proto Builder Generator
- gRPC Coroutines Client & Server
- gRPC Stub Extensions
  - Rpc Method Coroutine Support
- Mock Service Generator
- Extendable Messages Generator
- User Defined Generator Scripts
  - Insertion Scripts
  - Generator Scripts

Proto Builder Generator (Message DSL)

Setup & Documentation

This generator creates lambda based builders for message types

     val starPlatinum = Stand {
        name = "Star Platinum"
        powerLevel = 500
        speed = 550
        attack {
            name = "ORA ORA ORA"
            damage = 100
            range = Attack.Range.CLOSE
        }
    }
    
    val attack = Attack {
        name = "ORA ORA ORA"
        damage = 100
        range = Attack.Range.CLOSE
    }
    
    // Copy extensions
    val newAttack = attack.copy { damage = 200 }            
    
    // orDefault() will return the messages default instance when null
    val nullableAttack: Attack? = null
    nullableAttack.orDefault()
    
    // Plus operator extensions 
    val mergedAttack = attack + Attack { name = "Sunlight Yellow Overdrive" }

gRPC Coroutines Client & Server

This option requires the artifact kroto-plus-coroutines as a dependency.

Configuration Options

Client / Server Examples
Method Signature Option Support

Design
- Back pressure is supported via Manual Flow Control
  - Related Reading: Understanding Reactive gRPC Flow Control
- Cooperative cancellation across network boundaries.
Client Stubs
- Designed to work well with Structured Concurrency
- Cancellation of the client CoroutineScope will propagate to the server.
- Cancellations can now be propagated across usages of a specific stub instance.
- Rpc methods are overloaded with inline builders for request types
- The request parameter for rpc methods defaults to RequestType.defaultsInstance

// Creates new stub with a default coroutine context of `EmptyCoroutineContext`
val stub = GreeterCoroutineGrpc.newStub(channel)

// Suspends and creates new stub using the current coroutine context as the default. 
val stub = GreeterCoroutineGrpc.newStubWithContext(channel)

// An existing stub can replace its current coroutine context using either 
stub.withCoroutineContext()
stub.withCoroutineContext(coroutineContext)

// Stubs can accept message builder lambdas as an argument  
stub.sayHello { name = "John" }

// For more idiomatic usage in coroutines, stubs can be created
// with an explicit coroutine scope using the `newGrpcStub` scope extension function.
launch {
    // Using `newGrpcStub` makes it clear that the resulting stub will use the receiving 
    // coroutine scope to launch any concurrent work. (usually for manual flow control in streaming apis) 
    val stub = newGrpcStub(GreeterCoroutineGrpc.GreeterCoroutineStub, channel)
    
    val (requestChannel, responseChannel) = stub.sayHelloStreaming()
    ...
}

Service Base Impl
- Rpc calls are wrapped within a scope initialized with the following context elements.
  - CoroutineName set to MethodDescriptor.fullMethodName
  - GrpcContextElement set to io.grpc.Context.current()
- Base services implement ServiceScope and allow overriding the initial coroutineContext used for each rpc method invocation.
- Each services initialContext defaults to EmptyCoroutineContext
- A common case for overriding the initialContext is for setting up application specific ThreadContextElement or CoroutineDispatcher, such as MDCContext() or newFixedThreadPoolContext(...)

Cancellation Propagation

Client
- Both normal and exceptional coroutine scope cancellation will cancel the underlying call stream. See ClientCall.cancel() in io.grpc.ClientCall.java for more details.
- In the case of service implementations using coroutines, this client call stream cancellation will cancel the coroutine scope of the rpc method being invoked on the server.
Server
- Exceptional cancellation of the coroutine scope for the rpc method will be mapped to an instance of StatusRuntimeException and returned to the client.
- Normal cancellation of the coroutine scope for the rpc method will be mapped to an instance of StatusRuntimeException with a status of Status.CANCELLED, and returned to the client.
- Cancellation signals from the corresponding client will cancel the coroutine scope of the rpc method being invoked.

Examples

Unary
Client Streaming
Server Streaming
Bi-Directional Streaming

Unary

Client: Unary calls will suspend until a response is received from the corresponding server. In the event of a cancellation or the server responds with an error the call will throw the appropriate StatusRuntimeException

val response = stub.sayHello { name = "John" }

Server: Unary rpc methods can respond to client requests by either returning the expected response type, or throwing an exception.

override suspend fun sayHello(request: HelloRequest): HelloReply {

    if (isValid(request.name))
        return HelloReply { message = "Hello there, ${request.name}!" } else
        throw Status.INVALID_ARGUMENT.asRuntimeException()
}

Client Streaming

Client: requestChannel.send() will suspend until the corresponding server signals it is ready by requesting a message. In the event of a cancellation or the server responds with an error, both requestChannel.send() and response.await(), will throw the appropriate StatusRuntimeException.

val (requestChannel, response) = stub.sayHelloClientStreaming()

launchProducerJob(requestChannel){
    repeat(5){
        send { name = "name #$it" }
    }
}

println("Client Streaming Response: ${response.await()}")

Server: Client streaming rpc methods can respond to client requests by either returning the expected response type, or throwing an exception. Calls to requestChannel.receive() will suspend and notify the corresponding client that the server is ready to accept a message.

override suspend fun sayHelloClientStreaming(
    requestChannel: ReceiveChannel<HelloRequest>
): HelloReply =  HelloReply {
    message = requestChannel.toList().joinToString()
}

Server Streaming

Client: responseChannel.receive() will suspend and notify the corresponding server that the client is ready to accept a message.

val responseChannel = stub.sayHelloServerStreaming { name = "John" }

responseChannel.consumeEach {
    println("Server Streaming Response: $it")
}

Server: Server streaming rpc methods can respond to client requests by submitting messages of the expected response type to the response channel. Completion of service method implementations will automatically close response channels in order to prevent abandoned rpcs.

Calls to responseChannel.send() will suspend until the corresponding client signals it is ready by requesting a message. Error responses can be returned to clients by either throwing an exception or invoking close on responseChannel with the desired exception.

For an example of how to implement long lived response streams please reference MultipleClientSubscriptionsExample.kt.

override suspend fun sayHelloServerStreaming(
    request: HelloRequest,
    responseChannel: SendChannel<HelloReply>
) {        
    for(char in request.name) {
        responseChannel.send {
            message = "Hello $char!"
        }
    }
}

Bi-Directional Streaming

Client: requestChannel.send() will suspend until the corresponding server signals it is ready by requesting a message. In the event of a cancellation or the server responds with an error, both requestChannel.send() and response.await(), will throw the appropriate StatusRuntimeException.

val (requestChannel, responseChannel) = stub.sayHelloStreaming()

launchProducerJob(requestChannel){
    repeat(5){
        send { name = "person #$it" }
    }
}

responseChannel.consumeEach {
    println("Bidi Response: $it")
}

Server: Bidi streaming rpc methods can respond to client requests by submitting messages of the expected response type to the response channel. Completion of service method implementations will automatically close response channels in order to prevent abandoned rpcs.

Calls to responseChannel.send() will suspend until the corresponding client signals it is ready by requesting a message. Error responses can be returned to clients by either throwing an exception or invoking close on responseChannel with the desired exception.

For an example of how to implement long lived response streams please reference MultipleClientSubscriptionsExample.kt.

override suspend fun sayHelloStreaming(
    requestChannel: ReceiveChannel<HelloRequest>,
    responseChannel: SendChannel<HelloReply>
) {
    requestChannel.mapTo(responseChannel){
    
        HelloReply {
            message = "Hello there, ${it.name}!"
        }
    }
}

gRPC Stub Extensions

Configuration Options

This modules generates convenience extensions that overload the request message argument for rpc methods with a builder lambda block and a default value. It also supports generating overloads based off (google.api.method_signature) method options. More info available here

               
    //Kroto+ Generated Extension
    val response = serviceStub.myRpcMethod {
         id = 100
         name = "some name"
    }

    //Original Java Fluent builders
    val response = serviceStub.myRpcMethod(ExampleServiceGrpc.MyRpcMethodRequest
        .newBuilder()
        .setId(100)
        .setName("some name")
        .build())

For unary rpc methods, the generator will create the following extensions

    //Future Stub with default argument
    fun ServiceBlockingStub.myRpcMethod(request: Request = Request.defaultInstance): ListenableFuture<Response>
    
    //Future Stub with builder lambda 
    inline fun ServiceFutureStub.myRpcMethod(block: Request.Builder.() -> Unit): ListenableFuture<Response>
        
    //Blocking Stub with default argument
    fun ServiceBlockingStub.myRpcMethod(request: Request = Request.defaultInstance): Response
    
    //Blocking Stub with builder lambda
    inline fun ServiceBlockingStub.myRpcMethod(block: Request.Builder.() -> Unit): Response

Coroutine Support

In addition to request message arguments as builder lambda rpc overloads, coroutine overloads for rpc calls can also be generated. This provides the same functionality as the generated coroutine stubs. Usage is identical to the client examples outlined in Coroutine Client Examples.

This is accomplished by defining extension functions for async service stubs.
This option requires the artifact kroto-plus-coroutines as a dependency.
If using rpc interceptors or other code that relies on io.grpc.Context then you need to be sure to add a GrpcContextElement to your CoroutineContext when launching a coroutine. Child coroutines will inherit this ThreadContextElement and the dispatcher will ensure that your grpc context is present on the executing thread.

    Context.current().withValue(MY_KEY, myValue).attach()
    
    val myGrpcContext = Context.current()
    
    val job = launch( GrpcContextElement() ) { //Alternate usage:  myGrpcContext.asContextElement() 
       
        launch {
            assertEquals(myGrpcContext, Context.current())
        }
       
        GlobalScope.launch{
            assertNotEquals(myGrpcContext, Context.current())
        } 
    }

Mock Service Generator

Configuration Options

This generator creates mock implementations of proto service definitions. This is useful for orchestrating a set of expected responses, aiding in unit testing methods that rely on rpc calls. Full example for mocking services in unit tests. The code generated relies on the kroto-plus-test artifact as a dependency. It is a small library that provides utility methods used by the mock services.

If no responses are added to the response queue then the mock service will return the default instance of the response type.
Currently only unary methods are being mocked, with support for other method types on the way

@Test fun `Test Unary Response Queue`(){
    
    MockStandService.getStandByNameResponseQueue.apply {
       //Queue up a valid response message
       addMessage {
           name = "Star Platinum"
           powerLevel = 500
           speed = 550
           addAttacks {
               name = "ORA ORA ORA"
               damage = 100
               range = StandProto.Attack.Range.CLOSE
           }
       }   
          
       //Queue up an error
       addError(Status.INVALID_ARGUMENT)
   }
   
   val standStub = StandServiceGrpc.newBlockingStub(grpcServerRule.channel)
   
   standStub.getStandByName { name = "Star Platinum" }.let{ response ->
       assertEquals("Star Platinum",response.name)
       assertEquals(500,response.powerLevel)
       assertEquals(550,response.speed)
       response.attacksList.first().let{ attack ->
           assertEquals("ORA ORA ORA",attack.name)
           assertEquals(100,attack.damage)
           assertEquals(StandProto.Attack.Range.CLOSE,attack.range)
       }
   }
   
   try{
       standStub.getStandByName { name = "The World" }
       fail("Exception was expected with status code: ${Status.INVALID_ARGUMENT.code}")
   }catch (e: StatusRuntimeException){
       assertEquals(Status.INVALID_ARGUMENT.code, e.status.code)
   }
}

Extendable Messages Generator (Experimental)

Configuration Options

Generated code relies on the kroto-plus-message artifact. This generator adds tagging interfaces to the java classes produce by protoc. It also adds pseudo companion objects to provide a way to access proto message APIs in a non static manner. The following is a small example of how to write generic methods and extensions that resolve both message and builders type.

inline fun <reified M, B> M.copy( block: B.() -> Unit ): M
        where M : KpMessage<M, B>, B : KpBuilder<M> {
    return this.toBuilder.apply(block).build()
}

// Usage
myMessage.copy { ... }

inline fun <reified M, B> build( block: B.() -> Unit ): M
        where M : KpMessage<M, B>, B : KpBuilder<M> {

    return KpCompanion.Registry[M::class.java].build(block)
}

// Usage
build<MyMessage> { ... }

inline fun <M, B> KpCompanion<M, B>.build( block: B.() -> Unit ): M
        where B : KpBuilder<M>,M : KpMessage<M,B> {

    return newBuilder().apply(block).build()
}

// Usage
MyMessage.Companion.build { ... }

User Defined Generator Scripts

Users can define kotlin scripts that they would like to run during code generation. For type completion, scripts can be couple with a small gradle build script, although this is completely optional. Samples are available in the kp-script directory of the example project.

There are two categories of scripts available.

Insertion Scripts
- Configuration Options
- Using the insertion api from the java protoc plugin, users can add code at specific points in generated java classes.
- This is useful for adding code to allow more idiomatic use of generated java classes from Kotlin.
- The entire ExtendableMessages generator can be implemented using an insertion script, an example can be in the example script extendableMessages.kts.
- Additional information regarding the insertion api can be found in the official docs
Generator Scripts
- Configuration Options
- These scripts implement the Generator interface used by all internal kroto+ code generators.
- Generators rely on the GeneratorContext, which is available via the property context.
- The context is used for iterating over files, messages, and services submitted by protoc.
- Example usage can be found in the kp-script directory of the example project, as well as inside the generators package of the protoc-gen-kroto-plus artifact.

Community Scripts

Community contributions for scripts are welcomed and more information regarding guidelines will be published soon.

Method Signature Options Support

Usage of (google.api.method_signature) method option is now supported. This allows users to customize the method parameters outputted in generated clients as well as stub extensions. To config your rpc methods, first add the google common proto dependency to your build

dependencies{
    compileOnly "com.google.api.grpc:proto-google-common-protos:1.16.0"
}

Then add the following import to your proto definition.

import "google/api/client.proto";

Now the method option should be available for usage in your method definition

// Sends a greeting
rpc SayHello (HelloRequest) returns (HelloReply){
    option (google.api.method_signature) = "name";
};

This will result in the following method signature being outputed from gRPC and stub extension code generators.

 fun GreeterStub.sayHello(name: String): HelloReply{
    val request = HelloRequest.newBuilder()
        .setName(name)
        .build()
    return sayHello(request)
 }

Getting Started With Gradle

Repositories

Available on jcenter() or mavenCentral()
SNAPSHOT

repositories {
    maven { url 'https://oss.jfrog.org/artifactory/oss-snapshot-local' }
}

Bintray

// Useful when syncronization to jcenter or maven central are taking longer than expected
repositories {
    maven { url 'https://dl.bintray.com/marcoferrer/kroto-plus/' }
}

Configuring Protobuf Gradle Plugin

plugins{
    id 'com.google.protobuf' version '0.8.6'
}

protobuf {
    protoc { artifact = "com.google.protobuf:protoc:$protobufVersion"}

    plugins {
        kroto {
            artifact = "com.github.marcoferrer.krotoplus:protoc-gen-kroto-plus:$krotoPlusVersion"
        }
    }

    generateProtoTasks {
        def krotoConfig = file("krotoPlusConfig.asciipb") // Or .json

        all().each{ task ->
            // Adding the config file to the task inputs lets UP-TO-DATE checks
            // include changes to configuration
            task.inputs.files krotoConfig

            task.plugins {
                kroto {
                    outputSubDir = "java"
                    option "ConfigPath=$krotoConfig"
                }
            }
        }
    }
}

Getting Started With Maven

Repositories

Available on jcenter or mavenCentral
SNAPSHOT

<repository>
    <id>oss-snapshot</id>
    <name>OSS Snapshot Repository</name>
    <url>https://oss.jfrog.org/artifactory/oss-snapshot-local</url>
    <snapshots>
        <enabled>true</enabled>
    </snapshots>
</repository>

Bintray

<!-- Useful when syncronization to jcenter or maven central are taking longer than expected-->
<repository>
    <id>kroto-plus-bintray</id>
    <name>Kroto Plus Bintray Repository</name>
    <url>https://dl.bintray.com/marcoferrer/kroto-plus/</url>
</repository>

Configuring Protobuf Maven Plugin

<plugin>
    <groupId>org.xolstice.maven.plugins</groupId>
    <artifactId>protobuf-maven-plugin</artifactId>
    <version>0.6.1</version>
    <configuration>
        <protocArtifact>com.google.protobuf:protoc:3.6.1:exe:${os.detected.classifier}</protocArtifact>
    </configuration>
    <executions>
        <execution>
            <goals><goal>compile</goal></goals>
        </execution>
        <execution>
            <id>grpc-java</id>
            <goals><goal>compile-custom</goal></goals>
            <configuration>
                <pluginId>grpc-java</pluginId>
                <pluginArtifact>io.grpc:protoc-gen-grpc-java:1.17.1:exe:${os.detected.classifier}</pluginArtifact>
            </configuration>
        </execution>
        <execution>
            <id>kroto-plus</id>
            <goals>
                <goal>compile-custom</goal>
            </goals>
            <configuration>
                <pluginId>kroto-plus</pluginId>
                <pluginArtifact>com.github.marcoferrer.krotoplus:protoc-gen-kroto-plus:${krotoPlusVersion}:exe:${os.detected.classifier}</pluginArtifact>
                <pluginParameter>ConfigPath=${project.basedir}/krotoPlusConfig.asciipb</pluginParameter>
            </configuration>
        </execution>
    </executions>
</plugin>

Add generated sources to Kotlin plugin

<plugin>
    <artifactId>kotlin-maven-plugin</artifactId>
    <groupId>org.jetbrains.kotlin</groupId>
    <version>${kotlin.version}</version>
    <executions>
        <execution>
            <id>compile</id>
            <goals>
                <goal>compile</goal>
            </goals>
            <configuration>
                <sourceDirs>
                    <sourceDir>${project.basedir}/target/generated-sources/protobuf/kroto-plus</sourceDir>
                </sourceDirs>
            </configuration>
        </execution>
    </executions>
</plugin>

Configuring Generators

Documentation & Usage Examples

Credit

This project relies on Kotlin Poet for building Kotlin sources. A big thanks to all of its contributors.

Files

README.md

Latest commit

History

README.md

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gRPC Kotlin Coroutines, Protobuf DSL, Scripting for Protoc

Community Contributions are Welcomed

Quick Start: gRPC Coroutines

Version 0.5.0

Getting Started

Code Generators

Proto Builder Generator (Message DSL)

Setup & Documentation

gRPC Coroutines Client & Server

Configuration Options

Cancellation Propagation

Examples

Unary

Client Streaming

Server Streaming

Bi-Directional Streaming

gRPC Stub Extensions

Configuration Options

Coroutine Support

Mock Service Generator

Configuration Options

Extendable Messages Generator (Experimental)

Configuration Options

User Defined Generator Scripts

Insertion Scripts

Generator Scripts

Community Scripts

Method Signature Options Support

Getting Started With Gradle

Repositories

Configuring Protobuf Gradle Plugin

Getting Started With Maven

Repositories

Configuring Protobuf Maven Plugin

Configuring Generators

Credit