Dart gRPC 教程

This tutorial provides a basic Dart programmer’s introduction to working with gRPC.

By walking through this example you’ll learn how to:

• Define a service in a .proto file.
• Generate server and client code using the protocol buffer compiler.
• Use the Dart gRPC API to write a simple client and server for your service.

It assumes that you have read the Overview and are familiar with protocol buffers. Note that the example in this tutorial uses the proto3 version of the protocol buffers language: you can find out more in the proto3 language guide.

Why use gRPC?

Our example is a simple route mapping application that lets clients get information about features on their route, create a summary of their route, and exchange route information such as traffic updates with the server and other clients.

With gRPC we can define our service once in a .proto file and implement clients and servers in any of gRPC’s supported languages, which in turn can be run in environments ranging from servers inside Google to your own tablet - all the complexity of communication between different languages and environments is handled for you by gRPC. We also get all the advantages of working with protocol buffers, including efficient serialization, a simple IDL, and easy interface updating.

Example code and setup

The example code for our tutorial is in grpc/grpc-dart/example/route_guide. To download the example, clone the grpc-dart repository by running the following command:

$ git clone https://github.com/grpc/grpc-dart.git

Then change your current directory to grpc-dart/example/route_guide:

$ cd grpc-dart/example/route_guide

You also should have the relevant tools installed to generate the server and client interface code - if you don’t already, follow the setup instructions in the Dart quick start guide.

Defining the service

Our first step (as you’ll know from the Overview) is to define the gRPC service and the method request and response types using protocol buffers. You can see the complete .proto file inexample/route_guide/protos/route_guide.proto.

To define a service, you specify a named service in your .proto file:

service RouteGuide {
   ...
}

Then you define rpc methods inside your service definition, specifying their request and response types. gRPC lets you define four kinds of service method, all of which are used in the RouteGuide service:

• A simple RPC where the client sends a request to the server using the stub and waits for a response to come back, just like a normal function call.

// Obtains the feature at a given position.
rpc GetFeature(Point) returns (Feature) {}

• A server-side streaming RPC where the client sends a request to the server and gets a stream to read a sequence of messages back. The client reads from the returned stream until there are no more messages. As you can see in our example, you specify a server-side streaming method by placing the stream keyword before the response type.

// Obtains the Features available within the given Rectangle.  Results are
// streamed rather than returned at once (e.g. in a response message with a
// repeated field), as the rectangle may cover a large area and contain a
// huge number of features.
rpc ListFeatures(Rectangle) returns (stream Feature) {}

• A client-side streaming RPC where the client writes a sequence of messages and sends them to the server, again using a provided stream. Once the client has finished writing the messages, it waits for the server to read them all and return its response. You specify a client-side streaming method by placing the streamkeyword before the request type.

// Accepts a stream of Points on a route being traversed, returning a
// RouteSummary when traversal is completed.
rpc RecordRoute(stream Point) returns (RouteSummary) {}

• A bidirectional streaming RPC where both sides send a sequence of messages using a read-write stream. The two streams operate independently, so clients and servers can read and write in whatever order they like: for example, the server could wait to receive all the client messages before writing its responses, or it could alternately read a message then write a message, or some other combination of reads and writes. The order of messages in each stream is preserved. You specify this type of method by placing the streamkeyword before both the request and the response.

// Accepts a stream of RouteNotes sent while a route is being traversed,
// while receiving other RouteNotes (e.g. from other users).
rpc RouteChat(stream RouteNote) returns (stream RouteNote) {}

Our .proto file also contains protocol buffer message type definitions for all the request and response types used in our service methods - for example, here’s the Point message type:

// Points are represented as latitude-longitude pairs in the E7 representation
// (degrees multiplied by 10**7 and rounded to the nearest integer).
// Latitudes should be in the range +/- 90 degrees and longitude should be in
// the range +/- 180 degrees (inclusive).
message Point {
  int32 latitude = 1;
  int32 longitude = 2;
}

Generating client and server code

Next we need to generate the gRPC client and server interfaces from our .proto service definition. We do this using the protocol buffer compiler protoc with a special Dart plugin. This is similar to what we did in the quickstart guide

From the route_guide example directory run :

 protoc -I protos/ protos/route_guide.proto --dart_out=grpc:lib/src/generated

Running this command generates the following files in the lib/src/generated directory under the route_guideexample directory:

• route_guide.pb.dart
• route_guide.pbenum.dart
• route_guide.pbgrpc.dart
• route_guide.pbjson.dart

This contains:

• All the protocol buffer code to populate, serialize, and retrieve our request and response message types
• An interface type (or stub) for clients to call with the methods defined in the RouteGuide service.
• An interface type for servers to implement, also with the methods defined in the RouteGuide service.

Creating the server

First let’s look at how we create a RouteGuide server. If you’re only interested in creating gRPC clients, you can skip this section and go straight to Creating the client (though you might find it interesting anyway!).

There are two parts to making our RouteGuide service do its job:

• Implementing the service interface generated from our service definition: doing the actual “work” of our service.
• Running a gRPC server to listen for requests from clients and dispatch them to the right service implementation.

You can find our example RouteGuide server in grpc-dart/example/route_guide/lib/src/server.dart. Let’s take a closer look at how it works.

Implementing RouteGuide

As you can see, our server has a RouteGuideService class that extends the generated abstract RouteGuideServiceBase class:

class RouteGuideService extends RouteGuideServiceBase {
  Future<Feature> getFeature(grpc.ServiceCall call, Point request) async {
    ...
  }

  Stream<Feature> listFeatures(
      grpc.ServiceCall call, Rectangle request) async* {
    ...
  }

  Future<RouteSummary> recordRoute(
      grpc.ServiceCall call, Stream<Point> request) async {
    ...
  }

  Stream<RouteNote> routeChat(
      grpc.ServiceCall call, Stream<RouteNote> request) async* {
    ...
  }

  ...
}

Simple RPC

RouteGuideService implements all our service methods. Let’s look at the simplest type first, GetFeature, which just gets a Point from the client and returns the corresponding feature information from its database in a Feature.

/// GetFeature handler. Returns a feature for the given location.
/// The [context] object provides access to client metadata, cancellation, etc.
@override
Future<Feature> getFeature(grpc.ServiceCall call, Point request) async {
  return featuresDb.firstWhere((f) => f.location == request,
      orElse: () => new Feature()..location = request);
}

The method is passed a context object for the RPC and the client’s Point protocol buffer request. It returns a Feature protocol buffer object with the response information. In the method we populate the Feature with the appropriate information, and then return it to the gRPC framework, which sends it back to the client.

Server-side streaming RPC

Now let’s look at one of our streaming RPCs. ListFeatures is a server-side streaming RPC, so we need to send back multiple Features to our client.

/// ListFeatures handler. Returns a stream of features within the given
/// rectangle.
@override
Stream<Feature> listFeatures(
    grpc.ServiceCall call, Rectangle request) async* {
  final normalizedRectangle = _normalize(request);
  // For each feature, check if it is in the given bounding box
  for (var feature in featuresDb) {
    if (feature.name.isEmpty) continue;
    final location = feature.location;
    if (_contains(normalizedRectangle, location)) {
      yield feature;
    }
  }
}

As you can see, instead of getting and returning simple request and response objects in our method, this time we get a request object (the Rectangle in which our client wants to find Features) and return a Stream of Featureobjects.

In the method, we populate as many Feature objects as we need to return, adding them to the returned stream using yield. The stream is automatically closed when the method returns, telling gRPC that we have finished writing responses.

Should any error happen in this call, the error will be added as an exception to the stream, and the gRPC layer will translate it into an appropriate RPC status to be sent on the wire.

Client-side streaming RPC

Now let’s look at something a little more complicated: the client-side streaming method RecordRoute, where we get a stream of Points from the client and return a single RouteSummary with information about their trip. As you can see, this time the request parameter is a stream, which the server can use to both read request messages from the client. The server returns its single response just like in the simple RPC case.

/// RecordRoute handler. Gets a stream of points, and responds with statistics
/// about the "trip": number of points, number of known features visited,
/// total distance traveled, and total time spent.
@override
Future<RouteSummary> recordRoute(
    grpc.ServiceCall call, Stream<Point> request) async {
  int pointCount = 0;
  int featureCount = 0;
  double distance = 0.0;
  Point previous;
  final timer = new Stopwatch();

  await for (var location in request) {
    if (!timer.isRunning) timer.start();
    pointCount++;
    final feature = featuresDb.firstWhere((f) => f.location == location,
        orElse: () => null);
    if (feature != null) {
      featureCount++;
    }
    // For each point after the first, add the incremental distance from the
    // previous point to the total distance value.
    if (previous != null) distance += _distance(previous, location);
    previous = location;
  }
  timer.stop();
  return new RouteSummary()
    ..pointCount = pointCount
    ..featureCount = featureCount
    ..distance = distance.round()
    ..elapsedTime = timer.elapsed.inSeconds;
}

In the method body we use await for in the request stream to repeatedly read in our client’s requests (in this case Point objects) until there are no more messages. Once the request stream is done, the server can return itsRouteSummary.

Bidirectional streaming RPC

Finally, let’s look at our bidirectional streaming RPC RouteChat().

/// RouteChat handler. Receives a stream of message/location pairs, and
/// responds with a stream of all previous messages at each of those
/// locations.
@override
Stream<RouteNote> routeChat(
    grpc.ServiceCall call, Stream<RouteNote> request) async* {
  await for (var note in request) {
    final notes = routeNotes.putIfAbsent(note.location, () => <RouteNote>[]);
    for (var note in notes) yield note;
    notes.add(note);
  }
}

This time we get a stream of RouteNote that, as in our client-side streaming example, can be used to read messages. However, this time we return values via our method’s returned stream while the client is still writing messages to their message stream.

The syntax for reading and writing here is the same as our client-streaming and server-streaming methods. Although each side will always get the other’s messages in the order they were written, both the client and server can read and write in any order — the streams operate completely independently.

Starting the server

Once we’ve implemented all our methods, we also need to start up a gRPC server so that clients can actually use our service. The following snippet shows how we do this for our RouteGuide service:

Future<Null> main(List<String> args) async {
  final server =
      new grpc.Server([new RouteGuideService()]);
  await server.serve(port: 8080);
  print('Server listening...');
}

To build and start a server, we:

1. Create an instance of the gRPC server using new grpc.Server(), giving a list of service implementations.
2. Call serve() on the server to start listening for requests, optionally passing in the address and port to listen on. The server will continue to serve requests asynchronously until shutdown() is called on it.

Creating the client

In this section, we’ll look at creating a Dart client for our RouteGuide service. You can see our complete example client code in grpc-dart/example/route_guide/lib/src/client.dart.

Creating a stub

To call service methods, we first need to create a gRPC channel to communicate with the server. We create this by passing the server address and port number to new ClientChannel() as follows:

final channel = new ClientChannel('127.0.0.1',
    port: 8080,
    options: const ChannelOptions(
        credentials: const ChannelCredentials.insecure()));

You can use ChannelOptions to set TLS options (e.g., trusted certificates) for the channel, if necessary.

Once the gRPC channel is setup, we need a client stub to perform RPCs. We get by creating a new instance of the RouteGuideClient object provided in the package we generated from our .proto.

final client = new RouteGuideClient(channel,
    options: new CallOptions(timeout: new Duration(seconds: 30)));

You can use CallOptions to set the auth credentials (e.g., GCE credentials, JWT credentials) if the service you request requires that - however, we don’t need to do this for our RouteGuide service.

Calling service methods

Now let’s look at how we call our service methods. Note that in gRPC-Dart, RPCs are always asynchronous, which means that the RPC returns a Future or Stream that must be listened to, to get the response from the server or an error.

Simple RPC

Calling the simple RPC GetFeature is nearly as straightforward as calling a local method.

final point = new Point()
  ..latitude = 409146138
  ..longitude = -746188906;
final feature = await stub.getFeature(point));

As you can see, we call the method on the stub we got earlier. In our method parameters we pass a request protocol buffer object (in our case Point). We can also pass an optional CallOptions object which lets us change our RPC’s behaviour if necessary, such as time-out. If the call doesn’t return an error, the returned Futurecompletes with the response information from the server. If there is an error, the Future will complete with the error.

Server-side streaming RPC

Here’s where we call the server-side streaming method ListFeatures, which returns a stream of geographical Features. If you’ve already read Creating the server some of this may look very familiar - streaming RPCs are implemented in a similar way on both sides.

final rect = new Rectangle()...; // initialize a Rectangle

try {
  await for (var feature in stub.listFeatures(rect)) {
    print(feature);
  }
catch (e) {
  print('ERROR: $e');
}

As in the simple RPC, we pass the method a request. However, instead of getting a Future back, we get a Stream. The client can use the stream to read the server’s responses.

We use await for on the returned stream to repeatedly read in the server’s responses to a response protocol buffer object (in this case a Feature) until there are no more messages.

Client-side streaming RPC

The client-side streaming method RecordRoute is similar to the server-side method, except that we pass the method a Stream and get a Future back.

final random = new Random();

// Generate a number of random points
Stream<Point> generateRoute(int count) async* {
  for (int i = 0; i < count; i++) {
    final point = featuresDb[random.nextInt(featuresDb.length)].location;
    yield point;
  }
}

final pointCount = random.nextInt(100) + 2; // Traverse at least two points

final summary = await stub.recordRoute(generateRoute(pointCount));
print('Route summary: $summary');

Since the generateRoute() method is async*, the points will be generated when gRPC listens to the request stream and sends the point messages to the server. Once the stream is done (when generateRoute() returns), gRPC knows that we’ve finished writing and are expecting to receive a response. The returned Future will either complete with the RouteSummary message received from the server, or an error.

Bidirectional streaming RPC

Finally, let’s look at our bidirectional streaming RPC RouteChat(). As in the case of RecordRoute, we pass the method a stream where we will write the request messages, and like in ListFeatures, we get back a stream that we can use to read the response messages. However, this time we will send values via our method’s stream while the server is also writing messages to their message stream.

Stream<RouteNote> outgoingNotes = ...;

final responses = stub.routeChat(outgoingNotes);
await for (var note in responses) {
  print('Got message ${note.message} at ${note.location.latitude}, ${note
      .location.longitude}');
}

The syntax for reading and writing here is very similar to our client-side and server-side streaming methods. Although each side will always get the other’s messages in the order they were written, both the client and server can read and write in any order — the streams operate completely independently.

Try it out!

Go to the examples/route_guide folder.

First, make sure dependencies are downloaded:

$ pub get

To run the server, simply:

$ dart bin/server.dart

Likewise, to run the client:

$ dart bin/client.dart

Reporting issues

Should you encounter an issue, please help us out by filing issues in our issue tracker.