Basics tutorial
A basic tutorial introduction to gRPC in Dart.
Basics tutorial
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 Introduction to gRPC 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 generate clients
and servers in any of gRPC’s supported languages, which in turn can be run in
environments ranging from servers inside a large data center 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 --depth 1 https://github.com/grpc/grpc-dart
Then change your current directory to grpc-dart/example/route_guide
:
$ cd grpc-dart/example/route_guide
You should have already installed the tools needed to generate client and server interface code – if you haven’t, see Quick start for setup instructions.
Defining the service
Our first step (as you’ll know from the Introduction to gRPC) is to
define the gRPC service and the method request and response types using
protocol buffers. You can see the
complete .proto
file in
example/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
stream
keyword 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
stream
keyword 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 Quick start.
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_guide
example 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: () => 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 Feature
s 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 Feature
s) and return a Stream
of Feature
objects.
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 Point
s 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 = Stopwatch();
await for (var location in request) {
if (!timer.isRunning) timer.start();
pointCount++;
final feature = featuresDb.firstWhereOrNull((f) => f.location == location);
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 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 its
RouteSummary
.
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<void> main(List<String> args) async {
final server = grpc.Server.create([RouteGuideService()]);
await server.serve(port: 8080);
print('Server listening...');
}
To build and start a server, we:
- Create an instance of the gRPC server using
grpc.Server.create()
, giving a list of service implementations. - 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 untilshutdown()
is called on it.
Creating the client
In this section, we’ll look at creating a Dart client for our RouteGuide
service. The complete client code is available from
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
ClientChannel()
as follows:
final channel = ClientChannel('127.0.0.1',
port: 8080,
options: const ChannelOptions(
credentials: ChannelCredentials.insecure()));
You can use ChannelOptions
to set TLS options (for example, trusted
certificates) for the channel, if necessary.
Once the gRPC channel is setup, we need a client stub to perform RPCs. We
get it by instantiating RouteGuideClient
, which is provided by the package
generated from the example .proto
file.
stub = RouteGuideClient(channel,
options: CallOptions(timeout: Duration(seconds: 30)));
You can use CallOptions
to set auth credentials (for example, GCE credentials
or JWT credentials) when a service requires them. The RouteGuide
service
doesn’t require any credentials.
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 = 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
behavior if necessary, such as time-out. If the call doesn’t return an error,
the returned Future
completes 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 Feature
s. 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 = 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 = 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!
Work from the example directory:
$ cd example/route_guide
Get packages:
$ dart pub get
Run the server:
$ dart bin/server.dart
From a different terminal, run the client:
$ dart bin/client.dart
Reporting issues
If you find a problem with Dart gRPC, please file an issue in our issue tracker.