Basics tutorial
A basic tutorial introduction to gRPC in Dart.
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 until
shutdown()
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:
Get packages:
Run the server:
From a different terminal, run the client:
Reporting issues
If you find a problem with Dart gRPC, please
file an issue
in our issue tracker.