Wednesday, May 4, 2016

Unboxing Packages: json_rpc_2

Last week I wrote about the stream_channel package for two-way communication, so this week it seemed natural to move to a package that uses it: json_rpc_2. This is an implementation of the JSON-RPC 2.0 specification, which is a popular protocol for providing structure and standardization to WebSocket APIs.

Although it’s most commonly used with WebSockets, the protocol itself is explicitly independent of the underlying transport mechanism. This makes it a great fit for stream channels, which can be used to represent a two-way stream of JSON objects in a way that works with any underlying mechanism. Thanks to stream channels, JSON-RPC 2.0 can be used across WebSockets, isolates, or any channel a user chooses to wrap.

Shared APIs

There are three main classes in json_rpc_2: Client makes requests and receives responses, Server handles requests and returns responses, and Peer does both at once. Because all of these involve two-way communication, they all have the same two constructors. The default constructor takes a StreamChannel<String> where each string is an encoded JSON object, and automatically decodes incoming objects and encodes outgoing ones. On the other hand, if you want to communicate using decoded maps and lists, you can use the withoutJson() constructor, which only requires that the objects be JSON-compatible.

The three classes also have the same lifecycle management. In order to give the user time to set up request handlers or enqueue request batches, they don’t start listening to the stream channel until listen() is called. Once it is, it returns a future that completes once the channel has closed—also accessible as the done getter. And if the user wants to close the channel themselves, they can call close().


The Client class is in charge of making requests of a server. The core method for this is sendRequest(), which takes a method (the name of the remote procedure to call) and parameters to pass to that method.

The structure of these parameters depends what the server accepts. JSON-RPC 2.0 allows both positional parameters, which are passed as an Iterable of JSON-safe objects, and named ones, which are passed as a Map from string names to JSON-safe values. The parameters can also be omitted entirely if the method doesn’t take any.

The call to sendRequest() returns a future that completes with the server’s response. The protocol defines two types of response: “success” and “error”. On a success, the server returns a JSON-safe object which the sendRequest() future emits. On a failure, the server returns an error object with associated metadata. This metadata is wrapped up as an RpcException and thrown by the future.

import 'package:json_rpc_2/json_rpc_2.dart' as rpc;

/// Uses the VM service protocol to get the Dart version of a Dart process.
/// The [observatoryUrl] should be a `ws://` URL for the process's VM service.
Future<String> getVersion(Uri observatoryUrl) async {
  var channel = new WebSocketChannel.connect(observatoryUrl);
  var client = new rpc.Client(channel);

  // getVM() returns an object with a bunch of metadata about the VM itself.
  var vm = await client.sendRequest("getVM");
  return vm["version"];

If you don’t care whether the request succeeds, you can also call sendNotification(). JSON-RPC 2.0 defines a notification as a request that doesn’t require a response, and a compliant server shouldn’t send one at all. Notifications are commonly used by peers for emitting events, but I’ll get to that later.

JSON-RPC 2.0 also has a notion of batches, where a bunch of requests are sent as part of the same underlying message. The server is allowed to process batched requests in whatever order it wants, but it’s required to send the responses back as a single message as well. This can use less bandwidth if you have a bunch of requests that don’t have strong ordering needs.

The json_rpc_2 client lets the user create batches using the withBatch() method. This takes a callback (which may be asynchronous), and puts all requests that are sent while that callback is running into a single batch. This batch is sent once the callback is complete.


The Server class handles requests from one or more clients. Its core API is registerMethod(), which controls how those requests are handled. It just takes a method name and a callback to run when that method is called. The value returned by that callback becomes the result returned to the client.

import "package:json_rpc_2/json_rpc_2.dart" as rpc;
import "package:shelf/shelf_io.dart" as io;
import "package:shelf_web_socket/shelf_web_socket.dart";

var _i = 0;

main() async {
  io.serve(webSocketHandler((webSocketChannel) {
    var server = new rpc.Server(webSocketChannel);

    // Increments [_i] and returns its new value.
    server.handleMethod("increment", () => ++_i);
  }), 'localhost', 1234);

The server presents an interesting API design challenge. Most methods require certain sorts of parameters—one might need exactly three positional parameters, one might need two mandatory named and one optional parameter, and another might not allow any parameters at all. JSON-RPC 2.0 is pretty clear about how to handle this at the protocol level, but how do we let the user specify it?

We could have users manually validate the parameters—and in fact, for complex validations we do. Users can always manually throw new RpcException.invalidParams() based on whatever logic they code. But it’s a huge pain to manually validate the presence and type of every parameter, so Server uses a couple clever tricks to figure out requirements with minimal user code.

The first trick is that the callback passed to registerMethod() can take either zero or one parameters. This is how Server figures out whether the method allows parameters at all. In the example above, if a client tried to call increment with parameters of any kind, they would get an “invalid parameters” error. But the most clever trick is how parameters that are passed are parsed, and it involves an entirely new class.


The Parameters class wraps a JSON-safe object and provides methods to access it in a type-safe way that will automatically throw RpcExceptions if the object isn’t the expected format. It’s what gets passed to the registerMethod() callback, if it takes a parameter at all.

If you call asList and the caller passed the parameters by name, it’ll throw an RpcException. If you call asMap and the parameters were passed by position? RpcException as well. Or you can just call value and get the underlying parameter no matter what form it takes.

Parameters also lets you verify the parameter values themselves. The [] operator can be used for either positional parameters (with int arguments) or named parameters (with string arguments), and returns a Parameter object which extends Parameters with a bunch of methods for validating types beyond just lists and maps.

All of the native JSON types have getters like asString, asNum, and similar. Just like asList and asMap, these getters return the parameter values if they’re the correct types and throw RpcExceptions if they aren’t. There are also derived getters like asDateTime and asUri which ensure that the value can be parsed as the appropriate type, and asInt which ensures that a number is an integer.

// Sets [_i] to the given value.
server.handleMethod("set", (parameters) {
  _i = parameters[0].asInt;
  return _i;

It’s important to note that the [] operator will return a parameter even if it doesn’t exist, either because there weren’t enough positional parameters passed or because a parameter with that name wasn’t passed. This makes it easy to support optional parameters.

A parameter that doesn’t exist will always throw an RpcException for its asType methods, and even for value. But there are methods where it won’t throw. If you call asStringOr() for a parameter that exists, it behaves just like asString, but for a non-existent parameter it’ll return the defaultValue parameter. Every asType getter has a corresponding asTypeOr() method. Even value has valueOr().

// Returns the logarithm of [_i].
// If the `"base"` named parameter is passed, uses that as the base. Otherwise,
// uses `e`.
server.handleMethod("log", (parameters) {
  return math.log(_i)/math.log(parameters["base"].asNumOr(math.E));


The Peer class works as both a Server and a Client over the same underlying connection. In terms of API, it’s exactly the sum of those two classes. It adds no methods of its own, so in that sense you already know everything about it. But it’s still instructive to talk about why it exists.

While I can easily imagine a structure where two endpoints are truly peers, each invoking methods on the other and receiving results, in practice most of the time I’ve seen peer-structured protocols has been for the sake of event dispatch. You see, JSON-RPC 2.0 doesn’t include an explicit mechanism for the server pushing events to the client. It can only respond to requests made by the client. This is intentional, since it makes the protocol much simpler, and the peer structure is the standard way around it.

To support server events, both the client and server must act as peers, able to send and receive requests. In this world, events are modeled as requests sent from the server to the client—or more specifically, notifications, since the server doesn’t expect a response. The client registers a method for each type of event it wants to handle, and the server sends a request for every dispatch.

/// Uses the VM service protocol to print the VM name.
/// Prints the VM name again every time it's changed.
void printVersions(Uri observatoryUrl) async {
  var channel = new WebSocketChannel.connect(observatoryUrl);
  var peer = new rpc.Peer(channel);

  peer.registerMethod("streamNotify", (parameters) async {
    if (parameters["streamId"].asString != "VMUpdate") {
      throw new rpc.RpcException.invalidParams(
          "Only expected VMUpdate events.");

    print("VM name is ${await peer.sendRequest("getVM")["version"]}.");

  print("VM name is ${await client.sendRequest("getVM")["version"]}.");

RPC Home

Next time you need to communicate with a JSON-RPC 2.0 server, you know where to turn. Next time you need to create an RPC server, I hope you look to JSON-RPC 2.0 as the underlying protocol. It’s clean and straightforward, and best of all, it’s got a great implementation already written and ready to use.

I wrote about stream_channel in my last article. In this article, I wrote about json_rpc_2, which uses stream_channel. Join me in two weeks when I build this layer cake a little higher and write about a package that uses json_rpc_2!