Protocol Buffers are a language-neutral, platform-neutral, extensible way of serializing structured data for use in communications protocols, data storage, and more, originally designed at Google (see).

protobuf.js is a pure JavaScript implementation with TypeScript support for node.js and the browser. It's super easy to use, blazingly fast and works out of the box with .proto files!

Contents

• Usage
  How to include protobuf.js in your project.

• Distributions
  A brief introduction to the available distributions and their use cases.

• Examples
  A few examples to get you started.

• Documentation
  A list of available documentation resources.

• Command line
  How to use the command line utility.

• Performance
  A few internals and a benchmark on performance.

• Compatibility
  Notes on compatibility regarding browsers and optional libraries.

• Building
  How to build the library and its components yourself.

Usage

node.js

$> npm install protobufjs [--save --save-prefix=~]

var protobuf = require("protobufjs");

Browsers

Development:

Production:

NOTE: Remember to replace the version tag with the exact release your project depends upon.

The protobuf namespace will always be available globally / also supports AMD loaders.

Distributions

The library supports both reflection-based and code-based use cases:

1. Parsing protocol buffer definitions (.proto files) to reflection
2. Loading JSON descriptors to reflection
3. Generating static code without any reflection features

There is a suitable distribution for each of these:

	Gzipped	Downloads	How to require	Description
full	18.5kb	dist	require("protobufjs")	All features. Works with everything.
light	15.5kb	dist/light	require("protobufjs/light")	All features except tokenizer, parser and bundled common types. Works with JSON definitions, pure reflection and static code.
minimal	6.0kb+	dist/minimal	require("protobufjs/minimal")	Just enough to run static code. No reflection.

In case of doubt you can just use the full library.

Examples

Using .proto files

It's possible to load existing .proto files using the full library, which parses and compiles the definitions to ready to use (reflection-based) message classes:

// awesome.proto
package awesomepackage;
syntax = "proto3";

message AwesomeMessage {
    string awesome_field = 1; // becomes awesomeField
}

protobuf.load("awesome.proto", function(err, root) {
    if (err)
        throw err;

    // Obtain a message type
    var AwesomeMessage = root.lookup("awesomepackage.AwesomeMessage");

    // Create a new message
    var message = AwesomeMessage.create({ awesomeField: "AwesomeString" });

    // Verify the message if necessary (i.e. when possibly incomplete or invalid)
    var errMsg = AwesomeMessage.verify(message);
    if (errMsg)
        throw Error(errMsg);

    // Encode a message to an Uint8Array (browser) or Buffer (node)
    var buffer = AwesomeMessage.encode(message).finish();
    // ... do something with buffer

    // Or, encode a plain object
    var buffer = AwesomeMessage.encode({ awesomeField: "AwesomeString" }).finish();
    // ... do something with buffer

    // Decode an Uint8Array (browser) or Buffer (node) to a message
    var message = AwesomeMessage.decode(buffer);
    // ... do something with message

    // If your application uses length-delimited buffers, there is also encodeDelimited and decodeDelimited.
});

Note: To avoid redundant assertions where messages are already known to be valid, there is a separate method for encoding and verification.

• Message.encode does not implicitly verify a message but tries to encode whatever is specified, possibly resulting in a runtime error being thrown somewhere down the road.
• Message.verify can be used to explicitly perform verification prior to encoding where necessary. Instead of throwing, it returns the error message, if any.
• Message.decode throws if a buffer is invalid or missing required fields (a protobuf.util.ProtocolError with an instance property set to the so far decoded message in the latter case) and doesn't require calling Message.verify afterwards.

Additionally, promise syntax can be used by omitting the callback, if preferred:

protobuf.load("awesome.proto")
    .then(function(root) {
       ...
    });

Using JSON descriptors

The library utilizes a JSON format that is equivalent to a .proto definition (see also: Command line usage).

The following is identical to the .proto definition seen above, but it can also be used with just the light library because it doesn't require the parser:

// awesome.json
{
  "nested": {
    "AwesomeMessage": {
      "fields": {
        "awesomeField": {
          "type": "string",
          "id": 1
        }
      }
    }
  }
}

A JSON descriptor can either be loaded the usual way:

protobuf.load("awesome.json", function(err, root) {
    if (err) throw err;

    // Continue at "Obtain a message type" above
});

Or you can load it inline:

var jsonDescriptor = require("./awesome.json"); // exemplary for node

var root = protobuf.Root.fromJSON(jsonDescriptor);

// Continue at "Obtain a message type" above

Using reflection only

Both the full and the light library include full reflection support. You could, for example, define the .proto definitions seen in the examples above using just reflection:

...
var Root  = protobuf.Root,
    Type  = protobuf.Type,
    Field = protobuf.Field;

var AwesomeMessage = new Type("AwesomeMessage").add(new Field("awesomeField", 1, "string"));

var root = new Root().define("awesomepackage").add(AwesomeMessage);

// Continue at "Create a new message" above
...

Detailed information on the reflection structure is available within the documentation.

Using custom classes

You can also extend runtime message classes with your own custom functionality by registering your own class with a reflected message type:

...

// Define your own prototypal class
function AwesomeMessage(properties) {
    protobuf.Message.call(this, properties); // call the super constructor
}

// Register your custom class with its reflected type (*)
protobuf.Class.create(root.lookup("awesomepackage.AwesomeMessage") /* or use reflection */, AwesomeMessage);

// Define your custom functionality
AwesomeMessage.customStaticMethod = function() { ... };
AwesomeMessage.prototype.customInstanceMethod = function() { ... };

// Continue at "Create a message" above (you can also use the constructor directly)

Afterwards, decoded messages of this type are instanceof AwesomeMessage.

(*) Besides referencing its reflected type through AwesomeMessage.$type and AwesomeMesage#$type, the respective custom class is automatically populated with:

• AwesomeMessage.create
• AwesomeMessage.encode and AwesomeMessage.encodeDelimited
• AwesomeMessage.decode and AwesomeMessage.decodeDelimited
• AwesomeMessage.verify
• AwesomeMessage.fromObject, AwesomeMessage.toObject, AwesomeMessage#toObject and AwesomeMessage#toJSON

Using services

The library also supports services but it doesn't make any assumptions about the actual transport channel. Instead, a user must provide a suitable RPC implementation, which is an asynchronous function that takes the reflected service method, the binary request and a node-style callback as its parameters:

function rpcImpl(method, requestData, callback) {
    // perform the request using an HTTP request or a WebSocket for example
    var responseData = ...;
    // and call the callback with the binary response afterwards:
    callback(null, responseData);
}

Example:

// greeter.proto
syntax = "proto3";

service Greeter {
    rpc SayHello (HelloRequest) returns (HelloReply) {}
}

message HelloRequest {
    string name = 1;
}

message HelloReply {
    string message = 1;
}

...
var Greeter = root.lookup("Greeter");
var greeter = Greeter.create(/* see above */ rpcImpl, /* request delimited? */ false, /* response delimited? */ false);

greeter.sayHello({ name: 'you' }, function(err, response) {
    console.log('Greeting:', response.message);
});

Services also support promises:

greeter.sayHello({ name: 'you' })
    .then(function(response) {
        console.log('Greeting:', response.message);
    });

There is also an example for streaming RPC.

Usage with TypeScript

The library ships with its own type definitions and modern editors like Visual Studio Code should automatically detect and use them for code completion when following this pattern:

// node.js
import * as protobuf from "protobufjs";
import * as Long from "long"; // optional

// browser only (alternatively)
import * as protobuf from "./node_modules/protobufjs/index.js";
import * as Long from "./node_modules/long/dist/long.js"; // optional

protobuf.load("awesome.proto", function(err, root) {
  if (err)
    throw err;

  // example code
  var AwesomeMessage = root.lookupType("AwesomeMessage");
  var message = AwesomeMessage.create({ awesomeField: "hello" });
  var buffer = AwesomeMessage.encode(message).finish();
  ...
});

To achieve the same with static code generated by pbjs, there is the pbts command line utility to generate type definitions from static code as well.

Let's say you generated your static code to bundle.js and its type definitions to bundle.d.ts, then you can do:

import * as root from "./bundle.js";

// example code
var AwesomeMessage = root.AwesomeMessage;
var message = AwesomeMessage.create({ awesomeField: "hello" });
var buffer = AwesomeMessage.encode(message).finish();
...

Documentation

Protocol Buffers

• Google's Developer Guide

protobuf.js

• API Documentation
• CHANGELOG
• Frequently asked questions on our wiki

Community

• Questions and answers on StackOverflow

Command line

The pbjs command line utility can be used to bundle and translate between .proto and .json files. It also generates static code.

Consolidates imports and converts between file formats.

  -t, --target    Specifies the target format. Also accepts a path to require a custom target.

                  json          JSON representation
                  json-module   JSON representation as a module
                  proto2        Protocol Buffers, Version 2
                  proto3        Protocol Buffers, Version 3
                  static        Static code without reflection
                  static-module Static code without reflection as a module

  -p, --path      Adds a directory to the include path.

  -o, --out       Saves to a file instead of writing to stdout.

  Module targets only:

  -w, --wrap      Specifies the wrapper to use. Also accepts a path to require a custom wrapper.

                  default   Default wrapper supporting both CommonJS and AMD
                  commonjs  CommonJS wrapper
                  amd       AMD wrapper
                  es6       ES6 wrapper (implies --es6)

  -r, --root      Specifies an alternative protobuf.roots name.

  -l, --lint      Linter configuration. Defaults to protobuf.js-compatible rules:

                  eslint-disable block-scoped-var, no-redeclare, no-control-regex, no-prototype-builtins

  --es6           Enables ES6 syntax (const/let instead of var)

  Proto sources only:

  --keep-case     Keeps field casing instead of converting to camel case.

  Static targets only:

  --no-create     Does not generate create functions used for reflection compatibility.
  --no-encode     Does not generate encode functions.
  --no-decode     Does not generate decode functions.
  --no-verify     Does not generate verify functions.
  --no-convert    Does not generate convert functions like from/toObject
  --no-delimited  Does not generate delimited encode/decode functions.
  --no-beautify   Does not beautify generated code.
  --no-comments   Does not output any JSDoc comments.

usage: pbjs [options] file1.proto file2.json ...  (or)  other | pbjs [options] -

For production environments it is recommended to bundle all your .proto files to a single .json file, which minimizes the number of network requests and avoids any parser overhead (hint: works with just the light library):

$> pbjs -t json file1.proto file2.proto > bundle.json

Now, either include this file in your final bundle:

var root = protobuf.Root.fromJSON(require("./bundle.json"));

or load it the usual way:

protobuf.load("bundle.json", function(err, root) {
    ...
});

The pbjs utility is also capable of generating static code (hint: works with just the minimal library). For example

$> pbjs -t static-module -w commonjs -o compiled.js file1.proto file2.proto

will generate static code for definitions within file1.proto and file2.proto to a CommonJS module compiled.js.

ProTip! Documenting your .proto files with /** ... */-blocks or (trailing) /// ... lines translates to generated static code.

Generating TypeScript definitions from static modules

Likewise, the pbts command line utility can be used to generate TypeScript definitions from pbjs-generated static modules.

Generates TypeScript definitions from annotated JavaScript files.

  -o, --out       Saves to a file instead of writing to stdout.

  -g, --global    Name of the global object in browser environments, if any.

  --no-comments   Does not output any JSDoc comments.

  Internal flags:

  -n, --name      Wraps everything in a module of the specified name.

  -m, --main      Whether building the main library without any imports.

usage: pbts [options] file1.js file2.js ...  (or)  other | pbts [options] -

Picking up on the example above, the following not just generates static code to a CommonJS module compiled.js but also its respective TypeScript definitions to compiled.d.ts:

$> pbjs -t static-module -w commonjs -o compiled.js file1.proto file2.proto
$> pbts -o compiled.d.ts compiled.js

Additionally, TypeScript definitions of static modules are compatible with their reflection-based counterparts (i.e. as exported by JSON modules), as long as the following conditions are met:

1. Instead of using new SomeMessage(...), always use SomeMessage.create(...) because reflection objects do not provide a constructor.
2. Types, services and enums must start with an uppercase letter to become available as properties of the reflected types as well (i.e. to be able to use MyMessage.MyEnum instead of root.lookup("MyMessage.MyEnum")).

For example, the following generates a JSON module bundle.js and a bundle.d.ts, but no static code:

$> pbjs -t json-module -w commonjs -o bundle.js file1.proto file2.proto
$> pbjs -t static-module file1.proto file2.proto | pbts -o bundle.d.ts -

On reflection vs. static code

While using .proto files directly requires the full library respectively pure reflection/JSON the light library, pretty much all code but the relatively short descriptors is shared.

Static code, on the other hand, requires just the minimal library, but generates additional, albeit editable, source code without any reflection features.

There is no significant difference performance-wise as the code generated statically is pretty much the same as generated at runtime and both are largely interchangeable as seen in the previous section.

Using pbjs and pbts programmatically

Both utilities can be used programmatically by providing command line arguments and a callback to their respective main functions:

var pbjs = require("protobufjs/cli/pbjs");

pbjs.main([ "--target", "json-module", "path/to/myproto.proto" ], function(err, output) {
    if (err)
        throw err;
    // do something with output
});

Performance

The package includes a benchmark that tries to compare performance to native JSON as far as this is possible. On an i7-2600K running node 6.9.1 it yields:

benchmarking encoding performance ...

Type.encode to buffer x 547,361 ops/sec ±0.27% (94 runs sampled)
JSON.stringify to string x 310,848 ops/sec ±0.73% (92 runs sampled)
JSON.stringify to buffer x 173,608 ops/sec ±1.51% (86 runs sampled)

      Type.encode to buffer was fastest
   JSON.stringify to string was 43.5% slower
   JSON.stringify to buffer was 68.7% slower

benchmarking decoding performance ...

Type.decode from buffer x 1,294,378 ops/sec ±0.86% (90 runs sampled)
JSON.parse from string x 291,944 ops/sec ±0.72% (92 runs sampled)
JSON.parse from buffer x 256,325 ops/sec ±1.50% (90 runs sampled)

    Type.decode from buffer was fastest
     JSON.parse from string was 77.4% slower
     JSON.parse from buffer was 80.3% slower

benchmarking combined performance ...

Type to/from buffer x 254,126 ops/sec ±1.13% (91 runs sampled)
JSON to/from string x 122,896 ops/sec ±1.29% (90 runs sampled)
JSON to/from buffer x 88,005 ops/sec ±0.87% (89 runs sampled)

        Type to/from buffer was fastest
        JSON to/from string was 51.7% slower
        JSON to/from buffer was 65.3% slower

benchmarking verifying performance ...

Type.verify x 6,246,765 ops/sec ±2.00% (87 runs sampled)

benchmarking message from object performance ...

Type.fromObject x 2,892,973 ops/sec ±0.70% (92 runs sampled)

benchmarking message to object performance ...

Type.toObject x 3,601,738 ops/sec ±0.72% (93 runs sampled)

Note that JSON is a native binding nowadays and as such is about as fast as it possibly can get. So, how can protobuf.js be faster?

• The benchmark is somewhat flawed.
• Reader and writer interfaces configure themselves according to the environment to eliminate redundant conditionals.
• Node-specific reader and writer subclasses benefit from node's buffer binding.
• Reflection has built-in code generation that builds type-specific encoders, decoders and verifiers at runtime.
• Encoders and decoders do not implicitly call verify on messages to avoid unnecessary overhead where messages are already known to be valid. It's up to the user to call verify where necessary.
• Quite a bit of V8-specific profiling is accountable for everything else.

You can also run the benchmark ...

$> npm run bench

and the profiler yourself (the latter requires a recent version of node):

$> npm run prof  [iterations=10000000]

Note that as of this writing, the benchmark suite performs significantly slower on node 7.2.0 compared to 6.9.1 because moths.

Compatibility

• Because the internals of this package do not rely on google/protobuf/descriptor.proto, options are parsed and presented literally.
• If typed arrays are not supported by the environment, plain arrays will be used instead.
• Support for pre-ES5 environments (except IE8) can be achieved by using a polyfill.
• Support for Content Security Policy-restricted environments (like Chrome extensions without unsafe-eval) can be achieved by generating and using static code instead.
• If you need a proper way to work with 64 bit values (uint64, int64 etc.), you can install long.js alongside this library. All 64 bit numbers will then be returned as a Long instance instead of a possibly unsafe JavaScript number (see).

Building

To build the library or its components yourself, clone it from GitHub and install the development dependencies:

$> git clone https://github.com/dcodeIO/protobuf.js.git
$> cd protobuf.js
$> npm install

Building the respective development and production versions with their respective source maps to dist/:

$> npm run build

Building the documentation to docs/:

$> npm run docs

Building the TypeScript definition to index.d.ts:

$> npm run types

Browserify integration

By default, protobuf.js integrates into your browserify build-process without requiring any optional modules. Hence:

• If you need int64 support, explicitly require the long module somewhere in your project as it will be excluded otherwise. This assumes that a global require function is present that protobuf.js can call to obtain the long module.

  If there is no global require function present after bundling, it's also possible to assign the long module programmatically:

  var Long = ...;
  
  protobuf.util.Long = Long;
  protobuf.configure();
  

• If you have any special requirements, there is the bundler for reference.

License: BSD 3-Clause License