protobuf.js

protobuf.js is a very fast, conformant, and unusually versatile JavaScript implementation of Protocol Buffers for Node.js and browsers. It is independently maintained with contributions from the upstream Protocol Buffers project, works with .proto schemas without requiring protoc, and supports runtime reflection as well as specialized code generation with matching TypeScript declarations.

If protobuf.js is important to your project or organization, or if you depend on it commercially, consider supporting its ongoing maintenance. Sponsorship helps make bug fixes, releases, LTS/security handling, and user support more sustainable.

Getting started

Getting up and running is simple: Install the package, load a schema, and you are all set to encode and decode Protobuf messages. From there, protobuf.js grows with your requirements: Add code generation with TypeScript declarations, transport-agnostic services, support for text-based formats, and more as needed.

Install

npm install protobufjs

The command line utility for generating reflection bundles, static code and TypeScript declarations is published as an add-on package:

npm install --save-dev protobufjs-cli

The CLI is a JS-native protobuf.js toolchain that does not require setting up protoc. If you prefer a protoc-based workflow, it provides protoc-gen-pbjs as an option.

Browser builds

Canonical browser builds are provided via the jsDelivr CDN, supporting CommonJS, AMD and global window.protobuf. Make sure to pin an exact version in production.

Usage

The examples below use this schema:

syntax = "proto3";

package awesomepackage;

message AwesomeMessage {
  string awesome_field = 1;
}

protobuf.js converts .proto field names to camelCase by default, so awesome_field is used as awesomeField in JavaScript. Use the keepCase option when loading or parsing .proto files to preserve field names as written.

Load a schema

const protobuf = require("protobufjs");

const root = await protobuf.load("awesome.proto");
const AwesomeMessage = root.lookupType("awesomepackage.AwesomeMessage");

Optionally use load() with a callback, or loadSync() for synchronous loading on Node.js. Imports resolve relative to the importing file by default. To resolve imports against a specific base directory, create a Root and override root.resolvePath before calling root.load().

Encode and decode

const payload = { awesomeField: "hello" };

// Optionally create a message instance from already valid data
const message = AwesomeMessage.create(payload);

const encoded = AwesomeMessage.encode(message).finish();
const decoded = AwesomeMessage.decode(encoded);

encode expects a message instance or equivalent plain object and does not verify input implicitly. Use create to create a message instance from already valid data when useful, verify for plain objects whose shape is not guaranteed, and fromObject when conversion from broader JavaScript objects is needed.

Plain objects can be encoded directly when they already use protobuf.js runtime types: numbers for 32-bit numeric fields, booleans for bool, strings for string, Uint8Array or Buffer for bytes, arrays for repeated fields, and plain objects for maps. Map keys are the string representation of the respective value or an 8-character hash string for 64-bit keys.

Note that, as with any structured binary format, decoded structures incur runtime memory overhead beyond their encoded representation. Applications processing untrusted input should therefore apply appropriate input-size and concurrency limits to bound memory use. For this reason, unknown fields present on the wire are intentionally discarded as the safer default, but can be retained by setting reader.discardUnknown = false per reader, or by setting Reader.discardUnknown = false to make it the default for subsequently created readers. Preserved unknown field data can also be explicitly dropped with delete message.$unknowns.

Convert plain objects

Conversion is an explicit interoperability boundary. fromObject accepts common JavaScript inputs such as enum values by name, base64 bytes, decimal 64-bit strings, Long, and BigInt; toObject lets callers choose the output expected by their application or transport.

const message = AwesomeMessage.fromObject({ awesomeField: 42 });
const object = AwesomeMessage.toObject(message, {
  longs: String,
  enums: String,
  bytes: String
});

Common ConversionOptions are:

Message API

Message types expose focused methods for validation, conversion, and binary I/O.

• encode(message: Message | object, writer?: Writer): Writer
  Encodes a message or equivalent plain object. Call .finish() on the returned writer to obtain a buffer.

• encodeDelimited(message: Message | object, writer?: Writer): Writer
  Encodes a length-delimited message.

• decode(reader: Reader | Uint8Array): Message
  Decodes a message from protobuf binary data.

• decodeDelimited(reader: Reader | Uint8Array): Message
  Decodes a length-delimited message.

• create(properties?: object): Message
  Creates a message instance from already valid data.

• verify(object: object): null | string
  Checks whether a plain object can be encoded as-is. Returns null if valid, otherwise an error message.

• fromObject(object: object): Message
  Converts broader JavaScript input into a message instance.

• toObject(message: Message, options?: ConversionOptions): object
  Converts a message instance to a configurable plain JavaScript object.

• message.toJSON(): object
  Converts a message instance to JSON-compatible output using default conversion options.

Message instances provide stable runtime identity for testing with instanceof.

Length-delimited methods read and write a varint byte length before the message, which is useful for streams and framed protocols.

If required fields are missing while decoding proto2 data, decode throws protobuf.util.ProtocolError with the partially decoded message available as err.instance.

Code generation

Use protobufjs-cli to generate schema-specific code, either directly with pbjs or through the optional protoc-gen-pbjs plugin for protoc.

protobuf.js offers two code-generation modes, both with matching TypeScript declarations: reflection modules generate optimized code at runtime with reflection metadata retained; static modules generate reflection-free code ahead of time. Both use the same runtime package and automatically import only the runtime capabilities they need.

Module targets support --wrap default for CommonJS and AMD, plus esm, commonjs, amd, and closure; --wrap can also load a custom wrapper module.

Static modules

Static modules emit dedicated, reflection-free JavaScript code for your schema.

npx pbjs -t static-module -w esm -o awesome.js --dts awesome.proto

import { awesomepackage } from "./awesome.js";

const message = awesomepackage.AwesomeMessage.create({ awesomeField: "hello" });

Static code is repetitive by design, but compresses unusually well with Brotli or gzip and works in CSP-restricted environments.

Reflection modules

Reflection modules wrap schemas as compact JSON metadata while avoiding .proto parsing at runtime.

npx pbjs -t json-module -w esm -o awesome.js --dts awesome.proto

import { awesomepackage } from "./awesome.js";

const AwesomeMessage = awesomepackage.AwesomeMessage;

Declarations for reflection modules mirror static-module typings. Because JSON modules export reflection objects, message instances should be created with MyMessage.create(...) rather than constructors. Code using create(...) works with static modules as well. Separately, -t json can serialize reflection metadata as bare JSON bundles for use with load() or Root.fromJSON().

TypeScript integration

protobuf.js works with TypeScript out of the box: its runtime API is typed, and generated code can be paired with matching TypeScript declarations in a single CLI invocation. Declarations are strongly typed, including discriminated unions for oneofs and scoped types for plain-object usage:

message Profile {
  oneof contact {
    string email = 1;
    string phone = 2;
  }
}

const profile = Profile.create({
  contact: "email",
  email: "hello@example.com"
});

if (profile.contact === "email") {
  profile.email; // string
}

const decoded = Profile.decode(bytes);
if (decoded.contact === "phone") {
  decoded.phone; // string
}

The same narrowed shape is available for plain-object inputs:

const object: Profile.$Shape = {
  contact: "email",
  email: "hello@example.com"
};

Advanced usage

Programmatic schemas

Schemas can be constructed directly through reflection:

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

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

Custom message classes

A reflected type can use a custom class as its runtime constructor:

class AwesomeMessage extends protobuf.Message<AwesomeMessage> {
  awesomeField = "";

  constructor(properties?: protobuf.Properties<AwesomeMessage>) {
    super(properties);
    // ...
  }

  customInstanceMethod() {
    return this.awesomeField.toLowerCase();
  }
}

root.lookupType("awesomepackage.AwesomeMessage").ctor = AwesomeMessage;

const decoded = AwesomeMessage.decode(bytes);
decoded.customInstanceMethod(); // string

protobuf.js will populate the constructor with the usual static runtime methods and use it for decoded messages. When assigning constructors manually, add the type to its parent namespace/root first if fields reference other reflected types. In TypeScript, custom members are visible when using the custom class type in consuming code.

Services

protobuf.js supports service clients built from service definitions. The service API is transport-agnostic: provide an rpcImpl function to connect it to HTTP, WebSocket, gRPC, or another transport.

function myRpcImpl(method, requestData, callback) {
  // method.name
  // method.path
  // method.requestStream?
  // method.responseStream?
  performRequest(requestData, function(err, responseData) {
    callback(err, responseData);
  });
}

const myService = MyService.create(myRpcImpl/*, requestDelimited?, responseDelimited? */);

See examples/streaming-rpc.js for a streaming example.

See examples/grpc-service.js for an integration example with @grpc/grpc-js.

Extensions

The following extensions provide descriptor conversion and text-based protobuf formats when reflection metadata is available. Most applications only need the binary APIs above.

Descriptors

protobuf.js uses a compact JSON-based reflection representation internally. See ext/descriptor for use cases that need conversion between reflected roots and protoc descriptor messages.

ProtoJSON

Protocol Buffers support a special ProtoJSON format to share data with systems that do not support the binary wire format, for example when implementing gateways. Spec-compliant ProtoJSON is supported via ext/protojson.

Text Format

Protocol Buffers Text Format is a special syntax for representing protobuf data in text form, which can be useful for configurations or tests. Spec-compliant Text Format is supported via ext/textformat.

Conformance

protobuf.js is validated against the official Protocol Buffers conformance suite. It passes all required and recommended tests for the Proto2, Proto3 and Editions binary wire formats, with complete ProtoJSON and Text Format support available as optional extensions when those formats are needed.

Structured results of the conformance tests are also available as CI artifacts.

Performance

protobuf.js's reflection and static modes share the same code-generation backend and underlying hand-tuned reader and writer primitives. Reflection mode emits specialized encoders and decoders just in time, while static mode emits equivalent code ahead of time.

To see how this architecture compares in practice, the repository includes a reproducible benchmark suite measuring both modes alongside other general-purpose JavaScript implementations across three cases: our classic common message shape and two unmodified, structurally distinct fixtures sourced from other implementations. Each library is tested through its recommended serialization and deserialization path using identical schemas and message contents.

Structured results include environment details for this run and are committed alongside the charts. The suite also runs in CI.

To run the benchmark on your own hardware:

npm --prefix bench install
npm --prefix bench run generate
npm run bench

Compatibility

Supported runtimes are browsers, Node.js v12+, Deno and Bun. When using the CLI with Bun, Node.js must also be installed.

Security

Security-impacting reports are handled through coordinated GitHub Security Advisories where appropriate. See SECURITY.md for supported release lines and reporting instructions.

Development

git clone https://github.com/protobufjs/protobuf.js
cd protobuf.js
npm install
npm --prefix cli install

Running the tests:

npm test

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

npm run build

Additional documentation

• API Documentation
• Changelog
• Protocol Buffers Documentation