Gathering detailed insights and metrics for @apollo/protobufjs
Gathering detailed insights and metrics for @apollo/protobufjs
Gathering detailed insights and metrics for @apollo/protobufjs
Gathering detailed insights and metrics for @apollo/protobufjs
Protocol Buffers for JavaScript. Finally.
npm install @apollo/protobufjs
Module System
Min. Node Version
Typescript Support
Node Version
NPM Version
15 Stars
758 Commits
5 Forks
12 Watching
10 Branches
20 Contributors
Updated on 24 Jun 2024
JavaScript (99.81%)
TypeScript (0.19%)
Cumulative downloads
Total Downloads
Last day
2.7%
509,732
Compared to previous day
Last week
6.5%
2,604,267
Compared to previous week
Last month
9.6%
10,511,448
Compared to previous month
Last year
-8.6%
122,010,357
Compared to previous year
12
33
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 easy to use, blazingly fast and works out of the box with .proto files!
We have forked the source repo because we need to make changes to the package for use in Apollo Server.
Version 1.0.0 was forked from master
which contained version 6.8.8 plus a few unreleased commits. sha
Installation
How to include protobuf.js in your project.
Usage
A brief introduction to using the toolset.
Examples
A few examples to get you started.
Command line
How to use the command line utility.
Additional documentation
A list of available documentation resources.
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.
$> npm install @apollo/protobufjs [--save --save-prefix=~]
1var protobuf = require("@apollo/protobufjs");
Note that this library's versioning scheme is not semver-compatible for historical reasons. For guaranteed backward compatibility, always depend on ~6.A.B
instead of ^6.A.B
(hence the --save-prefix
above).
Development:
<script src="//cdn.rawgit.com/dcodeIO/protobuf.js/6.X.X/dist/protobuf.js"></script>
Production:
<script src="//cdn.rawgit.com/dcodeIO/protobuf.js/6.X.X/dist/protobuf.min.js"></script>
Remember to replace the version tag with the exact release your project depends upon.
The library supports CommonJS and AMD loaders and also exports globally as protobuf
.
Where bundle size is a factor, there are additional stripped-down versions of the full library (~19kb gzipped) available that exclude certain functionality:
When working with JSON descriptors (i.e. generated by pbjs) and/or reflection only, see the light library (~16kb gzipped) that excludes the parser. CommonJS entry point is:
1var protobuf = require("@apollo/protobufjs/light");
When working with statically generated code only, see the minimal library (~6.5kb gzipped) that also excludes reflection. CommonJS entry point is:
1var protobuf = require("@apollo/protobufjs/minimal");
Because JavaScript is a dynamically typed language, protobuf.js introduces the concept of a valid message in order to provide the best possible performance (and, as a side product, proper typings):
A valid message is an object (1) not missing any required fields and (2) exclusively composed of JS types understood by the wire format writer.
There are two possible types of valid messages and the encoder is able to work with both of these for convenience:
In a nutshell, the wire format writer understands the following types:
Field type | Expected JS type (create, encode) | Conversion (fromObject) |
---|---|---|
s-/u-/int32 s-/fixed32 | number (32 bit integer) | value | 0 if signedvalue >>> 0 if unsigned |
s-/u-/int64 s-/fixed64 | Long -like (optimal)number (53 bit integer) | Long.fromValue(value) with long.jsparseInt(value, 10) otherwise |
float double | number | Number(value) |
bool | boolean | Boolean(value) |
string | string | String(value) |
bytes | Uint8Array (optimal)Buffer (optimal under node)Array.<number> (8 bit integers) | base64.decode(value) if a string Object with non-zero .length is assumed to be buffer-like |
enum | number (32 bit integer) | Looks up the numeric id if a string |
message | Valid message | Message.fromObject(value) |
undefined
and null
are considered as not set if the field is optional.Array.<T>
.Object.<string,T>
with the key being the string representation of the respective value or an 8 characters long binary hash string for Long
-likes.With that in mind and again for performance reasons, each message class provides a distinct set of methods with each method doing just one thing. This avoids unnecessary assertions / redundant operations where performance is a concern but also forces a user to perform verification (of plain JavaScript objects that might just so happen to be a valid message) explicitly where necessary - for example when dealing with user input.
Note that Message
below refers to any message class.
Message.verify(message: Object
): null|string
verifies that a plain JavaScript object satisfies the requirements of a valid message and thus can be encoded without issues. Instead of throwing, it returns the error message as a string, if any.
1var payload = "invalid (not an object)"; 2var err = AwesomeMessage.verify(payload); 3if (err) 4 throw Error(err);
Message.encode(message: Message|Object
[, writer: Writer
]): Writer
encodes a message instance or valid plain JavaScript object. This method does not implicitly verify the message and it's up to the user to make sure that the payload is a valid message.
1var buffer = AwesomeMessage.encode(message).finish();
Message.encodeDelimited(message: Message|Object
[, writer: Writer
]): Writer
works like Message.encode
but additionally prepends the length of the message as a varint.
Message.decode(reader: Reader|Uint8Array
): Message
decodes a buffer to a message instance. If required fields are missing, it throws a util.ProtocolError
with an instance
property set to the so far decoded message. If the wire format is invalid, it throws an Error
.
1try { 2 var decodedMessage = AwesomeMessage.decode(buffer); 3} catch (e) { 4 if (e instanceof protobuf.util.ProtocolError) { 5 // e.instance holds the so far decoded message with missing required fields 6 } else { 7 // wire format is invalid 8 } 9}
Message.decodeDelimited(reader: Reader|Uint8Array
): Message
works like Message.decode
but additionally reads the length of the message prepended as a varint.
Message.create(properties: Object
): Message
creates a new message instance from a set of properties that satisfy the requirements of a valid message. Where applicable, it is recommended to prefer Message.create
over Message.fromObject
because it doesn't perform possibly redundant conversion.
1var message = AwesomeMessage.create({ awesomeField: "AwesomeString" });
Message.fromObject(object: Object
): Message
converts any non-valid plain JavaScript object to a message instance using the conversion steps outlined within the table above.
1var message = AwesomeMessage.fromObject({ awesomeField: 42 });
2// converts awesomeField to a string
Message.toObject(message: Message
[, options: ConversionOptions
]): Object
converts a message instance to an arbitrary plain JavaScript object for interoperability with other libraries or storage. The resulting plain JavaScript object might still satisfy the requirements of a valid message depending on the actual conversion options specified, but most of the time it does not.
1var object = AwesomeMessage.toObject(message, {
2 enums: String, // enums as string names
3 longs: String, // longs as strings (requires long.js)
4 bytes: String, // bytes as base64 encoded strings
5 defaults: true, // includes default values
6 arrays: true, // populates empty arrays (repeated fields) even if defaults=false
7 objects: true, // populates empty objects (map fields) even if defaults=false
8 oneofs: true // includes virtual oneof fields set to the present field's name
9});
For reference, the following diagram aims to display relationships between the different methods and the concept of a valid message:
In other words:
verify
indicates that callingcreate
orencode
directly on the plain object will [result in a valid message respectively] succeed.fromObject
, on the other hand, does conversion from a broader range of plain objects to create valid messages. (ref)
It is possible to load existing .proto files using the full library, which parses and compiles the definitions to ready to use (reflection-based) message classes:
1// awesome.proto 2package awesomepackage; 3syntax = "proto3"; 4 5message AwesomeMessage { 6 string awesome_field = 1; // becomes awesomeField 7}
1protobuf.load("awesome.proto", function(err, root) {
2 if (err)
3 throw err;
4
5 // Obtain a message type
6 var AwesomeMessage = root.lookupType("awesomepackage.AwesomeMessage");
7
8 // Exemplary payload
9 var payload = { awesomeField: "AwesomeString" };
10
11 // Verify the payload if necessary (i.e. when possibly incomplete or invalid)
12 var errMsg = AwesomeMessage.verify(payload);
13 if (errMsg)
14 throw Error(errMsg);
15
16 // Create a new message
17 var message = AwesomeMessage.create(payload); // or use .fromObject if conversion is necessary
18
19 // Encode a message to an Uint8Array (browser) or Buffer (node)
20 var buffer = AwesomeMessage.encode(message).finish();
21 // ... do something with buffer
22
23 // Decode an Uint8Array (browser) or Buffer (node) to a message
24 var message = AwesomeMessage.decode(buffer);
25 // ... do something with message
26
27 // If the application uses length-delimited buffers, there is also encodeDelimited and decodeDelimited.
28
29 // Maybe convert the message back to a plain object
30 var object = AwesomeMessage.toObject(message, {
31 longs: String,
32 enums: String,
33 bytes: String,
34 // see ConversionOptions
35 });
36});
Additionally, promise syntax can be used by omitting the callback, if preferred:
1protobuf.load("awesome.proto") 2 .then(function(root) { 3 ... 4 });
The library utilizes JSON descriptors that are equivalent to a .proto definition. For example, the following is identical to the .proto definition seen above:
1// awesome.json 2{ 3 "nested": { 4 "AwesomeMessage": { 5 "fields": { 6 "awesomeField": { 7 "type": "string", 8 "id": 1 9 } 10 } 11 } 12 } 13}
JSON descriptors closely resemble the internal reflection structure:
Type (T) | Extends | Type-specific properties |
---|---|---|
ReflectionObject | options | |
Namespace | ReflectionObject | nested |
Root | Namespace | nested |
Type | Namespace | fields |
Enum | ReflectionObject | values |
Field | ReflectionObject | rule, type, id |
MapField | Field | keyType |
OneOf | ReflectionObject | oneof (array of field names) |
Service | Namespace | methods |
Method | ReflectionObject | type, requestType, responseType, requestStream, responseStream |
T.fromJSON(name, json)
creates the respective reflection object from a JSON descriptorT#toJSON()
creates a JSON descriptor from the respective reflection object (its name is used as the key within the parent)Exclusively using JSON descriptors instead of .proto files enables the use of just the light library (the parser isn't required in this case).
A JSON descriptor can either be loaded the usual way:
1protobuf.load("awesome.json", function(err, root) { 2 if (err) throw err; 3 4 // Continue at "Obtain a message type" above 5});
Or it can be loaded inline:
1var jsonDescriptor = require("./awesome.json"); // exemplary for node 2 3var root = protobuf.Root.fromJSON(jsonDescriptor); 4 5// Continue at "Obtain a message type" above
Both the full and the light library include full reflection support. One could, for example, define the .proto definitions seen in the examples above using just reflection:
1... 2var Root = protobuf.Root, 3 Type = protobuf.Type, 4 Field = protobuf.Field; 5 6var AwesomeMessage = new Type("AwesomeMessage").add(new Field("awesomeField", 1, "string")); 7 8var root = new Root().define("awesomepackage").add(AwesomeMessage); 9 10// Continue at "Create a new message" above 11...
Detailed information on the reflection structure is available within the API documentation.
Message classes can also be extended with custom functionality and it is also possible to register a custom constructor with a reflected message type:
1...
2
3// Define a custom constructor
4function AwesomeMessage(properties) {
5 // custom initialization code
6 ...
7}
8
9// Register the custom constructor with its reflected type (*)
10root.lookupType("awesomepackage.AwesomeMessage").ctor = AwesomeMessage;
11
12// Define custom functionality
13AwesomeMessage.customStaticMethod = function() { ... };
14AwesomeMessage.prototype.customInstanceMethod = function() { ... };
15
16// Continue at "Create a new message" above
(*) 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
and AwesomeMessage#toJSON
Afterwards, decoded messages of this type are instanceof AwesomeMessage
.
Alternatively, it is also possible to reuse and extend the internal constructor if custom initialization code is not required:
1...
2
3// Reuse the internal constructor
4var AwesomeMessage = root.lookupType("awesomepackage.AwesomeMessage").ctor;
5
6// Define custom functionality
7AwesomeMessage.customStaticMethod = function() { ... };
8AwesomeMessage.prototype.customInstanceMethod = function() { ... };
9
10// Continue at "Create a new message" above
The library also supports consuming 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:
1function rpcImpl(method, requestData, callback) { 2 // perform the request using an HTTP request or a WebSocket for example 3 var responseData = ...; 4 // and call the callback with the binary response afterwards: 5 callback(null, responseData); 6}
Below is a working example with a typescript implementation using grpc npm package.
1const grpc = require('grpc')
2
3const Client = grpc.makeGenericClientConstructor({})
4const client = new Client(
5 grpcServerUrl,
6 grpc.credentials.createInsecure()
7)
8
9const rpcImpl = function(method, requestData, callback) {
10 client.makeUnaryRequest(
11 method.name,
12 arg => arg,
13 arg => arg,
14 requestData,
15 callback
16 )
17}
Example:
1// greeter.proto 2syntax = "proto3"; 3 4service Greeter { 5 rpc SayHello (HelloRequest) returns (HelloReply) {} 6} 7 8message HelloRequest { 9 string name = 1; 10} 11 12message HelloReply { 13 string message = 1; 14}
1...
2var Greeter = root.lookup("Greeter");
3var greeter = Greeter.create(/* see above */ rpcImpl, /* request delimited? */ false, /* response delimited? */ false);
4
5greeter.sayHello({ name: 'you' }, function(err, response) {
6 console.log('Greeting:', response.message);
7});
Services also support promises:
1greeter.sayHello({ name: 'you' }) 2 .then(function(response) { 3 console.log('Greeting:', response.message); 4 });
There is also an example for streaming RPC.
Note that the service API is meant for clients. Implementing a server-side endpoint pretty much always requires transport channel (i.e. http, websocket, etc.) specific code with the only common denominator being that it decodes and encodes messages.
The library ships with its own type definitions and modern editors like Visual Studio Code will automatically detect and use them for code completion.
The npm package depends on @types/node because of Buffer
and @types/long because of Long
. If you are not building for node and/or not using long.js, it should be safe to exclude them manually.
The API shown above works pretty much the same with TypeScript. However, because everything is typed, accessing fields on instances of dynamically generated message classes requires either using bracket-notation (i.e. message["awesomeField"]
) or explicit casts. Alternatively, it is possible to use a typings file generated for its static counterpart.
1import { load } from "@apollo/protobufjs"; // respectively "./node_modules/protobufjs" 2 3load("awesome.proto", function(err, root) { 4 if (err) 5 throw err; 6 7 // example code 8 const AwesomeMessage = root.lookupType("awesomepackage.AwesomeMessage"); 9 10 let message = AwesomeMessage.create({ awesomeField: "hello" }); 11 console.log(`message = ${JSON.stringify(message)}`); 12 13 let buffer = AwesomeMessage.encode(message).finish(); 14 console.log(`buffer = ${Array.prototype.toString.call(buffer)}`); 15 16 let decoded = AwesomeMessage.decode(buffer); 17 console.log(`decoded = ${JSON.stringify(decoded)}`); 18});
If you generated static code to bundle.js
using the CLI and its type definitions to bundle.d.ts
, then you can just do:
1import { AwesomeMessage } from "./bundle.js";
2
3// example code
4let message = AwesomeMessage.create({ awesomeField: "hello" });
5let buffer = AwesomeMessage.encode(message).finish();
6let decoded = AwesomeMessage.decode(buffer);
The library also includes an early implementation of decorators.
Note that decorators are an experimental feature in TypeScript and that declaration order is important depending on the JS target. For example, @Field.d(2, AwesomeArrayMessage)
requires that AwesomeArrayMessage
has been defined earlier when targeting ES5
.
1import { Message, Type, Field, OneOf } from "@apollo/protobufjs/light"; // respectively "./node_modules/protobufjs/light.js" 2 3export class AwesomeSubMessage extends Message<AwesomeSubMessage> { 4 5 @Field.d(1, "string") 6 public awesomeString: string; 7 8} 9 10export enum AwesomeEnum { 11 ONE = 1, 12 TWO = 2 13} 14 15@Type.d("SuperAwesomeMessage") 16export class AwesomeMessage extends Message<AwesomeMessage> { 17 18 @Field.d(1, "string", "optional", "awesome default string") 19 public awesomeField: string; 20 21 @Field.d(2, AwesomeSubMessage) 22 public awesomeSubMessage: AwesomeSubMessage; 23 24 @Field.d(3, AwesomeEnum, "optional", AwesomeEnum.ONE) 25 public awesomeEnum: AwesomeEnum; 26 27 @OneOf.d("awesomeSubMessage", "awesomeEnum") 28 public which: string; 29 30} 31 32// example code 33let message = new AwesomeMessage({ awesomeField: "hello" }); 34let buffer = AwesomeMessage.encode(message).finish(); 35let decoded = AwesomeMessage.decode(buffer);
Supported decorators are:
Type.d(typeName?: string
) (optional)
annotates a class as a protobuf message type. If typeName
is not specified, the constructor's runtime function name is used for the reflected type.
Field.d<T>(fieldId: number
, fieldType: string | Constructor<T>
, fieldRule?: "optional" | "required" | "repeated"
, defaultValue?: T
)
annotates a property as a protobuf field with the specified id and protobuf type.
MapField.d<T extends { [key: string]: any }>(fieldId: number
, fieldKeyType: string
, fieldValueType. string | Constructor<{}>
)
annotates a property as a protobuf map field with the specified id, protobuf key and value type.
OneOf.d<T extends string>(...fieldNames: string[]
)
annotates a property as a protobuf oneof covering the specified fields.
Other notes:
protobuf.roots["decorated"]
using a flat structure, so no duplicate names.ProTip! Not as pretty, but you can use decorators in plain JavaScript as well.
Note that moving the CLI to its own package is a work in progress. At the moment, it's still part of the main package.
The command line interface (CLI) can be used to translate between file formats and to generate static code as well as TypeScript definitions.
Translates between file formats and generates static code.
-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 (non-functional on its own)
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.
--sparse Exports only those types referenced from a main file (experimental).
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)
closure A closure adding to protobuf.roots where protobuf is a global
-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.
--force-long Enforces the use of 'Long' for s-/u-/int64 and s-/fixed64 fields.
--force-number Enforces the use of 'number' for s-/u-/int64 and s-/fixed64 fields.
--force-message Enforces the use of message instances instead of plain objects.
usage: pbjs [options] file1.proto file2.json ... (or pipe) 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:
1var root = protobuf.Root.fromJSON(require("./bundle.json"));
or load it the usual way:
1protobuf.load("bundle.json", function(err, root) { 2 ... 3});
Generated static code, on the other hand, 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.
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 only 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:
new SomeMessage(...)
, always use SomeMessage.create(...)
because reflection objects do not provide a constructor.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 -
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 source code without any reflection features. This also implies that there is a break-even point where statically generated code becomes larger than descriptor-based code once the amount of code generated exceeds the size of the full respectively light library.
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.
Source | Library | Advantages | Tradeoffs |
---|---|---|---|
.proto | full | Easily editable Interoperability with other libraries No compile step | Some parsing and possibly network overhead |
JSON | light | Easily editable No parsing overhead Single bundle (no network overhead) | protobuf.js specific Has a compile step |
static | minimal | Works where eval access is restrictedFully documented Small footprint for small protos | Can be hard to edit No reflection Has a compile step |
Both utilities can be used programmatically by providing command line arguments and a callback to their respective main
functions:
1var pbjs = require("@apollo/protobufjs/cli/pbjs"); // or require("@apollo/protobufjs/cli").pbjs / .pbts 2 3pbjs.main([ "--target", "json-module", "path/to/myproto.proto" ], function(err, output) { 4 if (err) 5 throw err; 6 // do something with output 7});
The package includes a benchmark that compares protobuf.js performance to native JSON (as far as this is possible) and Google's JS implementation. On an i7-2600K running node 6.9.1 it yields:
benchmarking encoding performance ...
protobuf.js (reflect) x 541,707 ops/sec ±1.13% (87 runs sampled)
protobuf.js (static) x 548,134 ops/sec ±1.38% (89 runs sampled)
JSON (string) x 318,076 ops/sec ±0.63% (93 runs sampled)
JSON (buffer) x 179,165 ops/sec ±2.26% (91 runs sampled)
google-protobuf x 74,406 ops/sec ±0.85% (86 runs sampled)
protobuf.js (static) was fastest
protobuf.js (reflect) was 0.9% ops/sec slower (factor 1.0)
JSON (string) was 41.5% ops/sec slower (factor 1.7)
JSON (buffer) was 67.6% ops/sec slower (factor 3.1)
google-protobuf was 86.4% ops/sec slower (factor 7.3)
benchmarking decoding performance ...
protobuf.js (reflect) x 1,383,981 ops/sec ±0.88% (93 runs sampled)
protobuf.js (static) x 1,378,925 ops/sec ±0.81% (93 runs sampled)
JSON (string) x 302,444 ops/sec ±0.81% (93 runs sampled)
JSON (buffer) x 264,882 ops/sec ±0.81% (93 runs sampled)
google-protobuf x 179,180 ops/sec ±0.64% (94 runs sampled)
protobuf.js (reflect) was fastest
protobuf.js (static) was 0.3% ops/sec slower (factor 1.0)
JSON (string) was 78.1% ops/sec slower (factor 4.6)
JSON (buffer) was 80.8% ops/sec slower (factor 5.2)
google-protobuf was 87.0% ops/sec slower (factor 7.7)
benchmarking combined performance ...
protobuf.js (reflect) x 275,900 ops/sec ±0.78% (90 runs sampled)
protobuf.js (static) x 290,096 ops/sec ±0.96% (90 runs sampled)
JSON (string) x 129,381 ops/sec ±0.77% (90 runs sampled)
JSON (buffer) x 91,051 ops/sec ±0.94% (90 runs sampled)
google-protobuf x 42,050 ops/sec ±0.85% (91 runs sampled)
protobuf.js (static) was fastest
protobuf.js (reflect) was 4.7% ops/sec slower (factor 1.0)
JSON (string) was 55.3% ops/sec slower (factor 2.2)
JSON (buffer) was 68.6% ops/sec slower (factor 3.2)
google-protobuf was 85.5% ops/sec slower (factor 6.9)
These results are achieved by
You can also run the benchmark ...
$> npm run bench
and the profiler yourself (the latter requires a recent version of node):
$> npm run prof <encode|decode|encode-browser|decode-browser> [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.
google/protobuf/descriptor.proto
, options are parsed and presented literally.Long
instance instead of a possibly unsafe JavaScript number (see).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
By default, protobuf.js integrates into any browserify build-process without requiring any optional modules. Hence:
If int64 support is required, 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:
1var Long = ...; 2 3protobuf.util.Long = Long; 4protobuf.configure();
If you have any special requirements, there is the bundler for reference.
License: BSD 3-Clause License
No vulnerabilities found.
Reason
no binaries found in the repo
Reason
security policy file detected
Details
Reason
license file detected
Details
Reason
Found 6/30 approved changesets -- score normalized to 2
Reason
0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Reason
no effort to earn an OpenSSF best practices badge detected
Reason
project is not fuzzed
Details
Reason
SAST tool is not run on all commits -- score normalized to 0
Details
Reason
62 existing vulnerabilities detected
Details
Score
Last Scanned on 2024-11-25
The Open Source Security Foundation is a cross-industry collaboration to improve the security of open source software (OSS). The Scorecard provides security health metrics for open source projects.
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