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protocore

Specify and deploy performant binary protocol structures in Node

GitHub | NPM

Install

npm i protocore

Then include the library in your code:

const {Schema, StreamingAbstractor, types, protospec} = require('protocore')

What is Protocore?

Protocore makes building custom binary protocols a snap.

It's a lightweight Node library that takes the pain out of making binary protocols for games, databases, and other performance-dependent applications!

Protocore allows developers to create advanced protocols with powerful functionality and maximum efficiency.

Protocore schemas are much more efficient than JSON

See benchmarks ->

Define a Schema

const personSchema = new Schema([
	{
		'name': 'firstName',
		'type': types.string
	},
	{
		'name': 'age',
		'type': types.uint,
		'size': 8
	},
	{
		'name': 'alive',
		'type': types.boolean
	}
])

The above code defines a simple schema which represents a person.

It includes a firstName string field and an age, which is a UInt8.

Build a Buffer from a Schema

const ethanBuf = personSchema.build({
	'name': 'Ethan Davis',
	'age': 17,
	'alive': true
})

// Now ethanBuf is a buffer representation of a person!

Here we've built a buffer from Ethan's data using the personSchema Schema. The Schema.build method returns a Buffer.

Parse a Buffer from a Schema

// ^ Let's say ethanBuf is a buffer created with the personSchema Schema

const parsed = personSchema.parse(ethanBuf)

// parsed will now be an object with the original information about Ethan!
// parsed = {'name': 'Ethan Davis', 'age': 17, 'alive': true}

Above a buffer was parsed using personSchema, which returned an object representation of the data!

Lists and Maps in Schemas

Lists and Maps can be defined in schemas as well.

const citySchema = new Schema([
	{
		'name': 'name',
		'type': types.string
	},
	{
		'name': 'buildings',
		'type': types.list,
		'of': new Schema([
			{
				'name': 'name',
				'type': types.string
			},
			{
				'name': 'constructed',
				'type': types.uint,
				'size': 16
			}
		])
	},
	{
		'name': 'residentLifetimes',
		'type': types.map,
		'key': {
			'type': types.string
		},
		'value': {
			'type': types.varint
		}
	}
])

We've now defined citySchema, which represents a city with buildings and residents. Buildings have names and also contain the year they were constructed. Residents' time spent in the city are represented in the residentLifetimes map.

Serializing Lists and Maps in Schemas

const sanFranciscoBuf = citySchema.build({
	'name': 'San Francisco',
	'buildings': [
		{
			'name': 'Salesforce Tower',
			'constructed': 2018
		},
		{
			'name': 'Ferry Building',
			'constructed': 1898
		}
	],
	'residentLifetimes': {
		'Ethan': 8,
		'James': 9,
		'Bohn': 12
	}
})

Parsing Lists and Maps in Schemas

const sanFrancisco = citySchema.parse(sanFranciscoBuf)

sanFrancisco will be similar to the object we built sanFranciscoBuf from. It will have an array of building objects. It will also have a map (object with appropriate types) for residentLifetimes.

Utilizing StreamingAbstractor

StreamingAbstractors allow us to create duplex, event-based streaming systems for applications.

Let's create a StreamingAbstractor.

const myAbstractor = new StreamingAbstractor()

myAbstractor.register('login', new Schema([
	{
		'name': 'username',
		'type': types.string
	},
	{
		'name': 'number',
		'type': types.uint,
		'size': 16
	}
]))

// Now we can bind myAbstractor to a stream using myAbstractor.bind(stream)

Above we've registered an event called 'login' in our abstractor. Now it can recieve login events from a stream connected to another StreamingAbstractor.

Recieving Events Through StreamingAbstractor

Now that we have a StreamingAbstractor (myAbstractor) with the login event registered, we'll listen for login on our end.

myAbstractor.on('login', (data) => {
	console.log('Login with username ' + data.username + ' and number ' + data.number + '.')
})

Sending Events Through StreamingAbstractor

Because we've registered the login event, we can send login events using myAbstractor.

myAbstractor.send('login', {
	'username': 'ethan',
	'number': 5135
})

Creating Custom Types

It's possible to build custom types for Protocore schemas to use, and it's not too complex either.

Protocore ships with its own built in types (ex. string, buffer, int, double, etc), and those are available for inspection in the types directory.

Writing Protocols with Protospec

Protospec is Protocore's protocol specification format. It is nice to write.

// my.pspec

def player private
string username
varint score
int x size=16
int y size=16

def join
instance player of=player

def updateAllPlayers
list players of=player

To import a Protospec as a StreamingAbstractor:

// ... load spec, ex. fs.readFileSync(path.join(__dirname, 'my.pspec'))

const myAbstractor = protospec.importAbstractor(spec)

myAbstractor.on('updateAllPlayers', (data) => {
	// Do something with data.players
})

To import a Protospec as an Object of Schemas:

const mySchemas = protospec.importAll(spec).schemas

const builtJoin = mySchemas.join.build({
	'player': {
		'username': 'a',
		'score': 2,
		'x': 100,
		'y': 200
	}
})

Exchanges in a protocol

Protocore has a built-in protocol feature called an Exchange which allows protocols to define transfers of information in a "request-response" manner.

def ReqUser private
string username

def ResUser private
string username
uint age size=8
aliasUses map key=string;value=varint

exchange getUser
request ReqUser
response ResUser

Note that in this Protospec, the ReqUser and ResUser definitions are private. This means that they should not be directly sent over the StreamingAbstractor.

Server handles requests:

perClientAbstractor.on('getUser', (req, res) => {
	res({
		'username': req.username,
		'age': Math.floor(Math.random() * 100),
		'aliasUses': {
			'test': 5,
			'testB': 7
		}
	})
})

Client sends requests:

const userRes = await clientAbstractor.request('getUser', {
	'username': 'ethan'
})

console.log(userRes)
// => {'username': 'ethan', 'age': 18, 'aliasUses': {'test': 5, 'testB': 7}}