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Merkle DAG that replicates based on scuttlebutt logs and causal linking

npm install hyperlog

build status dat

var hyperlog = require('hyperlog')

var log = hyperlog(db) // where db is a levelup instance

// add a node with value 'hello' and no links
log.add(null, 'hello', function(err, node) {
  console.log('inserted node', node)

  // insert 'world' with a link back to the above node
  log.add([node.key], 'world', function(err, node) {
    console.log('inserted new node', node)

Replicate graph

To replicate this log with another one simply use log.replicate() and pipe it together with a replication stream from another log.

var l1 = hyperlog(db1)
var l2 = hyperlog(db2)

var s1 = l1.replicate()
var s2 = l2.replicate()


s1.on('end', function() {
  console.log('replication ended')

A detailed write-up on how this replication protocol works will be added to this repo in the near future. For now see the source code.


log = hyperlog(db, opts={})

Create a new log instance. Valid keys for opts include:

  • id - some (ideally globally unique) string identifier for the log.
  • valueEncoding - a levelup-style encoding string or object (e.g. "json")
  • hash(links, value) - a hash function that runs synchronously. Defaults to a SHA-256 implementation.
  • asyncHash(links, value, cb) - an asynchronous hash function with node-style callback (cb(err, hash)).
  • identity, sign, verify - values for creating a cryptographically signed feed. See below.

You can also pass in an identity and sign/verify functions which can be used to create a signed log:

  identity: aPublicKeyBuffer, // will be added to all nodes you insert
  sign: function (node, cb) {
    // will be called with all nodes you add
    var signatureBuffer = someCrypto.sign(node.key, mySecretKey)
    cb(null, signatureBuffer)
  verify: function (node, cb) {
    // will be called with all nodes you receive
    if (!node.signature) return cb(null, false)
    cb(null, someCrypto.verify(node.key, node.signature. node.identity))

log.add(links, value, opts={}, [cb])

Add a new node to the graph. links should be an array of node keys that this node links to. If it doesn't link to any nodes use null or an empty array. value is the value that you want to store in the node. This should be a string or a buffer. The callback is called with the inserted node:

log.add([link], value, function(err, node) {
  // node looks like this
    change: ... // the change number for this node in the local log
    key:   ... // the hash of the node. this is also the key of the node
    value:  ... // the value (as the valueEncoding type, default buffer) you inserted
    log:    ... // the peer log this node was appended to
    seq:    ... // the peer log seq number
    links: ['hash-of-link-1', ...]

Optionally supply an opts.valueEncoding.

log.append(value, opts={}, [cb])

Add a value that links all the current heads.

Optionally supply an opts.valueEncoding.

log.batch(docs, opts={}, [cb])

Add many documents atomically to the log at once: either all the docs are inserted successfully or nothing is inserted.

docs is an array of objects where each object looks like:

  links: [...] // array of ancestor node keys
  value: ... // the value to insert

The callback cb(err, nodes) is called with an array of nodes. Each node is of the form described in the log.add() section.

You may specify an opts.valueEncoding.

log.get(hash, opts={}, cb)

Lookup a node by its hash. Returns a node similar to .add above.

Optionally supply an opts.valueEncoding.

log.heads(opts={}, cb)

Get the heads of the graph as a list. A head is node that no other node links to.

log.heads(function(err, heads) {
  console.log(heads) // prints an array of nodes

The method also returns a stream of heads which is useful if, for some reason, your graph has A LOT of heads

var headsStream = log.heads()

headsStream.on('data', function(node) {
  console.log('head:', node)

headsStream.on('end', function() {
  console.log('(no more heads)')

Optionally supply an opts.valueEncoding.

changesStream = log.createReadStream([options])

Tail the changes feed from the log. Everytime you add a node to the graph the changes feed is updated with that node.

var changesStream = log.createReadStream({live:true})

changesStream.on('data', function(node) {
  console.log('change:', node)

Options include:

  since: changeNumber     // only returns changes AFTER the number
  live: false             // never close the change stream
  tail: false             // since = lastChange
  limit: number           // only return up to `limit` changes
  until: number           // (for non-live streams) only returns changes BEFORE the number
  valueEncoding: 'binary'

replicationStream = log.replicate([options])

Replicate the log to another one using a replication stream. Simply pipe your replication stream together with another log's replication stream.

var l1 = hyperlog(db1)
var l2 = hyperlog(db2)

var s1 = l1.createReplicationStream()
var s2 = l2.createReplicationStream()


s1.on('end', function() {
  console.log('replication ended')

Options include:

  mode: 'push' | 'pull' | 'sync', // set replication mode. defaults to sync
  live: true, // keep the replication stream open. defaults to false
  metadata: someBuffer, // send optional metadata as part of the handshake
  frame: true // frame the data with length prefixes. defaults to true

If you send metadata it will be emitted as an metadata event on the stream. A detailed write up on how the graph replicates will be added later.

log.on('preadd', function (node) {})

On the same tick as log.add() is called, this event fires with the node about to be inserted into the log. At this stage of the add process, node has these properties:

  • node.log
  • node.key
  • node.value
  • node.links

log.on('add', function (node) {})

After a node has been successfully added to the log, this event fires with the full node object that the callback to .add() gets.

log.on('reject', function (node) {})

When a node is rejected, this event fires. Otherwise the add event will fire.

You can track preadd events against both add and reject events in combination to know when the log is completely caught up.

Hyperlog Hygiene

A hyperlog will refer to potentially many different logs as it replicates with others, each with its own ID. Bear in mind that each hyperlog's underlying leveldb contains a notion of what its own local ID is. If you make a copy of a hyperlog's leveldb and write different data to each copy, the results are unpredictable and likely disastrous. Always only use the included replication mechanism for making hyperlog copies!




Merkle DAG that replicates based on scuttlebutt logs and causal linking






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