@ldhop/core

LDhop - Follow your nose through Linked Data graph. This is the core engine package.

Usage

npm install @ldhop/core --save
yarn add @ldhop/core

import { QueryAndStore, RdfQuery, fetchRdfDocument, run } from '@ldhop/core'
import { foaf, rdfs } from 'rdf-namespaces'

// specify the steps of the query
// in this case fetch the whole foaf social network
// and also look in extended profile documents
const friendOfAFriendQuery: RdfQuery = [
  {
    type: 'match',
    subject: '?person',
    predicate: foaf.knows,
    pick: 'object',
    target: '?person',
  },
  {
    type: 'match',
    subject: '?person',
    predicate: rdfs.seeAlso,
    pick: 'object',
    target: '?extendedProfile',
  },
  {
    type: 'add resources',
    variable: '?extendedProfile',
  },
]

// specify starting points
const initialVariables = { person: new Set([webId]) }

// initialize the walk
const qas = new QueryAndStore(friendOfAFriendQuery, initialVariables)

// now, you need to ask for missing resources, fetch them, add them to QueryAndStore
// and keep doing that until there are no missing resources left
// you can use a simple helper provided by this library
await run(qas, fetch)
// or implement your own walk, using the following methods repeatedly:
const [missingResource] = qas.getMissingResources()
if (missingResource) {
  const { data } = await fetchRdfDocument(missingResource, fetch)
  qas.addResource(missingResource, data)
}

// now, you have the whole RDF graph collected in qas.store, which is n3.Store
// each triple has a graph element that corresponds to the url of the document of that triple
const store = qas.store

// you can show specific variable
qas.getVariable('person')
// or all variables
qas.getAllVariables()

Query

Query is an array of instructions to follow in order to discover and fetch desired Linked data.

It proceeds lazily - only requests next documents when they're needed for next steps, or if explicitly instructed.

The following steps are supported:

// step through the graph
type Match = {
  type: 'match'
  // optional constraints, either URI, or variable starting with ?
  subject?: string
  predicate?: string
  object?: string
  graph?: string
  // which of the quad components to assign to the target variable?
  pick: 'subject' | 'predicate' | 'object' | 'graph'
  // variable that results will be assigned to, starting with ?
  target: `?${string}`
}

// fetch documents behind variable, even if it isn't needed for next steps
type AddResources = {
  type: 'add resources'
  variable: `?${string}` // variable to fetch
}

// change variable, for example get container of a resource
type TransformVariable = {
  type: 'transform variable'
  source: `?${string}`
  target: `?${string}`
  // function to transform
  transform: (uri: Term) => Term | undefined
}

// edit the whole store in place
// this is a dangerous operation, because you can ruin the inner consistency of QueryAndStore
// don't use this unless you really really have to
type TransformStore = (qas: QueryAndStore) => void

Example query: Fetch Solid WebId Profile

See Solid WebID Profile specification for context.

import type { RdfQuery } from '@ldhop/core'

// find person and their profile documents
const webIdProfileQuery: RdfQuery = [
  // find and fetch preferences file
  {
    type: 'match',
    subject: '?person',
    predicate: pim.preferencesFile,
    pick: 'object',
    target: '?preferencesFile',
  },
  { type: 'add resources', variable: '?preferencesFile' },
  // find extended profile documents
  {
    type: 'match',
    subject: '?person',
    predicate: rdfs.seeAlso,
    pick: 'object',
    target: '?profileDocument',
  },
  // fetch the extended profile documents
  { type: 'add resources', variable: '?profileDocument' },
  // find public type index
  {
    type: 'match',
    subject: '?person',
    predicate: solid.publicTypeIndex,
    pick: 'object',
    target: '?publicTypeIndex',
  },
  // find private type index
  {
    type: 'match',
    subject: '?person',
    predicate: solid.privateTypeIndex,
    pick: 'object',
    target: '?privateTypeIndex',
  },
  // find inbox
  {
    type: 'match',
    subject: '?person',
    predicate: ldp.inbox,
    pick: 'object',
    target: '?inbox',
  },
]

The query corresponds to the following picture. The resources identified by the URIs within the variables in bold circles are fetched while it is executed.

API

QueryAndStore

creating an instance

const qas = new QueryAndStore(query, startingPoints, (store = new n3.Store()))

properties

• store: n3.Store - store containing RDF graph
• query: RdfQuery - ldhop query

methods

• getMissingResources() - returns list of resources that still need to be fetched and added
• addResource(uri: string, quads: n3.Quad[], status: 'success' | 'error' = 'success') - add resource after it has been fetched - you can use fetchRdfDocument function provided by this library to receive correct input for this function
• removeResource(uri: string) - delete resource from store
• getVariable(variableName: string) - get list of RDF nodes belonging to this variable
• getAllVariables() - get dictionary of lists of all discovered variables
• getResources(status?: 'missing', 'added', 'failed') - get list of resources with specific status, or all resources regardless of their status

fetchRdfDocument

Fetch turtle document and parse it to ldhop-compatible quads

const { data } = await fetchRdfDocument(uri, fetch)
qas.addResource(uri, data)

run

Execute the ldhop query until the walk through the graph is finished.

It runs simple loop that continues as long as qas.getMissingResources() returns something: It fetches one missing resource, adds it with qas.addResource() and repeats. You can probably implement something safer or more efficient yourself, e.g. fetch missing resources in parallel.

You can provide custom (e.g. authenticated) fetch.

const qas = new QueryAndStore(query, initialVariables)
await run(qas, fetch)