mocha-chai-rdf

Helpers to simplify testing code which uses RDF/JS data models.

chai matchers plugin

Setup

Register the matcher plugin with chai for example in a mocha test setup file:

import { use } from 'chai'
import rdfMatchers from 'mocha-chai-rdf/matchers.js'

use(rdfMatchers)

Term equality

The plugin overrides the eq assertion to compare RDF terms and clownface pointers.

import { expect } from 'chai'
import type { Term } from '@rdfjs/types'
import type { AnyPointer } from 'clownface'
import rdf from '@zazuko/env'

let actual: Term | AnyPointer
expect(actual).to.eq(rdf.ns.schema.Person)

Additionally, deep equality is also configured (chai v5+).

import { expect } from 'chai'
import type { Term } from '@rdfjs/types'
import type { AnyPointer } from 'clownface'
import rdf from '@zazuko/env'
  
let value: Record<{ type: Term }> // for example, results from SPARQL SELECT
expect(value).to.deep.eq([
  { type: rdf.ns.schema.Person }
])

Dataset snapshot testing

Usage

import type { DatasetCore } from '@rdfjs/types'
import { use } from 'chai'
import snapshots from 'mocha-chai-rdf/snapshots.js'

use(snapshots)

let dataset: DatasetCore
expect(dataset).canonical.toMatchSnapshot()

In-memory dataset in mocha tests

Basic example

In the example below, the call to createStore will load the RDF file test/my-test.spec.ts.ttl and populate an in-memory store with its contents. The store and other properties are then available in the test suite context under .rdf key.

// test/my-test.spec.ts
import { createStore } from 'mocha-chai-rdf/store.js'

describe('my test suite', () => {
  beforeEach(createStore(import.meta.url))
  
  context('foo', () => {
    context('bar', () => {
      it('should do something', function () {
        // you can access the dataset, graph and store
        // loaded from test fixture RDF file
        let { 
          dataset,       // RDF/JS dataset
          graph,         // clownface graph pointer
          store,         // oxigraph in-memory store
          parsingClient, // sparql-http-client-compatible client which returns parsed results
          streamClient   // sparql-http-client-compatible client which stream results
        } = this.rdf
      })
    })
  })
})

Load graphs from trig dataset files

To load graphs from a trig file, pass the trig option:

beforeEach(createStore(import.meta.url, { format: 'trig' }))

This will load a graph named <foo/bar> from the trig file. As you see, by default the topmost describe block name and the test name itself are omitted.

The titles of describe/context/it calls are encoded with to create valid URIs.

You can customize the options:

• include the default graph by adding includeDefaultGraph: true
• load all graphs by adding loadAll: true
• control the graph name by adding sliceTestPath: [number, number]. The default is [1, -1] which, as described above, omits the topmost describe block name and the test name itself, hence the first and last part are sliced from the array of block titles.

Initialise empty store

In case you'd only want to initialise an empty store:

import { createEmpty } from 'mocha-chai-rdf/store.js'

describe('my test suite', () => {
  beforeEach(createEmpty)
})