Modern Node.js: async/await based testing with Mocha & Chai

2017-04-09 · 4 min read

Mocha is a JavaScript test framework running on Node.js and in the browser. It can run both asynchronous and synchronous code serially. Test cases are created using describe() and it() methods, the former is used to provide a structure by allowing to put various tests cases in logical groups while the latter is where the tests are written.

In order to perform actual tests, there is a need for an assertion library: a runtime mechanism which can be used to verify assumptions made by the program and print a diagnostic message if this assumption is false. Node.js comes with a built-in assert library. Chai is another popular assertion library that provides both the BDD and TDD styles of programming for testing the code. BDD stands for Behavior-driven development while TDD stands for Test-driven development. In a nutshell, Chai provides a should keyword for BDD style which allows to chain assertions and an expect() method for TDD style. Choosing between one and another is a matter of personal preference.

Here's an example of BDD style using should:


And here's an example of TDD style using expect:

const expect = chai.expect;


Let's put all this together to test some asynchronous code using async/await syntax. Here we have an asynchronous add() function which adds two numbers. We combine Mocha with Chai's expect style while using ES7 async/await syntax.

const expect = require('chai').expect;

async function add(a, b) {
  return Promise.resolve(a + b);

describe('#add()', () => {
  it('2 + 2 is 4', async () => {
    const p = await add(2, 2)

  it('3 + 3 is 6', async () => {
    const p = await add(3, 3)

async/await syntax also makes plugins such chai-as-promised obsolete as we no longer need to assert facts about promises and we can only deal with values. Passing lambdas (or arrow functions) to Mocha is discouraged as it's impossible to access Mocha helper functions (lexically bound to this), but in practice those functions are rarely used.

In order to run let's create a new Node.js project

mkdir async-await-mocha-chai-example
cd async-await-mocha-chai-example
yarn init -y

Next, we need to install both mocha and chai as development dependencies

yarn add mocha chai --dev

Finally, let's put our test under test/add.test.js and run it.

yarn run mocha
yarn run v0.22.0

    ✓ 2 + 2 is 4
    ✓ 3 + 3 is 6

  4 passing (199ms)

✨  Done in 0.99s.

For convenience, we can add a test command in scripts section of package.json

"scripts": {
  "test": "mocha --reporter list"

This way we can now run yarn run test and specify some default options such --reporter once and for all test runs. We can select which Mocha tests to run using -g <pattern> or -f <substring> options.

Mocha also provides hook methods which are used to take care of external resources (setup and teardown) either before or after all tests using before() and after() methods, or before and after each particular test with beforeEach() and afterEach(). Here's an example showing how to test database persistance. The database connection is established once before all tests while the database is initialized from scratch before each test so they start from the same initial state.

const expect = require('chai').expect;
const Sequelize = require('sequelize');

describe('users', () => {
  let database;
  let User;

  before(async () => {
    database = new Sequelize('postgresql://localhost/app_test', { logging: false });
    User = database.define('user', {
      username: Sequelize.STRING,
      birthday: Sequelize.DATE

  beforeEach(async () => {
    await User.sync();
    await User.create({
      username: 'zaiste',
      birthday: new Date(1988, 1, 21)

  afterEach(async () => {
    await User.drop();

  describe('#find()', () => {
    it('should find a user', async () => {
      const user = await User.findOne({ where: { username: 'zaiste' }})

Finally Mocha, prints uncaught exceptions alongside the test cases in which they were thrown, making it easy to identify exactly what failed and why.

The code for this article is located on GitHub.

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