I'm trying to write a test to test a method that connects to mongo, but I don't actually want to have to have mongo running and actually make a connection to it to have my tests pass successfully.
Here's my current test which is successful when my mongo daemon is running.
describe('with a valid mongo string parameter', function() {
it('should return a rejected promise', function(done) {
var con = mongoFactory.getConnection('mongodb://localhost:27017');
expect(con).to.be.fulfilled;
done();
});
});
mongoFactory.getConnection code:
getConnection: function getConnection(connectionString) {
// do stuff here
// Initialize connection once
MongoClient.connect(connectionString, function(err, database) {
if (err) {
def.reject(err);
}
def.resolve(database);
});
return def.promise;
}
There are a couple of SO answers related to unit testing code that uses MongoDB as a data store:
- Mocking database in node.js?
- Mock/Test Mongodb Database Node.js
- Embedded MongoDB when running integration tests
- Similar: Unit testing classes that have online functionality
I'll make an attempt at consolidating these solutions.
Preamble
First and foremost, you should want MongoDB to be running while performing your tests. MongoDB's query language is complex, so running legitimate queries against a stable MongoDB instance is required to ensure your queries are running as planned and that your application is responding properly to the results. With this in mind, however, you should never run your tests against a production system, but instead a peripheral system to your integration environment. This can be on the same machine as your CI software, or simply relatively close to it (in terms of process, not necessarily network or geographically speaking).
This ENV could be low-footprint and completely run in memory (resource 1) (resource 2), but would not necessarily require the same performance characteristics as your production ENV. (If you want to performance test, this should be handled in a separate environment from your CI anyway.)
Setup
- Install a
mongod
service specifically for CI. If repl sets and/or sharding are of concern (e.g. write concern, no use of $isolated
, etc.), it is possible to mimic a clustered environment by running multiple mongod
instances (1 config, 2x2 data for shard+repl) and a mongos
instance on the same machine with either some init.d scripts/tweaks or something like docker.
- Use environment-specific configurations within your application (either embedded via .json files, or in some place like /etc, /home/user/.your-app or similar). Your application can load these based on a node environment variable like
NODE_ENV=int
. Within these configurations your db connection strings will differ. If you're not using env-specific configs, start doing this as a means to abstract the application runtime settings (i.e. "local", "dev", "int", "pre", "prod", etc.). I can provide a sample upon request.
- Include test-oriented fixtures with your application/testing suite. As mentioned in one of the linked questions, MongoDB's Node.js driver supports some helper libraries:
mongodb-fixtures
and node-database-cleaner
. Fixtures provide a working and consistent data set for testing: think of them as a bootstrap.
Builds/Tests
- Clean the associated database using something like
node-database-cleaner
.
- Populate your fixtures into the now empty database with the help of
mongodb-fixtures
.
- Perform your build and test.
- Repeat.
On the other hand...
If you still decide that not running MongoDB is the correct approach (and you wouldn't be the only one), then abstracting your data store calls from the driver with an ORM is your best bet (for the entire application, not just testing). For example, something like model
claims to be database agnostic, although I've never used it. Utilizing this approach, you would still require fixtures and env configurations, however you would not be required to install MongoDB. The caveat here is that you're at the mercy of the ORM you choose.
You could try tingodb.
TingoDB is an embedded JavaScript in-process filesystem or in-memory database upwards compatible with MongoDB at the API level.