As of 2023-04-04 this has been archived due to Compose being End of Life and so no one is maintaining this repository. It may become publicly open-sourced and supported under IBM Cloud at some point in the future.
Create mocks of modules (especially clients) with easily-defined scenarios (success, invalid, etc) and an optional in-memory persistence layer.
When unit testing, libraries that constitute dependencies become cumbersome to stub as complexity increases. Most of the time you want to simulate various high-level scenarios that can be produced in your library. Stubbing those high-level scenarios in your tests with low-level tools can be cumbersome and requires a lot of logic about your dependencies to be sprinked throughout your tests. Outright mocking the libraries in various ways (Webmock, VCR, DIY fake classes) can be tricky.
When you mock a library using Shoegaze, Shoegaze creates an Rspec double of the library. Using a simple DSL you can specify test implementations
and their scenarios
for the mocked library's methods. Swap out your real library implementation for the mock, then drive the high-level behavior in your tests by specifying the scenarios to run. This provides a consistent interface for creating mocks and forces you to mock your library's API, which is the right place to separate the concerns of the library from your tests.
class FakeTwitterClient < Shoegaze::Mock
# optional. provides in-memory persisted ActiveModel objects so that
# your mock can 'remember' its state
extend Shoegaze::Datastore
mock "Twitter::Client"
# creates both a FakeTwitterClient::Update 'model' and a FactoryBot
# factory for the model
datastore :Update do
id{ BSON::ObjectId.new }
date{ Time.new }
body{ Faker::Lorem.sentence }
location{ [Faker::Address.latitude, Faker::Address.longitude] }
end
implement :update do
scenario :success do
# optional. you can provide transforms for your 'models' to
# represent the data returned by the implementation in various
# ways
representer do
include Representable::JSON
property :id
property :date
property :body
# notice we omit location in this representation
end
# this method will call :as_json on the representer, meaning it
# will return a hash. you can also call to_json, for example, to
# return stringified JSON instead
represent_method :as_json
datasource do
# generate an update and store it in the memory store (you can
# grab it with FakerTwitterClient::Update.find(update.id)
FactoryBot.create(Update)
end
end
scenario :unavailable do
datasource do |id|
raise Twitter::ConnectionFailed.new(Struct.new(:status).new(status: "504"))
end
end
end
# you can mock chained methods by nesting implementations, too
#
# example: ProductMaker.accounts.create({name: "Jack Dorsey"})
implement :accounts do
scenario :success do
datasource do
implement :create do
# default scenarios can be specified
default do |params|
FactoryBot.create(Account, params)
end
end
end
end
end
end
class ProductMaker
class << self
def create(name)
# ...
twitter_client.update("We have a new product: #{product.name}!")
product
end
private
def twitter_client
@twitter_client ||= Twitter::Client.new
end
end
end
RSpec.configure do |config|
config.before :each do
# swap out the twitter client for the mock in all tests
stub_const("Twitter::Client", FakeTwitterClient.proxy)
end
end
describe ProductMaker do
describe "#create" do
describe "tweeting" do
describe "is successful" do
before :each do
FakeTwitterClient.calling(:update).with(update.body).yields(:success)
end
it "posts a twitter update" do
product = ProductMaker.create("some_product")
update = FakeTwitterClient::Update.find_by_body("We have a new product: #{product.name}!")
expect(update).to exist
end
end
describe "is unavailable" do
before :each do
FakeTwitterClient.calling(:update).with(update.body).yields(:unavailable)
end
it "raises a Twitter connection failed error" do
expect{ ProductMaker.create("some_product") }.to raise_exception(Twitter::ConnectionFailed)
end
end
end
end
end
If a component calls a Twitter client library, create a mock of the Twitter client library's API and swap the real implementation for the mock.
If you want to test how the component handles Twitter being unavailable, create a scenario in the mock implementation of the Twitter client library that simulates how the real implementation behaves when Twitter is unavailable.
Prove that your dependencies were called with the input you expect. In a unit test that should be good enough most of the time. If those dependency calls would have produced side-effects and it matters to your code, your unit may be too complex. Consider refactoring. If the side-effects the core intent of the the implementation, simulate the side-effects rather than actually producing the side-effects.
Much of the time arguments to the API you're testing are not
inspected in any meaningful way. If all you need to do is prove the
argument was passed-along correctly, a double
can do the job
rather than the real argument type.
Use Faker. Generate test data in the most flexible format. Generally that's a ruby object with accessors produced by Factory Bot, since it can easily be turned into a hash, JSON, or left as-is.
If a component calls Net:HTTP, don't serve HTTP, create a mock Net:HTTP object and prove it was called with the anticipated I/O.