Skip to main content

Testing Asynchronous APIs: Awaitility tutorial

Despite the growing popularity of test automation, most of it is still likely to be done on the frontend side of application. While GUI is a single layer that puts all the pieces together, focusing your automation efforts on the backend side requires dealing with distributed calls, concurrency, handling their diversity and integration.

Backend test automation is especially popular in the microservices architecture, with testing REST API’s. I’ve noticed that dealing with asynchronous events is particularly considered as challenging. In this article I want to cover basic usage of Awaitility – simple java library for testing asynchronous events. All the code examples are written in groovy and our REST client is Rest-Assured.

Synchronous vs Asynchronous 

In simple words, synchronous communication is when the API calls are dependent and their order matters, while asynchronous communication is when the API calls are independent. Quoting Apigee definition:

Synchronous 
If an API call is synchronous, it means that code execution will block (or wait) for the API call to return before continuing. This means that until a response is returned by the API, your application will not execute any further, which could be perceived by the user as latency or performance lag in your app. Making an API call synchronously can be beneficial, however, if there is code in your app that will only execute properly once the API response is received.

Asynchronous 
Asynchronous calls do not block (or wait) for the API call to return from the server. Execution continues on in your program, and when the call returns from the server, a “callback” function is executed.

Awaitility 

Awaitility is the JVM-based open-source library for verifying asynchronous calls. Let’s assume you’re publishing an event to the system:

publish(new event("Hello World"))

Since our event is asynchronous, we can’t synchronously block our test execution and wait for the event’s response. This’ll likely fail:

publish(new Event("Hello World"))
assert eventIsPublished() //likely to fail here

To handle this asynchronous check, we can wrap our assertion in the awaitility’s block and poll the resource for the event’s presence:

publish(new Event("Hello World"))
await().until(eventIsPublished())

By default, awaitility will wait for 10 seconds until eventIsPublished() is true. If not it’ll throw ConditionTimeoutException.

Installation 
In order to add awaitility to your classpath, you need to include its dependency. Since we want to implement our examples in Groovy, the library we’re looking for is: org.awaitility.awaitility-groovy. For maven users:

<dependency>
    <groupId>org.awaitility</groupId>
    <artifactId>awaitility-groovy</artifactId>
    <version>3.0.0</version>
</dependency>

For Gradle users:

compile group: 'org.awaitility', name: 'awaitility-groovy', version: '3.0.0'

To use Awaitility effectively it’s recommended to use static imports:

import static org.awaitility.Awaitility.*

Basic usage example 

Main goal of this article is to show how you can perform calls to asynchronous REST APIs in your tests. Imagine we have an RESTful resource: /deal, which is consuming asynchronous events. Subsequently, events are given unique dealId and you can request particular deal details with GET request on /deal/{dealId}. If there’s no (or not yet) deal with requested dealId, the response is HTTP code 404.

First thing we want to do is implement the REST client to /deal resource. Here’s the simple implementation with use of the REST-Assured library:


In the above implementation, we’re accessing deal/$dealId resource with GET method and returning extracted response object. The problem is the async nature of our service. We don’t know the exact time when the single deal is accessible – when there’s no deal our API is responding with 404, so the test like the one below would be highly non-deterministic.


How to handle this asynchronous events in our test? The solution comes with Awaitility’s library. In the second approach, we’re wrapping /deal request in await() method:


The method we will call in the test assertion is isPricePositive(). We’re using await() method there to poll for our asynchronous event. For this we’re using another helper method: is200(). This method calls our /deal client and if the response is 404 it returns false, if it’s not – it returns the response body. The third method is of course our REST client which stays exactly like the one implemented previously. The only change in our test is the then block, where we’re calling isPricePositive() assertion:


With this approach we’re handling all the issues with asynchronous calls to /deal resource, leaving test method clean, readable and – what’s the most important – deterministic.

Polling

There’s a list of settings which we can use to customise the await() calls. One of the most important are polling options, where we define the initial delay before polling begins and the interval between polls (poll interval). In the example below poll delay is 100ms and the poll interval is 200ms:


Awaitility has to offer much more in terms of polling options, check the documentation for more.

Defaults 

Having this variety of options, you can also define default values for polling, timeouts, etc. The snippet below shows an example implementation of defining default values in spock’s setupSpec block:


Better reuse 

In our example test, we used single-method condition in await() method. Awaitility also supports two parts conditions – supplying and matching:


Summary 

Test automation of the asynchronous systems and APIs can be challenging task, but with use of proper tools it can be also very rewarding. Above examples are just few use cases of implementing tests in groovy with Awaitility and Rest-Assured. I recommend you to use those frameworks for yourself and explore their possibilities. If you have any questions, feel free to leave a comment.

Popular posts from this blog

Rerun Flaky Tests – Spock Retry

One question I get asked a lot is how you can automatically rerun your test on failure. This is a typical case for heavy, functional test scenarios, which are often flaky. While test flakiness and its management is crucial and extensive matter itself, in this post I want to give a shout to the extremely simple yet useful library: Spock-Retry. It introduce possibility to create retry policies for Spock tests, without any additional custom-rules implementation – just one annotation. If you are not a fan of Spock testing framework and you prefer JUnit – stay tuned! I will post analogous bit about rerunning JUnit tests soon. Instalation  If you are an maven user, add following dependency: <dependency>       < groupId > com.anotherchrisberry < /groupId >       < artifactId > spock-retry < /artifactId >       < version > 0.6.2 < /version >       < type > pom < /type >   </dependency> For gradle users:

Performance Testing – Vegeta Attack!

Performance testing is crucial field of modern software development. Taking into account that in today’s world majority of app’s communication is web-based, it turns out to be even more important. However, it still enjoys less interest than automated functional testing, and publications on load testing subject usually focus on mature and complex tools like JMeter or Gatling. In this post I’d like to introduce command line usage of a super simple and lightweight tool for performance testing of HTTP services, which is Vegeta. Who is Vegeta  Besides Dragon Ball’s character, Vegeta is a simple load testing tool written in GO, that can be used both from command line and as an external library in your project. In order to use Vegeta, download executables from here . It is recommended to set environment variable for ease of use.  For Mac users, you can download vegeta directly from Homebrew repositories: $ brew update && brew install vegeta Vegeta’s Arsenal  Usage