Introduction

 

Debugging code in Project Reactor can be a challenging task, but with the right approach, you can quickly identify and fix any issues that arise. In this blog post, I’ll walk you through some best practices and techniques for debugging code in Project Reactor using Java, with plenty of code examples to illustrate each point.

Before we dive in, let’s start with a quick overview of Project Reactor. It’s a powerful library for building reactive applications in Java, based on the Reactive Streams specification. It provides a set of powerful abstractions for working with asynchronous and event-driven programming, including Flux and Mono types, which represent streams of data.

Now let’s take a look at some tips for debugging code in Project Reactor:

Use logging

 

One of the most straightforward ways to debug reactive code is to use logging. By logging the different stages of your reactive pipeline, you can easily see what’s happening at each step of the process. For example, you can log when a stream is created, when it emits data, and when it completes or errors out.

Here’s an example of using logging to debug a simple reactive pipeline:

   

Flux.just(1, 2, 3)
    .map(i -> i * 2)
    .log()
    .subscribe();

 

In this example, we create a Flux stream that emits the values 1, 2, and 3. We then map each value to its double and log the results. Finally, we subscribe to the stream, which triggers the execution of the pipeline. The log() method is what enables logging in this example.

 

Use breakpoints

 

Another powerful tool for debugging reactive code is using breakpoints. By setting breakpoints at various points in your code, you can pause the execution of your reactive pipeline and inspect the values at each stage. This can be particularly helpful for debugging complex pipelines that involve multiple operators.

Here’s an example of using breakpoints to debug a reactive pipeline:

 

Flux.just(1, 2, 3)
    .map(i -> i * 2)
    .doOnNext(i -> {
        if (i == 4) {
            System.out.println("Breakpoint here!");
        }
    })
    .subscribe();

 

In this example, we create a Flux stream that emits the values 1, 2, and 3. We then map each value to its double and use the doOnNext operator to log a message when the value 4 is emitted. By setting a breakpoint in the doOnNext operator, we can pause the pipeline execution and inspect the values at this point.

 

Use debugging tools

 

If you’re working with a complex reactive pipeline, you may need more powerful debugging tools to help you identify issues. One such tool is Reactor Debug Agent, which provides detailed information about your pipeline’s execution.

 

Here’s an example of using Reactor Debug Agent to debug a reactive pipeline:

 

Flux.just(1, 2, 3)
    .map(i -> i * 2)
    .doOnNext(i -> {
        if (i == 4) {
            System.out.println("Breakpoint here!");
        }
    })
    .debug()
    .subscribe();

 

In this example, we create a Flux stream that emits the values 1, 2, and 3. We then map each value to its double and use the doOnNext operator to log a message when the value 4 is emitted. We then enable debugging using the debug() method, which activates Reactor Debug Agent. This tool provides detailed information about the execution of the pipeline, including the values at each stage and any errors that occur.

 

Test

 

Unit tests are an essential part of developing reactive applications. By writing tests that cover different scenarios and edge cases, you can catch issues early and ensure that your code behaves as expected. When writing tests for reactive code, you’ll want to use the StepVerifier class, which is a testing utility provided by Project Reactor.

Here’s an example of using StepVerifier to test a reactive pipeline:

 

Flux<Integer> flux = Flux.just(1, 2, 3)
    .map(i -> i * 2);

StepVerifier.create(flux)
    .expectNext(2, 4, 6)
    .expectComplete()
    .verify();

 

In this example, we create a Flux stream that emits the values 1, 2, and 3. We then map each value to its double, creating a new stream. We use StepVerifier to test the new stream, expecting it to emit the values 2, 4, and 6, and complete without errors.

 

Check for errors

 

When debugging reactive code, it’s essential to pay close attention to error handling. Unlike traditional imperative programming, where exceptions can be caught and handled synchronously, errors in reactive pipelines can be harder to detect and debug. To ensure that your code handles errors correctly, you’ll want to use operators like onErrorResume and onErrorReturn, which allow you to gracefully handle errors and continue execution.

Here’s an example of using onErrorResume to handle errors in a reactive pipeline:

 

Flux.just(1, 2, 3)
    .map(i -> {
        if (i == 2) {
            throw new RuntimeException("Oops!");
        }
        return i;
    })
    .onErrorResume(e -> {
        System.out.println("Error occurred: " + e.getMessage());
        return Flux.empty();
    })
    .subscribe();

 

In this example, we create a Flux stream that emits the values 1, 2, and 3. We then map each value to itself, except for the value 2, which we throw a RuntimeException. We then use the onErrorResume operator to handle the error, printing a message and returning an empty stream. This ensures that the pipeline continues to execute without errors.

In conclusion, debugging code in Project Reactor requires a combination of logging, breakpoints, debugging tools, testing, and error handling. By following these best practices and techniques, you can quickly identify and fix any issues that arise in your reactive pipelines. Happy debugging!