Go programs, when properly implemented, are fairly simple to test programatically. Go unit tests offer:

Increased enforcement of behavior expectations beyond the compiler (providing critical assurance around rapidly changing code paths)

Fast execution speed (many popular modules’ tests can execute completely in seconds)

Easy integration into CI pipelines ( go test is built right in)

is built right in) Programmatic race condition detection through the -race flag

Consequently, they are by far one of the best ways to ensure code quality and prevent regressions. Tragically, however, unit testing seems to often be one of the most neglected aspects of any given Go project. It is often slept on until the effort required to implement it properly is Herculean.

This tendency seems at least partly due to a lack of quality resources explaining how to properly structure a Go program to be tested, and examples of doing so. This is a guide attempting to provide both and to increase the general quality of programs available in the Go community.

Don’t let the compiler lull you into a false sense of security: you’ll be glad you began testing sooner rather than later.

Overview

In this article I will walk you through:

Concepts for ensuring testability Four concrete examples to learn how to test effectively in Go

By the end, you should be armed with the knowledge you need in order to go forth and test.

Concepts

If you do not structure and test your program properly from the start, it will be astronomically more difficult to test down the road. This is a fairly universal axiom of programming but seems particularly true of Go testing due to its opinionated nature.

The three most important concepts to be able to use fluidly in order to test Go programs effectively are:

Using interfaces in your Go code Constructing higher-level interfaces through composition (embedding) Becoming familiar with go test and the testing module

Let’s take a look at each one and why it is important.

Using interfaces

You may be familiar with the use of interfaces from working through the Go walkthrough or from the official documentation. What you may not be familiar with is why interfaces are so important and why you should begin using your own interfaces as soon as possible.

For those who are unfamiliar with interfaces, I highly recommend you read the official documentation to understand how they work (I also have an article on interfaces).

Long story short:

Interfaces let you define a set of methods a type (often struct ) must define to be considered an implementation of that interface. When any given type implements all the methods of that interface, the Go compiler automatically knows that it is allowed to be used as that type.

This is used to great effect in the Go standard library so that, for instance, the same interface in database/sql can be used to write functionality that can interact with a variety of different databases using the same code.

Fledgling Go programmers may be familiar with writing unit tests in other languages such as Java, Python, or PHP, and using “stubs” or “mocks” to fake out the results of a method call and explore the various code paths you want to exercise in a fine-grained way. What many don’t seem to realize, however, is that interfaces can and should be used for this same type of operation in Go.

Due to being built into the language and supported in a huge way by the standard library, interfaces offer the test author in Go a vast amount of power and flexibility when used the correct way. One can wrap operations which are outside of the scope of a given test in an interface, and selectively re-implement them for the relevant tests. This allows the author to control every aspect of the program’s behavior within the test suite.

Using composition

Interfaces are great for increased flexibility and control, but they are not enough on their own. Consider, for instance, the case where we have a struct which exposes a large set of methods to external consumers but also relies on these methods internally for some operations. We cannot wrap the whole object in an interface to control the methods it relies on, since this would require implementing the method we are trying to test.

Consequently, it becomes critical to compose larger interfaces from smaller ones through embedding to enable control of the methods which we do want to change while still being able to test the ones we don’t want to change. This is a bit easier to see in an actual example, so I will eschew further abstract discussion until later in the article.

go test and testing

This may seem obvious, but at least skimming the documentation for the go test command and the testing package and familiarizing yourself with how each works will make you much more effective at unit testing. The tools and library can seem a bit quirky if you are not familiar with them or with Go tooling in general (though they are very nice once acclimated).

It might be tempting to reach for a 3rd party package which promises to help with testing, but I highly encourage you to avoid doing so until you have a handle on the basics and are absolutely certain that the dependency will bring you more benefit than headaches.

Please, please, read the docs, but the basic knowledge you need to get started is:

For any given file foo.go , the test is placed in a file in the same directory called foo_test.go .

, the test is placed in a file in the same directory called . go test . runs the unit tests in the current directory. go test ./... will run the tests in the current directory and every directory underneath it. go test foo_test.go not work because the file under test is not included.

runs the unit tests in the current directory. will run the tests in the current directory and every directory underneath it. not work because the file under test is not included. The -v flag for go test is useful because it prints out verbose output (the result of each individual test).

flag for is useful because it prints out verbose output (the result of each individual test). Tests are functions which accept a testing.T struct pointer as an argument and are idiomatically called TestFoo , where Foo is the name of the function being tested.

struct pointer as an argument and are idiomatically called , where is the name of the function being tested. You usually do not assert that conditions you expect are true like you may be accustomed to; rather, you fail the test by calling t.Fatal if you encounter conditions which are different than you expect.

if you encounter conditions which are different than you expect. Displaying output in tests may not work how you expect – use the t.Log and/or t.Logf methods if you need to print information in a test.

Examples

Enough discussion of fundamentals; let’s write some tests.

If you are curious to check out the source code in its final form for the following examples, they are organized in separate directories at https://github.com/nathanleclaire/testing-article.

Example #1: Hello, Testing!

I’m assuming that you have Go installed and configured for these exercises.

Make a new Go package in your GOPATH , e.g. I would execute:

$ mkdir -p ~/go/src/github.com/nathanleclaire/testing-article $ cd ~/go/src/github.com/nathanleclaire/testing-article

Create a file hello.go :

package main import ( "fmt" ) func hello() string { return "Hello, Testing!" } func main() { fmt.Println(hello()) }

Now let’s write a test for hello.go .

Make a file hello_test.go in the same directory:

package main import ( "testing" ) func TestHello(t *testing.T) { expectedStr := "Hello, Testing!" result := hello() if result != expectedStr { t.Fatalf("Expected %s, got %s", expectedStr, result) } }

Hopefully this test should be pretty self-explanatory. We inject an instance of *testing.T to the test, and this is used to control the test flow and output. We set what our expectations for the function call are in one variable, and then check it against what the function actually returns.

To run the test:

$ go test -v === RUN TestHello --- PASS: TestHello (0.00s) PASS ok github.com/nathanleclaire/testing-article 0.006s

Great, now let’s try something more complex.

Example #2: Using an interface to mock results

Let’s say that as part of a program we wanted to get some data from the GitHub API. In this case, let’s say we wanted to query the git tag which the latest release of a given repo corresponds to.

We could write some code like the following to do so:

package main import ( "encoding/json" "fmt" "io/ioutil" "log" "net/http" ) type ReleasesInfo struct { Id uint `json:"id"` TagName string `json:"tag_name"` } // Function to actually query the GitHub API for the release information. func getLatestReleaseTag(repo string) (string, error) { apiUrl := fmt.Sprintf("https://api.github.com/repos/%s/releases", repo) response, err := http.Get(apiUrl) if err != nil { return "", err } defer response.Body.Close() body, err := ioutil.ReadAll(response.Body) if err != nil { return "", err } releases := []ReleasesInfo{} if err := json.Unmarshal(body, &releases); err != nil { return "", err } tag := releases[0].TagName return tag, nil } // Function to get the message to display to the end user. func getReleaseTagMessage(repo string) (string, error) { tag, err := getLatestReleaseTag(repo) if err != nil { return "", fmt.Errorf("Error querying GitHub API: %s", err) } return fmt.Sprintf("The latest release is %s", tag), nil } func main() { msg, err := getReleaseTagMessage("docker/machine") if err != nil { fmt.Fprintln(os.Stderr, msg) } fmt.Println(msg) }

And, in fact, this is commonly how one will see Go programs structured in the wild.

But it is not very testable. If we were to test the getLatestReleaseTag function directly, our test would fail if the GitHub API went down or if GitHub decided to rate limit us (which is likely if running the test frequently such as in CI environments). Additionally, we’d have to update the test every time that the latest release tag changed. Yuck.

What to do? We can re-define the way that this is implemented to be a lot more testable. If we query the GitHub API through an interface instead of directly through a function call, then we can actually control the result of what will be returned through our test.

Let’s redefine the program a bit to have an interface, ReleaseInfoer , of which one implementation can be GithubReleaseInfoer . ReleaseInfoer only has one method, GetLatestReleaseTag , which is similar in nature to our function above (it accepts a repository name as an argument and returns a string and/or error for the result).

The interface definition looks like:

type ReleaseInfoer interface { GetLatestReleaseTag(string) (string, error) }

Then, we can update our above bare function call to be a method on a GithubReleaseInfoer struct instead:

type GithubReleaseInfoer struct {} // Function to actually query the GitHub API for the release information. func (gh GithubReleaseInfoer) GetLatestReleaseTag(repo string) (string, error) { // ... same code as above }

And, consequently, update the getReleaseTagMessage and main functions like so:

// Function to get the message to display to the end user. func getReleaseTagMessage(ri ReleaseInfoer, repo string) (string, error) { tag, err := ri.GetLatestReleaseTag(repo) if err != nil { return "", fmt.Errorf("Error query GitHub API: %s", err) } return fmt.Sprintf("The latest release is %s", tag), nil } func main() { gh := GithubReleaseInfoer{} msg, err := getReleaseTagMessage(gh, "docker/machine") if err != nil { fmt.Fprintln(os.Stderr, err) os.Exit(1) } fmt.Println(msg) }

Why bother? Well, now we can actually test the getReleaseTagMessage function by defining a new struct that fulfills the ReleaseInfoer interface with a method which we control completely. That way, at test time, we can ensure that the behavior of the method which we depend on is exactly as we expect.

We could define a FakeReleaseInfoer struct which behaves however we want. We simply define what to return in the parameters of the struct.

package main import "testing" type FakeReleaseInfoer struct { Tag string Err error } func (f FakeReleaseInfoer) GetLatestReleaseTag(repo string) (string, error) { if f.Err != nil { return "", f.Err } return f.Tag, nil } func TestGetReleaseTagMessage(t *testing.T) { f := FakeReleaseInfoer{ Tag: "v0.1.0", Err: nil, } expectedMsg := "The latest release is v0.1.0" msg, err := getReleaseTagMessage(f, "dev/null") if err != nil { t.Fatalf("Expected err to be nil but it was %s", err) } if expectedMsg != msg { t.Fatalf("Expected %s but got %s", expectedMsg, msg) } }

You can see above that the FakeReleaseInfoer struct was set to return "v0.1.0" and the returned error was set to nil.

That’s great for this case, but notice we’re not testing our error return. It would be preferable to cover this case as well.

Is there any way to express the various paths and return possibilities for this function concisely in our unit tests? Certainly. We can test a wide variety of cases in one function with an anonymous struct slice (thanks to Andrew Gerrand’s talk and David Cheney’s article on test tables for this idea).

func TestGetReleaseTagMessage(t *testing.T) { cases := []struct { f FakeReleaseInfoer repo string expectedMsg string expectedErr error }{ { f: FakeReleaseInfoer{ Tag: "v0.1.0", Err: nil, }, repo: "doesnt/matter", expectedMsg: "The latest release is v0.1.0", expectedErr: nil, }, { f: FakeReleaseInfoer{ Tag: "v0.1.0", Err: errors.New("TCP timeout"), }, repo: "doesnt/foo", expectedMsg: "", expectedErr: errors.New("Error querying GitHub API: TCP timeout"), }, } for _, c := range cases { msg, err := getReleaseTagMessage(c.f, c.repo) if !reflect.DeepEqual(err, c.expectedErr) { t.Errorf("Expected err to be %q but it was %q", c.expectedErr, err) } if c.expectedMsg != msg { t.Errorf("Expected %q but got %q", c.expectedMsg, msg) } } }

Note the use of reflect.DeepEqual there. It’s a useful method from the standard library which will check if two structs are equal by value. It’s used to check error equality here, but it also could be used to compare the contents of two struct s. Just == alone won’t work for equality for this due to the use of errors.New (I tried using the Error method but that doesn’t work with nil value errors, so if anyone has better ideas please mention it in the comments).

Something to take note of is that this technique can be used to gain more control over 3rd party libraries in tests. For instance, Sam Alba’s Golang Docker client will give you a type DockerClient struct to interact with, which is not easily mock-able for tests. But you could create a type DockerClient interface in your own module which specifies the methods you are using on dockerclient.DockerClient as the things to implement, use that in your code instead, and then create your own version of that interface for testing.

Aside from the benefits to testability which I’m focusing on here, using interfaces can potentially be a huge boon for future extensibility of your program. If you have structured every component which interacts with the GitHub API as working through an interface, for instance, you won’t need to change your program’s architecture at all to add support for another source code hosting platform. You could simply implement a BitbucketReleaseInfoer and use that wherever you want to wrap the Bitbucket API instead of GitHub. Granted, this type of wrapper abstraction won’t work for every use case, but it can be used powerfully to mock out external and internal dependencies.

Example #3: Using composition to test a large struct

The above example illustrates an introductory concept which can be very useful, but sometimes we might want to mock out parts of one struct which depend on each other and test each piece separately.

If you find yourself with an interface or struct which is starting to get larger in terms of the number of methods exposed, it might be a good candidate for breaking into several smaller interfaces and embedding them. For instance, let’s suppose that we have a Job interface which exposes a Log method both internally and externally to the structure. Any interface can be passed to this method with a variable number of arguments. It also provides supported for Run ing, Suspend ing, and Resume ing jobs.

type Job interface { Log(...interface{}) Suspend() error Resume() error Run() error }

If we are working on developing a struct which implements this interface , we may want to use the Log method inside of the Suspend and Resume methods to keep track of what has happened. Therefore, faking out the whole interface like in the previous example won’t work. How do we test the whole structure while mocking out only part of the interface?

We can do so by defining several smaller interfaces and using composition. Consider an implementation of a Job , PollerJob , which can be used for questionable homebrew system monitoring software. My first crack at coding it was this:

package main import ( "log" "net/http" "time" ) type Job interface { Log(...interface{}) Suspend() error Resume() error Run() error } type PollerJob struct { suspend chan bool resume chan bool resourceUrl string inMemLog string } func NewPollerJob(resourceUrl string) PollerJob { return PollerJob{ resourceUrl: resourceUrl, suspend: make(chan bool), resume: make(chan bool), } } func (p PollerJob) Log(args ...interface{}) { log.Println(args...) } func (p PollerJob) Suspend() error { p.suspend <- true return nil } func (p PollerJob) PollServer() error { resp, err := http.Get(p.resourceUrl) if err != nil { return err } p.Log(p.resourceUrl, "--", resp.Status) return nil } func (p PollerJob) Run() error { for { select { case <-p.suspend: <-p.resume default: if err := p.PollServer(); err != nil { p.Log("Error trying to get resource: ", err) } time.Sleep(1 * time.Second) } } } func (p PollerJob) Resume() error { p.resume <- true return nil } func main() { p := NewPollerJob("https://nathanleclaire.com") go p.Run() time.Sleep(5 * time.Second) p.Log("Suspending monitoring of server for 5 seconds...") p.Suspend() time.Sleep(5 * time.Second) p.Log("Resuming job...") p.Resume() // Wait for a bit before exiting time.Sleep(5 * time.Second) }

The output of the above program, when run, looks like:

$ go run -race job.go 2015/10/11 20:37:59 https://nathanleclaire.com -- 200 OK 2015/10/11 20:38:01 https://nathanleclaire.com -- 200 OK 2015/10/11 20:38:02 https://nathanleclaire.com -- 200 OK 2015/10/11 20:38:03 https://nathanleclaire.com -- 200 OK 2015/10/11 20:38:04 https://nathanleclaire.com -- 200 OK 2015/10/11 20:38:04 Suspending monitoring of server for 5 seconds... 2015/10/11 20:38:10 Resuming job... 2015/10/11 20:38:10 https://nathanleclaire.com -- 200 OK 2015/10/11 20:38:11 https://nathanleclaire.com -- 200 OK 2015/10/11 20:38:12 https://nathanleclaire.com -- 200 OK 2015/10/11 20:38:14 https://nathanleclaire.com -- 200 OK 2015/10/11 20:38:15 https://nathanleclaire.com -- 200 OK 2015/10/11 20:38:16 https://nathanleclaire.com -- 200 OK

If we want to test the various complex interactions at play here, how do we do so? With everything in one structure, it seems to be daunting to test each component of the program in isolation and without using external resources.

The solution is to break the higher-level Job interface into several other interfaces and embed them all into the PollerJob struct, allowing us to mock out each piece in isolation when we do testing.

We can break the Job interface into a few different interfaces like so:

type Logger interface { Log(...interface{}) } type SuspendResumer interface { Suspend() error Resume() error } type Job interface { Logger SuspendResumer Run() error }

You can see that there is an interface SuspendResumer for handling suspend/resume functionality, and an interface Log whose only purpose is to manage the Log method. Additionally, we will create a PollServer interface for controlling the status calls to the server we are polling:

type ServerPoller interface { PollServer() (string, error) }

With all of these component interfaces in place, we can begin re-constructing our PollerJob implementation of the Job interface. By embedding Logger and ServerPoller (both interfaces) and a pointer to a PollSuspendResumer struct, we ensure that the compiler is satisfied for the definition of PollerJob as a Job . We provide a NewPollerJob function which will provide an instance of the struct with all of the components set up and initialized properly. Notice that we use our own implementation of the components such as Logger in the struct literal that this function returns.

type PollerLogger struct{} type URLServerPoller struct { resourceUrl string } type PollSuspendResumer struct { SuspendCh chan bool ResumeCh chan bool } type PollerJob struct { WaitDuration time.Duration ServerPoller Logger *PollSuspendResumer } func NewPollerJob(resourceUrl string, waitDuration time.Duration) PollerJob { return PollerJob{ WaitDuration: waitDuration, Logger: &PollerLogger{}, ServerPoller: &URLServerPoller{ resourceUrl: resourceUrl, }, PollSuspendResumer: &PollSuspendResumer{ SuspendCh: make(chan bool), ResumeCh: make(chan bool), }, } }

The rest of the code defines the methods on the relevant structs, and is available in full on GitHub here.

This provides us with the flexibility that we need to actually fake out each component of the PollerJob struct in isolation when we do testing. Each “mock” component can be re-used and/or re-worked to be more flexible where needed, allowing us to cover a wide range of possible outcomes from the components which we depend on.

We can now test Run in isolation, and without talking to any actual servers. We simply control what the ServerPoller returns and verify that what was written to the Logger was as we expect by re-implementing those interfaces. Consequently the test file for PollerJob looks similar to this.

package main import ( "errors" "fmt" "testing" "time" ) type ReadableLogger interface { Logger Read() string } type MessageReader struct { Msg string } func (mr *MessageReader) Read() string { return mr.Msg } type LastEntryLogger struct { *MessageReader } func (lel *LastEntryLogger) Log(args ...interface{}) { lel.Msg = fmt.Sprint(args...) } type DiscardFirstWriteLogger struct { *MessageReader writtenBefore bool } func (dfwl *DiscardFirstWriteLogger) Log(args ...interface{}) { if dfwl.writtenBefore { dfwl.Msg = fmt.Sprint(args...) } dfwl.writtenBefore = true } type FakeServerPoller struct { result string err error } func (fsp FakeServerPoller) PollServer() (string, error) { return fsp.result, fsp.err } func TestPollerJobRunLog(t *testing.T) { waitBeforeReading := 100 * time.Millisecond shortInterval := 20 * time.Millisecond longInterval := 200 * time.Millisecond testCases := []struct { p PollerJob logger ReadableLogger sp ServerPoller expectedMsg string }{ { p: NewPollerJob("madeup.website", shortInterval), logger: &LastEntryLogger{&MessageReader{}}, sp: FakeServerPoller{"200 OK", nil}, expectedMsg: "200 OK", }, { p: NewPollerJob("down.website", shortInterval), logger: &LastEntryLogger{&MessageReader{}}, sp: FakeServerPoller{"500 SERVER ERROR", nil}, expectedMsg: "500 SERVER ERROR", }, { p: NewPollerJob("error.website", shortInterval), logger: &LastEntryLogger{&MessageReader{}}, sp: FakeServerPoller{"", errors.New("DNS probe failed")}, expectedMsg: "Error trying to get state: DNS probe failed", }, { p: NewPollerJob("some.website", longInterval), // Discard first write since we want to verify that no // additional logs get made after the first one (time // out) logger: &DiscardFirstWriteLogger{MessageReader: &MessageReader{}}, sp: FakeServerPoller{"200 OK", nil}, expectedMsg: "", }, } for _, c := range testCases { c.p.Logger = c.logger c.p.ServerPoller = c.sp go c.p.Run() time.Sleep(waitBeforeReading) if c.logger.Read() != c.expectedMsg { t.Errorf("Expected message did not align with what was written:

\texpected: %q

\tactual: %q", c.expectedMsg, c.logger.Read()) } } }

Note the creative flexibility that making our own ReadableLogger interface for testing, and being able to implement Logger in a variety of ways, provides us. Suspend and Resume functionality can likewise be tested meticulously by controlling the ServerPoller interface component of JobPoller .

func TestPollerJobSuspendResume(t *testing.T) { p := NewPollerJob("foobar.com", 20*time.Millisecond) waitBeforeReading := 100 * time.Millisecond expectedLogLine := "200 OK" normalServerPoller := &FakeServerPoller{expectedLogLine, nil} logger := &LastEntryLogger{&MessageReader{}} p.Logger = logger p.ServerPoller = normalServerPoller // First start the job / polling go p.Run() time.Sleep(waitBeforeReading) if logger.Read() != expectedLogLine { t.Errorf("Line read from logger does not match what was expected:

\texpected: %q

\tactual: %q", expectedLogLine, logger.Read()) } // Then suspend the job if err := p.Suspend(); err != nil { t.Errorf("Expected suspend error to be nil but got %q", err) } // Fake the log line to detect if poller is still running newExpectedLogLine := "500 Internal Server Error" logger.MessageReader.Msg = newExpectedLogLine // Give it a second to poll if it's going to poll time.Sleep(waitBeforeReading) // If this log writes, we know we are polling the server when we're not // supposed to (job should be suspended). if logger.Read() != newExpectedLogLine { t.Errorf("Line read from logger does not match what was expected:

\texpected: %q

\tactual: %q", newExpectedLogLine, logger.Read()) } if err := p.Resume(); err != nil { t.Errorf("Expected resume error to be nil but got %q", err) } // Give it a second to poll if it's going to poll time.Sleep(waitBeforeReading) if logger.Read() != expectedLogLine { t.Errorf("Line read from logger does not match what was expected:

\texpected: %q

\tactual: %q", expectedLogLine, logger.Read()) } }

It certainly might seem like a lot of boilerplate to test a small file, but it will scale well as the size of the code base grows. Mocking out dependent bits in this fashion makes it easier to specify what behavior should be like in error cases or to control flow in the case of tricky concurrency issues.

Due to the practical and creative enhancements that interfaces offer to testability, it is preferred to wrap external dependencies in one and then combine them to create higher-order interfaces wherever possible. As you can hopefully see, even small one-method interfaces are useful to combine into bigger pieces of functionality.

Example #4: Using and faking standard library functionality

The concepts illustrated above are useful for your own programs, but you will also notice that many of the constructs in the Go standard library can be managed in your unit tests in a similar fashion (and indeed they are frequently used in such a manner in the tests for the standard library itself).

Let’s take a look at testing an example HTTP server. It might be tempting to actually start up the HTTP server in a goroutine and send it the requests that you expect it to be able to handle directly (e.g. with http.Get ). But that is far more like an integration test than a proper unit test. Let’s take a look at a little HTTP server and discuss how to approach testing it.

package main import ( "fmt" "log" "net/http" ) func mainHandler(w http.ResponseWriter, r *http.Request) { token := r.Header.Get("X-Access-Token") if token == "magic" { fmt.Fprintf(w, "You have some magic in you

") log.Println("Allowed an access attempt") } else { http.Error(w, "You don't have enough magic in you", http.StatusForbidden) log.Println("Denied an access attempt") } } func main() { http.HandleFunc("/", mainHandler) log.Fatal(http.ListenAndServe(":8080", nil)) }

The above HTTP server listens on :8080/ for requests, and checks if they have a X-Access-Token header set. If the token matches our "magic" value, we allow the users access and return a HTTP 200 OK status code. Otherwise, we reject the request with a HTTP 403 Access Forbidden status code. This is a crude imitation of how some API servers handle authorization. How can we test it?

As you can see, the mainHandler function accepts two arguments: a http.ResponseWriter (note that it is an interface , which you can verify by reading the source of http or the documentation) and a http.Request struct pointer. To test the handler, we could make our own implementation of the http.ResponseWriter interface which we could also read from later, but fortunately the Go authors have already provided a httptest package with a ResponseRecorder struct which is meant to help with exactly this issue. Having such a module to provide common testing functionality where needed is a useful and not uncommon pattern.

Given that, we can also create a hand-crafted http.Request struct by calling NewRequest with the expected parameters. We simply have to call Header.Set on the Request to set the desired header. We specify in the NewRequest method that it should be GET method and not contain any information in the request body, though we could also test POST requests and so on if we wanted to by creating structures for those instead.

The initial test looks like this:

package main import ( "bytes" "net/http" "net/http/httptest" "testing" ) func TestMainHandler(t *testing.T) { rootRequest, err := http.NewRequest("GET", "/", nil) if err != nil { t.Fatal("Root request error: %s", err) } cases := []struct { w *httptest.ResponseRecorder r *http.Request accessTokenHeader string expectedResponseCode int expectedResponseBody []byte }{ { w: httptest.NewRecorder(), r: rootRequest, accessTokenHeader: "magic", expectedResponseCode: http.StatusOK, expectedResponseBody: []byte("You have some magic in you

"), }, { w: httptest.NewRecorder(), r: rootRequest, accessTokenHeader: "", expectedResponseCode: http.StatusForbidden, expectedResponseBody: []byte("You don't have enough magic in you

"), }, } for _, c := range cases { c.r.Header.Set("X-Access-Token", c.accessTokenHeader) mainHandler(c.w, c.r) if c.expectedResponseCode != c.w.Code { t.Errorf("Status Code didn't match:

\t%q

\t%q", c.expectedResponseCode, c.w.Code) } if !bytes.Equal(c.expectedResponseBody, c.w.Body.Bytes()) { t.Errorf("Body didn't match:

\t%q

\t%q", string(c.expectedResponseBody), c.w.Body.String()) } } }

However, there is one glaring omission of testing functionality we can account for. We do not check that what was written to the log is what we expected at all. How can we do so?

Well, if we examine the source for the standard library’s log package, we can see that the log.Println method directly wraps an instance of the Logger struct which internally calls the Write method on a Writer interface (in the case of the std struct which is written to if you invoke log.* directly, that Writer is os.Stdout ). Hm, I wonder if there’s any way we could set that interface to whatever we want so we can verify that what was written is what we expected?

Naturally, there is a way to do so. We can invoke the log.SetOutput method to specify our own custom writer for logging to. In order to pass something in which we can read from later, we create the Writer to pass in using io.Pipe . This will provide us with a Reader that we can use to Read the subsequent Write calls made in the Logger . We wrap the given PipeReader in a bufio.Reader so that we can easily read line-by-line using a call to bufio.Reader ’s ReadString method.

Note that in PipeWriter ’s documentation it says:

Write implements the standard Write interface: it writes data to the pipe, blocking until readers have consumed all the data or the read end is closed.

Therefore, we have to concurrently read from the PipeReader as the mainHandler function is writing to it, so we run that bit of the test in its own goroutine. In my original version I got this wrong and discovered my error by using go test ’s -timeout flag, which will panic any given test if it stalls for longer than the specified interval.

Put together, it all looks like this:

func TestMainHandler(t *testing.T) { rootRequest, err := http.NewRequest("GET", "/", nil) if err != nil { t.Fatal("Root request error: %s", err) } cases := []struct { w *httptest.ResponseRecorder r *http.Request accessTokenHeader string expectedResponseCode int expectedResponseBody []byte expectedLogs []string }{ { w: httptest.NewRecorder(), r: rootRequest, accessTokenHeader: "magic", expectedResponseCode: http.StatusOK, expectedResponseBody: []byte("You have some magic in you

"), expectedLogs: []string{ "Allowed an access attempt

", }, }, { w: httptest.NewRecorder(), r: rootRequest, accessTokenHeader: "", expectedResponseCode: http.StatusForbidden, expectedResponseBody: []byte("You don't have enough magic in you

"), expectedLogs: []string{ "Denied an access attempt

", }, }, } for _, c := range cases { logReader, logWriter := io.Pipe() bufLogReader := bufio.NewReader(logReader) log.SetOutput(logWriter) c.r.Header.Set("X-Access-Token", c.accessTokenHeader) go func() { for _, expectedLine := range c.expectedLogs { msg, err := bufLogReader.ReadString('

') if err != nil { t.Errorf("Expected to be able to read from log but got error: %s", err) } if !strings.HasSuffix(msg, expectedLine) { t.Errorf("Log line didn't match suffix:

\t%q

\t%q", expectedLine, msg) } } }() mainHandler(c.w, c.r) if c.expectedResponseCode != c.w.Code { t.Errorf("Status Code didn't match:

\t%q

\t%q", c.expectedResponseCode, c.w.Code) } if !bytes.Equal(c.expectedResponseBody, c.w.Body.Bytes()) { t.Errorf("Body didn't match:

\t%q

\t%q", string(c.expectedResponseBody), c.w.Body.String()) } } }

I hope that this example illustrates clearly the value of having well-architected interfaces in the Go standard library as well as in your own code, and how reading the source code of modules upon which you are relying (including the Go standard library, which is meticulously documented) can make your understanding of the code you are working with better as well as ease testing.