This is the 7th post taken from a WIP project called Learn Go by writing Tests the aim of which is to get a familiarity with Go and learn techniques around TDD
- The first post got you up to speed with TDD
- The second post discusses arrays and slices
- The third post teaches structs, methods, interfaces & table driven tests
- The fourth post shows how to do errors and why pointers are useful
- The fifth post showed you how and why to do dependency injection
- The 6th post introduced concurrency
This chapter is about mocking. Even if you don't have a great familiarity with Go, if you want to learn about mocking this post should be helpful.
Mocking
You have been asked to write a program which counts from 3, printing each number on a new line (with a 1 second pause) and when it reaches zero it will print "Go!" and exit.
3
2
1
Go!
We'll tackle this by writing a function called Countdown
which we will then put inside a main
program so it looks something like this:
package main
func main() {
Countdown()
}
While this is a pretty trivial program, to test it fully we will need as always to take an iterative, test-driven approach.
What do I mean by iterative? We make sure we take the smallest steps we can to have useful software.
We dont want to spend a long time with code that will theoretically work after some hacking because that's often how developers fall down rabit holes. It's an important skill to be able to slice up requirements as small as you can so you can have working software.
Here's how we can divide our work up and iterate on it
- Print 3
- Print 3 to Go!
- Wait a second between each line
Write the test first
Our software needs to print to stdout and we saw how we could use DI to facilitate testing this in the DI section.
func TestCountdown(t *testing.T) {
buffer := &bytes.Buffer{}
Countdown(buffer)
got := buffer.String()
want := "3"
if got != want {
t.Errorf("got '%s' want '%s'", got, want)
}
}
If anything like buffer
is unfamiliar to you, re-read the previous section.
We know we want our Countdown
function to write data somewhere and io.Writer
is the de-facto way of capturing that as an interface in Go.
- In
main
we will send toos.Stdout
so our users see the countdown printed to the terminal - In test we will send to
bytes.Buffer
so our tests can capture what data is being generated
Try and run the test
./countdown_test.go:11:2: undefined: Countdown
Write the minimal amount of code for the test to run and check the failing test output
Define Countdown
func Countdown() {}
Try again
./countdown_test.go:11:11: too many arguments in call to Countdown
have (*bytes.Buffer)
want ()
The compiler is telling you what your function signature could be, so update it.
func Countdown(out *bytes.Buffer) {}
countdown_test.go:17: got '' want '3'
Perfect!
Write enough code to make it pass
func Countdown(out *bytes.Buffer) {
fmt.Fprint(out, "3")
}
We're using fmt.Fprint
which takes an io.Writer
(like *bytes.Buffer
) and sends a string
to it. The test should pass.
Refactor
We know that while *bytes.Buffer
works, it would be better to use a general purpose interface instead.
func Countdown(out io.Writer) {
fmt.Fprint(out, "3")
}
Re-run the tests and they should be passing.
To complete matters, let's now wire up our function into a main
so we have some working software to reassure ourselves we're making progress.
package main
import (
"fmt"
"io"
"os"
)
func Countdown(out io.Writer) {
fmt.Fprint(out, "3")
}
func main() {
Countdown(os.Stdout)
}
Try and run the program and be amazed at your handywork.
Yes this seems trivial but this approach is what I would recommend for any project. Take a thin slice of functionality and make it work end-to-end, backed by tests.
Next we can make it print 2,1 and then "Go!".
Write the test first
By investing in getting the overall plumbing working right, we can iterate on our solution safely and easily. We will no longer need to stop and re-run the program to be confident of it working as all the logic is tested.
func TestCountdown(t *testing.T) {
buffer := &bytes.Buffer{}
Countdown(buffer)
got := buffer.String()
want := `3
2
1
Go!`
if got != want {
t.Errorf("got '%s' want '%s'", got, want)
}
}
The backtick syntax is another way of creating a string
but lets you put things like newlines which is perfect for our test.
Try and run the test
countdown_test.go:21: got '3' want '3
2
1
Go!'
Write enough code to make it pass
func Countdown(out io.Writer) {
for i := 3; i > 0; i-- {
fmt.Fprintln(out, i)
}
fmt.Fprint(out, "Go!")
}
Use a for
loop counting backwards with i--
and use fmt.Fprintln
to print to out
with our number followed by a newline character. Finally use fmt.Fprint
to send "Go!" aftward
Refactor
There's not much to refactor other than refactoring some magic values into named constants.
const finalWord = "Go!"
const countdownStart = 3
func Countdown(out io.Writer) {
for i := countdownStart; i > 0; i-- {
fmt.Fprintln(out, i)
}
fmt.Fprint(out, finalWord)
}
If you run the program now, you should get the desired output but we dont have it as a dramatic countdown with the 1 second pauses.
Go let's you achieve this with time.Sleep
. Try adding it in to our code.
func Countdown(out io.Writer) {
for i := countdownStart; i > 0; i-- {
time.Sleep(1 * time.Second)
fmt.Fprintln(out, i)
}
time.Sleep(1 * time.Second)
fmt.Fprint(out, finalWord)
}
If you run the program it works as we want it to.
Mocking
The tests still pass and the software works as intended but we have some problems:
- Our tests take 4 seconds to run.
- Every forward thinking post about software development emphasises the importance of quick feedback loops.
- Slow tests ruin developer productivity.
- Imagine if the requirements get more sophisticated warranting more tests. Are we happy with 4s added to the test run for every new test of
Countdown
?
- We have not tested an important property of our function.
We have a dependency on Sleep
ing which we need to extract so we can then control it in our tests.
If we can mock time.Sleep
we can use dependency injection to use it instead of a "real" time.Sleep
and then we can spy on the calls to make assertions on them.
Write the test first
Let's define our dependency as an interface. This lets us then use a real Sleeper in main
and a spy sleeper in our tests. By using an interface our Countdown
function is obvlivious to this and adds some flexibility for the caller.
type Sleeper interface {
Sleep()
}
I made a design decision that our Countdown
function would not be responsible
for how long the sleep is. This simplifies our code a little for now at least
and means a user of our function can configure that sleepiness however they
like.
Now we need to make a mock of it for our tests to use.
type SpySleeper struct {
Calls int
}
func (s *SpySleeper) Sleep() {
s.Calls++
}
Spies are a kind of mock which can record how a dependency is used. They can record the arguments sent in, how many times, etc. In our case, we're keeping track of how many times Sleep()
is called so we can check it in our test.
Update the tests to inject a dependency on our Spy and assert that the sleep has been called 4 times.
func TestCountdown(t *testing.T) {
buffer := &bytes.Buffer{}
spySleeper := &SpySleeper{}
Countdown(buffer, spySleeper)
got := buffer.String()
want := `3
2
1
Go!`
if got != want {
t.Errorf("got '%s' want '%s'", got, want)
}
if spySleeper.Calls != 4 {
t.Errorf("not enough calls to sleeper, want 4 got %d", spySleeper.Calls)
}
}
Try and run the test
too many arguments in call to Countdown
have (*bytes.Buffer, Sleeper)
want (io.Writer)
Write the minimal amount of code for the test to run and check the failing test output
We need to update Countdown
to accept our Sleeper
func Countdown(out io.Writer, sleeper Sleeper) {
for i := countdownStart; i > 0; i-- {
time.Sleep(1 * time.Second)
fmt.Fprintln(out, i)
}
time.Sleep(1 * time.Second)
fmt.Fprint(out, finalWord)
}
If you try again, your main
will no longer compile for the same reason
./main.go:26:11: not enough arguments in call to Countdown
have (*os.File)
want (io.Writer, Sleeper)
Let's create a real sleeper which implements the interface we need
type ConfigurableSleeper struct {
duration time.Duration
}
func (o *ConfigurableSleeper) Sleep() {
time.Sleep(o.duration)
}
I decided to make a little extra effort and make it so our real sleeper is
configurable but you could just as easily not bother and hard-code it for
1 second.
We can then use it in our real application like so
func main() {
sleeper := &ConfigurableSleeper{1 * time.Second}
Countdown(os.Stdout, sleeper)
}
Write enough code to make it pass
The test is now compiling but not passing because we're still calling the time.Sleep
rather than the injected in dependency. Let's fix that.
func Countdown(out io.Writer, sleeper Sleeper) {
for i := countdownStart; i > 0; i-- {
sleeper.sleep()
fmt.Fprintln(out, i)
}
sleeper.sleep()
fmt.Fprint(out, finalWord)
}
The test should pass and no longer taking 4 seconds.
Still some problems
There's still another important property we haven't tested.
Countdown
should sleep before the first print and then after each one until the last, e.g:
Sleep
Print N
Sleep
Print N-1
Sleep
- etc
Our latest change only asserts that it has slept 4 times, but those sleeps could occur out of sequence
When writing tests if you're not confident that your tests are giving you sufficient confidence, just break it! (make sure you have commited your changes to source control first though). Change the code to the following
func Countdown(out io.Writer, sleeper Sleeper) {
for i := countdownStart; i > 0; i-- {
sleeper.Sleep()
}
for i := countdownStart; i > 0; i-- {
fmt.Fprintln(out, i)
}
sleeper.Sleep()
fmt.Fprint(out, finalWord)
}
If you run your tests they should still be passing even though the implementation is wrong.
Let's use spying again with a new test to check the order of operations is correct.
We have two different dependencies and we want to record all of their operations into one list. So we'll create one spy for them both.
type CountdownOperationsSpy struct {
Calls []string
}
func (s *CountdownOperationsSpy) Sleep() {
s.Calls = append(s.Calls, sleep)
}
func (s *CountdownOperationsSpy) Write(p []byte) (n int, err error) {
s.Calls = append(s.Calls, write)
return
}
const write = "write"
const sleep = "sleep"
Our CountdownOperationsSpy
implements both io.Writer
and Sleeper
, recording every call into one slice. In this test we're only concerned about the order of operations, so just recording them as list of named operations is sufficient.
We can now add a sub-test into our test suite.
t.Run("sleep after every print", func(t *testing.T) {
spySleepPrinter := &CountdownOperationsSpy{}
Countdown(spySleepPrinter, spySleepPrinter)
want := []string{
sleep,
write,
sleep,
write,
sleep,
write,
sleep,
write,
}
if !reflect.DeepEqual(want, spySleepPrinter.Calls) {
t.Errorf("wanted calls %v got %v", want, spySleepPrinter.Calls)
}
})
This test should now fail. Revert it back and the new test should pass.
We now have two tests spying on the Sleeper
so we can now refactor our test so one is testing what is being printed and the other one is ensuring we're sleeping in between the prints. Finally we can delete our first spy as it's not used anymore.
func TestCountdown(t *testing.T) {
t.Run("prints 3 to Go!", func(t *testing.T) {
buffer := &bytes.Buffer{}
Countdown(buffer, &CountdownOperationsSpy{})
got := buffer.String()
want := `3
2
1
Go!`
if got != want {
t.Errorf("got '%s' want '%s'", got, want)
}
})
t.Run("sleep after every print", func(t *testing.T) {
spySleepPrinter := &CountdownOperationsSpy{}
Countdown(spySleepPrinter, spySleepPrinter)
want := []string{
sleep,
write,
sleep,
write,
sleep,
write,
sleep,
write,
}
if !reflect.DeepEqual(want, spySleepPrinter.Calls) {
t.Errorf("wanted calls %v got %v", want, spySleepPrinter.Calls)
}
})
}
We now have our function and its 2 important properties properly tested.
But isn't mocking evil?
You may have heard mocking is evil. Just like anything in software development it can be used for evil, just like DRY.
People normally get in to a bad state when they don't listen to their tests and are not respecting the refactoring stage.
If your mocking code is becoming complicated or you are having to mock out lots of things to test something, you should listen to that bad feeling and think about your code. Usually it is a sign of
- The thing you are testing is having to do too many things.
- Break the module apart so it does less
- Its dependencies are too fine-grained
- Think about how you can consolidate some of these dependencies into one meaningful module.
- Your test is too concerned with implementation details
- Favour testing expected behaviour rather than the implementation
Normally a lot of mocking points to bad abstraction in your code.
What people see here is a weakness in TDD but it is actually a strength, more often than not poor test code is a result of bad design or put more nicely, well-designed code is easy to test.
But mocks and tests are still making my life hard!
Ever run into this situation?
- You want to do some refactoring
- To do this you end up changing lots of tests
- You question TDD and make a post on Medium titled "Mocking considered harmful"
This is usually a sign of you testing too much implementation detail. Try to make it so your tests are testing useful behaviour unless the implementation is really important to how the system runs.
It is sometimes hard to know what level to test exactly but here are some thought processes and rules I try to follow
-
The definition of refactoring is that the code changes but the behaviour stays the same. If you have decided to do some refactoring in theory you should be able to do make the commit without any test changes. So when writing a test ask yourself
- Am i testing the behaviour I want or the implementation details?
- If i were to refactor this code, would I have to make lots of changes to the tests?
- Although Go lets you test private functions, I would avoid it as private functions are to do with implementation.
- I feel like if a test is working with more than 3 mocks then it is a red flag - time for a rethink on the design
- Use spies with caution. Spies let you see the insides of the algorithm you are writing which can be very useful but that means a tighter coupling between your test code and the implementation. Be sure you actually care about these details if you're going to spy on them
As always, rules in software development aren't really rules and there can be exceptions. Uncle Bob's article of "When to mock" has some excellent pointers.
Wrapping up
More on TDD approach
- When faced with less trivial examples, break the problem down into "thin vertical slices". Try to get to a point where you have working software backed by tests as soon as you can, to avoid getting in rabbit holes and taking a "big bang" approach.
- Once you have some working software it should be easier to iterate with small steps until you arrive at the software you need.
Mocking
- Without mocking important areas of your code will be untested. In our case we would not be able to test that our code paused between each print but there are countless other examples. Calling a service that can fail? Wanting to test your system in a particular state? It is very hard to test these scenarios without mocking.
- Without mocks you may have to set up databases and other third parties things just to test simple business rules. You're likely to have slow tests, resulting in slow feedback loops.
- By having to spin up a database or a webservice to test something you're likely to have fragile tests due to the unreliability of such services.
Once a developer learns about mocking it becomes very easy to over-test every single facet of a system in terms of the way it works rather than what it does. Always be mindful about the value of your tests and what impact they would have in future refactoring.
In this post about mocking we have only covered Spies which are a kind of mock. There are different kind of mocks. Uncle Bob explains the types in a very easy to read article. In later chapters we will need to write code that depends on others for data, which is where we will show Stubs in action.
Top comments (5)
I'm very confused with mocking in Go.
I've been struggling on that topic for a few hours now and what you nicely shows here in your post is not acceptable for me, except for an "hello world!" app.
I can't imagine writing the mocks for each dependency by myself, and above all, I can't imagine modifying my code to replace my dependencies by my interface.
It must be possible with reflection, no?
If you know a way to do that properly like with doubles in PHPUnit, or with mocks in Java/Mockito, then I'm interested!
Anyway, thanks for this great article!
Well what can I say, I and many others take this approach for large applications and it's fine.
Writing mocks, especially if you have an IDE that lets you auto implement interfaces at a keystroke is very trivial.
You can also do embedding if you wish to only mock a part of an interface
I'm not sure using reflection is any more "proper". In my experience mockito and the like give you a superficial "easiness" but then run into the usual problems with reflection which are a lack of clarity, type-safety and speed.
Debugging null pointer exceptions with my oh-so-easy mocks in mockito have wasted too much of my life already.
There are auto mocking libraries out there for Go of course, but I steer clear of them. I think GoMock is used by some.
Think about why you need to set up so many mocks. Are you over-testing things? Is the design of your system right?
You may be pointing out something interesting: maybe I am over-testing things, sometimes.
I love this concept in Go, where you craft many things by yourself.
This is achieved thanks to the great standard library.
That's why no framework emerged, unlike Laravel in PHP or Spring in Java.
In PHP, I was used to unit test every single part of my code, by mocking the sub-dependencies of my functions, and by spying calls.
By the time, it always become a kind of hell to maintain.
Maybe in Go, I could be a little less exhaustive in unit testing, and rely more on the strong typing. I mean, testing the inputs & outputs of my web APIs should be enough most of the time. But in some cases, I still need to check that data are written in db or that a log in sent to stdout because we have dashboards that consume it and this is critical for the business.
Thank you for your answer, it helped me to better understand what I really need.
Static typing certainly removes a lot of the tests you would need in a dynamic language but you still benefit from tests
I allude to this in the book in various chapters about how you should favour testing behaviour over implementation detail. It's a myth that unit testing means "tests on classes/functions/whatever" You write unit tests on behaviour, that could be a class which has a number of internal collaborators. You dont have to test them. In fact by testing them you may harm your efforts if you wish to change the implementation (refactoring)
i plan to do a talk/blog on this subject in more detail... sometime when i get the time.
Yes, Chris this IS helpful. I have a little more to learn w TDD but I’m in a good place due to this post. 👍🏾