* clean up and document integration test convention * clarify integration test conventions * clean up integration tests that don't follow convention * mark testIntegration* functions as helpers to avoid confusion
8.1 KiB
Backend style guide
Grafana's backend has been developed for a long time with a mix of code styles. This guide explains how we want to write Go code in the future.
Unless stated otherwise, use the guidelines listed in the following articles:
Linting and formatting
To ensure consistency across the Go codebase, we require all code to pass a number of linter checks.
We use the standard following linters:
In addition to the standard linters, we also use:
- revive with a custom config
- GolangCI-Lint
- gosec
To run all linters, use the lint-go
Makefile target:
make lint-go
Testing
We value clean and readable code, that is loosely coupled and covered by unit tests. This makes it easier to collaborate and maintain the code.
Tests must use the standard library, testing
. For assertions, prefer using testify.
The majority of our tests uses GoConvey but that's something we want to avoid going forward.
In the sqlstore
package we do database operations in tests and while some might say that's not suited for unit tests. We think they are fast enough and provide a lot of value.
Integration Tests
We run unit and integration tests separately, to help keep our CI pipeline running smoothly and provide a better developer experience.
To properly mark a test as being an integration test, you must format your test function definition as follows, with the function name starting with TestIntegration
and the check for testing.Short()
:
func TestIntegrationFoo(t *testing.T) {
if testing.Short() {
t.Skip("skipping integration test")
}
// function body
}
If you do not follow this convention, your integration test may be run twice or not run at all.
Assertions
Use respectively assert.*
functions to make assertions that
should not halt the test ("soft checks") and require.*
functions to make assertions that should halt the test ("hard checks"). Typically you want to use the latter type of
check to assert that errors have or have not happened, since continuing the test after such an assertion fails is
chaotic (the system under test will be in an undefined state) and you'll often have segfaults in practice.
Sub-tests
Use t.Run
to group sub-test cases, since it allows common setup and teardown
code, plus lets you run each test case in isolation when debugging. Don't use t.Run
to e.g. group assertions.
Cleanup
Use t.Cleanup
to clean up resources in tests. It's a less fragile choice than defer
, since it's independent of which
function you call it in. It will always execute after the test is over in reverse call order (last t.Cleanup
first, same as defer
).
Mock
Optionally, we use mock.Mock
package to generate mocks. This is
useful when you expect different behaviours of the same function.
Tips
- Use
Once()
orTimes(n)
to make this mock only worksn
times. - Use
mockedClass.AssertExpectations(t)
to guarantee that the mock is called the times asked.- If any mock set is not called or its expects more calls, the test fails.
- You can pass
mock.Anything
as argument if you don't care about the argument passed. - Use
mockedClass.AssertNotCalled(t, "FunctionName")
to assert that this test is not called.
Example
This is an example to easily create a mock of an interface.
Given this interface:
func MyInterface interface {
Get(ctx context.Context, id string) (Object, error)
}
Mock implementation should be like this:
import
func MockImplementation struct {
mock.Mock
}
func (m *MockImplementation) Get(ctx context.Context, id string) error {
args := m.Called(ctx, id) // Pass all arguments in order here
return args.Get(0).(Object), args.Error(1)
}
And use it as the following way:
objectToReturn := Object{Message: "abc"}
errToReturn := errors.New("my error")
myMock := &MockImplementation{}
defer myMock.AssertExpectations(t)
myMock.On("Get", mock.Anything, "id1").Return(objectToReturn, errToReturn).Once()
myMock.On("Get", mock.Anything, "id2").Return(Object{}, nil).Once()
anyService := NewService(myMock)
resp, err := anyService.Call("id1")
assert.Equal(t, resp.Message, objectToReturn.Message)
assert.Error(t, err, errToReturn)
resp, err = anyService.Call("id2")
assert.Nil(t, err)
Mockery
When an interface to test is too big, it's annoying to mock each function manually. To avoid this, you can
use mockery
library to generate the mocks.
The command is like the following (there are more options documented if you need to use another one):
mockery --name InterfaceName --structname MockImplementationName --inpackage --filename my_implementation_mock.go
--name
: Interface to mock--structname
: Mock implementation name--inpackage
: To use the same package name as the interface--filename
: Your mock generated file name
If any interface signature changes, executing the command again updates the mock.
Additionally, you can put go:generate
command on the top of the file as a comment. It's useful because some IDEs
like Goland and Visual Studio Code allows executing scripts from the IDE.
package <package>
import (
...
)
//go:generate mockery --name InterfaceName --structname MockImplementationName --inpackage --filename my_implementation_mock.go
Globals
As a general rule of thumb, avoid using global variables, since they make the code difficult to maintain and reason about, and to write tests for. The Grafana codebase currently does use a lot of global variables, especially when it comes to configuration, but that is a problem we're trying to solve.
Pointers
In general, use value types and only reach for pointers when there's a real need. The reason being that pointers increase the risk of bugs, since a pointer can be nil and dereferencing a nil pointer leads to a panic (AKA segfault). Valid reasons to use a pointer include (but not necessarily limited to):
- You might need to pass a modifiable argument to a function
- Copying an object might incur a performance hit (benchmark to check your assumptions, copying is often faster than allocating heap memory)
- You might need
nil
to tell if a variable isn't set, although usually it's better to use the type's zero value to tell instead
Database
In database related code, we follow certain patterns.
Foreign keys
While they can be useful, we don't generally use foreign key constraints in Grafana, for historical and technical reasons. See this comment by Torkel for context.
Unique columns
If a column, or column combination, should be unique, add a corresponding uniqueness constraint through a migration.
JSON
The simplejson package is used a lot throughout the backend codebase, but it's legacy, so if at all possible avoid using it in new code. Use json-iterator instead, which is a more performant drop-in alternative to the standard encoding/json package. While encoding/json is a fine choice, profiling shows that json-iterator may be 3-4 times more efficient for encoding. We haven't profiled its parsing performance yet, but according to json-iterator's own benchmarks, it appears even more superior in this department.