RSpec inspired test framework for F#
The aim of this project is to provide a test framework to the .NET platform having the same elegance as the RSpec framework has on Ruby.
You can easily use this framework to test C# code - that was in fact the original intent for this project.
Currently the following features are supported
- Nested example groups/contexts
- Setup/teardown in example groups
- Test context - can be used to pass data from setup to test
- Metadata on individual examples or example groups (accessible from setup)
- Assertion framework
- Implicit subject
- Automatically disposing IDisposable instances
- Support for missing metadata, i.e. test context can try to retrieve meta data that may or may not have been initialized.
- Better error messages when context/meta data does not exist, or is of incorrect type.
- One liner examples
- Visual Studio Integration
Ideas for future improvements
- Context data and meta data keys can be other types than strings, e.g. discriminated unions, partly to avoid name clashes.
- Global setup/teardown code, useful for clearing database between tests.
The framework is self testing, i.e. the framework is used to test itself.
I have written a few blog posts about FSpec
FSpec is stil in it's 0.x phase, so there is a risk that the API could change.
The easiest way to get started is to create a console application. Add the following main function.
module MySpecs.Program
[<EntryPoint>]
let main argv =
System.Reflection.Assembly.GetExecutingAssembly() |>
FSpec.TestDiscovery.runSingleAssembly
Add .fs files containing the tests, and assign them to a value named spec. The test discovery mechanism looks for this particular value name. E.g.:
module MySpecModule
open FSpec.Dsl
let specs =
describe "Some component" [
describe "Some feature" [
context "In some context" [
it "has some specific behaviour" (fun _ ->
()
)
it "has some other specific behavior" (fun _ ->
()
)
]
context "In some other context" [
it "has some completely different behavior" (fun _ ->
()
)
]
]
]
If you find the paranthesis noisy, you can use the backward pipe operator
let specs =
describe "Some feature" [
context "In some context" [
it "has some specific behaviour" <| fun _ ->
()
it "has some other specific behaviour" <| fun _ ->
()
You can use the function pending as the test body to indicate a test that needs to be written.
let specs =
describe "Some feature" [
it "has some specific behaviour" pending
it "has some other specific behaviour" pending
]
This allows you to quickly describe required functionality without being forced to write a full test up front.
The test runner reports pending tests, thus you will know if you have more work to do before the feature is complete. The test runner will not fail because of pending tests.
The functions before and after can be used to hold general setup/teardown code.
let specs =
describe "Some feature" <| fun _ ->
before (fun _ ->
// setup code here ...
)
after (fun _ ->
// teardown code here ...
)
it "Has some behavior" (fun _ ->
// Actual example here
)
In typical xUnit based frameworks, where tests are methods on classes, you typically use member variables to share data between setup code and individual tests (with the risk of forgetting to reset between tests).
In FSpec, you place such data in a TestContext, a value passed to all test functions, as well as setup and tear down code. A new TestContext is created for each test, so there is no risk of data getting carried over from one test to the next.
This pattern is also used in the JavaScript test frameworks Mocha and Jasmine, where a test context is passed as this to all test functions.
The context data is accessible using the ? operator.
let specs =
describe "createUser function" [
before (fun _ ->
ctx?user <- createUser "John" "Doe")
it "sets the first name" (fun ctx ->
ctx?user |> (fun x -> x.FirstName) |> should equal "John"
)
it "sets the last name" (fun ctx ->
ctx?user |> (fun x -> x.LastName) |> should equal "Doe"
)
]
Internally, the data is stored as instances of type obj, but the ? operator works with the type inference system, so it will automatically cast the data to the expected type.
In the above example, the fun x -> x.FirstName would be inferred to be of type User -> string - assuming the User type was the only type with a FirstName property currently opened.
If we created custome matchers for members on the User type, we could have rewritten the above code as:
let specs =
describe "createUser function" [
before (fun ctx -> ctx?user <- createUser "John" "Doe")
it "sets the first name" (fun ctx ->
ctx?user.Should (haveFirstName "John"))
it "sets the last name" (fun ctx ->
ctx?user.Should (haveLastName "Doe"))
]
Because the matchers themselves are typed to the type of the expected value, the type inference system will bring the expected type to the ? operator.
If you get a compiler error saying that the it cannot infer the type, you can use the generic TestContext.Get<'T> function instead.
let specs =
describe "createUser function" [
before (fun _ -> ctx?user = createUser "John" "Doe")
it "sets the first name" (fun ctx ->
let user = ctx.Get<User> "user"
user.FirstName |> should equal "John")
]
Any object added to the TestContext that implements IDisposable are automatically disposed when the test has finished.
let specs =
describe "The data access layer" [
before (fun ctx -> ctx?connection <- createDatabaseConnection () )
it "uses the connection" ...
]
The database connection will in this case automatically be disposed.
A special context variable, Subject, can be used to reference the thing under test. The variable is of type obj, but the generic function GetSubject<'T> will cast the subject to the expected type
let specs =
describe "createUser function" [
subject (fun _ -> createuser "John" "Doe")
it "sets the first name" (fun ctx ->
let user = ctx.GetSubject<User> ()
user.FirstName |> should (equal "John"))
it "sets the last name" (fun ctx ->
let user = ctx.GetSubject<User> ()
user.LastName |> should (equal "Doe"))
]
With a subject defined, you can write single-line tests. Again, here we assume we have created the custom matchers, haveFirstName, and haveLastName
let specs =
describe "createUser function" [
subject (fun _ -> createuser "John" "Doe")
itShould (haveFirstName "John")
itShould (haveLastName "Doe")
]
There are two extension methods declared on obj: Should, and ShouldNot. These will automatically cast the subject to the type expected by the matcher.
let specs =
describe "createUser function" [
subject (fun _ -> createuser "John" "Doe")
it "sets the first name" (fun ctx ->
ctx.Subject.Should (haveFirstName "John"))
it "sets the last name" (fun ctx ->
ctx.Subject.Should (haveLastName "Doe"))
]
If you don't have custom matchers for the properties on the subject, there is a third option Apply which allows you pass a function to retrieve the data from the subject that is of interest.
let specs =
describe "createUser function" [
subject <| fun _ -> createuser "john" "doe"
it "sets the first name" <| fun ctx ->
ctx.Subject.Apply (fun x -> x.FirstName)
|> should (equal "John")
it "sets the last name" <| fun ctx ->
ctx.Subject.Apply (fun x -> x.LastName)
|> should (equal "Doe")
]
The subject can also be a function.
let specs =
describe "createUser function, when user already exists" [
...
subject (fun _ ->
(fun () -> CreateAndSaveNewUser()))
it "should fail" <| fun ctx ->
ctx.Subject.Should fail
// or simply
itShould fail
You can associate metadata to an individual example, or an example group. The syntax is currently a strange set of operators. The metadata is basically a map of string keys and obj values.
Meta data assigned to an example, or example group, will be available on the TestContext when executing the example.
Metadata can be useful when you want to modify a general setup in a more specific context.
let specs =
describe "Register new user feature" [
before (fun ctx ->
let user = ctx?existing_user // Reads the from metatada
Mock<IUserRepository>()
.Setup(fun x -> <@ x.FindByEmail(email) @>)
.Returns(user)
.Create()
|> // do something with the mock
)
// When running tests in this context, the setup code will setup the
// FindByEmail function to return null
("existing_user", null) **>
context "when no user exists" [
it "succeeds" (...)
]
// When running tests in this context, the setup code will setup the
// FindByEmail function to return a valid user
("existing_user", createValidUser()) **>
context "when a user has already been registered with that email" [
it "fails" (...)
]
The funny looking **> operator is chosen because it is right-to-left associative, allowing us to reduce the required no of parenthesis.
The metadata getter is generic, but metadata lookup will fail at runtime if the actual data is not of the correct type.
Metadata with the same name on a child example group will override the value of the parent group, and metadata on an example will override that of the group.
Several pieces of metadata can be applied at once:
context "an example with many pieces of metadata" [
("data1", 42) **>
("data2", "Yummy") **>
("data3", Some [1;2;3]) **>
it "can easily specify a lot of metadata" (fun _ -> ())
]
]
FSpec has it's own set of assertions (not very complete currently). The assertions are typed, so the actual value must be of the correct type
5 |> should (equal 5) // pass
5 |> should (be.greaterThan 6) // fail
5 |> should (equal 5.0) // does not compile, incompatible types
"foobar" |> should (be.string.matching "ooba") // pass
A matcher requires a matcher function, a function that takes an actual value as input and returns a match result:
type MatchResult<'TSuccess> =
| MatchSuccess of 'TSuccess
| MatchFail of obj
type MatcherFunc<'a,'b> = 'a -> MatchResult<'b>
A matcher is a structure that contains a matcher function, and a set of messages describing the expected outcome:
type Matcher<'TActual,'TSuccess> = {
Run : MatcherFunc<'TActual,'TSuccess>
ExpectationMsgForShould : string
ExpectationMsgForShouldNot : string
}
Because a successful match carries the matched value, it is possible to chain matchers.
let haveLength = { Run: fun actual -> actual |> Seq.length |> MatchSuccess
ExpectationMsgForShould = "have length"
ExpectationMsgForShouldNot = "not have length" }
itShould (haveLength >>> equal 42)
Note how that haveLength matcher itself will never fail, it is created for the sole purpose of making it easy to read and write verification code.
There are two matcher creation helper functions:
createMatcher<'a,'b> : MatcherFunc<'a,'b> -> string -> Matcher<'a,'b>
createBoolMatcher<'a> : ('a -> bool) -> string -> Matcher<'a,'a>
The create matcher takes the matcher function and the expectation string as input. The negated expectation string is created by prefixing the expectation message with "not ".
The createBoolMatcher simply builds a matcher function from a predicate. Makes some matchers easier to create:
let equals expected =
createBoolMatcher
(fun actual -> actual = expected)
(sprintf "equal %A" expected)
Common test functionality can be created by writing extensions to the TestContext type. E.g. here, where FSpec is used to test a C# project following a typical dependency injection architecture.
module MyApplicationSpecs.TestHelpers
open FSpec.Core
type TestContext with
member self.AutoMocker =
self.GetOrDefault "auto_mocker" (fun _ -> AutoMocker())
member self.GetMock<'T> () = self.AutoMocker.GetMock<'T> ()
member self.Get<'T> () = self.AutoMocker.Get<'T> ()
Open the TestHelpers module from any test module where you need to test a component with mocked dependencies, and you will have access to the Get<'T>() and GetMock<'T>() methods.
The GetOrDefault<'T> calls the function to initialize a value if it hasn't already been initialized, otherwise the value stored in the context is returned.
Because examples are data structure, you can use List operations to generate batches of test cases.
let specs =
describe "Email validator" (
yield! (["[email protected]"
...
"[email protected]"]
|> List.map (fun email ->
it (sprintf "validates email: %s" email) (fun _ ->
email |> validateEmail |> should equal true))
)
yield! (["user@example";
...
"[email protected]"]
|> List.map (fun email ->
it (sprintf "does not validate email: %s" email) (fun _ ->
email |> validateEmail |> should equal false))
)
)
Although this example is a bit noisy, it shows that it can be done with the current api.
Alternately, you can create helper functions to create tests for you.
let itIsValidEmail email =
it (sprintf "validates email: %s" email) (fun _ ->
email |> validateEmail |> should (equal true))
let itIsInvalidEmail email =
it (sprintf "does not validate email: %s" email) (fun _ ->
email |> validateEmail |> should (equal false))
let specs =
describe "Email validator" (
itIsValidEmail "[email protected]"
...
itIsValidEmail "[email protected]"
itIsInvalidEmail "user@example"
...
itIsInvalidEmail "[email protected]"
)
You can use the NCrunch plugin for Visual Studio to run unit tests automatically as you are writing code.
The integration is based on the fact that MbUnit
allows the creation of a
DynamicTestFactory
that can return tests as instances of a TestCase
class.
FSpec provides a base class that contains wrapping code, mapping FSpec to MbUnit dynamic tests suites.
In the spec assembly, add the FSpec.MbUnitWrapper
nuget package, and create a
class that derives from MbUnitWrapperBase
.
[<MbUnit.Framework.TestFixtureAttribute>]
type Wrapper() =
inherit FSpec.MbUnitWrapper.MbUnitWrapperBase()
Just make sure that you have enabled MbUnit support with NCrunch. This has been tested with NCrunch 2.
Unfortunately, NCrunch cannot see each individual test, it only recognizes the entire test suite as a single test. But if your tests are fast, that should work fine for a normal red/green/refactor workflow.