scalamock create basic setup and easily change it - scala

I started writing my own MockSetter, to make some basic mocks before each tests, on in every of it be able to change of of them or add new one.
Trait for Spec looks like:
trait MocksSetter extends MockFactory with BeforeAndAfterEach { self: Suite =>
type PositionWithMockTuple = (Int, (() => CallHandler[Any]))
private var standardMocks: Seq[PositionWithMockTuple] = Seq.empty
def setupStandardMocks(mocks: Seq[PositionWithMockTuple]) = {
standardMocks = mocks
}
//Replaces current standard mock in a given position
def replaceMock(position: Int, newMockedFunc: () => CallHandler[Any]) = {
val updatedMocks = standardMocks.map {
case (pos, _) if pos == position => (pos, newMockedFunc)
case (pos, mf) => (pos, mf)
}
standardMocks = updatedMocks
}
//Puts new mock in the end
def insertMock(newMockedFunc: () => CallHandler[Any]) = {
standardMocks = standardMocks :+ ((standardMocks.last._1 + 1, newMockedFunc))
}
override def beforeEach(): Unit = {
standardMocks.foreach {
case (_, mockFunc) => mockFunc().once()
}
super.beforeEach()
}
}
but when I try to pass mocks:
[error] found : org.scalamock.handlers.CallHandler[Boolean]
[error] required: org.scalamock.handlers.CallHandler[Any]
[error] Note: Boolean <: Any, but class CallHandler is invariant in type R.
[error] You may wish to define R as +R instead. (SLS 4.5)
[error] setupStandardMocks(Seq((1, () => someMethodMock(false))))
Is it possible to achieve this goal ?
My idea is simple, before all tests save basic mocks, which are executed before each test ( by using .once() ). Of course different specs may differ between each other, and when doing tests there is a lot of code repeated in every test. If there are for example 10 methods inside, for each test I need to write mocks for every method, and change only what is needed.
Would be nice to make it using basic setup and change according to specific test.

Ok solution can be done in easier way.
In spec we can create abstract class with parameters.
We will run spec by doing
"x y z" in new StandardMocks(onlyOneParamChanged = "xyz") {
...
}
Of course class parameters will have default values, which we can override easily.
Inside class do the mocking stuff by takich parameters and thats it.

Related

Returning a Stream of Entities using a Transactor inside a Resource in Doobie

I'm trying to implement a query that returns the extracted information inside a fs2.Stream. I defined the Jobs algebra:
trait Jobs[F[_]] {
def all(): fs2.Stream[F, Job]
}
Then, I implemented an interpreter for the algebra:
final class LiveJobs[F[_]: MonadCancelThrow](postgres: Resource[F, Transactor[F]]) extends Jobs[F] {
override def all(): fs2.Stream[F, Job] = for {
jobs <- postgres.use { xa =>
sql"SELECT * FROM jobs".query[Job].stream.transact(xa)
}
} yield jobs
}
However, the compiler yells because the types are not aligned:
type mismatch;
[error] found : fs2.Stream[[_]F[_],Job]
[error] required: F[?]
[error] sql"SELECT * FROM jobs".query[Job].stream.transact(xa)
[error] ^
[error] one error found
The Resource.use method needs a function that produces an F[*], not an fs2.Stream[F, Job]. I cannot find anything that lets me convert between the two types or a different way to use the postgres resource.
The following is probably the design you want to follow:
trait Jobs[F[_]] {
def all: fs2.Stream[F, Job] =
}
object Jobs {
// I am not exactly sure which typeclass you require here, so i will use Async
def live[F[_]](implicit ev: Async[F]): Resource[F, Jobs[F]] = {
val transactor: Resource[F, Transactor[F]] = ... // Whatever you already have here.
transactor.map(xa => new LiveJobs(xa))
}
}
private[pckg] final class LiveJobs[F[_]](xa: Transactor[F])(implicit ev: MonadCancelThrow[F]) extends Jobs[F] {
override final val all: fs2.Stream[F, Job] =
sql"SELECT * FROM jobs".query[Job].stream.transact(xa)
}
Also, my personal advice, stick to concrete IO while learning; and maybe even after.
The whole F[_] thing will just cause more trouble than worth originally.

How do I turn a cats IO into a Effect using http4s

I've got some code that returns an IO but I need a Effect in http4s.
import cats.effect.{Effect, IO}
class Service[F[_]: Effect] extends Http4sDsl[F] {
val service: HttpService[F] = {
HttpService[F] {
case GET -> Root =>
val data: IO[String] = getData()
data.map(d => Ok(d))
}
}
}
gives
[error] found : cats.effect.IO[F[org.http4s.Response[F]]]
[error] required: F[org.http4s.Response[F]]
[error] data.map(d => Ok(d))
[error] ^
One way we can get around using a concrete IO[A] is using LiftIO[F]:
class Service[F[_]: Effect] extends Http4sDsl[F] {
val service: HttpService[F] = {
HttpService[F] {
case GET -> Root =>
getData().liftIO[F].flatMap(Ok(_))
}
}
}
LiftIO lifts will lift: IO[A] => F[A], but this yields us F[F[Response[F]. In order to get things to compile, we'll flatten on F since it has a Monad (or FlatMap) instance in cats due to our Effect context bounds requirement.
If we want more detail, this is the -Xprint:typer result:
cats.implicits.catsSyntaxFlatten[F, org.http4s.Response[F]](
cats.effect.LiftIO.apply[F](Service.this.evidence$1)
.liftIO[F[org.http4s.Response[F]]](
data.map[F[org.http4s.Response[F]]](
((d: String) => Service.this.http4sOkSyntax(Service.this.Ok)
.apply[String](d)(Service.this.evidence$1,
Service.this.stringEncoder[F](
Service.this.evidence$1, Service.this.stringEncoder$default$2[F]))))))(Service.this.evidence$1).flatten(Service.this.evidence$1)
And at the end of the world when you want to give a concrete effect, for example Service[IO], we get:
val serv: Service[cats.effect.IO] =
new Service[cats.effect.IO]()(effect.this.IO.ioConcurrentEffect)
Where ioConcurrentEffect is the Effect[IO] instance.
It seems that all the good stuff is defined at org.http4s.syntax.AllSyntax trait.

Left to right arguments type inference

I have a case where I wish to apply modifications to an object based on the presence of (a few, say, 5 to 10) optionals. So basically, if I were to do it imperatively, what I'm aiming for is :
var myObject = ...
if (option.isDefined) {
myObject = myObject.modify(option.get)
}
if (option2.isDefined) {
myObject = myObject.someOtherModification(option2.get)
}
(Please note : maybe my object is mutable, maybe not, that is not the point here.)
I thought it'd look nicer if I tried to implement a fluent way of writing this, such as (pseudo code...) :
myObject.optionally(option, _.modify(_))
.optionally(option2, _.someOtherModification(_))
So I started with a sample code, which intelliJ does not highlight as an error, but that actually does not build.
class MyObject(content: String) {
/** Apply a transformation if the optional is present */
def optionally[A](optional: Option[A], operation: (A, MyObject) => MyObject): MyObject =
optional.map(operation(_, this)).getOrElse(this)
/** Some possible transformation */
def resized(length : Int): MyObject = new MyObject(content.substring(0, length))
}
object Test {
val my = new MyObject("test")
val option = Option(2)
my.optionally(option, (size, value) => value.resized(size))
}
Now, in my case, the MyObject type is of some external API, so I created an implicit conversion to help, so what it really does look like :
// Out of my control
class MyObject(content: String) {
def resized(length : Int): MyObject = new MyObject(content.substring(0, length))
}
// What I did : create a rich type over MyObject
class MyRichObject(myObject: MyObject) {
def optionally[A](optional: Option[A], operation: (A, MyObject) => MyObject): MyObject = optional.map(operation(_, myObject)).getOrElse(myObject)
}
// And an implicit conversion
object MyRichObject {
implicit def apply(myObject: MyObject): MyRichObject = new MyRichObject(myObject)
}
And then, I use it this way :
object Test {
val my = new MyObject("test")
val option = Option(2)
import MyRichObject._
my.optionally(option, (size, value) => value.resized(size))
}
And this time, it fails in IntelliJ and while compiling because the type of the Option is unknown :
Error:(8, 26) missing parameter type
my.optionally(option, (size, value) => value.resized(size))
To make it work, I can :
Actively specify a type of the size argument : my.optionally(option, (size: Int, value) => value.resized(size))
Rewrite the optionally to a curried-version
None of them is really bad, but if I may ask :
Is there a reason that a curried version works, but a multi argument version seems to fail to infer the parametrized type,
Could it be written in a way that works without specifying the actual types
and as a bonus (although this might be opinion based), how would you write it (some sort of foldLeft on a sequence of optionals come to my mind...) ?
One option for your consideration:
// Out of my control
class MyObject(content: String) {
def resized(length : Int): MyObject = new MyObject(content.substring(0, length))
}
object MyObjectImplicits {
implicit class OptionalUpdate[A](val optional: Option[A]) extends AnyVal {
def update(operation: (A, MyObject) => MyObject): MyObject => MyObject =
(obj: MyObject) => optional.map(a => operation(a, obj)).getOrElse(obj)
}
}
object Test {
val my = new MyObject("test")
val option = Option(2)
import MyObjectImplicits._
Seq(
option.update((size, value) => value.resized(size)),
// more options...
).foldLeft(my)(_)
}
Might as well just use a curried-version of your optionally, like you said.
A nicer way to think about the need to add the type there is write it this way:
object Test {
val my = new MyObject("test")
val option = Some(2)
my.optionally[Int](option, (size, value) => value.resized(size))
}
Another way, if you only will manage one type since the object creation, is to move the generic to the class creation, but be careful, with this option you only can have one type per instance:
class MyObject[A](content: String) {
def optionally(optional: Option[A], operation: (A, MyObject[A]) => MyObject[A]): MyObject[A] =
optional.map(operation(_, this)).getOrElse(this)
def resized(length : Int): MyObject[A] = new MyObject[A](content.substring(0, length))
}
object Test {
val my = new MyObject[Int]("test")
val option = Some(2)
my.optionally(option, (size, value) => value.resized(size))
}
As you can see, now all the places where the generics was is taken by the Int type, because that is what you wanted in the first place, here is a pretty answer telling why:
(just the part that I think applies here:)
4)When the inferred return type would be more general than you intended, e.g., Any.
Source: In Scala, why does a type annotation must follow for the function parameters ? Why does the compiler not infer the function parameter types?

Explanation on the error with for comprehension and co-variance

Question
Would like to get assistance to understand the cause of the error. The original is from Coursera Scala Design Functional Random Generators.
Task
With the factories for random int and random boolean, trying to implement a random tree factory.
trait Factory[+T] {
self => // alias of 'this'
def generate: T
def map[S](f: T => S): Factory[S] = new Factory[S] {
def generate = f(self.generate)
}
def flatMap[S](f: T => Factory[S]): Factory[S] = new Factory[S] {
def generate = f(self.generate).generate
}
}
val intFactory = new Factory[Int] {
val rand = new java.util.Random
def generate = rand.nextInt()
}
val boolFactory = intFactory.map(i => i > 0)
Problem
The implementation in the 1st block causes the error but if it changed into the 2nd block, it does not. I believe Factory[+T] meant that Factory[Inner] and Factory[Leaf] could be both treated as Factory[Tree].
I have no idea why the same if expression in for block is OK but it is not OK in yield block. I appreciate explanations.
trait Tree
case class Inner(left: Tree, right: Tree) extends Tree
case class Leaf(x: Int) extends Tree
def leafFactory: Factory[Leaf] = intFactory.map(i => new Leaf(i))
def innerFactory: Factory[Inner] = new Factory[Inner] {
def generate = new Inner(treeFactory.generate, treeFactory.generate)
}
def treeFactory: Factory[Tree] = for {
isLeaf <- boolFactory
} yield if (isLeaf) leafFactory else innerFactory
^^^^^^^^^^^ ^^^^^^^^^^^^
type mismatch; found : Factory[Inner] required: Tree
type mismatch; found : Factory[Leaf] required: Tree
However, below works.
def treeFactory: Factory[Tree] = for {
isLeaf <- boolFactory
tree <- if (isLeaf) leafFactory else innerFactory
} yield tree
I have no idea why the same if expression in for block is OK but it is
not OK in yield block
Because they are translated differently by the compiler. The former example is translated into:
boolFactory.flatMap((isLeaf: Boolean) => if (isLeaf) leafFactory else innerFactor)
Which yields the expected Factory[Tree], while the latter is being translated to:
boolFactory.map((isLeaf: Boolean) => if (isLeaf) leafFactory else innerFactory)
Which yields a Factory[Factory[Tree]], not a Factory[Tree], thus not conforming to your method signature. This isn't about covariance, but rather how for comprehension translates these statements differently.

Inferring result type in continuations

Is it possible to remove some types from the following code:
import util.continuations._
object TrackingTest extends App {
implicit def trackable(x: Int) = new {
def tracked[R] = shift { cf: (Int => (R, Set[Int])) =>
cf(x) match {
case (r, ints) => (r, ints + x)
}
}
}
def track[R](body: => R #cpsParam[(R, Set[Int]), (R, Set[Int])]) = reset {
(body, Set[Int]())
}
val result = track(7.tracked[Int] + 35.tracked[Int])
assert(result == (42, Set(7, 35)))
val differentTypes = track(9.tracked[String].toString)
assert(differentTypes == ("9", Set(9)))
}
track function tracks calls of tracked on Int instances (e.g. 7.tracked).
Is it possible to infer type parameter on tracked implicit, so the following would compile:
track(7.tracked + 35.tracked)
Your question made me think of how continuations can track state. So I adapted that to your case and came up with this:
import util.continuations._
object TrackingTest extends App {
type State = Set[Int]
type ST = State => State
implicit class Tracked(val i: Int) extends AnyVal {
def tracked = shift{ (k: Int=>ST) => (state:State) => k(i)(state + i) }
}
def track[A](thunk: => A#cps[ST]): (A, State) = {
var result: A = null.asInstanceOf[A]
val finalSate = (reset {
result = thunk
(state:State) => state
}).apply(Set[Int]())
(result, finalSate)
}
val result = track(7.tracked + 35.tracked)
assert(result == (42, Set(7, 35)))
val differentTypes = track(9.tracked.toString)
assert(differentTypes == ("9", Set(9)))
}
This is using 2.10.1 but it works fine with 2.9.1 as well provided you replace the 2.10.x implicit value class with:
implicit def tracked(i: Int) = new {
def tracked = shift{ (k: Int=>ST) => (state:State) => k(i)(state + i) }
}
The key change I made is to have tracked not use any type inference, fixing to Int#cps[ST]. The CPS plugin then maps the computation to the right type (like String#cps[ST]) as appropriate. The state is threaded by the continuation returning a State=>State function that takes the current state (the set of ints) and returns the next state. The return type of reset is a function from state to state (of type ST) that will take the initial state and will return the final state.
The final trick is to use a var to capture the result while still keeping the expected type for reset.
While the exact answer to this question can be given only by the authors of the compiler, we can guess it is not possible by giving a look to the continuation plugin source code.
If you look to the source of the continuations you can see this:
val anfPhase = new SelectiveANFTransform() {
val global = SelectiveCPSPlugin.this.global
val runsAfter = List("pickler")
}
val cpsPhase = new SelectiveCPSTransform() {
val global = SelectiveCPSPlugin.this.global
val runsAfter = List("selectiveanf")
}
The anfPhase phase is executed after the pickler phase, and the cpsPhase after selectiveAnf. If you look to SelectiveANFTransform.scala
abstract class SelectiveANFTransform extends PluginComponent with Transform with
TypingTransformers with CPSUtils {
// inherits abstract value `global' and class `Phase' from Transform
import global._ // the global environment
import definitions._ // standard classes and methods
import typer.atOwner // methods to type trees
/** the following two members override abstract members in Transform */
val phaseName: String = "selectiveanf"
If we use scalac -Xshow-phases, we can see the phases during the compilation process:
parser
namer
packageobjects
typer
superaccessors
pickler
refchecks
selectiveanf
liftcode
selectivecps
uncurry
......
As you can see the typer phase is applied before the selectiveAnf and selectiveCps phases. It should be confirmed that type inference occurs in the typer phase, but if this is really the case and it would make sense, it should be now clear why you can't omit the Int type on 7.tracked and 35.tracked.
Now if you are not satisfied yet, you should know that the compiler works by performing a set of transformations on "trees", which you might look, using the following options:
-Xprint: shows your scala code after a certain phase have been executed
-Xprint: -Yshow-trees shows your scala code and the trees after the phase have been executed
-YBrowse: opens a GUI to surf both.