Can't use Gatling Expression Language inside my own code/functions - scala

I'm creating one report for all simulations in SCALA, in part of them I don't have all attributes and I need to replace that because I'm getting no attribute defined error.
I was trying below code and many many more:
val dbc_communityID = if ("${communityID.exists()}" == true) "${communityID}" else "N/A"
I always have "N/A". I also checked
== 1
== "true"
I spend definitely to much time of that,
Please help

Quoting Gatling official documentation:
This Expression Language only works on String values being passed to Gatling DSL
methods. Such Strings are parsed only once, when the Gatling
simulation is being instantiated.
For example queryParam("latitude", session => "${latitude}") wouldn’t
work because the parameter is not a String, but a function that
returns a String.
Also, queryParam("latitude", "${latitude}".toInt) wouldn’t because the
toInt would happen before passing the parameter to the queryParam
method.
The solution here would be to pass a function:
session => session("latitude").validate[Int].
In short: you can't mix Gatling EL and functions/custom code. If you want to implement some custom logic that deals with Session data, you have to use the Session API, eg:
session => session("communityID").asOption[String].getOrElse("N/A")

if ("${communityID.exists()}" == true)
You are comparing a fixed String with a Boolean so the result will always be false. There is probably a compiler warning about this.
It is possible that you want this, but hard to say without know more about the rest of the code:
if (s"${communityID.exists()}" == "true")
But in that case it is simpler to write
if (communityID.exists())

Related

Is returning Either/Option/Try/Or considered a viable / idiomatic approach when function has preconditions for arguments?

First of all, I'm very new to Scala and don't have any experience writing production code with it, so I lack understanding of what is considered a good/best practice among community. I stumbled upon these resources:
https://github.com/alexandru/scala-best-practices
https://nrinaudo.github.io/scala-best-practices/
It is mentioned there that throwing exceptions is not very good practice, which made me think what would be a good way to define preconditions for function then, because
A function that throws is a bit of a lie: its type implies it’s total function when it’s not.
After a bit of research, it seems that using Option/Either/Try/Or(scalactic) is a better approach, since you can use something like T Or IllegalArgumentException as return type to clearly indicate that function is actually partial, using exception as a way to store message that can be wrapped in other exceptions.
However lacking Scala experience I don't quite understand if this is actually viable approach for a real project or using Predef.require is a way to go. I would appreciate if someone explained how things are usually done in Scala community and why.
I've also seen Functional assertion in Scala, but while the idea itself looks interesting, I think PartialFunction is not very suitable for the purpose as it is, because often more than one argument is passed and tuples look like a hack in this case.
Option or Either is definitely the way to go for functional programming.
With Option it is important to document why None might be returned.
With Either, the left side is the unsuccessful value (the "error"), while the right side is the successful value. The left side does not necessarily have to be an Exception (or a subtype of it), it can be a simple error message String (type aliases are your friend here) or a custom data type that is suitable for you application.
As an example, I usually use the following pattern when error handling with Either:
// Somewhere in a package.scala
type Error = String // Or choose something more advanced
type EitherE[T] = Either[Error, T]
// Somewhere in the program
def fooMaybe(...): EitherE[Foo] = ...
Try should only be used for wrapping unsafe (most of the time, plain Java) code, giving you the ability to pattern-match on the result:
Try(fooDangerous()) match {
case Success(value) => ...
case Failure(value) => ...
}
But I would suggest only using Try locally and then go with the above mentioned data types from there.
Some advanced datatypes like cats.effect.IO or monix.reactive.Observable contain error handling natively.
I would also suggest looking into cats.data.EitherT for typeclass-based error handling. Read the documentation, it's definitely worth it.
As a sidenote, for everyone coming from Java, Scala treats all Exceptions as Java treats RuntimeExceptions. That means, even when an unsafe piece of code from one of your dependencies throws a (checked) IOException, Scala will never require you to catch or otherwise handle the exception. So as a rule of thumb, when using Java - dependencies, almost always wrap them in a Try (or an IO if they execute side effects or block the thread).
I think your reasoning is correct. If you have a simple total (opposite of partial) function with arguments that can have invalid types then the most common and simple solution is to return some optional result like Option, etc.
It's usually not advisable to throw exceptions as they break FP laws. You can use any library that can return a more advanced type than Option like Scalaz Validation if you need to compose results in ways that are awkward with Option.
Another two alternatives I could offer is to use:
Type constrained arguments that enforce preconditions. Example: val i: Int Refined Positive = 5 based on https://github.com/fthomas/refined. You can also write your own types which wrap primitive types and assert some properties. The problem here is if you have arguments that have multiple interdependent valid values which are mutually exclusive per argument. For instance x > 1 and y < 1 or x < 1 and y > 1. In such case you can return an optional value instead of using this approach.
Partial functions, which in the essence resemble optional return types: case i: Int if i > 0 => .... Docs: https://www.scala-lang.org/api/2.12.1/scala/PartialFunction.html.
For example:
PF's def lift: (A) ⇒ Option[B] converts PF to your regular function.
Turns this partial function into a plain function returning an Option
result.
Which is similar to returning an option. The problem with partial functions that they are a bit awkward to use and not fully FP friendly.
I think Predef.require belongs to very rare cases where you don't want to allow any invalid data to be constructed and is more of a stop-everything-if-this-happens kind of measure. Example would be that you get arguments you never supposed to get.
You use the return type of the function to indicate the type of the result.
If you want to describe a function that can fail for whatever reason, of the types you mentioned you would probably return Try or Either: I am going to "try" to give your a result, or I am going to return "either" a success or an failure.
Now you can specify a custom exception
case class ConditionException(message: String) extends RuntimeException(message)
that you would return if your condition is not satisfied, e.g
import scala.util._
def myfunction(a: String, minLength: Int): Try[String] = {
if(a.size < minLength) {
Failure(ConditionException(s"string $a is too short")
} else {
Success(a)
}
}
and with Either you would get
import scala.util._
def myfunction(a: String, minLength: Int): Either[ConditionException,String] = {
if(a.size < minLength) {
Left(ConditionException(s"string $a is too short")
} else {
Right(a)
}
}
Not that the Either solution clearly indicates the error your function might return

Is a while loop already implemented with pass-by-name parameters? : Scala

The Scala Tour Of Scala docs explain pass-by-name parameters using a whileLoop function as an example.
def whileLoop(condition: => Boolean)(body: => Unit): Unit =
if (condition) {
body
whileLoop(condition)(body)
}
var i = 2
whileLoop (i > 0) {
println(i)
i -= 1
} // prints 2 1
The section explains that if the condition is not met then the body is not evaluated, thus improving performance by not evaluating a body of code that isn't being used.
Does Scala's implementation of while already use pass-by-name parameters?
If there's a reason or specific cases where it's not possible for the implementation to use pass-by-name parameters, please explain to me, I haven't been able to find any information on it so far.
EDIT: As per Valy Dia's (https://stackoverflow.com/users/5826349/valy-dia) answer, I would like to add another question...
Would a method implementation of the while statement perform better than the statement itself if it's possible not to evaluate the body at all for certain cases? If so, why use the while statement at all?
I will try to test this, but I'm new to Scala so it might take me some time. If someone would like to explain, that would be great.
Cheers!
The while statement is not a method, so the terminology by-name parameter is not really relevant... Having said so the while statement has the following structure:
while(condition){
body
}
where the condition is repeatedly evaluated and the body is evaluated only upon the condition being verified, as show this small examples:
scala> while(false){ throw new Exception("Boom") }
// Does nothing
scala> while(true){ throw new Exception("Boom") }
// java.lang.Exception: Boom
scala> while(throw new Exception("boom")){ println("hello") }
// java.lang.Exception: Boom
Would a method implementation of the while statement perform better than the statement itself if it's possible not to evaluate the body at all for certain cases?
No. The built-in while also does not evaluate the body at all unless it has to, and it is going to compile to much more efficient code (because it does not need to introduce the "thunks"/closures/lambdas/anonymous functions that are used to implement "pass-by-name" under the hood).
The example in the book was just showing how you could implement it with functions if there was no built-in while statement.
I assumed that they were also inferring that the while statement's body will be evaluated whether or not the condition was met
No, that would make the built-in while totally useless. That is not what they were driving at. They wanted to say that you can do this kind of thing with "call-by-name" (as opposed to "call-by-value", not as opposed to what the while loop does -- because the latter also works like that).
The main takeaway is that you can build something that looks like a control structure in Scala, because you have syntactic sugar like "call-by-name" and "last argument group taking a function can be called with a block".

(Scala) Am I using Options correctly?

I'm currently working on my functional programming - I am fairly new to it. Am i using Options correctly here? I feel pretty insecure on my skills currently. I want my code to be as safe as possible - Can any one point out what am I doing wrong here or is it not that bad? My code is pretty straight forward here:
def main(args: Array[String]): Unit =
{
val file = "myFile.txt"
val myGame = Game(file) //I have my game that returns an Option here
if(myGame.isDefined) //Check if I indeed past a .txt file
{
val solutions = myGame.get.getAllSolutions() //This returns options as well
if(solutions.isDefined) //Is it possible to solve the puzzle(crossword)
{
for(i <- solutions.get){ //print all solutions to the crossword
i.solvedCrossword foreach println
}
}
}
}
-Thanks!! ^^
When using Option, it is recommended to use match case instead of calling 'isDefined' and 'get'
Instead of the java style for loop, use higher-order function:
myGame match {
case Some(allSolutions) =>
val solutions = allSolutions.getAllSolutions
solutions.foreach(_.solvedCrossword.foreach(println))
case None =>
}
As a rule of thumb, you can think of Option as a replacement for Java's null pointer. That is, in cases where you might want to use null in Java, it often makes sense to use Option in Scala.
Your Game() function uses None to represent errors. So you're not really using it as a replacement for null (at least I'd consider it poor practice for an equivalent Java method to return null there instead of throwing an exception), but as a replacement for exceptions. That's not a good use of Option because it loses error information: you can no longer differentiate between the file not existing, the file being in the wrong format or other types of errors.
Instead you should use Either. Either consists of the cases Left and Right where Right is like Option's Some, but Left differs from None in that it also takes an argument. Here that argument can be used to store information about the error. So you can create a case class containing the possible types of errors and use that as an argument to Left. Or, if you never need to handle the errors differently, but just present them to the user, you can use a string with the error message as the argument to Left instead of case classes.
In getAllSolutions you're just using None as a replacement for the empty list. That's unnecessary because the empty list needs no replacement. It's perfectly fine to just return an empty list when there are no solutions.
When it comes to interacting with the Options, you're using isDefined + get, which is a bit of an anti pattern. get can be used as a shortcut if you know that the option you have is never None, but should generally be avoided. isDefined should generally only be used in situations where you need to know whether an option contains a value, but don't need to know the value.
In cases where you need to know both whether there is a value and what that value is, you should either use pattern matching or one of Option's higher-order functions, such as map, flatMap, getOrElse (which is kind of a higher-order function if you squint a bit and consider by-name arguments as kind-of like functions). For cases where you want to do something with the value if there is one and do nothing otherwise, you can use foreach (or equivalently a for loop), but note that you really shouldn't do nothing in the error case here. You should tell the user about the error instead.
If all you need here is to print it in case all is good, you can use for-comprehension which is considered quite idiomatic Scala way
for {
myGame <- Game("mFile.txt")
solutions <- myGame.getAllSolutions()
solution <- solutions
crossword <- solution.solvedCrossword
} println(crossword)

Best way to implement behavior based in type in scala

In a friendly chat that I was having with a friend during a code review we notice that in the code there was a lot of:
unknownTypeVal match {
case asStr: String => //DO SOMETHING FOR STRING
case asInt: Integer => //DO SOMETHING FOR Integer
case asMyOwnClass: MyOwnClass => //DO SOMETHING FOR MyOwnClass
}
problem that was initially generated by methods that return Any or Option and there is no way to remove that because we are using libraries as XPath, and JSONPath, which return instances of Any or Option for a provided path.
I don't want to get into discussions of "preference", this is not an opinion question, I want to know either by standard defined preferably by Scala, or any other organization of impact, to do this kind of "type checking" in code in a more organized way, we think that this functionality can be reduced to a single function call to a method which contains a map of function and based on "something" (name of the class or something else that I do not know right now) determine how to process such parameter:
process(myAnnonimusVal: Any) = myMapOfFunct(myAnnonimusVal.getClass) //and based on the function that this will return execute such function pasing myAnnonimusVal
what is encouraged to do by Scala devs or Scala community
In principle, match is the cleanest way to execute code conditional on matching the Any type to something else. Any chain of if-else, instanceOf, etc is bound to turn out to be even more cumbersome and less elegant. A possible exception is a case where you know what the actual type is and can act accordingly, where a direct cast might be permissible.
That said, if you find yourself making the same matches many times, you might as well encapsulate the match in order to avoid code repetition. A partial function might be exactly what you have in mind here.

Scala, Specs2, Mockito and null return values

I'm trying to test-drive some Scala code using Specs2 and Mockito. I'm relatively new to all three, and having difficulty with the mocked methods returning null.
In the following (transcribed with some name changes)
"My Component's process(File)" should {
"pass file to Parser" in new modules {
val file = mock[File]
myComponent.process(file)
there was one(mockParser).parse(file)
}
"pass parse result to Translator" in new modules {
val file = mock[File]
val myType1 = mock[MyType1]
mockParser.parse(file) returns (Some(myType1))
myComponent.process(file)
there was one(mockTranslator).translate(myType1)
}
}
The "pass file to Parser" works until I add the translator call in the SUT, and then dies because the mockParser.parse method has returned a null, which the translator code can't take.
Similarly, the "pass parse result to Translator" passes until I try to use the translation result in the SUT.
The real code for both of these methods can never return null, but I don't know how to tell Mockito to make the expectations return usable results.
I can of course work around this by putting null checks in the SUT, but I'd rather not, as I'm making sure to never return nulls and instead using Option, None and Some.
Pointers to a good Scala/Specs2/Mockito tutorial would be wonderful, as would a simple example of how to change a line like
there was one(mockParser).parse(file)
to make it return something that allows continued execution in the SUT when it doesn't deal with nulls.
Flailing about trying to figure this out, I have tried changing that line to
there was one(mockParser).parse(file) returns myResult
with a value for myResult that is of the type I want returned. That gave me a compile error as it expects to find a MatchResult there rather than my return type.
If it matters, I'm using Scala 2.9.0.
If you don't have seen it, you can look the mock expectation page of the specs2 documentation.
In your code, the stub should be mockParser.parse(file) returns myResult
Edited after Don's edit:
There was a misunderstanding. The way you do it in your second example is the good one and you should do exactly the same in the first test:
val file = mock[File]
val myType1 = mock[MyType1]
mockParser.parse(file) returns (Some(myType1))
myComponent.process(file)
there was one(mockParser).parse(file)
The idea of unit testing with mock is always the same: explain how your mocks work (stubbing), execute, verify.
That should answer the question, now a personal advice:
Most of the time, except if you want to verify some algorithmic behavior (stop on first success, process a list in reverse order) you should not test expectation in your unit tests.
In your example, the process method should "translate things", thus your unit tests should focus on it: mock your parsers and translators, stub them and only check the result of the whole process. It's less fine grain but the goal of a unit test is not to check every step of a method. If you want to change the implementation, you should not have to modify a bunch of unit tests that verify each line of the method.
I have managed to solve this, though there may be a better solution, so I'm going to post my own answer, but not accept it immediately.
What I needed to do was supply a sensible default return value for the mock, in the form of an org.mockito.stubbing.Answer<T> with T being the return type.
I was able to do this with the following mock setup:
val defaultParseResult = new Answer[Option[MyType1]] {
def answer(p1: InvocationOnMock): Option[MyType1] = None
}
val mockParser = org.mockito.Mockito.mock(implicitly[ClassManifest[Parser]].erasure,
defaultParseResult).asInstanceOf[Parser]
after a bit of browsing of the source for the org.specs2.mock.Mockito trait and things it calls.
And now, instead of returning null, the parse returns None when not stubbed (including when it's expected as in the first test), which allows the test to pass with this value being used in the code under test.
I will likely make a test support method hiding the mess in the mockParser assignment, and letting me do the same for various return types, as I'm going to need the same capability with several return types just in this set of tests.
I couldn't locate support for a shorter way of doing this in org.specs2.mock.Mockito, but perhaps this will inspire Eric to add such. Nice to have the author in the conversation...
Edit
On further perusal of source, it occurred to me that I should be able to just call the method
def mock[T, A](implicit m: ClassManifest[T], a: org.mockito.stubbing.Answer[A]): T = org.mockito.Mockito.mock(implicitly[ClassManifest[T]].erasure, a).asInstanceOf[T]
defined in org.specs2.mock.MockitoMocker, which was in fact the inspiration for my solution above. But I can't figure out the call. mock is rather overloaded, and all my attempts seem to end up invoking a different version and not liking my parameters.
So it looks like Eric has already included support for this, but I don't understand how to get to it.
Update
I have defined a trait containing the following:
def mock[T, A](implicit m: ClassManifest[T], default: A): T = {
org.mockito.Mockito.mock(
implicitly[ClassManifest[T]].erasure,
new Answer[A] {
def answer(p1: InvocationOnMock): A = default
}).asInstanceOf[T]
}
and now by using that trait I can setup my mock as
implicit val defaultParseResult = None
val mockParser = mock[Parser,Option[MyType1]]
I don't after all need more usages of this in this particular test, as supplying a usable value for this makes all my tests work without null checks in the code under test. But it might be needed in other tests.
I'd still be interested in how to handle this issue without adding this trait.
Without the full it's difficult to say but can you please check that the method you're trying to mock is not a final method? Because in that case Mockito won't be able to mock it and will return null.
Another piece of advice, when something doesn't work, is to rewrite the code with Mockito in a standard JUnit test. Then, if it fails, your question might be best answered by someone on the Mockito mailing list.