Strange case class syntax - scala

I've been learning Scala and decided to play with JSON parsing using json4s. I decided to use XPath syntax for deserializing and came across this strange bit of syntax I've never seen before.
val json = JsonMethods.parse("""{"meaningOfLife": 42}""")
val JInt(x) = json\"meaningOfLife"
The part confusing me is this bit right here
val JInt(x) = ...
I can't wrap my mind around what's happening there, I don't even know how to search this syntax or what it's called. Can anyone help me out? Scala is an amazing language with a lot of neat features that I'm not used to in other languages like C++ and Java.
Edit
To clarify, I'm confused because x isn't defined, but it's somehow being passed into a function or constructor then being assigned to the result of json\"meaningOfLife" which returns a JValue.
Edit 2
After some research and playing around, I figured out that this has something to do with case classes. I was able to run the following code.
case class MyCaseClass (x: Int)
val MyCaseClass(x) = new MyCaseClass(5)
println(x, x.getClass) // prints (5,int)
Which, after looking at some of the code, gives me a good understanding at what's happening.
val MyCaseClass(x) = MyCaseClass(5)
Is extracting (for lack of a better term) the Int value 5 from the instantiated MyCaseClass and storing that into x, meaning x will be of type Int.
In the code for json4s a JInt is a JValue which the \ operator returns. So the JInt(x) is taking out a BigInt (stored in the class JInt) and putting that into the value x from what I gather.
But I still have a question. What is this process called? Is there any documentation on it?

It's called "irrefutable pattern matching" and it's essentially equivalent to this bit of code:
val json = JsonMethods.parse("""{"meaningOfLife": 42}""")
val x = json match {
case JInt(xMatched) => xMatched
}
In other words, any case class or any extractor that fits the pattern of the declaration's left-hand-side can be used in this way.
Addendum:
The "irrefutable" means that a MatchError will be thrown if the pattern cannot be satisfied.

Related

Check the runtime type of Scala class instance

If I run the following code, then I get an error:
import scala.reflect.ClassTag
class General {
}
class SubGeneral extends General {
def test() = println("tested")
}
class ProGeneral[T <: General: ClassTag] {
var array = Array.ofDim[T](3, 3)
def funcForSubGeneral(): Unit =
if (array(0)(0).isInstanceOf[SubGeneral]) then array(0)(0).test()
}
That is because General does not have the function test().
I know that I can fix this with pattern matching. This instead of the above funcForSubGeneral() works:
def funcForSubGeneral(): Unit =
array(0)(0) match {
case s: SubGeneral => s.test()
case _ => println("nope")
}
But I was wondering if it is possible to get the runtime type of array(0)(0) and check if it is a SubGeneral, and if that is the case then I call test(), which shouldn't cause a problem?
That is what I was actually trying by using isIntanceOf. I want to omit pattern matching since I'm just interested in one type.
isInstanceOf doesn't change anything, you would need to do array(0)(0).asInstanceOf[SubGeneral].test() in order to force the casting.
Note that the casting may fail at runtime, so that is why you need to check with the if before. Thus the end code looks like this:
if (array(0)(0).isInstanceOf[SubGeneral]) then array(0)(0).asInstanceOf[SubGeneral].test()
But, since this is cumbersome and error-prone, we have pattern matching:
array(0)(0) match {
case subGeneral: SubGeneral => subGeneral.test()
}
However, note that type tests are considered a bad practice; mainly because they are actually class checks and may fail certain circumstances. For example:
List("a", "b", "c") match {
case numbers: List[Int] => numbers.head + 1
}
Will throw an exception in runtime since, due to type erasure, we lost the [String] part and it matches only List then it tries to read the first element as an Int which is an error.
Anyways, this is the fourth time in two days you ask a question that shows bad practices and unidiomatic code.
My advice:
I would bet you are not following an appropriate resource to learn the language. Rather, it seems you are just trying to mimic another language (Python?) with different syntax. - Thus, I encourage you to pick an appropriate book, course, tutorial, etc; that properly introduces the language and its idioms.
I would encourage you to join the official Discord server which is more suitable for newcomers than StackOverflow.
I would recommend you to explain the meta-problem you are trying to solve in detail (either here in a new question or in the Discord server), I am pretty sure there are better and more idiomatic ways to solve it.

how can i do dynamic casting of a variable from one type to another in Scala

I would like to do dynamic casting for a scala variable, the casting type is stored in a different variable or in the database or provided by the user.
I am new to Scala and have mainly done coding on python. Here we are trying to take Any type input and query the type of the variable as per the type saved in DB eg.: "String/Int" and user-defined classes and cast them before any future processing.
in python:
eval("str('123')")
in scala I have tried
var a = 123.05
a.asInstanceOf['Int']
gives me error
error: identifier expected but string literal found.
And I want the code to be something as follows:
var a = 123.05
var b = "Int"
a.asInstanceOf[b]
gives me error
error: not found: type b
Ok so I have to be fairly exhaustive here because the stuff you're trying to do is tricky due to the static vs dynamic typing difference of scala and python.
First what you're doing in Python is not type casting but rather a conversion.
str(12)
in python takes the integer value 12 and converts it to a (UTF-8 ? dunno in python) string. The same thing in scala would be
12.toString
typecasting in the meantime is basically a pinky promise to the compilers typechecker that you know more than it and it should just believe you. It also should be avoided like the pest because you basically drop all the safety that static typechecking gives you. However there are certain cases where it is unavoidable
in a bit more fundamental terms. lets say you have the following scala snippet
sealed trait Foo
final case class Bar(i:Int) extends Foo
final case class Baz(s:String) extends Foo
val f:Foo = Bar(2)
//won't work because the compiler thinks f is of type Foo due to the type ascription bove
println(f.i)
//will work
println(f.asInstanceOf[Bar].i)
the Type Foo can be either Bar or Baz (because of the sealed and final, this is called an ADT) but we specifically told the compiler to treat f as a Foo which means we forgot which specific type it was. this is the case where you could use typecasting, note that we don't convert but rather tell the compiler that it is actually a Bar
Now this all happens during compile time which means you can't cast according to a runtime value like this
var a = 123.05
var b = "Int"
a.asInstanceOf[b]
Now as I understand you have some sort of stringly typed input and need to convert it according to some schema. The scalafiddle below has an example how you could do this: https://scalafiddle.io/sf/i97WZlA/0
However note that this makes use of some fairly advanced concepts in scala to ensure the types line up.
This will also work https://scalafiddle.io/sf/i97WZlA/1 but note that we lose all the type information requiring us to do a typecast if we want to do anything meaningful with out
EDIT/ADDENDUM: I thought I should also do an example on how to consume such values and make the schema dynamic.
https://scalafiddle.io/sf/i97WZlA/2
As a final note be warned that this is getting close to the limits what the compiler can do and necessitates a lot of boxing and unboxing to carry along the type information (in SchemaValue) also it's not stacksafe and has lackluster errorhandling. this solution would require some serious engineering to make viable but it should get the idea across
If you have a String value, then you can use toInt or toDouble to parse that string:
val s = "123.05"
val i = s.toInt
val d = s.toDouble
If you have an Any value then it is best to use match to convert it:
val a: Any = ...
a match {
case i: Int => // It is an Int
case d: Double => // It is a Double
case _ => // It is a different type
}
If all else fails you can explicitly pick a type, but this is not good practice:
val i = a.asInstanceOf[Int]
Any decent database framework will give you the ability to read and write values of specific types, so this should not be a problem with the right library.

(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)

Convert a Seq[String] to a case class in a typesafe way

I have written a parser which transforms a String to a Seq[String] following some rules. This will be used in a library.
I am trying to transform this Seq[String] to a case class. The case class would be provided by the user (so there is no way to guess what it will be).
I have thought to shapeless library because it seems to implement the good features and it seems mature, but I have no idea to how to proceed.
I have found this question with an interesting answer but I don't find how to transform it for my needs. Indeed, in the answer there is only one type to parse (String), and the library iterates inside the String itself. It probably requires a deep change in the way things are done, and I have no clue how.
Moreover, if possible, I want to make this process as easy as possible for the user of my library. So, if possible, unlike the answer in link above, the HList type would be guess from the case class itself (however according to my search, it seems the compiler needs this information).
I am a bit new to the type system and all these beautiful things, if anyone is able to give me an advice on how to do, I would be very happy!
Kind Regards
--- EDIT ---
As ziggystar requested, here is some possible of the needed signature:
//Let's say we are just parsing a CSV.
#onUserSide
case class UserClass(i:Int, j:Int, s:String)
val list = Seq("1,2,toto", "3,4,titi")
// User transforms his case class to a function with something like:
val f = UserClass.curried
// The function created in 1/ is injected in the parser
val parser = new Parser(f)
// The Strings to convert to case classes are provided as an argument to the parse() method.
val finalResult:Seq[UserClass] = parser.parse(list)
// The transfomation is done in two steps inside the parse() method:
// 1/ first we have: val list = Seq("1,2,toto", "3,4,titi")
// 2/ then we have a call to internalParserImplementedSomewhereElse(list)
// val parseResult is now equal to Seq(Seq("1", "2", "toto"), Seq("3","4", "titi"))
// 3/ finally Shapeless do its magick trick and we have Seq(UserClass(1,2,"toto"), UserClass(3,4,"titi))
#insideTheLibrary
class Parser[A](function:A) {
//The internal parser takes each String provided through argument of the method and transforms each String to a Seq[String]. So the Seq[String] provided is changed to Seq[Seq[String]].
private def internalParserImplementedSomewhereElse(l:Seq[String]): Seq[Seq[String]] = {
...
}
/*
* Class A and B are both related to the case class provided by the user:
* - A is the type of the case class as a function,
* - B is the type of the original case class (can be guessed from type A).
*/
private def convert2CaseClass[B](list:Seq[String]): B {
//do something with Shapeless
//I don't know what to put inside ???
}
def parse(l:Seq[String]){
val parseResult:Seq[Seq[String]] = internalParserImplementedSomewhereElse(l:Seq[String])
val finalResult = result.map(convert2CaseClass)
finalResult // it is a Seq[CaseClassProvidedByUser]
}
}
Inside the library some implicit would be available to convert the String to the correct type as they are guessed by Shapeless (similar to the answered proposed in the link above). Like string.toInt, string.ToDouble, and so on...
May be there are other way to design it. It's just what I have in mind after playing with Shapeless few hours.
This uses a very simple library called product-collecions
import com.github.marklister.collections.io._
case class UserClass(i:Int, j:Int, s:String)
val csv = Seq("1,2,toto", "3,4,titi").mkString("\n")
csv: String =
1,2,toto
3,4,titi
CsvParser(UserClass).parse(new java.io.StringReader(csv))
res28: Seq[UserClass] = List(UserClass(1,2,toto), UserClass(3,4,titi))
And to serialize the other way:
scala> res28.csvIterator.toList
res30: List[String] = List(1,2,"toto", 3,4,"titi")
product-collections is orientated towards csv and a java.io.Reader, hence the shims above.
This answer will not tell you how to do exactly what you want, but it will solve your problem. I think you're overcomplicating things.
What is it you want to do? It appears to me that you're simply looking for a way to serialize and deserialize your case classes - i.e. convert your Scala objects to a generic string format and the generic string format back to Scala objects. Your serialization step presently is something you seem to already have defined, and you're asking about how to do the deserialization.
There are a few serialization/deserialization options available for Scala. You do not have to hack away with Shapeless or Scalaz to do it yourself. Try to take a look at these solutions:
Java serialization/deserialization. The regular serialization/deserialization facilities provided by the Java environment. Requires explicit casting and gives you no control over the serialization format, but it's built in and doesn't require much work to implement.
JSON serialization: there are many libraries that provide JSON generation and parsing for Java. Take a look at play-json, spray-json and Argonaut, for example.
The Scala Pickling library is a more general library for serialization/deserialization. Out of the box it comes with some binary and some JSON format, but you can create your own formats.
Out of these solutions, at least play-json and Scala Pickling use macros to generate serializers and deserializers for you at compile time. That means that they should both be typesafe and performant.

How can I serialize anything without specifying type?

I'm integrating with ZeroMQ and Akka to send case classes from different instances. Problem is that when I try to compile this code:
def persistRelay(relayEvent:String, relayData:Any) = {
val relayData = ser.serialize(relayData).fold(throw _, identity)
relayPubSocket ! ZMQMessage(Seq(Frame(relayEvent), Frame(relayData)))
}
The Scala compilers throws back recursive value relayData needs type.
The case classes going in are all different and look like Team(users:List[Long], teamId:Long) and so on.
Is there a method to allow any type in the serializer or a workaround? I'd prefer to avoid writing a serializer for every single function creating the data unless absolutely necessary.
Thanks!
This isn't really a typing issue. The problem is:
val relayData = ser.serialize(relayData).fold(throw _, identity)
You're declaring a val relayData in the same line that you're making a reference to the method parameter relayData. The Scala compiler doesn't understand that you have/want two variables with the same name, and, instead, interprets it as a recursive definition of val relayData. Changing the name of one of those variables should fix the error.
Regardless, since you didn't quite follow what the Scala compiler was asking for, I think that it would also be good to fill you in on what it is that the compiler even wanted from you (even though it's advice that, if followed, probably would have just led to you getting yet another error that wouldn't seem to make a lot of sense, given the circumstances).
It said "recursive value relayData needs type". The meaning of this is that it wanted you to simply specify the type of relayData by having
val relayData = ...
become something like
val relayData: Serializable = ...
(or, in place of Serializable, use whatever type it was that you wanted relayData to have)
It needs this information in order to create a recursive definition. For instance, take the simple case of
val x = x + 1
This code is... bizarre, to say the least, but what I'm doing is defining x in a (shallowly) recursive way. But there's a problem: how can the compiler know what type to use for the inner x? It can't really determine the type through type inference, because type inference involves leveraging the type information of other definitions, and this definition requires x's type information. Now, we might be able to infer that I'm probably talking about an Int, but, theoretically, x could be so many things! In fact, here's the ambiguity in action:
val x: Int = x + 1 // Default value for an Int is '0'
x: Int = 1
val y: String = y + 1 // Default value for a String is 'null'
y: String = null1
All that really changed was the type annotation, but the results are drastically different–and this is only a very simple case! So, yeah, to summarize all this... in most cases, when it's complaining about recursive values needing types, you should just have some empathy on the poor compiler and give it the type information that it so direly craves. It would do the same for you, DeLongey! It would do the same for you!