Scala: Create object only if it doesn't exist yet - scala

I'm new to Scala, and this probably a very simple question, but I'm struggling to figure out how to make an object only if one doesn't exist yet.
I would like to query a database, and find out if there's anything present, if so, store it in an object, otherwise create a new one. In Java I know that this would be something like
PushMessage push = null;
if(GetFromDatabase() == null) {
push = new PushMessaage(param1, param2...);
}
else {
push = GetFromDatabase();
}
But, how do I do this in Scala. When I try and do the same thing, it tells me that GetFromDatabase() doesn't conform to expected type Null. Similarly, I tried doing pattern matching and doing something like
val push = GetFromDatabase match {
case Some(pushMessage) => pushMessage
case None => new PushMessage(param1, param2...)
}
But, that also didn't work as it told me that
Constructor cannot be instantiated to expected type, found: Some[A], expected: PushMessage
So, how do I do this? Any and all help would be really appreciated.

I assume your GetFromDatabase returns either null or PushMessage, so in order to pattern match correctly, you need to wrap it into Option:
val push = Option(GetFromDatabase) match {
case Some(pushMessage) => pushMessage
case None => new PushMessage(param1, param2...)
}
Or (bad style, but gives an understanding of how it works):
// Option(null) === None, Option(notNull) === Some(notNull):
// same as `if (x ne null) Some(x) else None
val pushMaybe: Option[PushMessage] = Option(GetFromDatabase)
val push: PushMessage =
if (pushMaybe.isEmpty) new PushMessage(param1, param2...)
else pushMaybe.get
You can simplify it all with:
val push = Option(GetFromDatabase).getOrElse(new PushMessage(param1, param2...))
P.S. If GetFromDatabase isn't some external method, it's better to rewrite it as returning Option[PushMessage] instead of PushMessage, something like:
def getFromDatabase = {
val rs = driver.getResulSet(query)
if (!rs.isBeforeFirst()) None else Some(parse(rs))
}

Here's a little demonstration why "cool" things are not always cool. Let's see Scala generated code for two cases (I made them very simple):
def getMessage: String = null
val m = getMessage
val push = if (m == null) new AnyRef else m
=>
iw.this.m = iw.this.getMessage();
iw.this.push = if (iw.this.m().==(null))
new Object()
else
iw.this.m();
vs
def getMessage: String = null
val push = Option(getMessage) match {
case Some(x) => x
case None => new AnyRef
}
=>
iw.this.push = {
case <synthetic> val x1: Option = scala.Option.apply(iw.this.getMessage());
case6(){
if (x1.$isInstanceOf[Some]())
{
<synthetic> val x2: Some = (x1.$asInstanceOf[Some](): Some);
{
val x: String = x2.x().$asInstanceOf[String]();
matchEnd5(x)
}
}
else
case7()
};
case7(){
if (scala.None.==(x1))
matchEnd5(new Object())
else
case8()
};
case8(){
matchEnd5(throw new MatchError(x1))
};
matchEnd5(x: Object){
x
}
};
So as long as we are not propagating null (and we don't) I don't see any advantages of the second option.
UPDATE
As requested:
val path = Option(m).getOrElse(new AnyRef)
=>
final <artifact> private[this] def $anonfun$1(): Object = new Object();
...
iw.this.path = scala.Option.apply($line13.iw.m()).getOrElse({
(() => iw.this.$anonfun$1())
});
I wouldn't consider it much better than the second option above. getOrElse hides about the same logic, and we have anonymous function since getOrElse takes by-name argument.
In fact it's not just about saving cycles. Constructing and deconstructing Option object for the sake of avoiding local null? Or saving one line? I would totally accept it if we used Option for passing it further.

Related

Scala - How to safely operate on a map element

I want to get an element from a mutable map and do an operation on it.
For example I want to change his name value (the element on the map will be with the new value)
and I want to return it in the end
to start I wrote a working code but it is very Java
var newAppKey: AppKey = null
val appKey = myMap(request.appKeyId)
if (appKey != null) {
newAppKey = appKey.copy(name = request.appKeyName)
myMap.put(appKey.name, newAppKey)
newAppKey
} else {
newAppKey = null
}
This code works but it very java.
I though about something like
val newAppKey = appIdToApp(request.appKeyId) match {
case: Some(appKey) => appKey.copy(name = request.appKeyName)
case: None => None{AppKey}
}
Which doesn't compile or updates the myMap object with the new value.
How do I improve it to scala concepts.
Simply:
val key = request.appKeyId
val newValueOpt = myMap.get(key).map(_.copy(name = request.appKeyName))
newValueOpt.foreach(myMap.update(key, _))
There are a couple of mistakes in your code.
case: Some(appKey) => appKey.copy(name = request.appKeyName)
This syntax for case is incorrect. It should be
case Some(appKey) => appKey.copy(name = request.appKeyName)
Also, the return type of your expression is currently Any (Scala equivalent of Object), because your success case returns an object of type (appKey's type) whereas the failure case returns a None, which is of type Option. To make things consistent, your success case should return
Some(appKey.copy(name = request.appKeyName))
While there are better ways to deal with Options than pattern matching, the corrected code would be
val newAppKey = appIdToApp(request.appKeyId) map (appKey =>
appKey.copy(name = request.appKeyName))

Cleanest way in Scala to avoid nested ifs when transforming collections and checking for error conditions in each step

I have some code for validating ip addresses that looks like the following:
sealed abstract class Result
case object Valid extends Result
case class Malformatted(val invalid: Iterable[IpConfig]) extends Result
case class Duplicates(val dups: Iterable[Inet4Address]) extends Result
case class Unavailable(val taken: Iterable[Inet4Address]) extends Result
def result(ipConfigs: Iterable[IpConfig]): Result = {
val invalidIpConfigs: Iterable[IpConfig] =
ipConfigs.filterNot(ipConfig => {
(isValidIpv4(ipConfig.address)
&& isValidIpv4(ipConfig.gateway))
})
if (!invalidIpConfigs.isEmpty) {
Malformatted(invalidIpConfigs)
} else {
val ipv4it: Iterable[Inet4Address] = ipConfigs.map { ipConfig =>
InetAddress.getByName(ipConfig.address).asInstanceOf[Inet4Address]
}
val dups = ipv4it.groupBy(identity).filter(_._2.size != 1).keys
if (!dups.isEmpty) {
Duplicates(dups)
} else {
val ipAvailability: Map[Inet4Address, Boolean] =
ipv4it.map(ip => (ip, isIpAvailable(ip)))
val taken: Iterable[Inet4Address] = ipAvailability.filter(!_._2).keys
if (!taken.isEmpty) {
Unavailable(taken)
} else {
Valid
}
}
}
}
I don't like the nested ifs because it makes the code less readable. Is there a nice way to linearize this code? In java, I might use return statements, but this is discouraged in scala.
I personally advocate using a match everywhere you can, as it in my opinion usually makes code very readable
def result(ipConfigs: Iterable[IpConfig]): Result =
ipConfigs.filterNot(ipc => isValidIpv4(ipc.address) && isValidIpv4(ipc.gateway)) match {
case Nil =>
val ipv4it = ipConfigs.map { ipc =>
InetAddress.getByName(ipc.address).asInstanceOf[Inet4Address]
}
ipv4it.groupBy(identity).filter(_._2.size != 1).keys match {
case Nil =>
val taken = ipv4it.map(ip => (ip, isIpAvailable(ip))).filter(!_._2).keys
if (taken.nonEmpty) Unavailable(taken) else Valid
case dups => Duplicates(dups)
}
case invalid => Malformatted(invalid)
}
Note that I've chosen to match on the else part first, since you generally go from specific to generic in matches, since Nil is a subclass of Iterable I put that as the first case, eliminating the need for an i if i.nonEmpty in the other case, since it would be a given if it didn't match Nil
Also a thing to note here, all your vals don't need the type explicitly defined, it significantly declutters the code if you write something like
val ipAvailability: Map[Inet4Address, Boolean] =
ipv4it.map(ip => (ip, isIpAvailable(ip)))
as simply
val ipAvailability = ipv4it.map(ip => (ip, isIpAvailable(ip)))
I've also taken the liberty of removing many one-off variables I didn't find remotely necessary, as all they did was add more lines to the code
A thing to note here about using match over nested ifs, is that is that it's easier to add a new case than it is to add a new else if 99% of the time, thereby making it more modular, and modularity is always a good thing.
Alternatively, as suggested by Nathaniel Ford, you can break it up into several smaller methods, in which case the above code would look like so:
def result(ipConfigs: Iterable[IpConfig]): Result =
ipConfigs.filterNot(ipc => isValidIpv4(ipc.address) && isValidIpv4(ipc.gateway)) match {
case Nil => wellFormatted(ipConfigs)
case i => Malformatted(i)
}
def wellFormatted(ipConfigs: Iterable[IpConfig]): Result = {
val ipv4it = ipConfigs.map(ipc => InetAddress.getByName(ipc.address).asInstanceOf[Inet4Address])
ipv4it.groupBy(identity).filter(_._2.size != 1).keys match {
case Nil => noDuplicates(ipv4it)
case dups => Duplicates(dups)
}
}
def noDuplicates(ipv4it: Iterable[IpConfig]): Result =
ipv4it.map(ip => (ip, isIpAvailable(ip))).filter(!_._2).keys match {
case Nil => Valid
case taken => Unavailable(taken)
}
This has the benefit of splitting it up into smaller more manageable chunks, while keeping to the FP ideal of having functions that only do one thing, but do that one thing well, rather than having god-methods that do everything.
Which style you prefer, of course is up to you.
This has some time now but I will add my 2 cents. The proper way to handle this is with Either. You can create a method like:
def checkErrors[T](errorList: Iterable[T], onError: Result) : Either[Result, Unit] = if(errorList.isEmpty) Right() else Left(onError)
so you can use for comprehension syntax
val invalidIpConfigs = getFormatErrors(ipConfigs)
val result = for {
_ <- checkErrors(invalidIpConfigs, Malformatted(invalidIpConfigs))
dups = getDuplicates(ipConfigs)
_ <- checkErrors(dups, Duplicates(dups))
taken = getAvailability(ipConfigs)
_ <- checkErrors(taken, Unavailable(taken))
} yield Valid
If you don't want to return an Either use
result.fold(l => l, r => r)
In case of the check methods uses Futures (could be the case for getAvailability, for example), you can use cats library to be able of use it in a clean way: https://typelevel.org/cats/datatypes/eithert.html
I think it's pretty readable and I wouldn't try to improve it from there, except that !isEmpty equals to nonEmpty.

Is there any way to use immutable collections here + make the code look better?

I have to validate some variables manually for some reason and return a map with the sequance of the error messages for each variable. I've decided to use mutable collections for this because I think there is no other choise left:
val errors = collection.mutable.Map[String, ListBuffer[String]]()
//field1
val fieldToValidate1 = getData1()
if (fieldToValidate1 = "")
errors("fieldToValidate1") += "it must not be empty!"
if (validate2(fieldToValidate1))
errors("fieldToValidate1") += "validation2!"
if (validate3(fieldToValidate1))
errors("fieldToValidate1") += "validation3!"
//field2
val fieldToValidate2 = getData1()
//approximately the same steps
if (fieldToValidate2 = "")
errors("fieldToValidate2") += "it must not be empty!"
//.....
To my mind, it look kind of clumsy and there should other elegant solution. I'd also like to not use mutable collections if possible. Your ideas?
Instead of using mutable collections, you can define errors with var and update it in this way.
var errors = Map[String, List[String]]().withDefaultValue(Nil)
errors = errors updated ("fieldToValidate1", errors("fieldToValidate1") ++ List("it must not be empty!"))
errors = errors updated ("fieldToValidate1", errors("fieldToValidate1") ++ List("validation2"))
The code looks more tedious, but it gets out of mutable collections.
So what is a good type for your check? I was thinking about A => Option[String] if A is the type of your object under test. If your error messages do not depend on the value of the object under test, (A => Boolean, String) might be more convenient.
//for constructing checks from boolean test and an error message
def checkMsg[A](check: A => Boolean, msg: => String): A => Option[String] =
x => if(check(x)) Some(msg) else None
val checks = Seq[String => Option[String]](
checkMsg((_ == ""), "it must not be empty"),
//example of using the object under test in the error message
x => Some(x).filterNot(_ startsWith "ab").map(x => x + " does not begin with ab")
)
val objectUnderTest = "acvw"
val errors = checks.flatMap(c => c(objectUnderTest))
Error labels
As I just noted, you were asking for a map with a label for each check. In this case, you need to provide the check label, of course. Then the type of your check would be (String, A => Option[String]).
Although a [relatively] widespread way of doing-the-thing-right would be using scalaz's Validation (as #senia has shown), I think it is a little bit overwhelming approach (if you're bringing scalaz to your project you have to be a seasoned scala developer, otherwise it may bring you more harm than good).
Nice alternative could be using ScalaUtils which has Or and Every specifically made for this purpose, in fact if you're using ScalaTest you already have seen an example of them in use (it uses scalautils underneath). I shamefully copy-pasted example from their doc:
import org.scalautils._
def parseName(input: String): String Or One[ErrorMessage] = {
val trimmed = input.trim
if (!trimmed.isEmpty) Good(trimmed) else Bad(One(s""""${input}" is not a valid name"""))
}
def parseAge(input: String): Int Or One[ErrorMessage] = {
try {
val age = input.trim.toInt
if (age >= 0) Good(age) else Bad(One(s""""${age}" is not a valid age"""))
}
catch {
case _: NumberFormatException => Bad(One(s""""${input}" is not a valid integer"""))
}
}
import Accumulation._
def parsePerson(inputName: String, inputAge: String): Person Or Every[ErrorMessage] = {
val name = parseName(inputName)
val age = parseAge(inputAge)
withGood(name, age) { Person(_, _) }
}
parsePerson("Bridget Jones", "29")
// Result: Good(Person(Bridget Jones,29))
parsePerson("Bridget Jones", "")
// Result: Bad(One("" is not a valid integer))
parsePerson("Bridget Jones", "-29")
// Result: Bad(One("-29" is not a valid age))
parsePerson("", "")
// Result: Bad(Many("" is not a valid name, "" is not a valid integer))
Having said this, I don't think you can do any better than your current approach if you want to stick with core scala without any external dependencies.
In case you can use scalaz the best solution for aggregation errors is Validation:
def validate1(value: String) =
if (value == "") "it must not be empty!".failNel else value.success
def validate2(value: String) =
if (value.length > 10) "it must not be longer than 10!".failNel else value.success
def validate3(value: String) =
if (value == "error") "it must not be equal to 'error'!".failNel else value.success
def validateField(name: String, value: String): ValidationNel[(String, String), String] =
(
validate1(value) |#|
validate2(value) |#|
validate3(value)
).tupled >| value leftMap { _.map{ name -> _ } }
val result = (
validateField("fieldToValidate1", getData1()) |#|
validateField("fieldToValidate2", getData2())
).tupled
Then you could get optional errors Map like this:
val errors =
result.swap.toOption.map{
_.toList.groupBy(_._1).map{ case (k, v) => k -> v.map(_._2) }
}
// Some(Map(fieldToValidate2 -> List(it must not be equal to 'error'!), fieldToValidate1 -> List(it must not be empty!)))

Why is this Option transformed to a String? [Scala]

I'm still a Scala noob, and this confuses me:
import java.util.regex._
object NumberMatcher {
def apply(x:String):Boolean = {
val pat = Pattern.compile("\\d+")
val matcher = pat.matcher(x)
return matcher.find
}
def unapply(x:String):Option[String] = {
val pat = Pattern.compile("\\d+")
val matcher = pat.matcher(x)
if(matcher.find) {
return Some(matcher.group())
}
None
}
}
object x {
def main(args : Array[String]) : Unit = {
val strings = List("geo12","neo493","leo")
for(val string <- strings) {
string match {
case NumberMatcher(group) => println(group)
case _ => println ("no")
}
}
}
}
I wanted to add pattern matching for strings containing digits ( so I can learn more about pattern matching ), and in unapply I decided to return a Option[String]. However, in the println in the NumberMatcher case, group is seen as a String and not as an Option. Can you shed some light? The output produced when this is ran is:
12,493,no
Take a look at this example.
The unapply method returns Some value if it succeeded in extracting one, otherwise None. So internally the
case NumberMatcher(group) => println(group)
invokes unapply and looks whether it returns some value. If it does, we already have to true result and therefore no Option type remains. The pattern matching extracts the returned value from the option.

How to use scalax.io.CommandLineParser?

I want to create a class that takes string array as a constructor argument and has command line option values as members vals. Something like below, but I don't understand how the Bistate works.
import scalax.data._
import scalax.io.CommandLineParser
class TestCLI(arguments: Array[String]) extends CommandLineParser {
private val opt1Option = new Flag("p", "print") with AllowAll
private val opt2Option = new Flag("o", "out") with AllowAll
private val strOption = new StringOption("v", "value") with AllowAll
private val result = parse(arguments)
// true or false
val opt1 = result(opt1Option)
val opt2 = result(opt2Option)
val str = result(strOption)
}
Here are shorter alternatives to that pattern matching to get a boolean:
val opt1 = result(opt1Option).isInstanceOf[Positive[_]]
val opt2 = result(opt2Option).posValue.isDefined
The second one is probably better. The field posValue is an Option (there's negValue as well). The method isDefined from Option tells you whether it is a Some(x) or None.
I'm not personally familiar with Scalax or Bistate in particular, but just looking at the scaladocs, it looks like a left-right disjunction. Scala's main library has a monad very much like this (Either), so I'm surprised that they didn't just use the standard one.
In essence, Bistate and Either are a bit like Option, except their "None-equivalent" can contain a value. For example, if I were writing code using Either, I might do something like this:
def div(a: Int, b: Int) = if (b != 0) Left(a / b) else Right("Divide by zero")
div(4, 2) match {
case Left(x) => println("Result: " + x)
case Right(e) => Println("Error: " + e)
}
This would print "Result: 2". In this case, we're using Either to simulate an exception. We return an instance of Left which contains the value we want, unless that value cannot be computed for some reason, in which case we return an error message wrapped up inside an instance of Right.
So if I want to assign to variable boolean value of whether flag is found I have to do like below?
val opt1 = result(opt1Option) match {
case Positive(_) => true
case Negative(_) => false
}
Isn't there a way to write this common case with less code than that?