I have a case class like below:
case class Class1(field1: String,
field2: Option[String] = None,
var var1: Option[String] = None,
var var2: Option[Boolean] = None,
var var3: Option[Double] = None
)
The list of variables is a bit longer. Now I want to convert all variables, which are inside the class, into a string. Say Option[] must be omitted and also Boolean, Double and Number must be converted to string type. My first approach was:
def anyOptionalToString(class1Dataset: Dataset[Class1]): DataFrame = {
val ds1 = class1Dataset.map { class1 =>
(
class1.field1,
class1.field2.getOrElse(""),
class1.var1.getOrElse(""),
class1.var2.getOrElse(false),
class1.var3.getOrElse(-1.0)
)
}
Is there a way to cast them without calling every field?
Speak in a kind of loop or something similar?
What I would do, is creating a new Seq containing the defaults you want to have. Let's say:
val defaults = Seq("", "", "", false, -1)
Now, we can use the productIterator to iterate over the existing elements, and choose whether we want to use the existing value, or the default:
val c1 = Class1("f1", Some("f2"), None, Some(true), Some(3))
c1.productIterator.zip(defaults.iterator).map {
case (None, default) => default
case (Some(value), _) => value
case (value, _) => value
}.map(_.toString)
The resulting type of the code above is Iterator[String]. Code run can be found at Scastie.
Related
There are many nice libraries for writing/reading Scala case classes to/from CSV files. I'm looking for something that goes beyond that, which can handle nested cases classes. For example, here a Match has two Players:
case class Player(name: String, ranking: Int)
case class Match(place: String, winner: Player, loser: Player)
val matches = List(
Match("London", Player("Jane",7), Player("Fred",23)),
Match("Rome", Player("Marco",19), Player("Giulia",3)),
Match("Paris", Player("Isabelle",2), Player("Julien",5))
)
I'd like to effortlessly (no boilerplate!) write/read matches to/from this CSV:
place,winner.name,winner.ranking,loser.name,loser.ranking
London,Jane,7,Fred,23
Rome,Marco,19,Giulia,3
Paris,Isabelle,2,Julien,5
Note the automated header line using the dot "." to form the column name for a nested field, e.g. winner.ranking. I'd be delighted if someone could demonstrate a simple way to do this (say, using reflection or Shapeless).
[Motivation. During data analysis it's convenient to have a flat CSV to play around with, for sorting, filtering, etc., even when case classes are nested. And it would be nice if you could load nested case classes back from such files.]
Since a case-class is a Product, getting the values of the various fields is relatively easy. Getting the names of the fields/columns does require using Java reflection.
The following function takes a list of case-class instances and returns a list of rows, each is a list of strings. It is using a recursion to get the values and headers of child case-class instances.
def toCsv(p: List[Product]): List[List[String]] = {
def header(c: Class[_], prefix: String = ""): List[String] = {
c.getDeclaredFields.toList.flatMap { field =>
val name = prefix + field.getName
if (classOf[Product].isAssignableFrom(field.getType)) header(field.getType, name + ".")
else List(name)
}
}
def flatten(p: Product): List[String] =
p.productIterator.flatMap {
case p: Product => flatten(p)
case v: Any => List(v.toString)
}.toList
header(classOf[Match]) :: p.map(flatten)
}
However, constructing case-classes from CSV is far more involved, requiring to use reflection for getting the types of the various fields, for creating the values from the CSV strings and for constructing the case-class instances.
For simplicity (not saying the code is simple, just so it won't be further complicated), I assume that the order of columns in the CSV is the same as if the file was produced by the toCsv(...) function above.
The following function starts by creating a list of "instructions how to process a single CSV row" (the instructions are also used to verify that the column headers in the CSV matches the the case-class properties). The instructions are then used to recursively produce one CSV row at a time.
def fromCsv[T <: Product](csv: List[List[String]])(implicit tag: ClassTag[T]): List[T] = {
trait Instruction {
val name: String
val header = true
}
case class BeginCaseClassField(name: String, clazz: Class[_]) extends Instruction {
override val header = false
}
case class EndCaseClassField(name: String) extends Instruction {
override val header = false
}
case class IntField(name: String) extends Instruction
case class StringField(name: String) extends Instruction
case class DoubleField(name: String) extends Instruction
def scan(c: Class[_], prefix: String = ""): List[Instruction] = {
c.getDeclaredFields.toList.flatMap { field =>
val name = prefix + field.getName
val fType = field.getType
if (fType == classOf[Int]) List(IntField(name))
else if (fType == classOf[Double]) List(DoubleField(name))
else if (fType == classOf[String]) List(StringField(name))
else if (classOf[Product].isAssignableFrom(fType)) BeginCaseClassField(name, fType) :: scan(fType, name + ".")
else throw new IllegalArgumentException(s"Unsupported field type: $fType")
} :+ EndCaseClassField(prefix)
}
def produce(instructions: List[Instruction], row: List[String], argAccumulator: List[Any]): (List[Instruction], List[String], List[Any]) = instructions match {
case IntField(_) :: tail => produce(tail, row.drop(1), argAccumulator :+ row.head.toString.toInt)
case StringField(_) :: tail => produce(tail, row.drop(1), argAccumulator :+ row.head.toString)
case DoubleField(_) :: tail => produce(tail, row.drop(1), argAccumulator :+ row.head.toString.toDouble)
case BeginCaseClassField(_, clazz) :: tail =>
val (instructionRemaining, rowRemaining, constructorArgs) = produce(tail, row, List.empty)
val newCaseClass = clazz.getConstructors.head.newInstance(constructorArgs.map(_.asInstanceOf[AnyRef]): _*)
produce(instructionRemaining, rowRemaining, argAccumulator :+ newCaseClass)
case EndCaseClassField(_) :: tail => (tail, row, argAccumulator)
case Nil if row.isEmpty => (Nil, Nil, argAccumulator)
case Nil => throw new IllegalArgumentException("Not all values from CSV row were used")
}
val instructions = BeginCaseClassField(".", tag.runtimeClass) :: scan(tag.runtimeClass)
assert(csv.head == instructions.filter(_.header).map(_.name), "CSV header doesn't match target case-class fields")
csv.drop(1).map(row => produce(instructions, row, List.empty)._3.head.asInstanceOf[T])
}
I've tested this using:
case class Player(name: String, ranking: Int, price: Double)
case class Match(place: String, winner: Player, loser: Player)
val matches = List(
Match("London", Player("Jane", 7, 12.5), Player("Fred", 23, 11.1)),
Match("Rome", Player("Marco", 19, 13.54), Player("Giulia", 3, 41.8)),
Match("Paris", Player("Isabelle", 2, 31.7), Player("Julien", 5, 16.8))
)
val csv = toCsv(matches)
val matchesFromCsv = fromCsv[Match](csv)
assert(matches == matchesFromCsv)
Obviously this should be optimized and hardened if you ever want to use this for production...
I have 2 Lists: lista and listb. For each element in lista, I want to check if a_type of each element is in b_type of listb. If true, get the b_name for corresponding b_type and construct an object objc. And, then I should return the list of of constructed objc.
Is there a way to do this in Scala and preferably without any mutable collections?
case class obja = (a_id: String, a_type: String)
case class objb = (b_id: String, b_type: String, b_name: String)
case class objc = (c_id: String, c_type: String, c_name: String)
val lista: List[obja] = List(...)
val listb: List[objb] = List(...)
def getNames(alist: List[obja], blist: List[objb]): List[objc] = ???
Lookup in lists requires traversal in O(n) time, this is inefficient. Therefore, the first thing you do is to create a map from b_type to b_name:
val bTypeToBname = listb.map(b => (b.b_type, b_name)).toMap
Then you iterate through lista, look up in the map whether there is a corresponding b_name for a given a.a_type, and construct the objc:
val cs = for {
a <- lista
b_name <- bTypeToBname.get(a.a_type)
} yield objc(a.a_id, a.a_type, b_name)
Notice how Scala for-comprehensions automatically filter those cases for which bTypeToBname(a.a_type) isn't defined: then the corresponding a is simply skipped. This because we use bTypeToBname.get(a.a_type) (which returns an Option), as opposed to calling bTypeToBname(a.a_type) directly (this would lead to a NoSuchElementException). As far as I understand, this filtering is exactly the behavior you wanted.
case class A(aId: String, aType: String)
case class B(bId: String, bType: String, bName: String)
case class C(cId: String, cType: String, cName: String)
def getNames(aList: List[A], bList: List[B]): List[C] = {
val bMap: Map[String, B] = bList.map(b => b.bType -> b)(collection.breakOut)
aList.flatMap(a => bMap.get(a.aType).map(b => C(a.aId, a.aType, b.bName)))
}
Same as Andrey's answer but without comprehension so you can see what's happening inside.
// make listb into a map from type to name for efficiency
val bs = listb.map(b => b.b_type -> b_name).toMap
val listc: Seq[objc] = lista
.flatMap(a => // flatmap to exclude types not in listb
bs.get(a.a_type) // get an option from blist
.map(bName => objc(a.a_id, a.a_type, bName)) // if there is a b name for that type, make an objc
)
I have a list of Person and want to retrieve a person by its id
val person = personL.find(_.id.equals(tempId))
After that, I want to get as a tuple the first and last element of a list which is an attribute of Person.
val marks: Option[(Option[String], Option[String])] = person.map { p =>
val marks = p.school.marks
(marks.headOption.map(_.midtermMark), marks.lastOption.map(_.finalMark))
}
This work's fine but now I want to transform the Option[(Option[String], Option[String])] to a simple (Option[String], Option[String]). Is it somehow possible to do this on-the-fly by using the previous map?
I suppose:
person.map{...}.getOrElse((None, None))
(None, None) is a default value here in case if your option of tuple is empty
You are, probably, looking for fold:
personL
.collectFirst {
case Person(`tempId`, _, .., school) => school.marks
}.fold[Option[String], Option[String]](None -> None) { marks =>
marks.headOption.map(_.midtermMark) -> marks.lastOption.map(_.finalMark)
}
New to Scala, continue to struggle with Option related code. I have a HashMap built of Case Class instances that themselves contain hash maps with Case Class instance values. It is not clear to me how to access properties of the retrieved Class instances:
import collection.mutable.HashMap
case class InnerClass(name: String, age: Int)
case class OuterClass(name: String, nestedMap: HashMap[String, InnerClass])
// Load some data...hash maps are mutable
val innerMap = new HashMap[String, InnerClass]()
innerMap += ("aaa" -> InnerClass("xyz", 0))
val outerMap = new HashMap[String, OuterClass]()
outerMap += ("AAA" -> OuterClass("XYZ", innerMap))
// Try to retrieve data
val outerMapTest = outerMap.getOrElse("AAA", None)
val nestedMap = outerMapTest.nestedMap
This produces error: value nestedMap is not a member of Option[ScalaFiddle.OuterClass]
// Try to retrieve data a different way
val outerMapTest = outerMap.getOrElse("AAA", None)
val nestedMap = outerMapTest.nestedMap
This produces error: value nestedMap is not a member of Product with Serializable
Please advise on how I would go about getting access to outerMapTest.nestedMap. I'll eventually need to get values and properties out of the nestedMap HashMap as well.
Since you are using .getOrElse("someKey", None) which returns you a type Product (not the actual type as you expect to be OuterClass)
scala> val outerMapTest = outerMap.getOrElse("AAA", None)
outerMapTest: Product with Serializable = OuterClass(XYZ,Map(aaa -> InnerClass(xyz,0)))
so Product either needs to be pattern matched or casted to OuterClass
pattern match example
scala> outerMapTest match { case x : OuterClass => println(x.nestedMap); case _ => println("is not outerclass") }
Map(aaa -> InnerClass(xyz,0))
Casting example which is a terrible idea when outerMapTest is None, (pattern matching is favored over casting)
scala> outerMapTest.asInstanceOf[OuterClass].nestedMap
res30: scala.collection.mutable.HashMap[String,InnerClass] = Map(aaa -> InnerClass(xyz,0))
But better way of solving it would simply use .get which very smart and gives you Option[OuterClass],
scala> outerMap.get("AAA").map(outerClass => outerClass.nestedMap)
res27: Option[scala.collection.mutable.HashMap[String,InnerClass]] = Some(Map(aaa -> InnerClass(xyz,0)))
For key that does not exist, gives you None
scala> outerMap.get("I dont exist").map(outerClass => outerClass.nestedMap)
res28: Option[scala.collection.mutable.HashMap[String,InnerClass]] = None
Here are some steps you can take to get deep inside a nested structure like this.
outerMap.lift("AAA") // Option[OuterClass]
.map(_.nestedMap) // Option[HashMap[String,InnerClass]]
.flatMap(_.lift("aaa")) // Option[InnerClass]
.map(_.name) // Option[String]
.getOrElse("no name") // String
Notice that if either of the inner or outer maps doesn't have the specified key ("aaa" or "AAA" respectively) then the whole thing will safely result in the default string ("no name").
A HashMap will return None if a key is not found so it is unnecessary to do getOrElse to return None if the key is not found.
A simple solution to your problem would be to use get only as below
Change your first get as
val outerMapTest = outerMap.get("AAA").get
you can check the output as
println(outerMapTest.name)
println(outerMapTest.nestedMap)
And change the second get as
val nestedMap = outerMapTest.nestedMap.get("aaa").get
You can test the outputs as
println(nestedMap.name)
println(nestedMap.age)
Hope this is helpful
You want
val maybeInner = outerMap.get("AAA").flatMap(_.nestedMap.get("aaa"))
val maybeName = maybeInner.map(_.name)
Which if your feeling adventurous you can get with
val name: String = maybeName.get
But that will throw an error if its not there. If its a None
you can access the nestMap using below expression.
scala> outerMap.get("AAA").map(_.nestedMap).getOrElse(HashMap())
res5: scala.collection.mutable.HashMap[String,InnerClass] = Map(aaa -> InnerClass(xyz,0))
if "AAA" didnt exist in the outerMap Map object then the below expression would have returned an empty HashMap as indicated in the .getOrElse method argument (HashMap()).
A Scala map contains a key X.
The value can be either an array of Strings Array("Y")
or a simple String object, "Y".
I need to retrieve the value from the map and test
if the value is a string,
mayMap("X")=="Y"
or, if the value is an array.
myMap("X").contains("Y")
I don't want to use an if statement statement to check the type first of the value first of all. One option would be to write a function which checks the value, if it is an array then return the array, otherwise create an array with the single string element contained in the map. Then the call would be:
myToArrayFunction(myMap("X")).contains("Y")
That's what I actually do in Java.
But this is Scala. Is there a better idiom to do this in one line using pre-existing functions?
This should work:
myMap.get("X") match {
case None => println("oh snap!")
case Some(x) => x match {
case i: String => println(s"hooray for my String $i") // do something with your String here
case a: Array[String] => println(s"It's an Array $a") // do something with your Array here
}
}
case class Y(name: String)
//val a = Map[String, Any]("X" -> "Y")
val a = Map[String, Any]("X" -> Y("Peter"))
a.getOrElse("X", "Default") match {
case s: String => println(s)
case Y(name) => println(name)
}
you can also use something like this:
//val a = Map[String, Any]("X" -> "Y")
val a = Map[String, Any]("X" -> Y("Peter"))
a.map(v => println(v._2))